Using a smart phone for information rendering in Computer-Aided Surgery

Abstract: Computer-aided surgery intensively uses the concept of navigation: after having collected CT data from a patient and transferred them to the operating room coordinate system, the surgical instrument (a puncture needle for instance) is localized and its position is visualized with respect to the patient organs which are not directly visible. This approach is very similar to the GPS paradigm. Traditionally, three orthogonal slices in the patient data are presented on a distant screen. Sometimes a 3D representation is also added. In this study we evaluated the potential of adding a smart phone as a man-machine interaction device. Different experiments involving operators puncturing a phantom are reported in this paper.


On the Degree Distribution of Faulty Peer-to-Peer Overlays

Abstract: This paper presents an analytical framework to model fault-tolerance in unstructured peer-to-peer overlays, represented as complex networks. We define a distributed protocol peers execute for managing the overlay and reacting to node faults. Based on the protocol, evolution equations are defined and manipulated by resorting to generating functions. Obtained outcomes provide insights on the nodes' degree probability distribution. From the study of the degree distribution, it is possible to estimate other important metrics of the peer-to-peer overlay, such as the diameter of the network. We study different networks, characterized by three specific desired degree distributions, i.e. nets with nodes having a fixed desired degree, random graphs and scale-free networks. All these networks are assessed via the analytical tool and simulation as well. Results show that the approach can be factually employed to dynamically tune the average attachment rate at peers so that they maintain their own desired degree and, in general, the desired network topology.


A Scalable Module System

Abstract: Symbolic and logic computation systems ranging from computer algebra systems to theorem provers are finding their way into science, technology, mathematics and engineering. But such systems rely on explicitly or implicitly represented mathematical knowledge that needs to be managed to use such systems effectively. While mathematical knowledge management (MKM) "in the small" is well-studied, scaling up to large, highly interconnected corpora remains difficult. We hold that in order to realize MKM "in the large", we need representation languages and software architectures that are designed systematically with large-scale processing in mind. Therefore, we have designed and implemented the MMT language -- a module system for mathematical theories. MMT is designed as the simplest possible language that combines a module system, a foundationally uncommitted formal semantics, and web-scalable implementations. Due to a careful choice of representational primitives, MMT allows us to integrate existing representation languages for formal mathematical knowledge in a simple, scalable formalism. In particular, MMT abstracts from the underlying mathematical and logical foundations so that it can serve as a standardized representation format for a formal digital library. Moreover, MMT systematically separates logic-dependent and logic-independent concerns so that it can serve as an interface layer between computation systems and MKM systems.


If more than Analytical Modeling is Needed to Predict Real Agents' Strategic Interaction

Abstract: This paper presents the research on the interdisciplinary research infrastructure for understanding human reasoning in game-theoretic terms. Strategic reasoning is considered to impact human decision making in social, economical and competitive interactions. The provided introduction explains and connects concepts from AI, game theory and psychology. First result is a concept of interdisciplinary game description language as a part of the focused interdisciplinary research infrastructure. The need of this domain-specific language is motivated and is aimed to accelerate the current developments. As second result, the paper provides a summary of ongoing research and its significance.


A simpler and more efficient algorithm for the next-to-shortest path problem

Abstract: Given an undirected graph $G=(V,E)$ with positive edge lengths and two vertices $s$ and $t$, the next-to-shortest path problem is to find an $st$-path which length is minimum amongst all $st$-paths strictly longer than the shortest path length. In this paper we show that the problem can be solved in linear time if the distances from $s$ and $t$ to all other vertices are given. Particularly our new algorithm runs in $O(|V|\log |V|+|E|)$ time for general graphs, which improves the previous result of $O(|V|^2)$ time for sparse graphs, and takes only linear time for unweighted graphs, planar graphs, and graphs with positive integer edge lengths.


