Verifying Safety Properties With the TLA+ Proof System

Abstract: TLAPS, the TLA+ proof system, is a platform for the development and mechanical verification of TLA+ proofs written in a declarative style requiring little background beyond elementary mathematics. The language supports hierarchical and non-linear proof construction and verification, and it is independent of any verification tool or strategy. A Proof Manager uses backend verifiers such as theorem provers, proof assistants, SMT solvers, and decision procedures to check TLA+ proofs. This paper documents the first public release of TLAPS, distributed with a BSD-like license. It handles almost all the non-temporal part of TLA+ as well as the temporal reasoning needed to prove standard safety properties, in particular invariance and step simulation, but not liveness properties.


Recursive Sketching For Frequency Moments

Abstract: In a ground-breaking paper, Indyk and Woodruff (STOC 05) showed how to compute $F_k$ (for $k>2$) in space complexity $O(\mbox{\em poly-log}(n,m)\cdot n^{1-\frac2k})$, which is optimal up to (large) poly-logarithmic factors in $n$ and $m$, where $m$ is the length of the stream and $n$ is the upper bound on the number of distinct elements in a stream. The best known lower bound for large moments is $\Omega(\log(n)n^{1-\frac2k})$. A follow-up work of Bhuvanagiri, Ganguly, Kesh and Saha (SODA 2006) reduced the poly-logarithmic factors of Indyk and Woodruff to $O(\log^2(m)\cdot (\log n+ \log m)\cdot n^{1-{2\over k}})$. Further reduction of poly-log factors has been an elusive goal since 2006, when Indyk and Woodruff method seemed to hit a natural "barrier." Using our simple recursive sketch, we provide a different yet simple approach to obtain a $O(\log(m)\log(nm)\cdot (\log\log n)^4\cdot n^{1-{2\over k}})$ algorithm for constant $\epsilon$ (our bound is, in fact, somewhat stronger, where the $(\log\log n)$ term can be replaced by any constant number of $\log $ iterations instead of just two or three, thus approaching $log^*n$. Our bound also works for non-constant $\epsilon$ (for details see the body of the paper). Further, our algorithm requires only $4$-wise independence, in contrast to existing methods that use pseudo-random generators for computing large frequency moments.


Reductions Between Expansion Problems

Abstract: The Small-Set Expansion Hypothesis (Raghavendra, Steurer, STOC 2010) is a natural hardness assumption concerning the problem of approximating the edge expansion of small sets in graphs. This hardness assumption is closely connected to the Unique Games Conjecture (Khot, STOC 2002). In particular, the Small-Set Expansion Hypothesis implies the Unique Games Conjecture (Raghavendra, Steurer, STOC 2010). Our main result is that the Small-Set Expansion Hypothesis is in fact equivalent to a variant of the Unique Games Conjecture. More precisely, the hypothesis is equivalent to the Unique Games Conjecture restricted to instance with a fairly mild condition on the expansion of small sets. Alongside, we obtain the first strong hardness of approximation results for the Balanced Separator and Minimum Linear Arrangement problems. Before, no such hardness was known for these problems even assuming the Unique Games Conjecture. These results not only establish the Small-Set Expansion Hypothesis as a natural unifying hypothesis that implies the Unique Games Conjecture, all its consequences and, in addition, hardness results for other problems like Balanced Separator and Minimum Linear Arrangement, but our results also show that the Small-Set Expansion Hypothesis problem lies at the combinatorial heart of the Unique Games Conjecture. The key technical ingredient is a new way of exploiting the structure of the Unique Games instances obtained from the Small-Set Expansion Hypothesis via (Raghavendra, Steurer, 2010). This additional structure allows us to modify standard reductions in a way that essentially destroys their local-gadget nature. Using this modification, we can argue about the expansion in the graphs produced by the reduction without relying on expansion properties of the underlying Unique Games instance (which would be impossible for a local-gadget reduction).


Rademacher Chaos, Random Eulerian Graphs and The Sparse Johnson-Lindenstrauss Transform

Abstract: The celebrated dimension reduction lemma of Johnson and Lindenstrauss has numerous computational and other applications. Due to its application in practice, speeding up the computation of a Johnson-Lindenstrauss style dimension reduction is an important question. Recently, Dasgupta, Kumar, and Sarlos (STOC 2010) constructed such a transform that uses a sparse matrix. This is motivated by the desire to speed up the computation when applied to sparse input vectors, a scenario that comes up in applications. The sparsity of their construction was further improved by Kane and Nelson (ArXiv 2010). We improve the previous bound on the number of non-zero entries per column of Kane and Nelson from $O(1/\epsilon \log(1/\delta)\log(k/\delta))$ (where the target dimension is $k$, the distortion is $1\pm \epsilon$, and the failure probability is $\delta$) to $$ O\left({1\over\epsilon} \left({\log(1/\delta)\log\log\log(1/\delta) \over \log\log(1/\delta)}\right)^2\right). $$ We also improve the amount of randomness needed to generate the matrix. Our results are obtained by connecting the moments of an order 2 Rademacher chaos to the combinatorial properties of random Eulerian multigraphs. Estimating the chance that a random multigraph is composed of a given number of node-disjoint Eulerian components leads to a new tail bound on the chaos. Our estimates may be of independent interest, and as this part of the argument is decoupled from the analysis of the coefficients of the chaos, we believe that our methods can be useful in the analysis of other chaoses.


A Formal Model for Dynamically Adaptable Services

Abstract: The growing complexity of software systems as well as changing conditions in their operating environment demand systems that are more flexible, adaptive and dependable. The service-oriented computing paradigm is in widespread use to support such adaptive systems, and, in many domains, adaptations may occur dynamically and in real time. In addition, services from heterogeneous, possibly unknown sources may be used. This motivates a need to ensure the correct behaviour of the adapted systems, and its continuing compliance to time bounds and other QoS properties. The complexity of dynamic adaptation (DA) is significant, but currently not well understood or formally specified. This paper elaborates a well-founded model and theory of DA, introducing formalisms written using COWS. The model is evaluated for reliability and responsiveness properties with the model checker CMC.


Decidability Classes for Mobile Agents Computing

Abstract: We establish a classification of decision problems that are to be solved by mobile agents operating in unlabeled graphs, using a deterministic protocol. The classification is with respect to the ability of a team of agents to solve the problem, possibly with the aid of additional information. In particular, our focus is on studying differences between the decidability of a decision problem by agents and its verifiability when a certificate for a positive answer is provided to the agents. We show that the class MAV of mobile agents verifiable problems is much wider than the class MAD of mobile agents decidable problems. Our main result shows that there exist natural MAV-complete problems: the most difficult problems in this class, to which all problems in MAV are reducible. Our construction of a MAV-complete problem involves two main ingredients in mobile agents computability: the topology of the quotient graph and the number of operating agents. Beyond the class MAV we show that, for a single agent, three natural oracles yield a strictly increasing chain of relative decidability classes.


A Solution to the P versus NP Problem

Abstract: The relationship between the complexity classes P and NP is a question that has not yet been answered by the Theory of Computation. The existence of a language in NP, proven not to belong to P, is sufficient evidence to establish the separation of P from NP. If a language is not recursive, it can't belong to the complexity class NP. We find a problem in NP which is not in P; because if it would be present in that class, then it will imply that some undecidable problem will be in NP too. That's why it can be confirmed by reduction ad absurdum the following result: P doesn't equal NP. This new problem named Certifying is to find a possible input given a particular deterministic Turing machine named Certified Turing machine and its output.


Compensating Interpolation Distortion by New Optimized Modular Method

Abstract: A modular method was suggested before to recover a band limited signal from the sample and hold and linearly interpolated (or, in general, an nth-order-hold) version of the regular samples. In this paper a novel approach for compensating the distortion of any interpolation based on modular method has been proposed. In this method the performance of the modular method is optimized by adding only some simply calculated coefficients. This approach causes drastic improvement in terms of SNRs with fewer modules compared to the classical modular method. Simulation results clearly confirm the improvement of the proposed method and also its superior robustness against additive noise.


Efficient K-Nearest Neighbor Join Algorithms for High Dimensional Sparse Data

Abstract: The K-Nearest Neighbor (KNN) join is an expensive but important operation in many data mining algorithms. Several recent applications need to perform KNN join for high dimensional sparse data. Unfortunately, all existing KNN join algorithms are designed for low dimensional data. To fulfill this void, we investigate the KNN join problem for high dimensional sparse data. In this paper, we propose three KNN join algorithms: a brute force (BF) algorithm, an inverted index-based(IIB) algorithm and an improved inverted index-based(IIIB) algorithm. Extensive experiments on both synthetic and real-world datasets were conducted to demonstrate the effectiveness of our algorithms for high dimensional sparse data.


System Virtualization and Efficient ID Transmission Method for RFID Tag Infrastructure Network

Abstract: The use of RFID tag which identifies a thing and an object will be expanded with progress of ubiquitous society, and it is necessary to study how to construct RFID network system as a social infrastructure like the Internet. First, this paper proposes the virtualization method of RFID tag network system to enable the same physical RFID network system to be used by multiple different service systems. The system virtualization not only reduces the system cost but also can dramatically reduce the installation space of physical readers and the operation cost. It is proposed that all equipments in the RFID network system except RFID tag could be shared with the conventional virtual technologies. Then, this paper proposes the conditional tag ID processing and the efficient tag ID transmission method which can greatly reduce the processing time and processing load in RFID tag Infrastructure network The conditional tag ID processing allows that tag ID is valid only at a certain time zone of day or in a certain area. The efficient tag ID transmission method uses the virtual network address of the service center as a part of the ID of an RF tag, which allows the direct ID forwarding to the service center.


