Embracing divergence: a formalism for when your semiring is simply not complete, with applications in quantum simulation

Abstract: There is a fundamental difficulty in generalizing weighted automata to the case of infinite words: in general the infinite sum-of-products from which the weight of a given word is derived will diverge. Many solutions to this problem have been proposed, including restricting the type of weights used and employing a different valuation function that forces convergence. In this paper we describe an alternative approach that, rather than seeking to avoid the inevitable divergences, instead embraces them as a source of useful information. Specifically, rather than taking coefficients from an arbitrary semiring S we instead take them from S^N. Doing this is useful because it gives us information about how the weight of an infinite word does or does not diverge, and if it does diverge what form the divergence takes --- e.g., polynomial, exponential, etc. This approach has proved to be incredibly useful in the field of quantum simulation because when studying infinite systems, information about how quantities of interest, such as energy or magnetization, diverge is exactly what we want. In this paper we introduce a new kind of automaton which we call a diverging automaton that maps infinite words to sequences of weights from a semiring and which employs a Buchi-like boundary condition. We then develop a theory for diverging power series and prove a Kleene Theorem connecting rational diverging power series to diverging automata. Afterward we repeat this process by introducing bidiverging automata which map biinfinite words to elements in S^(Z x N), developing a theory for bidiverging power series, and proving another Kleene Theorem. We conclude by describing how bidiverging automata are applied to simulate biinfinite quantum systems.


Triggercast: Enabling Wireless Collisions Constructive

Abstract: It is generally considered that concurrent transmissions should be avoided in order to reduce collisions in wireless sensor networks. Constructive interference (CI) envisions concurrent transmissions to positively interfere at the receiver. CI potentially allows orders of magnitude reductions in energy consumptions and improvements on link quality. In this paper, we theoretically introduce a sufficient condition to construct CI with IEEE 802.15.4 radio for the first time. Moreover, we propose Triggercast, a distributed middleware, and show it is feasible to generate CI in TMote Sky sensor nodes. To synchronize transmissions of multiple senders at the chip level, Triggercast effectively compensates propagation and radio processing delays, and has $95^{th}$ percentile synchronization errors of at most 250ns. Triggercast also intelligently decides which co-senders to participate in simultaneous transmissions, and aligns their transmission time to maximize the overall link PRR, under the condition of maximal system robustness. Extensive experiments in real testbeds reveal that Triggercast significantly improves PRR from 5% to 70% with 7 concurrent senders. We also demonstrate that Triggercast provides on average $1.3\times$ PRR performance gains, when integrated with existing data forwarding protocols.


Comparative Evaluation of Data Stream Indexing Models

Abstract: In recent years, the management and processing of data streams has become a topic of active research in several fields of computer science such as, distributed systems, database systems, and data mining. A data stream can be thought of as a transient, continuously increasing sequence of data. In data streams' applications, because of online monitoring, answering to the user's queries should be time and space efficient. In this paper, we consider the special requirements of indexing to determine the performance of different techniques in data stream processing environments. Stream indexing has main differences with approaches in traditional databases. Also, we compare data stream indexing models analytically that can provide a suitable method for stream indexing.


Efficient and Secure Key Extraction using CSI without Chasing down Errors

Abstract: Generating keys and keeping them secret is critical in secure communications. Due to the "open-air" nature, key distribution is more susceptible to attacks in wireless communications. An ingenious solution is to generate common secret keys by two communicating parties separately without the need of key exchange or distribution, and regenerate them on needs. Recently, it is promising to extract keys by measuring the random variation in wireless channels, e.g., RSS. In this paper, we propose an efficient Secret Key Extraction protocol without Chasing down Errors, SKECE. It establishes common cryptographic keys for two communicating parties in wireless networks via the realtime measurement of Channel State Information (CSI). It outperforms RSS-based approaches for key generation in terms of multiple subcarriers measurement, perfect symmetry in channel, rapid decorrelation with distance, and high sensitivity towards environments. In the SKECE design, we also propose effective mechanisms such as the adaptive key stream generation, leakage resilient consistence validation, and weighted key recombination, to fully exploit the excellent properties of CSI. We implement SKECE on off-the-shelf 802.11n devices and evaluate its performance via extensive experiments. The results demonstrate that SKECE achieves a more than 3x throughput gain in the key generation from one subcarrier in static scenarios, and due to its high efficiency, a 50% reduction on the communication overhead compared to the state-of-the-art RSS based approaches.


Semantic Web Requirements through Web Mining Techniques

Abstract: In recent years, Semantic web has become a topic of active research in several fields of computer science and has applied in a wide range of domains such as bioinformatics, life sciences, and knowledge management. The two fast-developing research areas semantic web and web mining can complement each other and their different techniques can be used jointly or separately to solve the issues in both areas. In addition, since shifting from current web to semantic web mainly depends on the enhancement of knowledge, web mining can play a key role in facing numerous challenges of this changing. In this paper, we analyze and classify the application of divers web mining techniques in different challenges of the semantic web in form of an analytical framework.


Imperfect best-response mechanisms

Abstract: Best-response mechanisms (Nisan, Schapira, Valiant, Zohar, 2011) provide a unifying framework for studying various distributed protocols in which the participants are instructed to repeatedly best respond to each others' strategies. Two fundamental features of these mechanisms are convergence and incentive compatibility. This work investigates convergence and incentive compatibility conditions of such mechanisms when players are not guaranteed to always best respond but they rather play an imperfect best-response strategy. That is, at every time step every player deviates from the prescribed best-response strategy according to some probability parameter. The results explain to what extent convergence and incentive compatibility depend on the assumption that players never make mistakes, and how robust such protocols are to "noise" or "mistakes".


Description of the Chord Protocol using ASMs Formalism

Abstract: This paper describes the overlay protocol Chord using the formalism of Abstract State Machines. The formalization concerns Chord actions that maintain ring topology and manipulate distributed keys. We define a class of runs and prove the correctness of our formalization with respect to it.


On logical hierarchies within FO^2-definable languages

Abstract: We consider the class of languages defined in the 2-variable fragment of the first-order logic of the linear order. Many interesting characterizations of this class are known, as well as the fact that restricting the number of quantifier alternations yields an infinite hierarchy whose levels are varieties of languages (and hence admit an algebraic characterization). Using this algebraic approach, we show that the quantifier alternation hierarchy inside FO^{2}[<] is decidable within one unit. For this purpose, we relate each level of the hierarchy with decidable varieties of languages, which can be defined in terms of iterated deterministic and co-deterministic products. A crucial notion in this process is that of condensed rankers, a refinement of the rankers of Weis and Immerman and the turtle languages of Schwentick, Th\'erien and Vollmer.


Universal Numeric Segment Display for Indian Scheduled Languages: an Architectural View

Abstract: India is country of several hundred different languages. Though twenty two languages have only been devised as scheduled to the Eighth Schedule of Indian Constitution in 2007. But as there is yet no proposed compact display architecture to display all the scheduled language numerals at a time, this paper proposes a uniform display architecture to display all twenty two different language digits with higher accuracy and simplicity by using a 17-segment display, which is an improvement over the 16-segment display.


Web based e-learning in india: the cumulative views of different aspects

Abstract: In the presence of great social diversity in India, it is difficult to change the social background of students, parents and their economical conditions. Therefore the only option left for us is to provide uniform or standardize teaching learning resources or methods. For high quality education throughout India there must be some nation-wide network, which provides equal quality education to all students, including the student from the rural areas and villages. The one and only simple solution to this is Web Based e-Learning. In this paper we try to give some innovative ideas to spread the Web Based e-Learning (WBeL) concept in to the minds of young India along with various approaches taken or to be taken, associated to it till date besides of instructional design models, different course developmental models, the role of technical writing and merit-demerit of WBeL till date.


A Random Walk Based Model Incorporating Social Information for Recommendations

Abstract: Collaborative filtering (CF) is one of the most popular approaches to build a recommendation system. In this paper, we propose a hybrid collaborative filtering model based on a Makovian random walk to address the data sparsity and cold start problems in recommendation systems. More precisely, we construct a directed graph whose nodes consist of items and users, together with item content, user profile and social network information. We incorporate user's ratings into edge settings in the graph model. The model provides personalized recommendations and predictions to individuals and groups. The proposed algorithms are evaluated on MovieLens and Epinions datasets. Experimental results show that the proposed methods perform well compared with other graph-based methods, especially in the cold start case.


Biff (Bloom Filter) Codes : Fast Error Correction for Large Data Sets

Abstract: Large data sets are increasingly common in cloud and virtualized environments. For example, transfers of multiple gigabytes are commonplace, as are replicated blocks of such sizes. There is a need for fast error-correction or data reconciliation in such settings even when the expected number of errors is small. Motivated by such cloud reconciliation problems, we consider error-correction schemes designed for large data, after explaining why previous approaches appear unsuitable. We introduce Biff codes, which are based on Bloom filters and are designed for large data. For Biff codes with a message of length $L$ and $E$ errors, the encoding time is $O(L)$, decoding time is $O(L + E)$ and the space overhead is $O(E)$. Biff codes are low-density parity-check codes; they are similar to Tornado codes, but are designed for errors instead of erasures. Further, Biff codes are designed to be very simple, removing any explicit graph structures and based entirely on hash tables. We derive Biff codes by a simple reduction from a set reconciliation algorithm for a recently developed data structure, invertible Bloom lookup tables. While the underlying theory is extremely simple, what makes this code especially attractive is the ease with which it can be implemented and the speed of decoding. We present results from a prototype implementation that decodes messages of 1 million words with thousands of errors in well under a second.