Transition Systems for Model Generators - A Unifying Approach

Abstract: A fundamental task for propositional logic is to compute models of propositional formulas. Programs developed for this task are called satisfiability solvers. We show that transition systems introduced by Nieuwenhuis, Oliveras, and Tinelli to model and analyze satisfiability solvers can be adapted for solvers developed for two other propositional formalisms: logic programming under the answer-set semantics, and the logic PC(ID). We show that in each case the task of computing models can be seen as "satisfiability modulo answer-set programming," where the goal is to find a model of a theory that also is an answer set of a certain program. The unifying perspective we develop shows, in particular, that solvers CLASP and MINISATID are closely related despite being developed for different formalisms, one for answer-set programming and the latter for the logic PC(ID).


Model Checking of Boolean Process Models

Abstract: In the field of Business Process Management formal models for the control flow of business processes have been designed since more than 15 years. Which methods are best suited to verify the bulk of these models? The first step is to select a formal language which fixes the semantics of the models. We adopt the language of Boolean systems as reference language for Boolean process models. Boolean systems form a simple subclass of coloured Petri nets. Their characteristics are low tokens to model explicitly states with a subsequent skipping of activations and arbitrary logical rules of type AND, XOR, OR etc. to model the split and join of the control flow. We apply model checking as a verification method for the safeness and liveness of Boolean systems. Model checking of Boolean systems uses the elementary theory of propositional logic, no modal operators are needed. Our verification builds on a finite complete prefix of a certain T-system attached to the Boolean system. It splits the processes of the Boolean system into a finite set of base processes of bounded length. Their behaviour translates to formulas from propositional logic. Our verification task consists in checking the satisfiability of these formulas. In addition we have implemented our model checking algorithm as a java program. The time needed to verify a given Boolean system depends critically on the number of initial tokens. Because the algorithm has to solve certain SAT-problems, polynomial complexity cannot be expected. The paper closes with the model checking of some Boolean process models which have been designed as Event-driven Process Chains.


Secure Position Verification for Wireless Sensor Networks in Noisy Channels

Abstract: Position verification in wireless sensor networks (WSNs) is quite tricky in presence of attackers (malicious sensor nodes), who try to break the verification protocol by reporting their incorrect positions (locations) during the verification stage. In the literature of WSNs, most of the existing methods of position verification have used trusted verifiers, which are in fact vulnerable to attacks by malicious nodes. They also depend on some distance estimation techniques, which are not accurate in noisy channels (mediums). In this article, we propose a secure position verification scheme for WSNs in noisy channels without relying on any trusted entities. Our verification scheme detects and filters out all malicious nodes from the network with very high probability.


Mark My Words! Linguistic Style Accommodation in Social Media

Abstract: The psycholinguistic theory of communication accommodation accounts for the general observation that participants in conversations tend to converge to one another's communicative behavior: they coordinate in a variety of dimensions including choice of words, syntax, utterance length, pitch and gestures. In its almost forty years of existence, this theory has been empirically supported exclusively through small-scale or controlled laboratory studies. Here we address this phenomenon in the context of Twitter conversations. Undoubtedly, this setting is unlike any other in which accommodation was observed and, thus, challenging to the theory. Its novelty comes not only from its size, but also from the non real-time nature of conversations, from the 140 character length restriction, from the wide variety of social relation types, and from a design that was initially not geared towards conversation at all. Given such constraints, it is not clear a priori whether accommodation is robust enough to occur given the constraints of this new environment. To investigate this, we develop a probabilistic framework that can model accommodation and measure its effects. We apply it to a large Twitter conversational dataset specifically developed for this task. This is the first time the hypothesis of linguistic style accommodation has been examined (and verified) in a large scale, real world setting. Furthermore, when investigating concepts such as stylistic influence and symmetry of accommodation, we discover a complexity of the phenomenon which was never observed before. We also explore the potential relation between stylistic influence and network features commonly associated with social status.