Improved Minimum Cuts and Maximum Flows in Undirected Planar Graphs

Abstract: In this paper we study minimum cut and maximum flow problems on planar graphs, both in static and in dynamic settings. First, we present an algorithm that given an undirected planar graph computes the minimum cut between any two given vertices in O(n log log n) time. Second, we show how to achieve the same O(n log log n) bound for the problem of computing maximum flows in undirected planar graphs. To the best of our knowledge, these are the first algorithms for those two problems that break the O(n log n) barrier, which has been standing for more than 25 years. Third, we present a fully dynamic algorithm that is able to maintain information about minimum cuts and maximum flows in a plane graph (i.e., a planar graph with a fixed embedding): our algorithm is able to insert edges, delete edges and answer min-cut and max-flow queries between any pair of vertices in O(n^(2/3) log^3 n) time per operation. This result is based on a new dynamic shortest path algorithm for planar graphs which may be of independent interest. We remark that this is the first known non-trivial algorithm for min-cut and max-flow problems in a dynamic setting.


Data Fusion Based Interference Matrix Generation for Cellular System Frequency Planning

Abstract: Interference matrix (IM) has been widely used in frequency planning/optimization of cellular systems because it describes the interaction between any two cells. IM is generated from the source data gathered from the cellular system, either mobile measurement reports (MMRs) or drive test (DT) records. IM accuracy is not satisfactory since neither MMRs nor DT records contain complete information on interference and traffic distribution. In this paper, two IM generation algorithms based on source data fusion are proposed. Data fusion in one algorithm is to reinforce MMRs data, using the frequency-domain information of DT data from the same region. Data fusion in another algorithm is to reshape DT data, using the traffic distribution information extracted from MMRs from the same region. The fused data contains more complete information so that more accurate IM can be obtained. Simulation results have validated this conclusion.


Web Conferencing Traffic - An Analysis using DimDim as Example

Abstract: In this paper, we present an evaluation of the Ethernet traffic for host and attendees of the popular opensource web conferencing system DimDim. While traditional Internet-centric approaches such as the MBONE have been used over the past decades, current trends for web-based conference systems make exclusive use of application-layer multicast. To allow for network dimensioning and QoS provisioning, an understanding of the underlying traffic characteristics is required. We find in our exemplary evaluations that the host of a web conference session produces a large amount of Ethernet traffic, largely due to the required control of the conference session, that is heavily-tailed distributed and exhibits additionally long-range dependence. For different groups of activities within a web conference session, we find distinctive characteristics of the generated traffic.


Reducing Higher Order Pi-Calculus to Spatial Logics

Abstract: In this paper, we show that theory of processes can be reduced to the theory of spatial logic. Firstly, we propose a spatial logic SL for higher order pi-calculus, and give an inference system of SL. The soundness and incompleteness of SL are proved. Furthermore, we show that the structure congruence relation and one-step transition relation can be described as the logical relation of SL formulae. We also extend bisimulations for processes to that for SL formulae. Then we extend all definitions and results of SL to a weak semantics version of SL, called WL. At last, we add mu-operator to SL. This new logic is named muSL. We show that WL is a sublogic of muSL and replication operator can be expressed in muSL.


Reified unit resolution and the failed literal rule

Abstract: Unit resolution can simplify a CNF formula or detect an inconsistency by repeatedly assign the variables occurring in unit clauses. Given any CNF formula sigma, we show that there exists a satisfiable CNF formula psi with size polynomially related to the size of sigma such that applying unit resolution to psi simulates all the effects of applying it to sigma. The formula psi is said to be the reified counterpart of sigma. This approach can be used to prove that the failed literal rule, which is an inference rule used by some SAT solvers, can be entirely simulated by unit resolution. More generally, it sheds new light on the expressive power of unit resolution.


Emoticonsciousness

Abstract: A temporal analysis of emoticon use in Swedish, Italian, German and English asynchronous electronic communication is reported. Emoticons are classified as positive, negative and neutral. Postings to newsgroups over a 66 week period are considered. The aggregate analysis of emoticon use in newsgroups for science and politics tend on the whole to be consistent over the entire time period. Where possible, events that coincide with divergences from trends in language-subject pairs are noted. Political discourse in Italian over the period shows marked use of negative emoticons, and in Swedish, positive emoticons.


A Survey of System Security in Contactless Electronic Passports

Abstract: A traditional paper-based passport contains a Machine- Readable Zone (MRZ) and a Visual Inspection Zone (VIZ). The MRZ has two lines of the holder's personal data, some document data, and verification characters encoded using the Optical Character Recognition font B (OCRB). The encoded data includes the holder's name, date of birth, and other identifying information for the holder or the document. The VIZ contains the holder's photo and signature, usually on the data page. However, the MRZ and VIZ can be easily duplicated with normal document reproduction technology to produce a fake passport which can pass traditional verification. Neither of these features actively verify the holder's identity; nor do they bind the holder's identity to the document. A passport also contains pages for stamps of visas and of country entry and exit dates, which can be easily altered to produce fake permissions and travel records. The electronic passport, supporting authentication using secure credentials on a tamper-resistant chip, is an attempt to improve on the security of the paper-based passport at minimum cost. This paper surveys the security mechanisms built into the firstgeneration of authentication mechanisms and compares them with second-generation passports. It analyzes and describes the cryptographic protocols used in Basic Access Control (BAC) and Extended Access Control (EAC).


A Distributed Clustering Algorithm for Dynamic Networks

Abstract: We propose an algorithm that builds and maintains clusters over a network subject to mobility. This algorithm is fully decentralized and makes all the different clusters grow concurrently. The algorithm uses circulating tokens that collect data and move according to a random walk traversal scheme. Their task consists in (i) creating a cluster with the nodes it discovers and (ii) managing the cluster expansion; all decisions affecting the cluster are taken only by a node that owns the token. The size of each cluster is maintained higher than $m$ nodes ($m$ is a parameter of the algorithm). The obtained clustering is locally optimal in the sense that, with only a local view of each clusters, it computes the largest possible number of clusters (\emph{ie} the sizes of the clusters are as close to $m$ as possible). This algorithm is designed as a decentralized control algorithm for large scale networks and is mobility-adaptive: after a series of topological changes, the algorithm converges to a clustering. This recomputation only affects nodes in clusters in which topological changes happened, and in adjacent clusters.


The Hamiltonian Syllogistic

Abstract: This paper undertakes a re-examination of Sir William Hamilton's doctrine of the quantification of the predicate. Hamilton's doctrine comprises two theses. First, the predicates of traditional syllogistic sentence-forms contain implicit existential quantifiers, so that, for example, "All p are q" is to be understood as "All p are some q". Second, these implicit quantifiers can be meaningfully dualized to yield novel sentence-forms, such as, for example, "All p are all q". Hamilton attempted to provide a deductive system for his language, along the lines of the classical syllogisms. We show, using techniques unavailable to Hamilton, that such a system does exist, though with qualifications that distinguish it from its classical counterpart.


Bounded Multivariate Surfaces On Monovariate Internal Functions

Abstract: Combining the properties of monovariate internal functions as proposed in Kolmogorov superimposition theorem, in tandem with the bounds wielded by the multivariate formulation of Chebyshev inequality, a hybrid model is presented, that decomposes images into homogeneous probabilistically bounded multivariate surfaces. Given an image, the model shows a novel way of working on reduced image representation while processing and capturing the interaction among the multidimensional information that describes the content of the same. Further, it tackles the practical issues of preventing leakage by bounding the growth of surface and reducing the problem sample size. The model if used, also sheds light on how the Chebyshev parameter relates to the number of pixels and the dimensionality of the feature space that associates with a pixel. Initial segmentation results on the Berkeley image segmentation benchmark indicate the effectiveness of the proposed decomposition algorithm.


Classification with Scattering Operators

Abstract: A scattering vector is a local descriptor including multiscale and multi-direction co-occurrence information. It is computed with a cascade of wavelet decompositions and complex modulus. This scattering representation is locally translation invariant and linearizes deformations. A supervised classification algorithm is computed with a PCA model selection on scattering vectors. State of the art results are obtained for handwritten digit recognition and texture classification.


Distributed Verification and Hardness of Distributed Approximation

Abstract: We study the {\em verification} problem in distributed networks, stated as follows. Let $H$ be a subgraph of a network $G$ where each vertex of $G$ knows which edges incident on it are in $H$. We would like to verify whether $H$ has some properties, e.g., if it is a tree or if it is connected. We would like to perform this verification in a decentralized fashion via a distributed algorithm. The time complexity of verification is measured as the number of rounds of distributed communication. In this paper we initiate a systematic study of distributed verification, and give almost tight lower bounds on the running time of distributed verification algorithms for many fundamental problems such as connectivity, spanning connected subgraph, and $s-t$ cut verification. We then show applications of these results in deriving strong unconditional time lower bounds on the {\em hardness of distributed approximation} for many classical optimization problems including minimum spanning tree, shortest paths, and minimum cut. Many of these results are the first non-trivial lower bounds for both exact and approximate distributed computation and they resolve previous open questions. Moreover, our unconditional lower bound of approximating minimum spanning tree (MST) subsumes and improves upon the previous hardness of approximation bound of Elkin [STOC 2004] as well as the lower bound for (exact) MST computation of Peleg and Rubinovich [FOCS 1999]. Our result implies that there can be no distributed approximation algorithm for MST that is significantly faster than the current exact algorithm, for {\em any} approximation factor. Our lower bound proofs show an interesting connection between communication complexity and distributed computing which turns out to be useful in establishing the time complexity of exact and approximate distributed computation of many problems.