A Novel Approach of Color Image Hiding using RGB Color planes and DWT

Abstract: This work proposes a wavelet based Steganographic technique for the color image. The true color cover image and the true color secret image both are decomposed into three separate color planes namely R, G and B. Each plane of the images is decomposed into four sub bands using DWT. Each color plane of the secret image is hidden by alpha blending technique in the corresponding sub bands of the respective color planes of the original image. During embedding, secret image is dispersed within the original image depending upon the alpha value. Extraction of the secret image varies according to the alpha value. In this approach the stego image generated is of acceptable level of imperceptibility and distortion compared to the cover image and the overall security is high.


Efficient Algorithms for Maximum Link Scheduling in Distributed Computing Models with SINR Constraints

Abstract: A fundamental problem in wireless networks is the maximum link scheduling problem: given a set $L$ of links, compute the largest possible subset $L'\subseteq L$ of links that can be scheduled simultaneously without interference. This problem is particularly challenging in the physical interference model based on SINR constraints (referred to as the SINR model), which has gained a lot of interest in recent years. Constant factor approximation algorithms have been developed for this problem, but low complexity distributed algorithms that give the same approximation guarantee in the SINR model are not known. Distributed algorithms are especially challenging in this model, because of its non-locality. In this paper, we develop a set of fast distributed algorithms in the SINR model, providing constant approximation for the maximum link scheduling problem under uniform power assignment. We find that different aspects of available technology, such as full/half-duplex communication, and non-adaptive/adaptive power control, have a significant impact on the performance of the algorithm; these issues have not been explored in the context of distributed algorithms in the SINR model before. Our algorithms' running time is $O(g(L) \log^c m)$, where $c=1,2,3$ for different problem instances, and $g(L)$ is the "link diversity" determined by the logarithmic scale of a communication link length. Since $g(L)$ is small and remains in a constant range in most cases, our algorithms serve as the first set of "sublinear" time distributed solution. The algorithms are randomized and crucially use physical carrier sensing in distributed communication steps.


Implementations of ICT Innovations: A Comparative Analysis in terms of Challenges between Developed and Developing Countries

Abstract: The main aim of this paper is to achieve a depth of understanding of the various similarities and differences in terms of challenges between developed and developing countries and in regards to the implementation of ICT innovations. Indeed, advances in Information and Communication Technologies (ICTs) have brought many innovations to the field of Information Systems (IS). Despite agreements on their importance to the success of organizations, the implementation processes of such innovations are multifaceted and require proper addressing of a wide-spread issues and challenges. In this study, we address this matter by first; synthesizing a comprehensive body of recent and classified literature concerningfive ICTinitiatives,second;analyzing and classifying ICTs challenges forboth developed and developing countries as well as justifying their similarities and differences following thematic analysis qualitative methods, and third; presenting the study conclusions and identifying future research areas drawn upon theconducted comparative analysis.


A Framework of Value Exchange and Role Playing in Web 2.0 WebSites

Abstract: Digitally engaged communities can be described as communities created and evolved within Web 2.0 Websites such as Facebook, Bebo, and Twitter. The growing importance of digitally engaged communities calls for the need to efficiently manage the building blocks of sustaining a healthy community. The initial operation of any digitally-engaged community depends on the existence of its own members, the beneficial values created and exchanged, and the relationships interlinking both. However, the level of contribution and involvement might vary depending on the benefits being gratified from engaging in such communities. In other words, motivations for participating and getting involved are purposive; individuals are driven into joining and /or taking part in any digitallyengaged network for capturing and purtaining certain beneficial values. Accordingly, this paper proposes a framework that classifies the values created and exchanged within these communities as well as the roles adopted and played by users of these communities. Utilizing ethnography as the primay methodological strategy to study Bebo digitally-engaged community, this research identifies five different roles of users: Newbie, Lurker, Novice, Insider, and Leader. Moreover, the research also identifies five value elements that could be captured by different users: Social, Hedonic, Epistemic, Gift, and Utilitarian. The results of this study provides insights for decision and policy makers, service providers, and developers; as it inspires them in knowing and meeting the needs and values of participants based on the roles adopted by users.


Portals and Task Innovation: A Theoretical Framework Founded on Business Intelligence Thinking

Abstract: The main aim of this study is to develop a theoretical framework for the success of Web portals in promoting task innovation. This is deemed significant as yet little research has tackled this important domain from the business intelligence perspective. The D&M IS Success Model was used as a foundational theory and then was refined to match the context of the current research. Importantly, in this study, system quality and information quality constructs were defined on the basis of portals' characteristics since a mapping was conducted between the most significant functions and features of Web portals and quality constructs. The developed framework is deemed useful for theory and practice. From theoretical perspective, the dimensions that affect the perceived quality of Web portals are identified, and the measures that affect each quality dimension are also defined. On the practical level, contributions gained by this study can be observed in terms of the benefits decision makers, strategists, operational employees and IT developers can gain. Assessing portals success in improving task innovation is important to help managers (i.e. decision makers) in making appropriate decisions concerning the adoption of portals' technology, by weighing its benefits against the costs needed to establish and run such a technology. Moreover, assessing Web portals' success gives some insight to IT developers and designers concerning what aspects should be taken when designing and establishing high quality portals, and what functions and features should be contained that would affect the perceived quality of portals and therefore users' intention to use portals.


Link Scheduling for Throughput Maximization in Multihop Wireless Networks Under Physical Interference

Abstract: We consider the problem of link scheduling for throughput maximization in multihop wireless networks. Majority of previous methods are restricted to graph-based interference models. In this paper we study the link scheduling problem using a more realistic physical interference model. Through some key observations about this model, we develop efficient link scheduling algorithms by exploiting the intrinsic connections between the physical interference model and the graph-based interference model. For one variant of the problem where each node can dynamically adjust its transmission power, we design a scheduling method with O(g(E)) approximation to the optimal throughput capacity where g(E) denotes length diversity. For the other variant where each node has a fixed but possible different transmission powers for different nodes, we design a method with O(g(E))-approximation ratio when the transmission powers of all nodes are within a constant factor of each other, and in general with an approximation ratio of O(g(E)log\rho) where log\rho is power diversity. We further prove that our algorithm for fixed transmission power case retains O(g(E)) approximation for any length-monotone, sub-linear fixed power setting. Furthermore, all these approximation factors are independent of network size.


Establishing Virtual R&D Teams: Obliged Policy

Abstract: In a global and technology oriented world the requirements that products and services have to fulfill are increasing and are getting more complicated. Research and development (R&D) is becoming increasingly important in creating the knowledge that makes research and business more competitive. Companies are obliged to produce more rapidly, more effectively and more efficiently. In order to meet these requirements and to secure the viability of business processes, services and products R&D teams need to access and retrieve information from as many sources as possible. From the other perspective virtual teams are important mechanisms for organizations seeking to leverage scarce resources across geographic and other boundaries moreover; virtual collaboration has become vital for most organizations. This is particularly true in the context of designing new product and service innovation. Such collaboration often involves a network of partners located around the world. However at the R&D project level, dealing with such distributed teams challenges both managers and specialists. In new product development, it is necessary to put together the growing different capabilities and services with the goal, through cooperation between suppliers and customers, service providers and scientific institutions to achieve innovations of high quality. In this paper based on comprehensive literature review of recent articles, at the first step provides an primary definition and characterization of virtual R&D team; next, the potential value created by virtual R&D teams for new product development is explored and lastly along with a guide line for future study, it is argued that the establishing of virtual R&D teams should be given consideration in the management of R&D projects.


A Session based Multiple Image Hiding Technique using DWT and DCT

Abstract: This work proposes Steganographic technique for hiding multiple images in a color image based on DWT and DCT. The cover image is decomposed into three separate color planes namely R, G and B. Individual planes are decomposed into subbands using DWT. DCT is applied in HH component of each plane. Secret images are dispersed among the selected DCT coefficients using a pseudo random sequence and a Session key. Secret images are extracted using the session key and the size of the images from the planer decomposed stego image. In this approach the stego image generated is of acceptable level of imperceptibility and distortion compared to the cover image and the overall security is high.


DoS and DDoS in Named-Data Networking

Abstract: With the growing realization that current Internet protocols are reaching the limits of their senescence, a number of on-going research efforts aim to design potential next-generation Internet architectures. Although they vary in maturity and scope, in order to avoid past pitfalls, these efforts seek to treat security and privacy as fundamental requirements. Resilience to Denial-of-Service (DoS) attacks that plague today's Internet is a major issue for any new architecture and deserves full attention. In this paper, we focus on DoS in a specific candidate next-generation Internet architecture called Named-Data Networking (NDN) -- an instantiation of Information-Centric Networking approach. By stressing content dissemination, NDN appears to be attractive and viable approach to many types of current and emerging communication models. It also incorporates some basic security features that mitigate certain attacks. However, NDN's resilience to DoS attacks has not been analyzed to-date. This paper represents the first step towards assessment and possible mitigation of DoS in NDN. After identifying and analyzing several new types of attacks, it investigates their variations, effects and counter-measures. This paper also sheds some light on the long-standing debate about relative virtues of self-certifying, as opposed to human-readable, names.