Robust Sign Language Recognition System Using ToF Depth Cameras

Abstract: Sign language recognition is a difficult task, yet required for many applications in real-time speed. Using RGB cameras for recognition of sign languages is not very successful in practical situations and accurate 3D imaging requires expensive and complex instruments. With introduction of Time-of-Flight (ToF) depth cameras in recent years, it has become easier to scan the environment for accurate, yet fast depth images of the objects without the need of any extra calibrating object. In this paper, a robust system for sign language recognition using ToF depth cameras is presented for converting the recorded signs to a standard and portable XML sign language named SiGML for easy transferring and converting to real-time 3D virtual characters animations. Feature extraction using moments and classification using nearest neighbor classifier are used to track hand gestures and significant result of 100% is achieved for the proposed approach.


Parameterized Complexity of Problems in Coalitional Resource Games

Abstract: Coalition formation is a key topic in multi-agent systems. Coalitions enable agents to achieve goals that they may not have been able to achieve on their own. Previous work has shown problems in coalitional games to be computationally hard. Wooldridge and Dunne (Artificial Intelligence 2006) studied the classical computational complexity of several natural decision problems in Coalitional Resource Games (CRG) - games in which each agent is endowed with a set of resources and coalitions can bring about a set of goals if they are collectively endowed with the necessary amount of resources. The input of coalitional resource games bundles together several elements, e.g., the agent set Ag, the goal set G, the resource set R, etc. Shrot, Aumann and Kraus (AAMAS 2009) examine coalition formation problems in the CRG model using the theory of Parameterized Complexity. Their refined analysis shows that not all parts of input act equal - some instances of the problem are indeed tractable while others still remain intractable. We answer an important question left open by Shrot, Aumann and Kraus by showing that the SC Problem (checking whether a Coalition is Successful) is W[1]-hard when parameterized by the size of the coalition. Then via a single theme of reduction from SC, we are able to show that various problems related to resources, resource bounds and resource conflicts introduced by Wooldridge et al are 1. W[1]-hard or co-W[1]-hard when parameterized by the size of the coalition. 2. para-NP-hard or co-para-NP-hard when parameterized by |R|. 3. FPT when parameterized by either |G| or |Ag|+|R|.


Topics in Matrix Sampling Algorithms

Abstract: We study three fundamental problems of Linear Algebra, lying in the heart of various Machine Learning applications, namely: 1)"Low-rank Column-based Matrix Approximation". We are given a matrix A and a target rank k. The goal is to select a subset of columns of A and, by using only these columns, compute a rank k approximation to A that is as good as the rank k approximation that would have been obtained by using all the columns; 2) "Coreset Construction in Least-Squares Regression". We are given a matrix A and a vector b. Consider the (over-constrained) least-squares problem of minimizing ||Ax-b||, over all vectors x in D. The domain D represents the constraints on the solution and can be arbitrary. The goal is to select a subset of the rows of A and b and, by using only these rows, find a solution vector that is as good as the solution vector that would have been obtained by using all the rows; 3) "Feature Selection in K-means Clustering". We are given a set of points described with respect to a large number of features. The goal is to select a subset of the features and, by using only this subset, obtain a k-partition of the points that is as good as the partition that would have been obtained by using all the features. We present novel algorithms for all three problems mentioned above. Our results can be viewed as follow-up research to a line of work known as "Matrix Sampling Algorithms". [Frieze, Kanna, Vempala, 1998] presented the first such algorithm for the Low-rank Matrix Approximation problem. Since then, such algorithms have been developed for several other problems, e.g. Graph Sparsification and Linear Equation Solving. Our contributions to this line of research are: (i) improved algorithms for Low-rank Matrix Approximation and Regression (ii) algorithms for a new problem domain (K-means Clustering).