Leakage-Aware Reallocation for Periodic Real-Time Tasks on Multicore Processors

Abstract: It is an increasingly important issue to reduce the energy consumption of computing systems. In this paper, we consider partition based energy-aware scheduling of periodic real-time tasks on multicore processors. The scheduling exploits dynamic voltage scaling (DVS) and core sleep scheduling to reduce both dynamic and leakage energy consumption. If the overhead of core state switching is non-negligible, however, the performance of this scheduling strategy in terms of energy efficiency might degrade. To achieve further energy saving, we extend the static task scheduling with run-time task reallocation. The basic idea is to aggregate idle time among cores so that as many cores as possible could be put into sleep in a way that the overall energy consumption is reduced. Simulation results show that the proposed approach results in up to 20% energy saving over traditional leakage-aware DVS.


Design and Implementation of a Wireless Sensor Network for Smart Homes

Abstract: Wireless sensor networks (WSNs) have become indispensable to the realization of smart homes. The objective of this paper is to develop such a WSN that can be used to construct smart home systems. The focus is on the design and implementation of the wireless sensor node and the coordinator based on ZigBee technology. A monitoring system is built by taking advantage of the GPRS network. To support multi-hop communications, an improved routing algorithm based on the Dijkstra algorithm is presented. Preliminary simulations have been conducted to evaluate the performance of the algorithm.


R-CA: A Routing-based Dynamic Channel Assignment Algorithm for Wireless Mesh Networks

Abstract: Even though channel assignment has been studied for years, the performance of most IEEE 802.11-based multi-hop wireless networks such as wireless sensor network (WSN), wireless mesh network (WMN), mobile ad hoc network (MANET) is limited by channel interference. Properly assigning orthogonal channels to wireless links can improve the throughput of multi-hop networks. To solve the dynamic channel assignment problem, a routing-based channel assignment algorithm called R-CA is proposed. R-CA can allocate channels for wireless nodes when needed and free channels after data transmission. Thus more channel resource can be explored by wireless nodes. Simulation results show that R-CA can effectively enhance the network throughput and packet delivery rate.


Decentralized Inter-User Interference Suppression in Body Sensor Networks with Non-cooperative Game

Abstract: Body Sensor Networks (BSNs) provide continuous health monitoring and analysis of physiological parameters. A high degree of Quality-of-Service (QoS) for BSN is extremely required. Inter-user interference is introduced by the simultaneous communication of BSNs congregating in the same area. In this paper, a decentralized inter-user interference suppression algorithm for BSN, namely DISG, is proposed. Each BSN measures the SINR from other BSNs and then adaptively selects the suitable channel and transmission power. By utilizing non-cooperative game theory and no regret learning algorithm, DISG provides an adaptive inter-user interference suppression strategy. The correctness and effectiveness of DISG is theoretically proved, and the experimental results show that DISG can reduce the effect of inter-user interference effectively.


A High-confidence Cyber-Physical Alarm System: Design and Implementation

Abstract: Most traditional alarm systems cannot address security threats in a satisfactory manner. To alleviate this problem, we developed a high-confidence cyber-physical alarm system (CPAS), a new kind of alarm systems. This system establishes the connection of the Internet (i.e. TCP/IP) through GPRS/CDMA/3G. It achieves mutual communication control among terminal equipments, human machine interfaces and users by using the existing mobile communication network. The CPAS will enable the transformation in alarm mode from traditional one-way alarm to two-way alarm. The system has been successfully applied in practice. The results show that the CPAS could avoid false alarms and satisfy residents' security needs.


A Trust Model Based on Service Classification in Mobile Services

Abstract: Internet of Things (IoT) and B3G/4G communication are promoting the pervasive mobile services with its advanced features. However, security problems are also baffled the development. This paper proposes a trust model to protect the user's security. The billing or trust operator works as an agent to provide a trust authentication for all the service providers. The services are classified by sensitive value calculation. With the value, the user's trustiness for corresponding service can be obtained. For decision, three trust regions are divided, which is referred to three ranks: high, medium and low. The trust region tells the customer, with his calculated trust value, which rank he has got and which authentication methods should be used for access. Authentication history and penalty are also involved with reasons.


A Practical Localization Algorithm Based on Wireless Sensor Networks

Abstract: Many localization algorithms and systems have been developed by means of wireless sensor networks for both indoor and outdoor environments. To achieve higher localization accuracy, extra hardware equipments are utilized by most of the existing localization algorithms, which increase the cost and greatly limit the range of location-based applications. In this paper we present a method which can effectively meet different localization accuracy requirements of most indoor and outdoor location services in realistic applications. Our algorithm is composed of two phases: partition phase, in which the target region is split into small grids and localization refinement phase in which a higher accuracy location can be generated by applying a trick algorithm. A realistic demo system using our algorithm has been developed to illustrate its feasibility and availability. The results show that our algorithm can improve the localization accuracy.


A Clustering-based Location Privacy Protection Scheme for Pervasive Computing

Abstract: In pervasive computing environments, Location- Based Services (LBSs) are becoming increasingly important due to continuous advances in mobile networks and positioning technologies. Nevertheless, the wide deployment of LBSs can jeopardize the location privacy of mobile users. Consequently, providing safeguards for location privacy of mobile users against being attacked is an important research issue. In this paper a new scheme for safeguarding location privacy is proposed. Our approach supports location K-anonymity for a wide range of mobile users with their own desired anonymity levels by clustering. The whole area of all users is divided into clusters recursively in order to get the Minimum Bounding Rectangle (MBR). The exact location information of a user is replaced by his MBR. Privacy analysis shows that our approach can achieve high resilience to location privacy threats and provide more privacy than users expect. Complexity analysis shows clusters can be adjusted in real time as mobile users join or leave. Moreover, the clustering algorithms possess strong robustness.


iZone: A Location-Based Mobile Social Networking System

Abstract: The rapid development of wireless technology, the extensive use of mobile phones and the availability of location information are facilitating personalized location-based applications. Easy to carry, easy to use and easy to buy, smart phones with certain software are of great advantage. Consequently, mobile social networking (MSN) systems have emerged rapidly, being a revolution for our everyday life. Based on the analysis of general requirements of MSN and location-based services (LBS), this paper presents the design of iZone, a mobile social networking system, as well as a prototype implementation. This platform exploits mobile GIS (Geographic Information Systems), LBS and J2ME technologies, combining geographical data to display map on mobile phones. It can provide a number of social networking services via smartphones.


A New Fuzzy MCDM Framework to Evaluate E-Government Security Strategy

Abstract: Ensuring security of e-government applications and infrastructures is crucial to maintain trust among stakeholders to store, process and exchange information over the e-government systems. Due to dynamic and continuous threats on e-government information security, policy makers need to perform evaluation on existing information security strategy as to deliver trusted e-government services. This paper presents an information security evaluation framework based on new fuzzy multi criteria decision making (MCDM) to help policy makers conduct comprehensive assessment of e-government security strategy.


Cyber-Physical Control over Wireless Sensor and Actuator Networks with Packet Loss

Abstract: There is a growing interest in design and implementation of cyber-physical control systems over wireless sensor and actuator networks (WSANs). Thanks to the use of wireless communications and distributed architectures, these systems encompass many advantages as compared to traditional networked control systems using hard wirelines. While WSANs are enabling a new generation of control systems, they also introduce considerable challenges for quality-of-service (QoS) provisioning. In this chapter we examine some of the major QoS challenges raised by WSANs, including resource constraints, platform heterogeneity, dynamic network topology, and mixed traffic. These challenges make it difficult to fulfill the requirements of cyber-physical control in terms of reliability and real-time. The focus of this chapter is on addressing the problem of network reliability. Specifically, we analyze the behavior of wireless channels via simulations based on a realistic link-layer model. Packet loss rate (PLR) is taken as a major metric for the analysis. The results confirm the unreliability of wireless communications and the uncertainty of packet loss over WSANs. To tackle packet loss, we present a simple solution that can take advantage of existing prediction algorithms. Simulations are conducted to evaluate the performance of several classical prediction algorithms used for packet loss compensation. The results give some insights into how to deal with packet loss in cyber-physical control systems over unreliable WSANs.


An Adaptive Fault-Tolerant Communication Scheme for Body Sensor Networks

Abstract: A high degree of reliability for critical data transmission is required in body sensor networks (BSNs). However, BSNs are usually vulnerable to channel impairments due to body fading effect and RF interference, which may potentially cause data transmission to be unreliable. In this paper, an adaptive and flexible fault-tolerant communication scheme for BSNs, namely AFTCS, is proposed. AFTCS adopts a channel bandwidth reservation strategy to provide reliable data transmission when channel impairments occur. In order to fulfill the reliability requirements of critical sensors, fault-tolerant priority and queue are employed to adaptively adjust the channel bandwidth allocation. Simulation results show that AFTCS can alleviate the effect of channel impairments, while yielding lower packet loss rate and latency for critical sensors at runtime.


The Local Emergence and Global Diffusion of Research Technologies: An Exploration of Patterns of Network Formation

Abstract: Grasping the fruits of "emerging technologies" is an objective of many government priority programs in a knowledge-based and globalizing economy. We use the publication records (in the Science Citation Index) of two emerging technologies to study the mechanisms of diffusion in the case of two innovation trajectories: small interference RNA (siRNA) and nano-crystalline solar cells (NCSC). Methods for analyzing and visualizing geographical and cognitive diffusion are specified as indicators of different dynamics. Geographical diffusion is illustrated with overlays to Google Maps; cognitive diffusion is mapped using an overlay to a map based on the ISI Subject Categories. The evolving geographical networks show both preferential attachment and small-world characteristics. The strength of preferential attachment decreases over time, while the network evolves into an oligopolistic control structure with small-world characteristics. The transition from disciplinary-oriented ("mode-1") to transfer-oriented ("mode-2") research is suggested as the crucial difference in explaining the different rates of diffusion between siRNA and NCSC.