P = NP

Abstract: The present work proves that P=NP. The proof, presented in this work, is a constructive one: the program of a polynomial time deterministic multi-tape Turing machine M_ExistsAcceptingPath, that determines if there exists an accepting computational path of a polynomial time non-deterministic single-tape Turing machine M_NP, is constructed (machine M_ExistsAcceptingPath is different for each Turing machine M_NP). Machine M_ExistsAcceptingPath is based on reduction to problem LP (linear programming) instead of reduction to problem 3-CNF-SAT which is commonly used. In more detail, machine M_AcceptingPath uses a reduction of the initial string problem to another string problem TCPE (defined in the paper) that is NP-complete and decidable in polynomial time. The time complexity of machine M_ExistsAcceptingPath is O(t(n)^{272}) wherein t(n) is an upper bound of the time complexity of machine M_NP.


Human Activity Learning using Object Affordances from RGB-D Videos

Abstract: Human activities comprise several sub-activities performed in a sequence and involve interactions with various objects. This makes reasoning about the object affordances a central task for activity recognition. In this work, we consider the problem of jointly labeling the object affordances and human activities from RGB-D videos. We frame the problem as a Markov Random Field where the nodes represent objects and sub-activities, and the edges represent the relationships between object affordances, their relations with sub-activities, and their evolution over time. We formulate the learning problem using a structural SVM approach, where labeling over various alternate temporal segmentations are considered as latent variables. We tested our method on a dataset comprising 120 activity videos collected from four subjects, and obtained an end-to-end precision of 81.8% and recall of 80.0% for labeling the activities.


APRIL: Active Preference-learning based Reinforcement Learning

Abstract: This paper focuses on reinforcement learning (RL) with limited prior knowledge. In the domain of swarm robotics for instance, the expert can hardly design a reward function or demonstrate the target behavior, forbidding the use of both standard RL and inverse reinforcement learning. Although with a limited expertise, the human expert is still often able to emit preferences and rank the agent demonstrations. Earlier work has presented an iterative preference-based RL framework: expert preferences are exploited to learn an approximate policy return, thus enabling the agent to achieve direct policy search. Iteratively, the agent selects a new candidate policy and demonstrates it; the expert ranks the new demonstration comparatively to the previous best one; the expert's ranking feedback enables the agent to refine the approximate policy return, and the process is iterated. In this paper, preference-based reinforcement learning is combined with active ranking in order to decrease the number of ranking queries to the expert needed to yield a satisfactory policy. Experiments on the mountain car and the cancer treatment testbeds witness that a couple of dozen rankings enable to learn a competent policy.


Design and implementation of a digital clock showing digits in Bangla font using microcontroller AT89C4051

Abstract: In this paper, a digital clock is designed where the microcontroller is used for timing controller and the font of the Bangla digits are designed, and programmed within the microcontroller. The design is cost effective, simple and easy for maintenance.


An Integrated Aerial Telecommunications Network that Supports Emergency Traffic

Abstract: This paper outlines how an aerial telecommunications network can optimally meet the stringent needs of emergency relief and recovery operations. We propose a novel architecture, made of an integrated and highly dynamic multi-purpose aerial telecommunications infrastructure that can be contextually extended with fast-deploying high or low altitude platforms. In particular, we analyze the interest and challenges of adapting core concepts from substitution networks and controlled mobility mechanisms, so that a base network can be seamlessly augmented, both in terms of capacity and functions. We give an estimation of the emergency traffic supported by the lower altitude platforms in an example scenario and discuss the challenges posed by this architecture, notably in terms of disaster resilience and ability to efficiently provide sustained first responder communications.


Competitive Assessments for HAP Delivery of Mobile Services in Emerging Countries

Abstract: In recent years, network deployment based on High Altitude Platforms (HAPs) has gained momentum through several initiatives where air vehicles and telecommunications payloads have been adapted and refined, resulting in more efficient and less expensive platforms. In this paper, we study HAP as an alternative or complementary fast-evolving technology to provide mobile services in rural areas of emerging countries, where business models need to be carefully tailored to the reality of their related markets. In these large areas with low user density, mobile services uptake is likely to be slowed by a service profitability which is in turn limited by a relatively low average revenue per user. Through three architectures enabling different business roles and using different terrestrial, HAP and satellite backhaul solutions, we devise how to use in an efficient and profitable fashion these multi-purpose aerial platforms, in complement to existing access and backhauling satellite or terrestrial technologies.


Image encryption schemes for JPEG and GIF formats based on 3D baker with compound chaotic sequence generator

Abstract: This paper proposed several methods to transplant the compound chaotic image encryption scheme with permutation based on 3D baker into image formats as Joint Photographic Experts Group (JPEG) and Graphics Interchange Format (GIF). The new method averts the lossy Discrete Cosine Transform and quantization and can encrypt and decrypt JPEG images lossless. Our proposed method for GIF keeps the property of animation successfully. The security test results indicate the proposed methods have high security. Since JPEG and GIF image formats are popular contemporarily, this paper shows that the prospect of chaotic image encryption is promising.


Social Trust as a solution to address sparsity-inherent problems of Recommender systems

Abstract: Trust has been explored by many researchers in the past as a successful solution for assisting recommender systems. Even though the approach of using a web-of-trust scheme for assisting the recommendation production is well adopted, issues like the sparsity problem have not been explored adequately so far with regard to this. In this work we are proposing and testing a scheme that uses the existing ratings of users to calculate the hypothetical trust that might exist between them. The purpose is to demonstrate how some basic social networking when applied to an existing system can help in alleviating problems of traditional recommender system schemes. Interestingly, such schemes are also alleviating the cold start problem from which mainly new users are suffering. In order to show how good the system is in that respect, we measure the performance at various times as the system evolves and we also contrast the solution with existing approaches. Finally, we present the results which justify that such schemes undoubtedly work better than a system that makes no use of trust at all.


Credibility in Web Search Engines

Abstract: Web search engines apply a variety of ranking signals to achieve user satisfaction, i.e., results pages that provide the best-possible results to the user. While these ranking signals implicitly consider credibility (e.g., by measuring popularity), explicit measures of credibility are not applied. In this chapter, credibility in Web search engines is discussed in a broad context: credibility as a measure for including documents in a search engine's index, credibility as a ranking signal, credibility in the context of universal search results, and the possibility of using credibility as an explicit measure for ranking purposes. It is found that while search engines-at least to a certain extent-show credible results to their users, there is no fully integrated credibility framework for Web search engines.


System identification and modeling for interacting and non-interacting tank systems using intelligent techniques

Abstract: System identification from the experimental data plays a vital role for model based controller design. Derivation of process model from first principles is often difficult due to its complexity. The first stage in the development of any control and monitoring system is the identification and modeling of the system. Each model is developed within the context of a specific control problem. Thus, the need for a general system identification framework is warranted. The proposed framework should be able to adapt and emphasize different properties based on the control objective and the nature of the behavior of the system. Therefore, system identification has been a valuable tool in identifying the model of the system based on the input and output data for the design of the controller. The present work is concerned with the identification of transfer function models using statistical model identification, process reaction curve method, ARX model, genetic algorithm and modeling using neural network and fuzzy logic for interacting and non interacting tank process. The identification technique and modeling used is prone to parameter change & disturbance. The proposed methods are used for identifying the mathematical model and intelligent model of interacting and non interacting process from the real time experimental data.


Uncertainty-dependent data collection in vehicular sensor networks

Abstract: Vehicular sensor networks (VSNs) are built on top of vehicular ad-hoc networks (VANETs) by equipping vehicles with sensing devices. These new technologies create a huge opportunity to extend the sensing capabilities of the existing road traffic control systems and improve their performance. Efficient utilisation of wireless communication channel is one of the basic issues in the vehicular networks development. This paper presents and evaluates data collection algorithms that use uncertainty estimates to reduce data transmission in a VSN-based road traffic control system.


An Enciphering Scheme Based on a Card Shuffle

Abstract: We introduce the swap-or-not shuffle and show that the technique gives rise to a new method to convert a pseudorandom function (PRF) into a pseudorandom permutation (PRP) (or, alternatively, to directly build a confusion/diffusion blockcipher). We then prove that swap-or-not has excellent quantitative security bounds, giving a Luby-Rackoff type result that ensures security (assuming an ideal round function) to a number of adversarial queries that is nearly the size of the construction's domain. Swap-or-not provides a direct solution for building a small-domain cipher and achieving format-preserving encryption, yielding the best bounds known for a practical scheme for enciphering credit-card numbers. The analysis of swap-or-not is based on the theory of mixing times of Markov chains.


Payment Rules through Discriminant-Based Classifiers

Abstract: In mechanism design it is typical to impose incentive compatibility and then derive an optimal mechanism subject to this constraint. By replacing the incentive compatibility requirement with the goal of minimizing expected ex post regret, we are able to adapt statistical machine learning techniques to the design of payment rules. This computational approach to mechanism design is applicable to domains with multi-dimensional types and situations where computational efficiency is a concern. Specifically, given an outcome rule and access to a type distribution, we train a support vector machine with a special discriminant function structure such that it implicitly establishes a payment rule with desirable incentive properties. We discuss applications to a multi-minded combinatorial auction with a greedy winner-determination algorithm and to an assignment problem with egalitarian outcome rule. Experimental results demonstrate both that the construction produces payment rules with low ex post regret, and that penalizing classification errors is effective in preventing failures of ex post individual rationality.