REFIM: A Practical Interference Management in Heterogeneous Wireless Access Networks

Abstract: Due to the increasing demand of capacity in wireless cellular networks, the small cells such as pico and femto cells are becoming more popular to enjoy a spatial reuse gain, and thus cells with different sizes are expected to coexist in a complex manner. In such a heterogeneous environment, the role of interference management (IM) becomes of more importance, but technical challenges also increase, since the number of cell-edge users, suffering from severe interference from the neighboring cells, will naturally grow. In order to overcome low performance and/or high complexity of existing static and other dynamic IM algorithms, we propose a novel low-complex and fully distributed IM scheme, called REFIM, in the downlink of heterogeneous multi-cell networks. We first formulate a general optimization problem that turns out to require intractable computation complexity for global optimality. To have a practical solution with low computational and signaling overhead, which is crucial for low-cost small-cell solutions, e.g., femto cells, in REFIM, we decompose it into per-BS problems based on the notion of reference user and reduce feedback overhead over backhauls both temporally and spatially. We evaluate REFIM through extensive simulations under various configurations, including the scenarios from a real deployment of BSs. We show that, compared to the schemes without IM, REFIM can yield more than 40% throughput improvement of cell-edge users while increasing the overall performance by 10~107%. This is equal to about 95% performance of the existing centralized IM algorithm that is known to be near-optimal but hard to implement in practice due to prohibitive complexity. We also present that as long as interference is managed well, the spectrum sharing policy can outperform the best spectrum splitting policy where the number of subchannels is optimally divided between macro and femto cells.


Collaborative Software Development on the Web

Abstract: Software development environments (IDEs) have not followed the IT industry's inexorable trend towards distribution. They do too little to address the problems raised by today's increasingly distributed projects; neither do they facilitate collaborative and interactive development practices. A consequence is the continued reliance of today's IDEs on paradigms such as traditional configuration management, which were developed for earlier modes of operation and hamper collaborative projects. This contribution describes a new paradigm: cloud-based development, which caters to the specific needs of distributed and collaborative projects. The CloudStudio IDE embodies this paradigm by enabling developers to work on a shared project repository. Configuration management becomes unobtrusive; it replaces the explicit update-modify-commit cycle by interactive editing and real-time conflict tracking and management. A case study involving three teams of pairs demonstrates the usability of CloudStudio and its advantages for collaborative software development over traditional configuration management practices.


Connecting a Set of Circles with Minimum Sum of Radii

Abstract: We consider the problem of assigning radii to a given set of points in the plane, such that the resulting set of circles is connected, and the sum of radii is minimized. We show that the problem is polynomially solvable if a connectivity tree is given. If the connectivity tree is unknown, the problem is NP-hard if there are upper bounds on the radii and open otherwise. We give approximation guarantees for a variety of polynomial-time algorithms, describe upper and lower bounds (which are matching in some of the cases), provide polynomial-time approximation schemes, and conclude with experimental results and open problems.


Considerations and Results in Multimedia and DVB Application Development on Philips Nexperia Platform

Abstract: This paper presents some experiments regarding applications development on high performance media processors included in Philips Nexperia Family. The PNX1302 dedicated DVB-T kit used has some limitations. Our work has succeeded to overcome these limitations and to make possible a general-purpose use of this kit. For exemplification two typical applications, important both for multimedia and DVB, are analyzed: MPEG2 video stream decoding and MP3 audio decoding. These original implementations are compared (in speed, memory requirements and costs) with Philips Nexperia Library.


Streaming Multimedia Information Using the Features of the DVB-S Card

Abstract: This paper presents a study of audio-video streaming using the additional possibilities of a DVB-S card. The board used for experiments (Technisat SkyStar 2) is one of the most frequently used cards for this purpose. Using the main blocks of the board's software support it is possible the implement a really useful and full functional system for audio-video streaming. The streaming is possible to be implemented either for decoded MPEG stream or for transport stream. In this last case it is possible to view not only a program, but any program from the same multiplex. This allows us to implement


A Simplest Undecidable Modal Logic

Abstract: Modal logics are widely used in computer science. The complexity of their satisfiability problems has been an active field of research since the 1970s. We prove that even very "simple" modal logics can be undecidable: We show that there is an undecidable modal logic that can be obtained by restricting the allowed models with a first-order formula in which only universal quantifiers appear.