E-net models for distribution, access and use of resources in security information systems

Abstract: This paper presents solutions for distribution, access and use of resources in information security systems. The solutions comprise the authors' experience in development and implementation of systems for information security in the Automated Information Systems. The models, the methods and the modus operandi are being explained.


Slightly smaller splitter networks

Abstract: The classic renaming protocol of Moir and Anderson (1995) uses a network of Theta(n^2) splitters to assign unique names to n processes with unbounded initial names. We show how to reduce this bound to Theta(n^{3/2}) splitters.


The Data Replication Method for the Classification with Reject Option

Abstract: Classification is one of the most important tasks of machine learning. Although the most well studied model is the two-class problem, in many scenarios there is the opportunity to label critical items for manual revision, instead of trying to automatically classify every item. In this paper we adapt a paradigm initially proposed for the classification of ordinal data to address the classification problem with reject option. The technique reduces the problem of classifying with reject option to the standard two-class problem. The introduced method is then mapped into support vector machines and neural networks. Finally, the framework is extended to multiclass ordinal data with reject option. An experimental study with synthetic and real data sets, verifies the usefulness of the proposed approach.


Stochastic Analysis of a Churn-Tolerant Structured Peer-to-Peer Scheme

Abstract: We present and analyze a simple and general scheme to build a churn (fault)-tolerant structured Peer-to-Peer (P2P) network. Our scheme shows how to "convert" a static network into a dynamic distributed hash table(DHT)-based P2P network such that all the good properties of the static network are guaranteed with high probability (w.h.p). Applying our scheme to a cube-connected cycles network, for example, yields a $O(\log N)$ degree connected network, in which every search succeeds in $O(\log N)$ hops w.h.p., using $O(\log N)$ messages, where $N$ is the expected stable network size. Our scheme has an constant storage overhead (the number of nodes responsible for servicing a data item) and an $O(\log N)$ overhead (messages and time) per insertion and essentially no overhead for deletions. All these bounds are essentially optimal. While DHT schemes with similar guarantees are already known in the literature, this work is new in the following aspects: (1) It presents a rigorous mathematical analysis of the scheme under a general stochastic model of churn and shows the above guarantees; (2) The theoretical analysis is complemented by a simulation-based analysis that validates the asymptotic bounds even in moderately sized networks and also studies performance under changing stable network size; (3) The presented scheme seems especially suitable for maintaining dynamic structures under churn efficiently. In particular, we show that a spanning tree of low diameter can be efficiently maintained in constant time and logarithmic number of messages per insertion or deletion w.h.p. Keywords: P2P Network, DHT Scheme, Churn, Dynamic Spanning Tree, Stochastic Analysis.


Truthfulness via Proxies

Abstract: This short note exhibits a truthful-in-expectation $O(\frac {\log m} {\log \log m})$-approximation mechanism for combinatorial auctions with subadditive bidders that uses polynomial communication.


Towards Increase in Quality by Preprocessed Source Code and Measurement Analysis of Software Applications

Abstract: In this paper two intensive problems faced during software application's analysis and development process arose by the software industry are briefly conversed i.e. identification of fault proneness and increase in rate of variability in the source code of traditional and product line applications. To contribute in the field of software application analysis and development, and to mitigate the aforementioned hurdles, a measurement analysis based approach is discussed in this paper. Furthermore, a prototype is developed based on the concepts of discussed approach i.e. analyzing preprocessed source code characteristics, identifying additional level of complexities using several procedural and object oriented source code measures and visualizing obtained results in different diagrams e.g. bar charts, file maps and graphs etc. Developed prototype is discussed in detail in this paper and validated by means of an experiment as well.


Integration of Flexible Web Based GUI in I-SOAS

Abstract: It is necessary to improve the concepts of the present web based graphical user interface for the development of more flexible and intelligent interface to provide ease and increase the level of comfort at user end like most of the desktop based applications. This research is conducted targeting the goal of implementing flexible GUI consisting of a visual component manager with different components by functionality, design and purpose. In this research paper we present a Rich Internet Application (RIA) based graphical user interface for web based product development, and going into the details we present a comparison between existing RIA Technologies, adopted methodology in the GUI development and developed prototype.


Integration of Agile Ontology Mapping towards NLP Search in I-SOAS

Abstract: In this research paper we address the importance of Product Data Management (PDM) with respect to its contributions in industry. Moreover we also present some currently available major challenges to PDM communities and targeting some of these challenges we present an approach i.e. I-SOAS, and briefly discuss how this approach can be helpful in solving the PDM community's faced problems. Furthermore, limiting the scope of this research to one challenge, we focus on the implementation of a semantic based search mechanism in PDM Systems. Going into the details, at first we describe the respective field i.e. Language Technology (LT), contributing towards natural language processing, to take advantage in implementing a search engine capable of understanding the semantic out of natural language based search queries. Then we discuss how can we practically take advantage of LT by implementing its concepts in the form of software application with the use of semantic web technology i.e. Ontology. Later, in the end of this research paper, we briefly present a prototype application developed with the use of concepts of LT towards semantic based search.


Improved Social Welfare Bounds for GSP at Equilibrium

Abstract: The Generalized Second Price auction is the primary method by which sponsered search advertisements are sold. We study the performance of this auction under various equilibrium concepts. In particular, we demonstrate that the Bayesian Price of Anarchy is at most $2(1-1/e)^{-1} \approx 3.16$, significantly improving upon previously known bounds. Our techniques are intuitively straightforward and extend in a number of ways. For one, our result extends to a bound on the performance of GSP at coarse correlated equilibria, which captures (for example) a repeated-auction setting in which agents apply regret-minimizing bidding strategies. In addition, our analysis is robust against the presence of byzantine agents who cannot be assumed to participate rationally. Additionally, we present tight bounds for the social welfare obtained at pure NE for the special case of an auction for 3 slots, and discuss potential methods for extending this analysis to an arbitrary number of slots.


Bayesian Based Comment Spam Defending Tool

Abstract: Spam messes up user's inbox, consumes network resources and spread worms and viruses. Spam is flooding of unsolicited, unwanted e mail. Spam in blogs is called blog spam or comment spam.It is done by posting comments or flooding spams to the services such as blogs, forums,news,email archives and guestbooks. Blog spams generally appears on guestbooks or comment pages where spammers fill a comment box with spam words. In addition to wasting user's time with unwanted comments, spam also consumes a lot of bandwidth. In this paper, we propose a software tool to prevent such blog spams by using Bayesian Algorithm based technique. It is derived from Bayes' Theorem. It gives an output which has a probability that any comment is spam, given that it has certain words in it. With using our past entries and a comment entry, this value is obtained and compared with a threshold value to find if it exceeds the threshold value or not. By using this concept, we developed a software tool to block comment spam. The experimental results show that the Bayesian based tool is working well. This paper has the major findings and their significance of blog spam filter.


Bisimulations for Nondeterministic Labeled Markov Processes

Abstract: We extend the theory of labeled Markov processes with internal nondeterminism, a fundamental concept for the further development of a process theory with abstraction on nondeterministic continuous probabilistic systems. We define nondeterministic labeled Markov processes (NLMP) and provide three definition of bisimulations: a bisimulation following a traditional characterization, a state based bisimulation tailored to our "measurable" non-determinism, and an event based bisimulation. We show the relation between them, including that the largest state bisimulation is also an event bisimulation. We also introduce a variation of the Hennessy-Milner logic that characterizes event bisimulation and that is sound w.r.t. the other bisimulations for arbitrary NLMP. This logic, however, is infinitary as it contains a denumerable $\lor$. We then introduce a finitary sublogic that characterize all bisimulations for image finite NLMP whose underlying measure space is also analytic. Hence, in this setting, all notions of bisimulation we deal with turn out to be equal. Finally, we show that all notions of bisimulations are different in the general case. The counterexamples that separate them turn to be non-probabilistic NLMP.


Multi-core: Adding a New Dimension to Computing

Abstract: Invention of Transistors in 1948 started a new era in technology, called Solid State Electronics. Since then, sustaining development and advancement in electronics and fabrication techniques has caused the devices to shrink in size and become smaller, paving the quest for increasing density and clock speed. That quest has suddenly come to a halt due to fundamental bounds applied by physical laws. But, demand for more and more computational power is still prevalent in the computing world. As a result, the microprocessor industry has started exploring the technology along a different dimension. Speed of a single work unit (CPU) is no longer the concern, rather increasing the number of independent processor cores packed in a single package has become the new concern. Such processors are commonly known as multi-core processors. Scaling the performance by using multiple cores has gained so much attention from the academia and the industry, that not only desktops, but also laptops, PDAs, cell phones and even embedded devices today contain these processors. In this paper, we explore state of the art technologies for multi-core processors and existing software tools to support parallelism. We also discuss present and future trend of research in this field. From our survey, we conclude that next few decades are going to be marked by the success of this "Ubiquitous parallel processing".


The Inverse Task of the Reflexive Game Theory: Theoretical Matters, Practical Applications and Relationship with Other Issues

Abstract: The Reflexive Game Theory (RGT) has been recently proposed by Vladimir Lefebvre to model behavior of individuals in groups. The goal of this study is to introduce the Inverse task. We consider methods of solution together with practical applications. We present a brief overview of the RGT for easy understanding of the problem. We also develop the schematic representation of the RGT inference algorithms to create the basis for soft- and hardware solutions of the RGT tasks. We propose a unified hierarchy of schemas to represent humans and robots. This hierarchy is considered as a unified framework to solve the entire spectrum of the RGT tasks. We conclude by illustrating how this framework can be applied for modeling of mixed groups of humans and robots. All together this provides the exhaustive solution of the Inverse task and clearly illustrates its role and relationships with other issues considered in the RGT.