Toward an Integrated Framework for Automated Development and Optimization of Online Advertising Campaigns

Abstract: Creating and monitoring competitive and cost-effective pay-per-click advertisement campaigns through the web-search channel is a resource demanding task in terms of expertise and effort. Assisting or even automating the work of an advertising specialist will have an unrivaled commercial value. In this paper we propose a methodology, an architecture, and a fully functional framework for semi- and fully- automated creation, monitoring, and optimization of cost-efficient pay-per-click campaigns with budget constraints. The campaign creation module generates automatically keywords based on the content of the web page to be advertised extended with corresponding ad-texts. These keywords are used to create automatically the campaigns fully equipped with the appropriate values set. The campaigns are uploaded to the auctioneer platform and start running. The optimization module focuses on the learning process from existing campaign statistics and also from applied strategies of previous periods in order to invest optimally in the next period. The objective is to maximize the performance (i.e. clicks, actions) under the current budget constraint. The fully functional prototype is experimentally evaluated on real world Google AdWords campaigns and presents a promising behavior with regards to campaign performance statistics as it outperforms systematically the competing manually maintained campaigns.


Seamless Handover for IMS over Mobile-IPv6 Using Context Transfer

Abstract: Mobility support for the next generation IPv6 networks has been one of the recent research issues due to the growing demand for wireless services over internet. In the other hand, 3GPP has introduced IP Multimedia Subsystem as the next generation IP based infrastructure for wireless and wired multimedia services. In this paper we present two context transfer mechanisms based on predictive and reactive schemes, to support seamless handover in IMS over Mobile IPv6. Those schemes reduce handover latency by transferring appropriate session information between the old and the new access networks. Moreover, we present two methods for QoS parameters negotiations to preserve service quality along the mobile user movement path. The performances of the proposed mechanisms are evaluated by simulations.


An efficient classification in IBE Provide with an improvement of BB2 to an efficient Commutative Blinding scheme

Abstract: Because of the revolution and the success of the technique IBE (Identification Based Encryption) in the recent years. The need is growing to have a standardization to this technology to streamline communication based on it. But this requires a thorough study to extract the strength and weakness of the most recognized cryptosystems. Our first goal in this work is to approach to this standardization, by applying a study which permit to extract the best cryptosystems. As we will see in this work and as Boneh and Boyen said in 2011 (Journal of Cryptology) the BB1 and BB2 are the most efficient schemes in the model selective ID and without random oracle (they are the only schemes traced in this model). This is right as those schemes are secure (under this model), efficient and useful for some applications. Our second goal behind this work is to make an approvement in BB2 to admit a more efficient schemes. We will study the security of our schemes, which is basing on an efficient strong Diffie-Hellman problem compared to BB1 and BB2. More than that our HIBE support s+ID-HIBE compared to BBG (Boneh Boyen Goh). Additionally the ID in our scheme will be in Zp instead of Zp* as with BBG. We will cite more clearly all these statements in in this article.


Building and Maintaining Halls of Fame over a Database

Abstract: Halls of Fame are fascinating constructs. They represent the elite of an often very large amount of entities---persons, companies, products, countries etc. Beyond their practical use as static rankings, changes to them are particularly interesting---for decision making processes, as input to common media or novel narrative science applications, or simply consumed by users. In this work, we aim at detecting events that can be characterized by changes to a Hall of Fame ranking in an automated way. We describe how the schema and data of a database can be used to generate Halls of Fame. In this database scenario, by Hall of Fame we refer to distinguished tuples; entities, whose characteristics set them apart from the majority. We define every Hall of Fame as one specific instance of an SQL query, such that a change in its result is considered a noteworthy event. Identified changes (i.e., events) are ranked using lexicographic tradeoffs over event and query properties and presented to users or fed in higher-level applications. We have implemented a full-fledged prototype system that uses either database triggers or a Java based middleware for event identification. We report on an experimental evaluation using a real-world dataset of basketball statistics.


On fixed-parameter algorithms for Split Vertex Deletion

Abstract: In the Split Vertex Deletion problem, given a graph G and an integer k, we ask whether one can delete k vertices from the graph G to obtain a split graph (i.e., a graph, whose vertex set can be partitioned into two sets: one inducing a clique and the second one inducing an independent set). In this paper we study fixed-parameter algorithms for Split Vertex Deletion parameterized by k: we show that, up to a factor quasipolynomial in k and polynomial in n, the Split Vertex Deletion problem can be solved in the same time as the well-studied Vertex Cover problem. Plugging the currently best fixed-parameter algorithm for Vertex Cover due to Chen et al. [TCS 2010], we obtain an algorithm that solves Split Vertex Deletion in time O(1.2738^k * k^O(log k) + n^O(1)). To achieve our goal, we prove the following structural result that may be of independent interest: for any graph G we may compute a family P of size n^O(log n) containing partitions of V(G) into two parts, such for any two disjoint subsets X_C, X_I of V(G) where G[X_C] is a clique and G[X_I] is an independent set, there is a partition in P which contains all vertices of X_C on one side and all vertices of X_I on the other.


A Polylogarithimic Approximation Algorithm for Edge-Disjoint Paths with Congestion 2

Abstract: In the Edge-Disjoint Paths with Congestion problem (EDPwC), we are given an undirected n-vertex graph G, a collection M={(s_1,t_1),...,(s_k,t_k)} of demand pairs and an integer c. The goal is to connect the maximum possible number of the demand pairs by paths, so that the maximum edge congestion - the number of paths sharing any edge - is bounded by c. When the maximum allowed congestion is c=1, this is the classical Edge-Disjoint Paths problem (EDP). The best current approximation algorithm for EDP achieves an $O(\sqrt n)$-approximation, by rounding the standard multi-commodity flow relaxation of the problem. This matches the $\Omega(\sqrt n)$ lower bound on the integrality gap of this relaxation. We show an $O(poly log k)$-approximation algorithm for EDPwC with congestion c=2, by rounding the same multi-commodity flow relaxation. This gives the best possible congestion for a sub-polynomial approximation of EDPwC via this relaxation. Our results are also close to optimal in terms of the number of pairs routed, since EDPwC is known to be hard to approximate to within a factor of $\tilde{\Omega}((\log n)^{1/(c+1)})$ for any constant congestion c. Prior to our work, the best approximation factor for EDPwC with congestion 2 was $\tilde O(n^{3/7})$, and the best algorithm achieving a polylogarithmic approximation required congestion 14.


The Power of Centralized PC Systems of Pushdown Automata

Abstract: Parallel communicating systems of pushdown automata (PCPA) were introduced in (Csuhaj-Varj{\'u} et. al. 2000) and in their centralized variants shown to be able to simulate nondeterministic one-way multi-head pushdown automata. A claimed converse simulation for returning mode (Balan 2009) turned out to be incomplete (Otto 2012) and a language was suggested for separating these PCPA of degree two (number of pushdown automata) from nondeterministic one-way two-head pushdown automata. We show that the suggested language can be accepted by the latter computational model. We present a different example over a single letter alphabet indeed ruling out the possibility of a simulation between the models. The open question about the power of centralized PCPA working in returning mode is then settled by showing them to be universal. Since the construction is possible using systems of degree two, this also improves the previous bound three for generating all recursively enumerable languages. Finally PCPAs are restricted in such a way that a simulation by multi-head automata is possible.


Data Selection for Semi-Supervised Learning

Abstract: The real challenge in pattern recognition task and machine learning process is to train a discriminator using labeled data and use it to distinguish between future data as accurate as possible. However, most of the problems in the real world have numerous data, which labeling them is a cumbersome or even an impossible matter. Semi-supervised learning is one approach to overcome these types of problems. It uses only a small set of labeled with the company of huge remain and unlabeled data to train the discriminator. In semi-supervised learning, it is very essential that which data is labeled and depend on position of data it effectiveness changes. In this paper, we proposed an evolutionary approach called Artificial Immune System (AIS) to determine which data is better to be labeled to get the high quality data. The experimental results represent the effectiveness of this algorithm in finding these data points.


Securing Instrumented Environments over Content-Centric Networking: the Case of Lighting Control

Abstract: Instrumented environments, such as modern building automation systems (BAS), are becoming commonplace and are increasingly interconnected with (and sometimes by) enterprise networks and the Internet. Regardless of the underlying communication platform, secure control of devices in such environments is a challenging task. The current trend is to move from proprietary communication media and protocols to IP over Ethernet. While the move to IP represents progress, new and different Internet architectures might be better-suited for instrumented environments. In this paper, we consider security of instrumented environments in the context of Content-Centric Networking (CCN). In particular, we focus on building automation over Named-Data Networking (NDN), a prominent instance of CCN. After identifying security requirements in a specific BAS sub-domain (lighting control), we construct a concrete NDN-based security architecture, analyze its properties and report on preliminary implementation and experimental results. We believe in securing a communication paradigm well outside of its claimed forte of content distribution. At the same time, we provide a viable (secure and efficient) communication platform for a class of instrumented environments exemplified by lighting control.


Algorithm for searching bridges of specified types in the protection graph for Take-Grant protection model

Abstract: The article contains the algorithm for searching a certain kind of bridges in the protection graph of Take-Grant model. The proposed algorithm is based on a classical breadth-first search algorithm.


Tracing scientist's research trends realtimely

Abstract: In this research, we propose a method to trace scientists' research trends realtimely. By monitoring the downloads of scientific articles in the journal of Scientometrics for 744 hours, namely one month, we investigate the download statistics. Then we aggregate the keywords in these downloaded research papers, and analyze the trends of article downloading and keyword downloading. Furthermore, taking both the download of keywords and articles into consideration, we design a method to detect the emerging research trends. We find that in scientometrics field, social media, new indices to quantify scientific productivity (g-index), webometrics, semantic, text mining, open access are emerging fields that scientometrics researchers are focusing on.