Domain Adaptation: Overfitting and Small Sample Statistics

Abstract: We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample domains, but where we have many samples in each domain. Our goal is to generalize to a new domain. For example, we may want to learn a similarity function using only certain classes of objects, but we desire that this similarity function be applicable to object classes not present in our training sample (e.g. we might seek to learn that "dogs are similar to dogs" even though images of dogs were absent from our training set). Our theoretical analysis shows that we can select many more features than domains while avoiding overfitting by utilizing data-dependent variance properties. We present a greedy feature selection algorithm based on using T-statistics. Our experiments validate this theory showing that our T-statistic based greedy feature selection is more robust at avoiding overfitting than the classical greedy procedure.


A Month in the Life of Groupon

Abstract: Groupon has become the latest Internet sensation, providing daily deals to customers in the form of discount offers for restaurants, ticketed events, appliances, services, and other items. We undertake a study of the economics of daily deals on the web, based on a dataset we compiled by monitoring Groupon over several weeks. We use our dataset to characterize Groupon deal purchases, and to glean insights about Groupon's operational strategy. Our focus is on purchase incentives. For the primary purchase incentive, price, our regression model indicates that demand for coupons is relatively inelastic, allowing room for price-based revenue optimization. More interestingly, mining our dataset, we find evidence that Groupon customers are sensitive to other, "soft", incentives, e.g., deal scheduling and duration, deal featuring, and limited inventory. Our analysis points to the importance of considering incentives other than price in optimizing deal sites and similar systems.


A resource analysis of the pi-calculus

Abstract: We give a new treatment of the pi-calculus based on the semantic theory of separation logic, continuing a research program begun by Hoare and O'Hearn. Using a novel resource model that distinguishes between public and private ownership, we refactor the operational semantics so that sending, receiving, and allocating are commands that influence owned resources. These ideas lead naturally to two denotational models: one for safety and one for liveness. Both models are fully abstract for the corresponding observables, but more importantly both are very simple. The close connections with the model theory of separation logic (in particular, with Brookes's action trace model) give rise to a logic of processes and resources.


GANC: Greedy Agglomerative Normalized Cut

Abstract: This paper describes a graph clustering algorithm that aims to minimize the normalized cut criterion and has a model order selection procedure. The performance of the proposed algorithm is comparable to spectral approaches in terms of minimizing normalized cut. However, unlike spectral approaches, the proposed algorithm scales to graphs with millions of nodes and edges. The algorithm consists of three components that are processed sequentially: a greedy agglomerative hierarchical clustering procedure, model order selection, and a local refinement. For a graph of n nodes and O(n) edges, the computational complexity of the algorithm is O(n log^2 n), a major improvement over the O(n^3) complexity of spectral methods. Experiments are performed on real and synthetic networks to demonstrate the scalability of the proposed approach, the effectiveness of the model order selection procedure, and the performance of the proposed algorithm in terms of minimizing the normalized cut metric.


Hardness and Parameterized Algorithms on Rainbow Connectivity problem

Abstract: A path in an edge colored graph is said to be a rainbow path if no two edges on the path have the same color. An edge colored graph is (strongly) rainbow connected if there exists a (geodesic) rainbow path between every pair of vertices. The (strong) rainbow connectivity of a graph G, denoted by (src(G), respectively) rc(G) is the smallest number of colors required to edge color the graph such that G is (strongly) rainbow connected. In this paper we study the rainbow connectivity problem and the strong rainbow connectivity problem from a computational point of view. Our main results can be summarised as below: 1) For every fixed k >= 3, it is NP-Complete to decide whether src(G) <= k even when the graph G is bipartite. 2) For every fixed odd k >= 3, it is NP-Complete to decide whether rc(G) <= k. This resolves one of the open problems posed by Chakraborty et al. (J. Comb. Opt., 2011) where they prove the hardness for the even case. 3) The following problem is fixed parameter tractable: Given a graph G, determine the maximum number of pairs of vertices that can be rainbow connected using two colors. 4) For a directed graph G, it is NP-Complete to decide whether rc(G) <= 2.