Reducing the Number of Annotations in a Verification-oriented Imperative Language

Abstract: Automated software verification is a very active field of research which has made enormous progress both in theoretical and practical aspects. Recently, an important amount of research effort has been put into applying these techniques on top of mainstream programming languages. These languages typically provide powerful features such as reflection, aliasing and polymorphism which are handy for practitioners but, in contrast, make verification a real challenge. In this work we present Pest, a simple experimental, while-style, multiprocedural, imperative programming language which was conceived with verifiability as one of its main goals. This language forces developers to concurrently think about both the statements needed to implement an algorithm and the assertions required to prove its correctness. In order to aid programmers, we propose several techniques to reduce the number and complexity of annotations required to successfully verify their programs. In particular, we show that high-level iteration constructs may alleviate the need for providing complex loop annotations.


The emergence of the physical world from information processing

Abstract: This paper links the conjecture that the physical world is a virtual reality to the findings of modern physics. What is usually the subject of science fiction is here proposed as a scientific theory open to empirical evaluation. We know from physics how the world behaves, and from computing how information behaves, so whether the physical world arises from ongoing information processing is a question science can evaluate. A prima facie case for the virtual reality conjecture is presented. If a photon is a pixel on a multi-dimensional grid that gives rise to space, the speed of light could reflect its refresh rate. If mass, charge and energy all arise from processing, the many conservation laws of physics could reduce to a single law of dynamic information conservation. If the universe is a virtual reality, then its big bang creation could be simply when the system was booted up. Deriving core physics from information processing could reconcile relativity and quantum theory, with the former how processing creates the space-time operating system and the latter how it creates energy and matter applications.


Worst case efficient single and multiple string matching in the Word-RAM model

Abstract: In this paper, we explore worst-case solutions for the problems of single and multiple matching on strings in the word RAM model with word length w. In the first problem, we have to build a data structure based on a pattern p of length m over an alphabet of size sigma such that we can answer to the following query: given a text T of length n, where each character is encoded using log(sigma) bits return the positions of all the occurrences of p in T (in the following we refer by occ to the number of reported occurrences). For the multi-pattern matching problem we have a set S of d patterns of total length m and a query on a text T consists in finding all positions of all occurrences in T of the patterns in S. As each character of the text is encoded using log sigma bits and we can read w bits in constant time in the RAM model, we assume that we can read up to (w/log sigma) consecutive characters of the text in one time step. This implies that the fastest possible query time for both problems is O((n(log sigma/w)+occ). In this paper we present several different results for both problems which come close to that best possible query time. We first present two different linear space data structures for the first and second problem: the first one answers to single pattern matching queries in time O(n(1/m+log sigma/w)+occ) while the second one answers to multiple pattern matching queries to O(n((log d+log y+log log d)/y+log sigma/w)+occ) where y is the length of the shortest pattern in the case of multiple pattern-matching. We then show how a simple application of the four russian technique permits to get data structures with query times independent of the length of the shortest pattern (the length of the only pattern in case of single string matching) at the expense of using more space.


Generic Modal Cut Elimination Applied to Conditional Logics

Abstract: We develop a general criterion for cut elimination in sequent calculi for propositional modal logics, which rests on absorption of cut, contraction, weakening and inversion by the purely modal part of the rule system. Our criterion applies also to a wide variety of logics outside the realm of normal modal logic. We give extensive example instantiations of our framework to various conditional logics. For these, we obtain fully internalised calculi which are substantially simpler than those known in the literature, along with leaner proofs of cut elimination and complexity. In one case, conditional logic with modus ponens and conditional excluded middle, cut elimination and complexity were explicitly stated as open in the literature.


Counting Colours in Compressed Strings

Abstract: Suppose we are asked to preprocess a string \(s [1..n]\) such that later, given a substring's endpoints, we can quickly count how many distinct characters it contains. In this paper we give a data structure for this problem that takes \(n H_0 (s) + \Oh{n} + \oh{n H_0 (s)}\) bits, where \(H_0 (s)\) is the 0th-order empirical entropy of $s$, and answers queries in $\Oh{\log^{1 + \epsilon} n}$ time for any constant \(\epsilon > 0\). We also show how our data structure can be made partially dynamic.


Distributed Construction of the Critical Geometric Graph in Dense Wireless Sensor Networks

Abstract: Wireless sensor networks are often modeled in terms of a dense deployment of smart sensor nodes in a two-dimensional region. Give a node deployment, the \emph{critical geometric graph (CGG)} over these locations (i.e., the connected \emph{geometric graph (GG)} with the smallest radius) is a useful structure since it provides the most accurate proportionality between hop-count and Euclidean distance. Hence, it can be used for GPS-free node localisation as well as minimum distance packet forwarding. It is also known to be asymptotically optimal for network transport capacity and power efficiency. In this context, we propose DISCRIT, a distributed and asynchronous algorithm for obtaining an approximation of the CGG on the node locations. The algorithm does not require the knowledge of node locations or internode distances, nor does it require pair-wise RSSI (Received Signal Strength Indication) measurements to be made. Instead, the algorithm makes use of successful Hello receipt counts (obtained during a Hello-protocol-based neighbour discovery process) as edge weights, along with a simple distributed min-max computation algorithm. In this paper, we first provide the theory for justifying the use of the above edge weights. Then we provide extensive simulation results to demonstrate the efficacy of DISCRIT in obtaining an approximation of the CGG. Finally, we show how the CGG obtained from DISCRIT performs when used in certain network self-organisation algorithms.


Pattern Kits

Abstract: Suppose we have just performed searches in a self-index for two patterns $A$ and $B$ and now we want to search for their concatenation \A B); how can we best make use of our previous computations? In this paper we consider this problem and, more generally, how we can store a dynamic library of patterns that we can easily manipulate in interesting ways. We give a space- and time-efficient data structure for this problem that is compatible with many of the best self-indexes.


Program Size and Temperature in Self-Assembly

Abstract: Winfree's abstract Tile Assembly Model (aTAM) is a model of molecular self-assembly of DNA complexes known as tiles, which float freely in solution and attach one at a time to a growing "seed" assembly based on specific binding sites on their four sides. We show that there is a polynomial-time algorithm that, given an n x n square, finds the minimal tile system (i.e., the system with the smallest number of distinct tile types) that uniquely self-assembles the square, answering an open question of Adleman, Cheng, Goel, Huang, Kempe, Moisset de Espanes, and Rothemund ("Combinatorial Optimization Problems in Self-Assembly", STOC 2002). Our investigation leading to this algorithm reveals other positive and negative results about the relationship between the size of a tile system and its "temperature" (the binding strength threshold required for a tile to attach).


Linearity in the non-deterministic call-by-value setting

Abstract: We consider the non-deterministic extension of the call-by-value lambda calculus, which corresponds to the additive fragment of the linear-algebraic lambda-calculus. We define a fine-grained type system, capturing the right linearity present in such formalisms. After proving the subject reduction and the strong normalisation properties, we propose a translation of this calculus into the System F with pairs, which corresponds to a non linear fragment of linear logic. The translation provides a deeper understanding of the linearity in our setting.


A Probabilistic Approach for Learning Folksonomies from Structured Data

Abstract: Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach to learning complex structures is to integrate many smaller, incomplete and noisy structure fragments. In this work, we present an unsupervised probabilistic approach that extends affinity propagation to combine the small ontological fragments into a collection of integrated, consistent, and larger folksonomies. This is a challenging task because the method must aggregate similar structures while avoiding structural inconsistencies and handling noise. We validate the approach on a real-world social media dataset, comprised of shallow personal hierarchies specified by many individual users, collected from the photosharing website Flickr. Our empirical results show that our proposed approach is able to construct deeper and denser structures, compared to an approach using only the standard affinity propagation algorithm. Additionally, the approach yields better overall integration quality than a state-of-the-art approach based on incremental relational clustering.


Technology Choices and Pricing Policies in Public and Private Wireless Networks

Abstract: This paper studies the provision of a wireless network by a monopolistic provider who may be either benevolent (seeking to maximize social welfare) or selfish (seeking to maximize provider profit). The paper addresses questions that do not seem to have been studied before in the engineering literature on wireless networks: Under what circumstances is it feasible for a provider, either benevolent or selfish, to operate a network in such a way as to cover costs? How is the optimal behavior of a benevolent provider different from the optimal behavior of a selfish provider, and how does this difference affect social welfare? And, most importantly, how does the medium access control (MAC) technology influence the answers to these questions? To address these questions, we build a general model, and provide analysis and simulations for simplified but typical scenarios; the focus in these scenarios is on the contrast between the outcomes obtained under carrier-sensing multiple access (CSMA) and outcomes obtained under time-division multiple access (TDMA). Simulation results demonstrate that differences in MAC technology can have a significant effect on social welfare, on provider profit, and even on the (financial) feasibility of a wireless network.


Fast GPGPU Data Rearrangement Kernels using CUDA

Abstract: Many high performance-computing algorithms are bandwidth limited, hence the need for optimal data rearrangement kernels as well as their easy integration into the rest of the application. In this work, we have built a CUDA library of fast kernels for a set of data rearrangement operations. In particular, we have built generic kernels for rearranging m dimensional data into n dimensions, including Permute, Reorder, Interlace/De-interlace, etc. We have also built kernels for generic Stencil computations on a two-dimensional data using templates and functors that allow application developers to rapidly build customized high performance kernels. All the kernels built achieve or surpass best-known performance in terms of bandwidth utilization.