Performance of MIMO Relay DCSK-CD Systems over Nakagami Fading Channels

Abstract: A multi-access multiple-input multiple-output (MIMO) relay differential chaos shift keying cooperative diversity (DCSK-CD) system is proposed in this paper as a comprehensive cooperation scheme, in which the relay and destination both employ multiple antennas to strengthen the robustness against signal fading in a wireless network. It is shown that, with spatial diversity gains, the bit error rate (BER) performance of the proposed system is remarkably better than the conventional DCSK non-cooperation (DCSK-NC) and DCSK cooperative communication (DCSK-CC) systems. Moreover, the exact BER and close-form expressions of the proposed system are derived over Nakagami fading channels through the moment generating function (MGF), which is shown to be highly consistent with the simulation results. Meanwhile, this paper illustrates a trade-off between the performance and the complexity, and provides a threshold for the number of relay antennas keeping the user consumed energy constant. Due to the above-mentioned advantages, the proposed system stands out as a good candidate or alternative for energy-constrained wireless communications based on chaotic modulation, especially for low-power and low-cost wireless personal area networks (WPANs).


A Locale for Minimal Bad Sequences

Abstract: We present a locale that abstracts over the necessary ingredients for constructing a minimal bad sequence, as required in classical proofs of Higman's lemma and Kruskal's tree theorem.


Getting Started with Isabelle/jEdit in 2018

Abstract: This is a beginner-oriented introduction to Isabelle/jEdit, the main user interface for the proof assistant Isabelle.


Compressed Sensing based Protocol for Efficient Reconstruction of Sparse Superimposed Data in a Multi-Hop Wireless Sensor Network

Abstract: We consider a multi-hop wireless sensor network that measures sparse events and propose a simple forwarding protocol based on Compressed Sensing (CS) which does not need any sophisticated Media Access Control (MAC) scheduling, neither a routing protocol, thereby making significant overhead and energy savings. By means of flooding, multiple packets with different superimposed measurements are received simultaneously at any node. Thanks to our protocol, each node is able to recover each measurement and forward it while avoiding cycles. Numerical results show that our protocol achieves close to zero reconstruction errors at the sink, while greatly reducing overhead. This initial research reveals a new and promising approach to protocol design through CS for wireless mesh and sensor networks.


Deploying Health Monitoring ECU Towards Enhancing the Performance of In-Vehicle Network

Abstract: Electronic Control Units (ECUs) are the fundamental electronic building blocks of any automotive system. They are multi-purpose, multi-chip and multicore computer systems where more functionality is delivered in software rather than hardware. ECUs are valuable assets for the vehicles as critical time bounded messages are communicated through. Looking into the safety criticality, already developed mission critical systems such as ABS, ESP etc, rely fully on electronic components leading to increasing requirements of more reliable and dependable electronic systems in vehicles. Hence it is inevitable to maintain and monitor the health of an ECU which will enable the ECUs to be followed, assessed and improved throughout their life-cycle starting from their inception into the vehicle. In this paper, we propose a Health monitoring ECU that enables the early trouble shooting and servicing of the vehicle prior to any catastrophic failure.


The Best Answers? Think Twice: Online Detection of Commercial Campaigns in the CQA Forums

Abstract: In an emerging trend, more and more Internet users search for information from Community Question and Answer (CQA) websites, as interactive communication in such websites provides users with a rare feeling of trust. More often than not, end users look for instant help when they browse the CQA websites for the best answers. Hence, it is imperative that they should be warned of any potential commercial campaigns hidden behind the answers. However, existing research focuses more on the quality of answers and does not meet the above need. In this paper, we develop a system that automatically analyzes the hidden patterns of commercial spam and raises alarms instantaneously to end users whenever a potential commercial campaign is detected. Our detection method integrates semantic analysis and posters' track records and utilizes the special features of CQA websites largely different from those in other types of forums such as microblogs or news reports. Our system is adaptive and accommodates new evidence uncovered by the detection algorithms over time. Validated with real-world trace data from a popular Chinese CQA website over a period of three months, our system shows great potential towards adaptive online detection of CQA spams.


Dense Subgraphs on Dynamic Networks

Abstract: In distributed networks, it is often useful for the nodes to be aware of dense subgraphs, e.g., such a dense subgraph could reveal dense subtructures in otherwise sparse graphs (e.g. the World Wide Web or social networks); these might reveal community clusters or dense regions for possibly maintaining good communication infrastructure. In this work, we address the problem of self-awareness of nodes in a dynamic network with regards to graph density, i.e., we give distributed algorithms for maintaining dense subgraphs that the member nodes are aware of. The only knowledge that the nodes need is that of the dynamic diameter $D$, i.e., the maximum number of rounds it takes for a message to traverse the dynamic network. For our work, we consider a model where the number of nodes are fixed, but a powerful adversary can add or remove a limited number of edges from the network at each time step. The communication is by broadcast only and follows the CONGEST model. Our algorithms are continuously executed on the network, and at any time (after some initialization) each node will be aware if it is part (or not) of a particular dense subgraph. We give algorithms that ($2 + \epsilon$)-approximate the densest subgraph and ($3 + \epsilon$)-approximate the at-least-$k$-densest subgraph (for a given parameter $k$). Our algorithms work for a wide range of parameter values and run in $O(D\log_{1+\epsilon} n)$ time. Further, a special case of our results also gives the first fully decentralized approximation algorithms for densest and at-least-$k$-densest subgraph problems for static distributed graphs.


Using Tableau to Decide Description Logics with Full Role Negation and Identity

Abstract: This paper presents a tableau approach for deciding expressive description logics with full role negation and role identity. We consider the description logic ALBOid, which is the extension of ALC with the Boolean role operators, inverse of roles, the identity role, and includes full support for individuals and singleton concepts. ALBOid is expressively equivalent to the two-variable fragment of first-order logic with equality and subsumes Boolean modal logic. In this paper we define a sound and complete tableau calculus for the ALBOid that provides a basis for decision procedures for this logic and all its sublogics. An important novelty of our approach is the use of a generic unrestricted blocking mechanism. Being based on a conceptually simple rule, unrestricted blocking performs case distinctions over whether two individuals are equal or not and equality reasoning to find finite models. The blocking mechanism ties the proof of termination of tableau derivations to the finite model property of ALBOid.


Guess Who Rated This Movie: Identifying Users Through Subspace Clustering

Abstract: It is often the case that, within an online recommender system, multiple users share a common account. Can such shared accounts be identified solely on the basis of the user- provided ratings? Once a shared account is identified, can the different users sharing it be identified as well? Whenever such user identification is feasible, it opens the way to possible improvements in personalized recommendations, but also raises privacy concerns. We develop a model for composite accounts based on unions of linear subspaces, and use subspace clustering for carrying out the identification task. We show that a significant fraction of such accounts is identifiable in a reliable manner, and illustrate potential uses for personalized recommendation.


Fuel Efficient Computation in Passive Self-Assembly

Abstract: In this paper we show that passive self-assembly in the context of the tile self-assembly model is capable of performing fuel efficient, universal computation. The tile self-assembly model is a premiere model of self-assembly in which particles are modeled by four-sided squares with glue types assigned to each tile edge. The assembly process is driven by positive and negative force interactions between glue types, allowing for tile assemblies floating in the plane to combine and break apart over time. We refer to this type of assembly model as passive in that the constituent parts remain unchanged throughout the assembly process regardless of their interactions. A computationally universal system is said to be fuel efficient if the number of tiles used up per computation step is bounded by a constant. Work within this model has shown how fuel guzzling tile systems can perform universal computation with only positive strength glue interactions. Recent work has introduced space-efficient, fuel-guzzling universal computation with the addition of negative glue interactions and the use of a powerful non-diagonal class of glue interactions. Other recent work has shown how to achieve fuel efficient computation within active tile self-assembly. In this paper we utilize negative interactions in the tile self-assembly model to achieve the first computationally universal passive tile self-assembly system that is both space and fuel-efficient. In addition, we achieve this result using a limited diagonal class of glue interactions.


Design For Change: Information-Centric Architecture to Support Agile Disaster Response

Abstract: This paper presents a case for the adoption of an information-centric architecture for a global disaster management system. Drawing from a case study of the 2010/2011 Queensland floods, we describe the challenges in providing every participant with relevant and actionable information. We use various examples to argue for a more flexible information dissemination framework which is designed from the ground up to minimise the effort needed to fix the unexpected and unavoidable information acquisition, quality, and dissemination challenges posed by any real disaster.


Low-Cost Bluetooth Mobile Positioning for Location-based Application

Abstract: Bluetooth is a promising short-range radio network technology. We present a low cost and easily deployed, scalable infrastructure for indoor location-based computing of mobile devices based on Bluetooth technology. The system consists of 2 main components, namely the Bluetooth (BT) Sensor System and the Central Navigation System which have been developed using the JDK 6.0. The Bluetooth Sensor System allows mobile devices whose Bluetooth mode is set to discoverable, to be scanned and detected, and they receive customizable text message of their positioning information, e.g. room identity. The positioning information is also sent to the Central Navigation System which in turn displays and updates the navigation map. The system is also used to track the movement of different BT mobile devices within the implemented environment.