Extra connectivity measures of 3-ary n-cubes

Abstract: The h-extra connectivity is an important parameter to measure the reliability and fault tolerance ability of large interconnection networks. The k-ary n-cube is an important interconnection network of parallel computing systems. The 1-restricted connectivity of k-ary n-cubes has been obtained by Chen et al. for k > 3 in [Y.-C. Chen, J. J. M. Tan, Restricted connectivity for three families of interconnection networks, Applied Mathematics and Computation 188 (2) (2007)1848--1855]. Nevertheless, the h-extra connectivity of 3-ary n-cubes has not been obtained yet. In this paper we prove that the 1-extra connectivity of a 3-ary n-cube is 4n-3 for n> 1 and the 2-extra connectivity of 3-ary n-cube is 6n-7 for n> 2.


Improving Network-on-Chip-based turbo decoder architectures

Abstract: In this work novel results concerning Network-on-Chip-based turbo decoder architectures are presented. Stemming from previous publications, this work concentrates first on improving the throughput by exploiting adaptive-bandwidth reduction techniques. This technique shows in the best case an improvement of more than 60 Mb/s. Moreover, it is known that double-binary turbo decoders require higher area than binary ones. This characteristic has the negative effect of increasing the data width of the network nodes. Thus, the second contribution of this work is to reduce the network complexity to support doublebinary codes, by exploiting bit-level and pseudo-floating-point representation of the extrinsic information. These two techniques allow for an area reduction of up to more than the 40% with a performance degradation of about 0.2 dB.


Adaptively Learning the Crowd Kernel

Abstract: We introduce an algorithm that, given n objects, learns a similarity matrix over all n^2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen triplet-based relative-similarity queries. Each query has the form "is object 'a' more similar to 'b' or to 'c'?" and is chosen to be maximally informative given the preceding responses. The output is an embedding of the objects into Euclidean space (like MDS); we refer to this as the "crowd kernel." SVMs reveal that the crowd kernel captures prominent and subtle features across a number of domains, such as "is striped" among neckties and "vowel vs. consonant" among letters.


A New Family of Practical Non-Malleable Diffie-Hellman Protocols

Abstract: Cryptography algorithm standards play a key role both to the practice of information security and to cryptography theory research. Among them, the MQV and HMQV protocols ((H)MQV, in short) are a family of (implicitly authenticated) Diffie-Hellman key-exchange (DHKE) protocols that are widely standardized and deployed. In this work, from some new perspectives and approaches and under some new design rationales and insights, we develop a new family of practical implicitly authenticated DHKE protocols, which enjoy notable performance among security, privacy, efficiency and easy deployment. We make detailed comparisons between our new DHKE protocols and (H)MQV, showing that the newly developed protocols outperform HMQV in most aspects. Along the way, guided by our new design rationales, we also identify a new vulnerability (H)MQV, which brings some new perspectives (e.g., computational fairness) to the literature.


English-Lithuanian-English Machine Translation lexicon and engine: current state and future work

Abstract: This article overviews the current state of the English-Lithuanian-English machine translation system. The first part of the article describes the problems that system poses today and what actions will be taken to solve them in the future. The second part of the article tackles the main issue of the translation process. Article briefly overviews the word sense disambiguation for MT technique using Google.


Progressive quantization in distributed average consensus

Abstract: We consider the problem of distributed average consensus in a sensor network where sensors exchange quantized information with their neighbors. We propose a novel quantization scheme that exploits the increasing correlation between the values exchanged by the sensors throughout the iterations of the consensus algorithm. A low complexity, uniform quantizer is implemented in each sensor, and refined quantization is achieved by progressively reducing the quantization intervals during the convergence of the consensus algorithm. We propose a recurrence relation for computing the quantization parameters that depend on the network topology and the communication rate. We further show that the recurrence relation can lead to a simple exponential model for the size of the quantization step size over the iterations, whose parameters can be computed a priori. Finally, simulation results demonstrate the effectiveness of the progressive quantization scheme that leads to the consensus solution even at low communication rate.


Public Key Protocol Based on Amalgamated Free Product

Abstract: In the spirit of Diffie Hellman the concept of a protocol algebra is introduced using certain amalgamated free product of Braid group B and Thompson group T together with a nilpotent subgroup H of index 2.