Approaching Throughput-optimality in Distributed CSMA Scheduling Algorithms with Collisions

Abstract: It was shown recently that CSMA (Carrier Sense Multiple Access)-like distributed algorithms can achieve the maximal throughput in wireless networks (and task processing networks) under certain assumptions. One important, but idealized assumption is that the sensing time is negligible, so that there is no collision. In this paper, we study more practical CSMA-based scheduling algorithms with collisions. First, we provide a Markov chain model and give an explicit throughput formula which takes into account the cost of collisions and overhead. The formula has a simple form since the Markov chain is "almost" time-reversible. Second, we propose transmission-length control algorithms to approach throughput optimality in this case. Sufficient conditions are given to ensure the convergence and stability of the proposed algorithms. Finally, we characterize the relationship between the CSMA parameters (such as the maximum packet lengths) and the achievable capacity region.


Optimizing real-time RDF data streams

Abstract: The Resource Description Framework (RDF) provides a common data model for the integration of "real-time" social and sensor data streams with the Web and with each other. While there exist numerous protocols and data formats for exchanging dynamic RDF data, or RDF updates, these options should be examined carefully in order to enable a Semantic Web equivalent of the high-throughput, low-latency streams of typical Web 2.0, multimedia, and gaming applications. This paper contains a brief survey of RDF update formats and a high-level discussion of both TCP and UDP-based transport protocols for updates. Its main contribution is the experimental evaluation of a UDP-based architecture which serves as a real-world example of a high-performance RDF streaming application in an Internet-scale distributed environment.


Stabilizing data-link over non-FIFO channels with optimal fault-resilience

Abstract: Self-stabilizing systems have the ability to converge to a correct behavior when started in any configuration. Most of the work done so far in the self-stabilization area assumed either communication via shared memory or via FIFO channels. This paper is the first to lay the bases for the design of self-stabilizing message passing algorithms over unreliable non-FIFO channels. We propose a fault-send-deliver optimal stabilizing data-link layer that emulates a reliable FIFO communication channel over unreliable capacity bounded non-FIFO channels.


Linear lambda Calculus with Explicit Substitutions as Proof-Search in Deep Inference

Abstract: SBV is a deep inference system that extends the set of logical operators of multiplicative linear logic with the non commutative operator Seq. We introduce the logical system SBVr which extends SBV by adding a self-dual atom-renaming operator to it. We prove that the cut elimination holds on SBVr. SBVr and its cut free subsystem BVr are complete and sound with respect to linear lambda calculus with explicit substitutions. Under any strategy, a sequence of evaluation steps of any linear lambda-term M becomes a process of proof-search in SBVr (BVr) once M is mapped into a formula of SBVr. Completeness and soundness follow from simulating linear beta-reduction with explicit substitutions as processes. The role of the new renaming operator of SBVr is to rename channel-names on-demand. This simulates the substitution that occurs in a beta-reduction. Despite SBVr is a minimal extension of SBV its proof-search can compute all boolean functions, as linear lambda-calculus with explicit substitutions can compute all boolean functions as well. So, proof search of SBVr and BVr is at least ptime-complete.


Directed Spanners via Flow-Based Linear Programs

Abstract: We examine directed spanners through flow-based linear programming relaxations. We design an $\~O(n^{2/3})$-approximation algorithm for the directed $k$-spanner problem that works for all $k\geq 1$, which is the first sublinear approximation for arbitrary edge-lengths. Even in the more restricted setting of unit edge-lengths, our algorithm improves over the previous $\~O(n^{1-1/k})$ approximation of Bhattacharyya et al. when $k\ge 4$. For the special case of $k=3$ we design a different algorithm achieving an $\~O(\sqrt{n})$-approximation, improving the previous $\~O(n^{2/3})$. Both of our algorithms easily extend to the fault-tolerant setting, which has recently attracted attention but not from an approximation viewpoint. We also prove a nearly matching integrality gap of $\Omega(n^{\frac13 - \epsilon})$ for any constant $\epsilon > 0$. A virtue of all our algorithms is that they are relatively simple. Technically, we introduce a new yet natural flow-based relaxation, and show how to approximately solve it even when its size is not polynomial. The main challenge is to design a rounding scheme that "coordinates" the choices of flow-paths between the many demand pairs while using few edges overall. We achieve this, roughly speaking, by randomization at the level of vertices.


Catalan structures and Catalan pairs

Abstract: A Catalan pair is a pair of binary relations (S,R) satisfying certain axioms. These objects are enumerated by the well-known Catalan numbers, and have been introduced with the aim of giving a common language to most of the structures counted by Catalan numbers. Here, we give a simple method to pass from the recursive definition of a generic Catalan structure to the recursive definition of the Catalan pair on the same structure, thus giving an automatic way to interpret Catalan structures in terms of Catalan pairs. We apply our method to many well-known Catalan structures, focusing on the meaning of the relations S and R in each considered case.


Commutative-like Encryption: A New Characterization of ElGamal

Abstract: Commutative encryption is a useful but rather strict notion in cryptography. In this paper, we deny a loose variation of commutative encryption-commutative-like encryption and give an example: the generalization of ElGamal scheme. The application of the new variation is also discussed.


On the Inverse Of General Cyclic Heptadiagonal and Anti-Heptadiagonal Matrices

Abstract: In the current work, the author present a symbolic algorithm for finding the determinant of any general nonsingular cyclic heptadiagonal matrices and inverse of anti-cyclic heptadiagonal matrices. The algorithms are mainly based on the work presented in [A. A. KARAWIA, A New Algorithm for Inverting General Cyclic Heptadiagonal Matrices Recursively, arXiv:1011.2306v1 [cs.SC]]. The symbolic algorithms are suited for implementation using Computer Algebra Systems (CAS) such as MATLAB, MAPLE and MATHEMATICA. An illustrative example is given.


Detecting and Tracking the Spread of Astroturf Memes in Microblog Streams

Abstract: Online social media are complementing and in some cases replacing person-to-person social interaction and redefining the diffusion of information. In particular, microblogs have become crucial grounds on which public relations, marketing, and political battles are fought. We introduce an extensible framework that will enable the real-time analysis of meme diffusion in social media by mining, visualizing, mapping, classifying, and modeling massive streams of public microblogging events. We describe a Web service that leverages this framework to track political memes in Twitter and help detect astroturfing, smear campaigns, and other misinformation in the context of U.S. political elections. We present some cases of abusive behaviors uncovered by our service. Finally, we discuss promising preliminary results on the detection of suspicious memes via supervised learning based on features extracted from the topology of the diffusion networks, sentiment analysis, and crowdsourced annotations.


Optimal Lower Bounds for Universal and Differentially Private Steiner Tree and TSP

Abstract: Given a metric space on n points, an {\alpha}-approximate universal algorithm for the Steiner tree problem outputs a distribution over rooted spanning trees such that for any subset X of vertices containing the root, the expected cost of the induced subtree is within an {\alpha} factor of the optimal Steiner tree cost for X. An {\alpha}-approximate differentially private algorithm for the Steiner tree problem takes as input a subset X of vertices, and outputs a tree distribution that induces a solution within an {\alpha} factor of the optimal as before, and satisfies the additional property that for any set X' that differs in a single vertex from X, the tree distributions for X and X' are "close" to each other. Universal and differentially private algorithms for TSP are defined similarly. An {\alpha}-approximate universal algorithm for the Steiner tree problem or TSP is also an {\alpha}-approximate differentially private algorithm. It is known that both problems admit O(logn)-approximate universal algorithms, and hence O(log n)-approximate differentially private algorithms as well. We prove an {\Omega}(logn) lower bound on the approximation ratio achievable for the universal Steiner tree problem and the universal TSP, matching the known upper bounds. Our lower bound for the Steiner tree problem holds even when the algorithm is allowed to output a more general solution of a distribution on paths to the root.


Realizable Paths and the NL vs L Problem

Abstract: A celebrated theorem of Savitch states that NSPACE(S) is contained in DSPACE(S^2). In particular, Savitch gave a deterministic algorithm to solve ST-CONNECTIVITY (an NL-complete problem) using O(log^2{n}) space, implying NL is in DSPACE(log^2{n}). While Savitch's theorem itself has not been improved in the last four decades, studying the space complexity of several special cases of ST-CONNECTIVITY has provided new insights into the space-bounded complexity classes. In this paper, we introduce new kind of graph connectivity problems which we call graph realizability problems. All of our graph realizability problems are generalizations of UNDIRECTED ST-CONNECTIVITY. ST-REALIZABILITY, the most general graph realizability problem, is LogCFL-complete. We define the corresponding complexity classes that lie between L and LogCFL and study their relationships. As special cases of our graph realizability problems we define two natural problems, BALANCED ST-CONNECTIVITY and POSITIVE BALANCED ST-CONNECTIVITY, that lie between L and NL. We present a deterministic O(lognloglogn) space algorithm for BALANCED ST-CONNECTIVITY. More generally we prove that SGSLogCFL, a generalization of BALANCED ST-CONNECTIVITY, is contained in DSPACE(lognloglogn). To achieve this goal we generalize several concepts (such as graph squaring and transitive closure) and algorithms (such as parallel algorithms) known in the context of UNDIRECTED ST-CONNECTIVITY.


iCare: A Mobile Health Monitoring System for the Elderly

Abstract: This paper describes a mobile health monitoring system called iCare for the elderly. We use wireless body sensors and smart phones to monitor the wellbeing of the elderly. It can offer remote monitoring for the elderly anytime anywhere and provide tailored services for each person based on their personal health condition. When detecting an emergency, the smart phone will automatically alert pre-assigned people who could be the old people's family and friends, and call the ambulance of the emergency centre. It also acts as the personal health information system and the medical guidance which offers one communication platform and the medical knowledge database so that the family and friends of the served people can cooperate with doctors to take care of him/her. The system also features some unique functions that cater to the living demands of the elderly, including regular reminder, quick alarm, medical guidance, etc. iCare is not only a real-time health monitoring system for the elderly, but also a living assistant which can make their lives more convenient and comfortable.