CeTA - A Tool for Certified Termination Analysis

Abstract: Since the first termination competition in 2004 it is of great interest, whether a proof that has been automatically generated by a termination tool, is indeed correct. The increasing number of termination proving techniques as well as the increasing complexity of generated proofs (e.g., combinations of several techniques, exhaustive labelings, tree automata, etc.), make certifying (i.e., checking the correctness of) such proofs more and more tedious for humans. Hence the interest in automated certification of termination proofs. This led to the general approach of using proof assistants (like Coq and Isabelle) for certification. We present the latest developments for IsaFoR/CeTA (version 1.03) which is the certifier CeTA, based on the Isabelle/HOL formalization of rewriting IsaFoR.


Certification extends Termination Techniques

Abstract: There are termination proofs that are produced by termination tools for which certifiers are not powerful enough. However, a similar situation also occurs in the other direction. We have formalized termination techniques in a more general setting as they have been introduced. Hence, we can certify proofs using techniques that no termination tool supports so far. In this paper we shortly present two of these formalizations: Polynomial orders with negative constants and Arctic termination.


A Relative Dependency Pair Framework

Abstract: In this paper we generalize the DP framework to a relative DP framework, where a so called split is possible.


Recording Completion for Finding and Certifying Proofs in Equational Logic

Abstract: When we want to answer/certify whether a given equation is entailed by an equational system we face the following problems: (1) It is hard to find a conversion (but easy to certify a given one). (2) Under the assumption that Knuth-Bendix completion is successful, it is easy to decide the existence of a conversion but hard to certify this decision. In this paper we introduce recording completion, which overcomes both problems.


Towards the Certification of Complexity Proofs

Abstract: We report on our formalization of matrix-interpretation in Isabelle/HOL. Matrices are required to certify termination proofs and we wish to utilize them for complexity proofs, too. For the latter aim, only basic methods have already been integrated, and we discuss some upcoming problems which arise when formalizing more complicated results on matrix-interpretations, which are based on Cayley-Hamilton's theorem or joint-spectral radius theory.


A Dynamic Phase Selection Strategy for Satisfiability Solvers

Abstract: The phase selection is an important of a SAT Solver based on conflict-driven DPLL. This paper presents a new phase selection strategy, in which the weight of each literal is defined as the sum of its implied-literals static weights. The implied literals of each literal is computed dynamically during the search. Therefore, it is call a dynamic phase selection strategy. In general, computing dynamically a weight is time-consuming. Hence, so far no SAT solver applies successfully a dynamic phase selection. Since the implied literal of our strategy conforms to that of the search process, the usual two watched-literals scheme can be applied here. Thus, the cost of our dynamic phase selection is very low. To improve Glucose 2.0 which won a Gold Medal for application category at SAT 2011 competition, we build five phase selection schemes using the dynamic phase selection policy. On application instances of SAT 2011, Glucose improved by the dynamic phase selection is significantly better than the original Glucose. We conduct also experiments on Lingeling, using the dynamic phase selection policy, and build two phase selection schemes. Experimental results show that the improved Lingeling is better than the original Lingeling.


Determinacy in Stochastic Games with Unbounded Payoff Functions

Abstract: We consider infinite-state turn-based stochastic games of two players, Box and Diamond, who aim at maximizing and minimizing the expected total reward accumulated along a run, respectively. Since the total accumulated reward is unbounded, the determinacy of such games cannot be deduced directly from Martin's determinacy result for Blackwell games. Nevertheless, we show that these games are determined both for unrestricted (i.e., history-dependent and randomized) strategies and deterministic strategies, and the equilibrium value is the same. Further, we show that these games are generally not determined for memoryless strategies. Then, we consider a subclass of Diamond-finitely-branching games and show that they are determined for all of the considered strategy types, where the equilibrium value is always the same. We also examine the existence and type of (epsilon-)optimal strategies for both players.


Graph Operations on Parity Games and Polynomial-Time Algorithms

Abstract: Parity games are games that are played on directed graphs whose vertices are labeled by natural numbers, called priorities. The players push a token along the edges of the digraph. The winner is determined by the parity of the greatest priority occurring infinitely often in this infinite play. A motivation for studying parity games comes from the area of formal verification of systems by model checking. Deciding the winner in a parity game is polynomial time equivalent to the model checking problem of the modal mu-calculus. Another strong motivation lies in the fact that the exact complexity of solving parity games is a long-standing open problem, the currently best known algorithm being subexponential. It is known that the problem is in the complexity classes UP and coUP. In this paper we identify restricted classes of digraphs where the problem is solvable in polynomial time, following an approach from structural graph theory. We consider three standard graph operations: the join of two graphs, repeated pasting along vertices, and the addition of a vertex. Given a class C of digraphs on which we can solve parity games in polynomial time, we show that the same holds for the class obtained from C by applying once any of these three operations to its elements. These results provide, in particular, polynomial time algorithms for parity games whose underlying graph is an orientation of a complete graph, a complete bipartite graph, a block graph, or a block-cactus graph. These are classes where the problem was not known to be efficiently solvable. Previous results concerning restricted classes of parity games which are solvable in polynomial time include classes of bounded tree-width, bounded DAG-width, and bounded clique-width. We also prove that recognising the winning regions of a parity game is not easier than computing them from scratch.


Fully Proportional Representation as Resource Allocation: Approximability Results

Abstract: We model Monroe's and Chamberlin and Courant's multiwinner voting systems as a certain resource allocation problem. We show that for many restricted variants of this problem, under standard complexity-theoretic assumptions, there are no constant-factor approximation algorithms. Yet, we also show cases where good approximation algorithms exist (briefly put, these variants correspond to optimizing total voter satisfaction under Borda scores, within Monroe's and Chamberlin and Courant's voting systems).


Performance Measurement and Method Analysis (PMMA) for Fingerprint Reconstruction

Abstract: Fingerprint reconstruction is one of the most well-known and publicized biometrics. Because of their uniqueness and consistency over time, fingerprints have been used for identification over a century, more recently becoming automated due to advancements in computed capabilities. Fingerprint reconstruction is popular because of the inherent ease of acquisition, the numerous sources (e.g. ten fingers) available for collection, and their established use and collections by law enforcement and immigration. Fingerprints have always been the most practical and positive means of identification. Offenders, being well aware of this, have been coming up with ways to escape identification by that means. Erasing left over fingerprints, using gloves, fingerprint forgery; are certain examples of methods tried by them, over the years. Failing to prevent themselves, they moved to an extent of mutilating their finger skin pattern, to remain unidentified. This article is based upon obliteration of finger ridge patterns and discusses some known cases in relation to the same, in chronological order; highlighting the reasons why offenders go to an extent of performing such act. The paper gives an overview of different methods and performance measurement of the fingerprint reconstruction.


An Efficient Automatic Attendance System Using Fingerprint Reconstruction Technique

Abstract: Biometric time and attendance system is one of the most successful applications of biometric technology. One of the main advantage of a biometric time and attendance system is it avoids "buddy-punching". Buddy punching was a major loophole which will be exploiting in the traditional time attendance systems. Fingerprint recognition is an established field today, but still identifying individual from a set of enrolled fingerprints is a time taking process. Most fingerprint-based biometric systems store the minutiae template of a user in the database. It has been traditionally assumed that the minutiae template of a user does not reveal any information about the original fingerprint. This belief has now been shown to be false; several algorithms have been proposed that can reconstruct fingerprint images from minutiae templates. In this paper, a novel fingerprint reconstruction algorithm is proposed to reconstruct the phase image, which is then converted into the grayscale image. The proposed reconstruction algorithm reconstructs the phase image from minutiae. The proposed reconstruction algorithm is used to automate the whole process of taking attendance, manually which is a laborious and troublesome work and waste a lot of time, with its managing and maintaining the records for a period of time is also a burdensome task. The proposed reconstruction algorithm has been evaluated with respect to the success rates of type-I attack (match the reconstructed fingerprint against the original fingerprint) and type-II attack (match the reconstructed fingerprint against different impressions of the original fingerprint) using a commercial fingerprint recognition system. Given the reconstructed image from our algorithm, we show that both types of attacks can be effectively launched against a fingerprint recognition system.


Mechanism Design for Time Critical and Cost Critical Task Execution via Crowdsourcing

Abstract: An exciting application of crowdsourcing is to use social networks in complex task execution. In this paper, we address the problem of a planner who needs to incentivize agents within a network in order to seek their help in executing an {\em atomic task} as well as in recruiting other agents to execute the task. We study this mechanism design problem under two natural resource optimization settings: (1) cost critical tasks, where the planner's goal is to minimize the total cost, and (2) time critical tasks, where the goal is to minimize the total time elapsed before the task is executed. We identify a set of desirable properties that should ideally be satisfied by a crowdsourcing mechanism. In particular, {\em sybil-proofness} and {\em collapse-proofness} are two complementary properties in our desiderata. We prove that no mechanism can satisfy all the desirable properties simultaneously. This leads us naturally to explore approximate versions of the critical properties. We focus our attention on approximate sybil-proofness and our exploration leads to a parametrized family of payment mechanisms which satisfy collapse-proofness. We characterize the approximate versions of the desirable properties in cost critical and time critical domain.