Sampling-based Algorithms for Optimal Motion Planning

Abstract: During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically optimal, i.e., such that the cost of the returned solution converges almost surely to the optimum. Moreover, it is shown that the computational complexity of the new algorithms is within a constant factor of that of their probabilistically complete (but not asymptotically optimal) counterparts. The analysis in this paper hinges on novel connections between stochastic sampling-based path planning algorithms and the theory of random geometric graphs.


Software Architecture for Fiji National University Campus Information Systems

Abstract: Software Architecture defines the overview of the system which consists of various components and their relationships among the software. Architectural design is very important in the development of large scale software solution and plays a very active role in achieving business goals, quality and reusable solution. It is often difficult to choose the best software architecture for your system from the several candidate types available. In this paper we look at the several architectural types and compare them based on the key requirements of our system, and select the most appropriate architecture for the implementation of campus information systems at Fiji National University. Finally we provide details of proposed architecture and outline future plans for implementation of our system.


Efficient Squares and Turing Universality at Temperature 1 with a Unique Negative Glue

Abstract: Is Winfree's abstract Tile Assembly Model (aTAM) "powerful?" Well, if certain tiles are required to "cooperate" in order to be able to bind to a growing tile assembly (a.k.a., temperature 2 self-assembly), then Turing universal computation and the efficient self-assembly of $N \times N$ squares is achievable in the aTAM (Rotemund and Winfree, STOC 2000). So yes, in a computational sense, the aTAM is quite powerful! However, if one completely removes this cooperativity condition (a.k.a., temperature 1 self-assembly), then the computational "power" of the aTAM (i.e., its ability to support Turing universal computation and the efficient self-assembly of $N \times N$ squares) becomes unknown. On the plus side, the aTAM, at temperature 1, isn't only Turing universal but also supports the efficient self-assembly $N \times N$ squares if self-assembly is allowed to utilize three spatial dimensions (Fu, Schweller and Cook, SODA 2011). We investigate the theoretical "power" of a seemingly simple, restrictive class of tile assembly systems (TASs) in which (1) the absolute value of every glue strength is 1, (2) there's a single negative strength glue type and (3) unequal glues can't interact. We call these the \emph{restricted glue} TASs (rgTAS). We first show the tile complexity of producing an $N \times N$ square with an rgTAS is $O(\frac{\log n}{\log \log n})$. We also prove that rgTASs are Turing universal with a construction that simulates an arbitrary Turing machine. Next, we provide results for a variation of the rgTAS class, partially restricted glue TASs, which is similar except that the magnitude of the negative glue's strength can only assumed to be $\ge 1$. These results consist of a construction with $O(\log n)$ tile complexity for building $N \times N$ squares, and one which simulates a Turing machine but with a greater scaling factor than for the rgTAS construction.


Multilingual lexicon design tool and database management system for MT

Abstract: The paper presents the design and development of English-Lithuanian-English dictionarylexicon tool and lexicon database management system for MT. The system is oriented to support two main requirements: to be open to the user and to describe much more attributes of speech parts as a regular dictionary that are required for the MT. Programming language Java and database management system MySql is used to implement the designing tool and lexicon database respectively. This solution allows easily deploying this system in the Internet. The system is able to run on various OS such as: Windows, Linux, Mac and other OS where Java Virtual Machine is supported. Since the modern lexicon database managing system is used, it is not a problem accessing the same database for several users.


A Comparison of Trojan Virus Behavior in Linux and Windows Operating Systems

Abstract: Trojan virus attacks pose one of the most serious threats to computer security. A Trojan horse is typically separated into two parts - a server and a client. It is the client that is cleverly disguised as significant software and positioned in peer-to-peer file sharing networks, or unauthorized download websites. The most common means of infection is through email attachments. The developer of the virus usually uses various spamming techniques in order to distribute the virus to unsuspecting users. Malware developers use chat software as another method to spread their Trojan horse viruses such as Yahoo Messenger and Skype. The objective of this paper is to explore the network packet information and detect the behavior of Trojan attacks to monitoring operating systems such as Windows and Linux. This is accomplished by detecting and analyzing the Trojan infected packet from a network segment -which passes through email attachment- before attacking a host computer. The results that have been obtained to detect information and to store infected packets through monitoring when using the web browser also compare the behaviors of Linux and Windows using the payload size after implementing the Wireshark sniffer packet results. Conclusions of the figures analysis from the packet captured data to analyze the control bit, and check the behavior of the control bits, and the usability of the operating systems Linux and Windows.