Artificial Hormone Reaction Networks: Towards Higher Evolvability in Evolutionary Multi-Modular Robotics

Abstract: The semi-automatic or automatic synthesis of robot controller software is both desirable and challenging. Synthesis of rather simple behaviors such as collision avoidance by applying artificial evolution has been shown multiple times. However, the difficulty of this synthesis increases heavily with increasing complexity of the task that should be performed by the robot. We try to tackle this problem of complexity with Artificial Homeostatic Hormone Systems (AHHS), which provide both intrinsic, homeostatic processes and (transient) intrinsic, variant behavior. By using AHHS the need for pre-defined controller topologies or information about the field of application is minimized. We investigate how the principle design of the controller and the hormone network size affects the overall performance of the artificial evolution (i.e., evolvability). This is done by comparing two variants of AHHS that show different effects when mutated. We evolve a controller for a robot built from five autonomous, cooperating modules. The desired behavior is a form of gait resulting in fast locomotion by using the modules' main hinges.


Non-Orthodox Combinatorial Models Based on Discordant Structures

Abstract: This paper introduces a novel method for compact representation of sets of n-dimensional binary sequences in a form of compact triplets structures (CTS), supposing both logic and arithmetic interpretations of data. Suitable illustration of CTS application is the unique graph-combinatorial model for the classic intractable 3-Satisfiability problem and a polynomial algorithm for the model synthesis. The method used for Boolean formulas analysis and classification by means of the model is defined as a bijective mapping principle for sets of components of discordant structures to a basic set. The statistic computer-aided experiment showed efficiency of the algorithm in a large scale of problem dimension parameters, including those that make enumeration procedures of no use. The formulated principle expands resources of constructive approach to investigation of intractable problems.


Decision Problems for Petri Nets with Names

Abstract: We prove several decidability and undecidability results for nu-PN, an extension of P/T nets with pure name creation and name management. We give a simple proof of undecidability of reachability, by reducing reachability in nets with inhibitor arcs to it. Thus, the expressive power of nu-PN strictly surpasses that of P/T nets. We prove that nu-PN are Well Structured Transition Systems. In particular, we obtain decidability of coverability and termination, so that the expressive power of Turing machines is not reached. Moreover, they are strictly Well Structured, so that the boundedness problem is also decidable. We consider two properties, width-boundedness and depth-boundedness, that factorize boundedness. Width-boundedness has already been proven to be decidable. We prove here undecidability of depth-boundedness. Finally, we obtain Ackermann-hardness results for all our decidable decision problems.


On the approximation ability of evolutionary optimization with application to minimum set cover

Abstract: Evolutionary algorithms (EAs) are heuristic algorithms inspired by natural evolution. They are often used to obtain satisficing solutions in practice. In this paper, we investigate a largely underexplored issue: the approximation performance of EAs in terms of how close the solution obtained is to an optimal solution. We study an EA framework named simple EA with isolated population (SEIP) that can be implemented as a single- or multi-objective EA. We analyze the approximation performance of SEIP using the partial ratio, which characterizes the approximation ratio that can be guaranteed. Specifically, we analyze SEIP using a set cover problem that is NP-hard. We find that in a simple configuration, SEIP efficiently achieves an $H_n$-approximation ratio, the asymptotic lower bound, for the unbounded set cover problem. We also find that SEIP efficiently achieves an $(H_k-\frac{k-1}/{8k^9})$-approximation ratio, the currently best-achievable result, for the k-set cover problem. Moreover, for an instance class of the k-set cover problem, we disclose how SEIP, using either one-bit or bit-wise mutation, can overcome the difficulty that limits the greedy algorithm.


The Use of Rapid Digital Game Creation to Learn Computational Thinking

Abstract: Computational Thinking (CT) has been described as a universally applicable ability such as reading and writing. In this paper, we describe an innovative pedagogy using Rapid Digital Game Creation (RDGC) for learning CT skills. RDGC involves the rapid building of digital games with high-level software that requires little or no programming knowledge. We analyze how RDGC supports various CT concepts and how it may be mapped to equivalent Java concepts by building the same game using both RDGC and Java. We discuss the potential benefits of this approach for attracting computing majors, as a precursor to learning formal programming languages, for learning domain knowledge, and for bridging the digital divide. We present the implications of this work for teachers and researchers.


Progressive Decoding for Data Availability and Reliability in Distributed Networked Storage

Abstract: To harness the ever growing capacity and decreasing cost of storage, providing an abstraction of dependable storage in the presence of crash-stop and Byzantine failures is compulsory. We propose a decentralized Reed Solomon coding mechanism with minimum communication overhead. Using a progressive data retrieval scheme, a data collector contacts only the necessary number of storage nodes needed to guarantee data integrity. The scheme gracefully adapts the cost of successful data retrieval to the number of storage node failures. Moreover, by leveraging the Welch-Berlekamp algorithm, it avoids unnecessary computations. Compared to the state-of-the-art decoding scheme, the implementation and evaluation results show that our progressive data retrieval scheme has up to 35 times better computation performance for low Byzantine node rates. Additionally, the communication cost in data retrieval is derived analytically and corroborated by Monte-Carlo simulation results. Our implementation is flexible in that the level of redundancy it provides is independent of the number of data generating nodes, a requirement for distributed storage systems


World of Movable Objects. Part 1

Abstract: This book is about the transformation of screen objects into movable and resizable and about the design of applications entirely on the basis of such elements. The screen objects have a wide variety of shapes; they can be either graphical objects or controls; there are solitary objects and very complex objects parts of which are involved in individual, synchronous, and related movements. Objects can be involved in forward movements and rotation; they can be resized and reconfigured; all these movements and situations are considered. On the basis of total movability, the new type of programs - user-driven applications - are designed. These applications continue to work according to their main purposes, but the whole control of WHAT, WHEN, and HOW must appear on the screen is passed from designers to users. Due to the size restriction used on CoRR, the book is divided here into two parts and one appendix is deleted. At www.sourceforge.net in the project MoveableGraphics the whole book is available in a single file together with the accompanying application and source codes.


Motifs de graphe pour le calcul de d\'ependances syntaxiques compl\`etes

Abstract: This article describes a method to build syntactical dependencies starting from the phrase structure parsing process. The goal is to obtain all the information needed for a detailled semantical analysis. Interaction Grammars are used for parsing; the saturation of polarities which is the core of this formalism can be mapped to dependency relation. Formally, graph patterns are used to express the set of constraints which control dependency creations.


A full-custom ASIC design of a 8-bit, 25 MHz, Pipeline ADC using 0.35 um CMOS technology

Abstract: The purpose of this project was to design and implement a pipeline Analog-to-Digital Converter using 0.35um CMOS technology. Initial requirements of a 25-MHz conversion rate and 8-bits of resolution where the only given ones. Although additional secondary goals such as low power consumption and small area were stated. The architecture is based on a 1.5 bit per stage structure utilizing digital correction for each stage [12]. A differential switched capacitor circuit consisting of a cascade gm-C op-amp with 200MHz ft is used for sampling and amplification in each stage [12]. Differential dynamic comparators are used to implement the decision levels required for the 1.5-b per stage structure. Correction of the pipeline is accomplished by using digital correction circuit consist of D-latches and full-adders. Area and Power consumption of whole design was 0.24mm2 and 35mW respectively. The maximum sample rate at which the converter gave an adequate output was 33MHz.


A Short Story of a Subtle Error in LTL Formulas Reduction and Divine Incorrectness

Abstract: We identify a subtle error in LTL formulas reduction method used as one optimization step in an LTL to B\"uchi automata translation. The error led to some incorrect answers of the established model checker DiVinE. This paper should help authors of other model checkers to avoid this error.


Cross-Composition: A New Technique for Kernelization Lower Bounds

Abstract: We introduce a new technique for proving kernelization lower bounds, called cross-composition. A classical problem L cross-composes into a parameterized problem Q if an instance of Q with polynomially bounded parameter value can express the logical OR of a sequence of instances of L. Building on work by Bodlaender et al. (ICALP 2008) and using a result by Fortnow and Santhanam (STOC 2008) we show that if an NP-complete problem cross-composes into a parameterized problem Q then Q does not admit a polynomial kernel unless the polynomial hierarchy collapses. Our technique generalizes and strengthens the recent techniques of using OR-composition algorithms and of transferring the lower bounds via polynomial parameter transformations. We show its applicability by proving kernelization lower bounds for a number of important graphs problems with structural (non-standard) parameterizations, e.g., Chromatic Number, Clique, and Weighted Feedback Vertex Set do not admit polynomial kernels with respect to the vertex cover number of the input graphs unless the polynomial hierarchy collapses, contrasting the fact that these problems are trivially fixed-parameter tractable for this parameter. We have similar lower bounds for Feedback Vertex Set.


A Fuzzy Clustering Model for Fuzzy Data with Outliers

Abstract: In this paper a fuzzy clustering model for fuzzy data with outliers is proposed. The model is based on Wasserstein distance between interval valued data which is generalized to fuzzy data. In addition, Keller's approach is used to identify outliers and reduce their influences. We have also defined a transformation to change our distance to the Euclidean distance. With the help of this approach, the problem of fuzzy clustering of fuzzy data is reduced to fuzzy clustering of crisp data. In order to show the performance of the proposed clustering algorithm, two simulation experiments are discussed.


Should one compute the Temporal Difference fix point or minimize the Bellman Residual? The unified oblique projection view

Abstract: We investigate projection methods, for evaluating a linear approximation of the value function of a policy in a Markov Decision Process context. We consider two popular approaches, the one-step Temporal Difference fix-point computation (TD(0)) and the Bellman Residual (BR) minimization. We describe examples, where each method outperforms the other. We highlight a simple relation between the objective function they minimize, and show that while BR enjoys a performance guarantee, TD(0) does not in general. We then propose a unified view in terms of oblique projections of the Bellman equation, which substantially simplifies and extends the characterization of (schoknecht,2002) and the recent analysis of (Yu & Bertsekas, 2008). Eventually, we describe some simulations that suggest that if the TD(0) solution is usually slightly better than the BR solution, its inherent numerical instability makes it very bad in some cases, and thus worse on average.