Color Assessment and Transfer for Web Pages

Abstract: Colors play a particularly important role in both designing and accessing Web pages. A well-designed color scheme improves Web pages' visual aesthetic and facilitates user interactions. As far as we know, existing color assessment studies focus on images; studies on color assessment and editing for Web pages are rare. This paper investigates color assessment for Web pages based on existing online color theme-rating data sets and applies this assessment to Web color edit. This study consists of three parts. First, we study the extraction of a Web page's color theme. Second, we construct color assessment models that score the color compatibility of a Web page by leveraging machine learning techniques. Third, we incorporate the learned color assessment model into a new application, namely, color transfer for Web pages. Our study combines techniques from computer graphics, Web mining, computer vision, and machine learning. Experimental results suggest that our constructed color assessment models are effective, and useful in the color transfer for Web pages, which has received little attention in both Web mining and computer graphics communities.


Don't Be Strict in Local Search!

Abstract: Local Search is one of the fundamental approaches to combinatorial optimization and it is used throughout AI. Several local search algorithms are based on searching the k-exchange neighborhood. This is the set of solutions that can be obtained from the current solution by exchanging at most k elements. As a rule of thumb, the larger k is, the better are the chances of finding an improved solution. However, for inputs of size n, a na\"ive brute-force search of the k-exchange neighborhood requires n to the power of O(k) time, which is not practical even for very small values of k. Fellows et al. (IJCAI 2009) studied whether this brute-force search is avoidable and gave positive and negative answers for several combinatorial problems. They used the notion of local search in a strict sense. That is, an improved solution needs to be found in the k-exchange neighborhood even if a global optimum can be found efficiently. In this paper we consider a natural relaxation of local search, called permissive local search (Marx and Schlotter, IWPEC 2009) and investigate whether it enhances the domain of tractable inputs. We exemplify this approach on a fundamental combinatorial problem, Vertex Cover. More precisely, we show that for a class of inputs, finding an optimum is hard, strict local search is hard, but permissive local search is tractable. We carry out this investigation in the framework of parameterized complexity.


On Finding Optimal Polytrees

Abstract: Inferring probabilistic networks from data is a notoriously difficult task. Under various goodness-of-fit measures, finding an optimal network is NP-hard, even if restricted to polytrees of bounded in-degree. Polynomial-time algorithms are known only for rare special cases, perhaps most notably for branchings, that is, polytrees in which the in-degree of every node is at most one. Here, we study the complexity of finding an optimal polytree that can be turned into a branching by deleting some number of arcs or nodes, treated as a parameter. We show that the problem can be solved via a matroid intersection formulation in polynomial time if the number of deleted arcs is bounded by a constant. The order of the polynomial time bound depends on this constant, hence the algorithm does not establish fixed-parameter tractability when parameterized by the number of deleted arcs. We show that a restricted version of the problem allows fixed-parameter tractability and hence scales well with the parameter. We contrast this positive result by showing that if we parameterize by the number of deleted nodes, a somewhat more powerful parameter, the problem is not fixed-parameter tractable, subject to a complexity-theoretic assumption.


Ownership Authentication Transfer Protocol for Ubiquitous Computing Devices

Abstract: In ubiquitous computing devices, users tend to store some valuable information in their device. Even though the device can be borrowed by the other user temporarily, it is not safe for any user to borrow or lend the device as it may result the private data of the user to be public. To safeguard the user data and also to preserve user privacy we propose the technique of ownership authentication transfer. The user who is willing to sell the device has to transfer the ownership of the device under sale. Once the device is sold and the ownership has been transferred, the old owner will not be able to use that device at any cost. Either of the users will not be able to use the device if the process of ownership has not been carried out properly. This also takes care of the scenario when the device has been stolen or lost, avoiding the impersonation attack. The proposed protocol has been modeled and verified using Automated Validation of Internet Security Protocols and Applications (AVISPA) and is found to be safe.


Non-cooperative games with preplay negotiations

Abstract: We consider an extension of strategic normal form games with a phase of negotiations before the actual play of the game, where players can make binding offers for transfer of utilities to other players after the play of the game, in order to provide additional incentives for each other to play designated strategies. Such offers are conditional on the recipients playing the specified strategies and they effect transformations of the payoff matrix of the game by accordingly transferring payoffs between players. We introduce and analyze solution concepts for 2-player normal form games with such preplay offers under various assumptions for the preplay negotiation phase and obtain results for existence of efficient negotiation strategies of the players. Then we extend the framework to coalitional preplay offers in N-player games, as well as to extensive form games with inter-play offers for side payments.


RMR-Efficient Randomized Abortable Mutual Exclusion

Abstract: Recent research on mutual exclusion for shared-memory systems has focused on "local spin" algorithms. Performance is measured using the "remote memory references" (RMRs) metric. As common in recent literature, we consider a standard asynchronous shared memory model with N processes, which allows atomic read, write and compare-and-swap (short: CAS) operations. In such a model, the asymptotically tight upper and lower bound on the number of RMRs per passage through the Critical Section is Theta(log N) for the optimal deterministic algorithms (see Yang and Anderson,1995, and Attiya, Hendler and Woelfel, 2008). Recently, several randomized algorithms have been devised that break the Omega(log N) barrier and need only o(log N) RMRs per passage in expectation (see Hendler and Woelfel, 2010, Hendler and Woelfel, 2011, and Bender and Gilbert, 2011). In this paper we present the first randomized "abortable" mutual exclusion algorithm that achieves a sub-logarithmic expected RMR complexity. More precisely, against a weak adversary (which can make scheduling decisions based on the entire past history, but not the latest coin-flips of each process) every process needs an expected number of O(log N/ log log N) RMRs to enter end exit the critical section. If a process receives an abort-signal, it can abort an attempt to enter the critical section within a finite number of its own steps and by incurring O(log N/ log log N) RMRs.


Hybrid systems modeling for gas transmission network

Abstract: Gas Transmission Networks are large-scale complex systems, and corresponding design and control problems are challenging. In this paper, we consider the problem of control and management of these systems in crisis situations. We present these networks by a hybrid systems framework that provides required analysis models. Further, we discuss decision-making using computational discrete and hybrid optimization methods. In particular, several reinforcement learning methods are employed to explore decision space and achieve the best policy in a specific crisis situation. Simulations are presented to illustrate the efficiency of the method.


Guidelines for a Dynamic Ontology - Integrating Tools of Evolution and Versioning in Ontology

Abstract: Ontologies are built on systems that conceptually evolve over time. In addition, techniques and languages for building ontologies evolve too. This has led to numerous studies in the field of ontology versioning and ontology evolution. This paper presents a new way to manage the lifecycle of an ontology incorporating both versioning tools and evolution process. This solution, called VersionGraph, is integrated in the source ontology since its creation in order to make it possible to evolve and to be versioned. Change management is strongly related to the model in which the ontology is represented. Therefore, we focus on the OWL language in order to take into account the impact of the changes on the logical consistency of the ontology like specified in OWL DL.


Transformations of normal form games by preplay offers for payments among players

Abstract: We consider transformations of normal form games by binding preplay offers of players for payments of utility to other players conditional on them playing designated in the offers strategies. The game-theoretic effect of such preplay offers is transformation of the payoff matrix of the game by transferring payoffs between players. Here we analyze and completely characterize the possible transformations of the payoff matrix of a normal form game by sets of preplay offers.


The complexity of approximating conservative counting CSPs

Abstract: We study the complexity of approximately solving the weighted counting constraint satisfaction problem #CSP(F). In the conservative case, where F contains all unary functions, there is a classification known for the case in which the domain of functions in F is Boolean. In this paper, we give a classification for the more general problem where functions in F have an arbitrary finite domain. We define the notions of weak log-modularity and weak log-supermodularity. We show that if F is weakly log-modular, then #CSP(F)is in FP. Otherwise, it is at least as difficult to approximate as #BIS, the problem of counting independent sets in bipartite graphs. #BIS is complete with respect to approximation-preserving reductions for a logically-defined complexity class #RHPi1, and is believed to be intractable. We further sub-divide the #BIS-hard case. If F is weakly log-supermodular, then we show that #CSP(F) is as easy as a (Boolean) log-supermodular weighted #CSP. Otherwise, we show that it is NP-hard to approximate. Finally, we give a full trichotomy for the arity-2 case, where #CSP(F) is in FP, or is #BIS-equivalent, or is equivalent in difficulty to #SAT, the problem of approximately counting the satisfying assignments of a Boolean formula in conjunctive normal form. We also discuss the algorithmic aspects of our classification.


Real-time Data Collection Scheduling in Multi-hop Wireless Sensor Networks

Abstract: We study real time periodic query scheduling for data collection in multihop Wireless Sensor Networks (WSNs). Given a set of heterogenous data collection queries in WSNs, each query requires the data from the source sensor nodes to be collected to the control center within a certain end-to-end delay. We first propose almost-tight necessary conditions for a set of different queries to be schedulable by a WSN. We then develop a family of efficient and effective data collection algorithms that can meet the real-time requirement under resource constraints by addressing three tightly coupled tasks: (1) routing tree construction for data collection, (2) link activity scheduling, and (3) packet-level scheduling. Our theoretical analysis for the schedulability of these algorithms show that they can achieve a constant fraction of the maximum schedulable load. For the case of overloaded networks where not all queries can be possibly satisfied, we propose an efficient approximation algorithm to select queries to maximize the total weight of selected schedulable queries. The simulations corroborate our theoretical analysis.


Analysis of Trim Commands on Overprovisioning and Write Amplification in Solid State Drives

Abstract: This paper presents a performance model of the ATA/ATAPI SSD Trim command under various types of user workloads, including a uniform random workload, a workload with hot and cold data, and a workload with N temperatures of data. We first examine the Trim-modified uniform random workload to predict utilization, then use this result to compute the resultant level of effective overprovisioning. This allows modification of models previously suggested to predict write amplification of a non-Trim uniform random workload under greedy garbage collection. Finally, we expand the theory to cover a workload consisting of hot and cold data (and also N temperatures of data), providing formulas to predict write amplification in these scenarios.


Self-Organizing Time Map: An Abstraction of Temporal Multivariate Patterns

Abstract: This paper adopts and adapts Kohonen's standard Self-Organizing Map (SOM) for exploratory temporal structure analysis. The Self-Organizing Time Map (SOTM) implements SOM-type learning to one-dimensional arrays for individual time units, preserves the orientation with short-term memory and arranges the arrays in an ascending order of time. The two-dimensional representation of the SOTM attempts thus twofold topology preservation, where the horizontal direction preserves time topology and the vertical direction data topology. This enables discovering the occurrence and exploring the properties of temporal structural changes in data. For representing qualities and properties of SOTMs, we adapt measures and visualizations from the standard SOM paradigm, as well as introduce a measure of temporal structural changes. The functioning of the SOTM, and its visualizations and quality and property measures, are illustrated on artificial toy data. The usefulness of the SOTM in a real-world setting is shown on poverty, welfare and development indicators.


Metric Learning across Heterogeneous Domains by Respectively Aligning Both Priors and Posteriors

Abstract: In this paper, we attempts to learn a single metric across two heterogeneous domains where source domain is fully labeled and has many samples while target domain has only a few labeled samples but abundant unlabeled samples. To the best of our knowledge, this task is seldom touched. The proposed learning model has a simple underlying motivation: all the samples in both the source and the target domains are mapped into a common space, where both their priors P(sample)s and their posteriors P(label|sample)s are forced to be respectively aligned as much as possible. We show that the two mappings, from both the source domain and the target domain to the common space, can be reparameterized into a single positive semi-definite(PSD) matrix. Then we develop an efficient Bregman Projection algorithm to optimize the PDS matrix over which a LogDet function is used to regularize. Furthermore, we also show that this model can be easily kernelized and verify its effectiveness in crosslanguage retrieval task and cross-domain object recognition task.


Margin Distribution Controlled Boosting

Abstract: Schapire's margin theory provides a theoretical explanation to the success of boosting-type methods and manifests that a good margin distribution (MD) of training samples is essential for generalization. However the statement that a MD is good is vague, consequently, many recently developed algorithms try to generate a MD in their goodness senses for boosting generalization. Unlike their indirect control over MD, in this paper, we propose an alternative boosting algorithm termed Margin distribution Controlled Boosting (MCBoost) which directly controls the MD by introducing and optimizing a key adjustable margin parameter. MCBoost's optimization implementation adopts the column generation technique to ensure fast convergence and small number of weak classifiers involved in the final MCBooster. We empirically demonstrate: 1) AdaBoost is actually also a MD controlled algorithm and its iteration number acts as a parameter controlling the distribution and 2) the generalization performance of MCBoost evaluated on UCI benchmark datasets is validated better than those of AdaBoost, L2Boost, LPBoost, AdaBoost-CG and MDBoost.


Scaling Multiple-Source Entity Resolution using Statistically Efficient Transfer Learning

Abstract: We consider a serious, previously-unexplored challenge facing almost all approaches to scaling up entity resolution (ER) to multiple data sources: the prohibitive cost of labeling training data for supervised learning of similarity scores for each pair of sources. While there exists a rich literature describing almost all aspects of pairwise ER, this new challenge is arising now due to the unprecedented ability to acquire and store data from online sources, features driven by ER such as enriched search verticals, and the uniqueness of noisy and missing data characteristics for each source. We show on real-world and synthetic data that for state-of-the-art techniques, the reality of heterogeneous sources means that the number of labeled training data must scale quadratically in the number of sources, just to maintain constant precision/recall. We address this challenge with a brand new transfer learning algorithm which requires far less training data (or equivalently, achieves superior accuracy with the same data) and is trained using fast convex optimization. The intuition behind our approach is to adaptively share structure learned about one scoring problem with all other scoring problems sharing a data source in common. We demonstrate that our theoretically motivated approach incurs no runtime cost while it can maintain constant precision/recall with the cost of labeling increasing only linearly with the number of sources.


Stereo Acoustic Perception based on Real Time Video Acquisition for Navigational Assistance

Abstract: A smart navigation system (an Electronic Travel Aid) based on an object detection mechanism has been designed to detect the presence of obstacles that immediately impede the path, by means of real time video processing. The algorithm can be used for any general purpose navigational aid. This paper is discussed, keeping in mind the navigation of the visually impaired, and is not limited to the same. A video camera feeds images of the surroundings to a Da- Vinci Digital Media Processor, DM642, which works on the video, frame by frame. The processor carries out image processing techniques whose result contains information about the object in terms of image pixels. The algorithm aims to select the object which, among all others, poses maximum threat to the navigation. A database containing a total of three sounds is constructed. Hence, each image translates to a beep, where every beep informs the navigator of the obstacles directly in front of him. This paper implements an algorithm that is more efficient as compared to its predecessors.


Semantic Web Techniques for Yellow Page Service Providers

Abstract: Use of web pages providing unstructured information poses variety of problems to the user, such as use of arbitrary formats, unsuitability for machine processing and likely incompleteness of information. Structured data alleviates these problems but we require more. Very often yellow page systems are implemented using a centralized database. In some cases, human intermediaries accessible over the phone network examine a centralized database and use their reasoning ability to deal with the user's need for information. Scaling up such systems is difficult. This paper explores an alternative - a highly distributed system design meeting a variety of needs - considerably reducing efforts required at a central organization, enabling large numbers of vendors to enter information about their own products and services, enabling end-users to contribute information such as their own ratings, using an ontology to describe each domain of application in a flexible manner for uses foreseen and unforeseen, enabling distributed search and mash-ups, use of vendor independent standards, using reasoning to find the best matches to a given query, geo-spatial reasoning and a simple, interactive, mobile application/interface. We give importance to geo-spatial information and mobile applications because of the very wide-spread use of mobile phones and their inherent ability to provide some information about the current location of the user. We have created a prototype using the Jena Toolkit and geo-spatial extensions to SPARQL. We have tested this prototype by asking a group of typical users to use it and to provide structured feedback. We have summarized this feedback in the paper. We believe that the technology can be applied in many contexts in addition to yellow page systems.


Bittorrent Network Traffic Forecasting With ARMA

Abstract: In recent years, there are some major changes in the way content is being distributed over the network. The content distribution techniques have recently started to embrace peer-to-peer (P2P) systems as an alternative to the traditional client-server architecture. P2P systemsthat are based on the BitTorrent protocol uses end-users' resources to provide a cost effective distribution of bandwidth intensive content to thousands of users. The BitTorrent protocol system offers a scalable mechanism for distributing a large volume of data to a set of peers over the Internet. With the growing demand for file sharing and content distribution, BitTorrent has become one of the most popular Internet applications and contributes to a signification fraction of the Internet traffic. With the wide usage of the BitTorrent protocol system, it has basically solved one of the major problems where data can be quickly transferred to a group of interested parties. The strength of the BitTorrent protocol lies in efficient bandwidth utilization for the downloading and uploading processes. However, the usage of BitTorrent protocol also causes latency for other applications in terms of network bandwidth which in turn has caused concerns for the Internet Service Providers, who strives for quality of service for all their customers. In this paper, we study the network traffic patterns of theBitTorrent network traffic and investigate its behavior by usingthe time series ARMA model. Our experimental results show that BitTorrent network traffic can be modeled and forecasted by using ARMA models. We compared and evaluated the forecasted network traffic with the real traffic patterns. This modeling can be utilized by the Internet Service Providers to manage their network bandwidth and also detect any abnormality in their network.


Message Embedded cipher using 2-D chaotic map

Abstract: This paper constructs two encryption methods using 2-D chaotic maps, Duffings and Arnold's cat maps respectively. Both of the methods are designed using message embedded scheme and are analyzed for their validity, for plaintext sensitivity, key sensitivity, known plaintext and brute-force attacks. Due to the less key space generally many chaotic cryptosystem developed are found to be weak against Brute force attack which is an essential issue to be solved. For this issue, concept of identifiability proved to be a necessary condition to be fulfilled by the designed chaotic cipher to resist brute force attack, which is a basic attack. As 2-D chaotic maps provide more key space than 1-D maps thus they are considered to be more suitable. This work is accompanied with analysis results obtained from these developed cipher. Moreover, identifiable keys are searched for different input texts at various key values. The methods are found to have good key sensitivity and possess identifiable keys thus concluding that they can resist linear attacks and brute-force attacks.


Batch Spreadsheet for C Programmers

Abstract: A computing environment is proposed, based on batch spreadsheet processing, which produces a spreadsheet display from plain text input files of commands, similar to the way documents are created using LaTeX. In this environment, besides the usual spreadsheet rows and columns of cells, variables can be defined and are stored in a separate symbol table. Cell and symbol formulas may contain cycles, and cycles which converge can be used to implement iterative algorithms. Formulas are specified using the syntax of the C programming language, and all of C's numeric operators are supported, with operators such as ++, +=, etc. being implicitly cyclic. User-defined functions can be written in C and are accessed using a dynamic link library. The environment can be combined with a GUI front-end processor to enable easier interaction and graphics including plotting.