QoS-enabled ANFIS Dead Reckoning Algorithm for Distributed Interactive Simulation

Abstract: Dead Reckoning mechanisms are usually used to estimate the position of simulated entity in virtual environment. However, this technique often ignores available contextual information that may be influential to the state of an entity, sacrificing remote predictive accuracy in favor of low computational complexity. A novel extension of Dead Reckoning is suggested in this paper to increase the network availability and fulfill the required Quality of Service in large scale distributed simulation application. The proposed algorithm is referred to as ANFIS Dead Reckoning, which stands for Adaptive Neuro-based Fuzzy Inference System Dead Reckoning is based on a fuzzy inference system which is trained by the learning algorithm derived from the neuronal networks and fuzzy inference theory. The proposed mechanism takes its based on the optimization approach to calculate the error threshold violation in networking games. Our model shows it primary benefits especially in the decision making of the behavior of simulated entities and preserving the consistence of the simulation.


Coverage games in small cells networks

Abstract: This paper considers the problem of cooperative power control in distributed small cell wireless networks. We introduce a novel framework, based on repeated games, which models the interactions of the different transmit base stations in the downlink. By exploiting the specific structure of the game, we show that we can improve the system performance by selecting the Pareto optimal solution as well as reduce the price of stability.


Dynamic Magic Sets for Super-Consistent Answer Set Programs

Abstract: For many practical applications of ASP, for instance data integration or planning, query answering is important, and therefore query optimization techniques for ASP are of great interest. Magic Sets are one of these techniques, originally defined for Datalog queries (ASP without disjunction and negation). Dynamic Magic Sets (DMS) are an extension of this technique, which has been proved to be sound and complete for query answering over ASP programs with stratified negation. A distinguishing feature of DMS is that the optimization can be exploited also during the nondeterministic phase of ASP engines. In particular, after some assumptions have been made during the computation, parts of the program may become irrelevant to a query under these assumptions. This allows for dynamic pruning of the search space, which may result in exponential performance gains. In this paper, the correctness of DMS is formally established and proved for brave and cautious reasoning over the class of super-consistent ASP programs (ASP^{sc} programs). ASP^{sc} programs guarantee consistency (i.e., have answer sets) when an arbitrary set of facts is added to them. This result generalizes the applicability of DMS, since the class of ASP^{sc} programs is richer than ASP programs with stratified negation, and in particular includes all odd-cycle-free programs. DMS has been implemented as an extension of DLV, and the effectiveness of DMS for ASP^{sc} programs is empirically confirmed by experimental results with this system.


On Constructive Connectives and Systems

Abstract: Canonical inference rules and canonical systems are defined in the framework of non-strict single-conclusion sequent systems, in which the succeedents of sequents can be empty. Important properties of this framework are investigated, and a general non-deterministic Kripke-style semantics is provided. This general semantics is then used to provide a constructive (and very natural), sufficient and necessary coherence criterion for the validity of the strong cut-elimination theorem in such a system. These results suggest new syntactic and semantic characterizations of basic constructive connectives.


Compressed Transmission of Route Descriptions

Abstract: We present two methods to compress the description of a route in a road network, i.e., of a path in a directed graph. The first method represents a path by a sequence of via edges. The subpaths between the via edges have to be unique shortest paths. Instead of via edges also via nodes can be used, though this requires some simple preprocessing. The second method uses contraction hierarchies to replace subpaths of the original path by shortcuts. The two methods can be combined with each other. Also, we propose the application to mobile server based routing: We compute the route on a server which has access to the latest information about congestions for example. Then we transmit the computed route to the car using some mobile radio communication. There, we apply the compression to save costs and transmission time. If the compression works well, we can transmit routes even when the bandwidth is low. Although we have not evaluated our ideas with realistic data yet, they are quite promising.


New Algorithms on Wavelet Trees and Applications to Information Retrieval

Abstract: Wavelet trees are widely used in the representation of sequences, permutations, text collections, binary relations, discrete points, and other succinct data structures. We show, however, that this still falls short of exploiting all of the virtues of this versatile data structure. In particular we show how to use wavelet trees to solve fundamental algorithmic problems such as {\em range quantile} queries, {\em range next value} queries, and {\em range intersection} queries. We explore several applications of these queries in Information Retrieval, in particular {\em document retrieval} in hierarchical and temporal documents, and in the representation of {\em inverted lists}.


Cascading Link Failure in the Power Grid: A Percolation-Based Analysis

Abstract: Large-scale power blackouts caused by cascading failure are inflicting enormous socioeconomic costs. We study the problem of cascading link failures in power networks modelled by random geometric graphs from a percolation-based viewpoint. To reflect the fact that links fail according to the amount of power flow going through them, we introduce a model where links fail according to a probability which depends on the number of neighboring links. We devise a mapping which maps links in a random geometric graph to nodes in a corresponding dual covering graph. This mapping enables us to obtain the first-known analytical conditions on the existence and non-existence of a large component of operational links after degree-dependent link failures. Next, we present a simple but descriptive model for cascading link failure, and use the degree-dependent link failure results to obtain the first-known analytical conditions on the existence and non-existence of cascading link failures.


Algorithms for enumerating and counting D2CS of some graphs

Abstract: A D2CS of a graph G is a set $S \subseteq V(G)$ with $diam(G[S]) \leq 2$. We study the problem of counting and enumerating D2CS of a graph. First we give an explicit formula for the number of D2CS in a complete k-ary tree, Fibonacci tree, binary Fibonacci tree and the binomial tree. Next we give an algorithm for enumerating and counting D2CS of a graph. We then give a linear time algorithm for finding all maximal D2CS in a strongly chordal graph.


Continuation-Passing C: compiling threads to events through continuations

Abstract: In this paper, we introduce Continuation Passing C (CPC), a programming language for concurrent systems in which native and cooperative threads are unified and presented to the programmer as a single abstraction. The CPC compiler uses a compilation technique, based on the CPS transform, that yields efficient code and an extremely lightweight representation for contexts. We provide a proof of the correctness of our compilation scheme. We show in particular that lambda-lifting, a common compilation technique for functional languages, is also correct in an imperative language like C, under some conditions enforced by the CPC compiler. The current CPC compiler is mature enough to write substantial programs such as Hekate, a highly concurrent BitTorrent seeder. Our benchmark results show that CPC is as efficient, while using significantly less space, as the most efficient thread libraries available.


A New Algorithm for General Cyclic Heptadiagonal Linear Systems Using Sherman-Morrison-Woodbury formula

Abstract: In this paper, a new efficient computational algorithm is presented for solving cyclic heptadiagonal linear systems based on using of heptadiagonal linear solver and Sherman-Morrison-Woodbury formula. The implementation of the algorithm using computer algebra systems (CAS) such as MAPLE and MATLAB is straightforward. Numerical example is presented for the sake of illustration.


Generalized Tree-Based Wavelet Transform

Abstract: In this paper we propose a new wavelet transform applicable to functions defined on graphs, high dimensional data and networks. The proposed method generalizes the Haar-like transform proposed in [1], and it is defined via a hierarchical tree, which is assumed to capture the geometry and structure of the input data. It is applied to the data using a modified version of the common one-dimensional (1D) wavelet filtering and decimation scheme, which can employ different wavelet filters. In each level of this wavelet decomposition scheme, a permutation derived from the tree is applied to the approximation coefficients, before they are filtered. We propose a tree construction method that results in an efficient representation of the input function in the transform domain. We show that the proposed transform is more efficient than both the 1D and two-dimensional (2D) separable wavelet transforms in representing images. We also explore the application of the proposed transform to image denoising, and show that combined with a subimage averaging scheme, it achieves denoising results which are similar to those obtained with the K-SVD algorithm.


Opinion Polarity Identification through Adjectives

Abstract: "What other people think" has always been an important piece of information during various decision-making processes. Today people frequently make their opinions available via the Internet, and as a result, the Web has become an excellent source for gathering consumer opinions. There are now numerous Web resources containing such opinions, e.g., product reviews forums, discussion groups, and Blogs. But, due to the large amount of information and the wide range of sources, it is essentially impossible for a customer to read all of the reviews and make an informed decision on whether to purchase the product. It is also difficult for the manufacturer or seller of a product to accurately monitor customer opinions. For this reason, mining customer reviews, or opinion mining, has become an important issue for research in Web information extraction. One of the important topics in this research area is the identification of opinion polarity. The opinion polarity of a review is usually expressed with values 'positive', 'negative' or 'neutral'. We propose a technique for identifying polarity of reviews by identifying the polarity of the adjectives that appear in them. Our evaluation shows the technique can provide accuracy in the area of 73%, which is well above the 58%-64% provided by naive Bayesian classifiers.


Random Projections for $k$-means Clustering

Abstract: This paper discusses the topic of dimensionality reduction for $k$-means clustering. We prove that any set of $n$ points in $d$ dimensions (rows in a matrix $A \in \RR^{n \times d}$) can be projected into $t = \Omega(k / \eps^2)$ dimensions, for any $\eps \in (0,1/3)$, in $O(n d \lceil \eps^{-2} k/ \log(d) \rceil )$ time, such that with constant probability the optimal $k$-partition of the point set is preserved within a factor of $2+\eps$. The projection is done by post-multiplying $A$ with a $d \times t$ random matrix $R$ having entries $+1/\sqrt{t}$ or $-1/\sqrt{t}$ with equal probability. A numerical implementation of our technique and experiments on a large face images dataset verify the speed and the accuracy of our theoretical results.