Machine-Part cell formation through visual decipherable clustering of Self Organizing Map

Abstract: Machine-part cell formation is used in cellular manufacturing in order to process a large variety, quality, lower work in process levels, reducing manufacturing lead-time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In the cellular manufacturing the fundamental problem is the formation of part families and machine cells. The present paper deals with the Self Organising Map (SOM) method an unsupervised learning algorithm in Artificial Intelligence, and has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color-coding and labelling via the SOM map nodes in such a way that the part families are processed in that machine cells. The Umatrix, component plane, principal component projection, scatter plot and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and found immensely useful to both industry practitioners and researchers.


A Distributed Approximation Algorithm for the Metric Uncapacitated Facility Location Problem in the Congest Model

Abstract: We present a randomized distributed approximation algorithm for the metric uncapacitated facility location problem. The algorithm is executed on a bipartite graph in the Congest model yielding a (1.861 + epsilon) approximation factor, where epsilon is an arbitrary small positive constant. It needs O(n^{3/4}log_{1+epsilon}^2(n) communication rounds with high probability (n denoting the number of facilities and clients). To the best of our knowledge, our algorithm currently has the best approximation factor for the facility location problem in a distributed setting. It is based on a greedy sequential approximation algorithm by Jain et al. (J. ACM 50(6), pages: 795-824, 2003). The main difficulty in executing this sequential algorithm lies in dealing with situations, where multiple facilities are eligible for opening, but (in order to preserve the approximation factor of the sequential algorithm) only a subset of them can actually be opened. Note that while the presented runtime bound of our algorithm is "with high probability", the approximation factor is not "in expectation" but always guaranteed to be (1.861 + epsilon). Thus, our main contribution is a sublinear time selection mechanism that, while increasing the approximation factor by an arbitrary small additive term, allows us to decide which of the eligible facilities to open.


Pruned Continuous Haar Transform of 2D Polygonal Patterns with Application to VLSI Layouts

Abstract: We introduce an algorithm for the efficient computation of the continuous Haar transform of 2D patterns that can be described by polygons. These patterns are ubiquitous in VLSI processes where they are used to describe design and mask layouts. There, speed is of paramount importance due to the magnitude of the problems to be solved and hence very fast algorithms are needed. We show that by techniques borrowed from computational geometry we are not only able to compute the continuous Haar transform directly, but also to do it quickly. This is achieved by massively pruning the transform tree and thus dramatically decreasing the computational load when the number of vertices is small, as is the case for VLSI layouts. We call this new algorithm the pruned continuous Haar transform. We implement this algorithm and show that for patterns found in VLSI layouts the proposed algorithm was in the worst case as fast as its discrete counterpart and up to 12 times faster.


Eigengestures for natural human computer interface

Abstract: We present the application of Principal Component Analysis for data acquired during the design of a natural gesture interface. We investigate the concept of an eigengesture for motion capture hand gesture data and present the visualisation of principal components obtained in the course of conducted experiments. We also show the influence of dimensionality reduction on reconstructed gesture data quality.


Matchmaking Semantic Based for Information System Interoperability

Abstract: Unlike the traditional model of information pull, matchmaking is base on a cooperative partnership between information providers and consumers, assisted by an intelligent facilitator (the matchmaker). Refer to some experiments, the matchmaking to be most useful in two different ways: locating information sources or services that appear dynamically and notification of information changes. Effective information and services sharing in distributed such as P2P based environments raises many challenges, including discovery and localization of resources, exchange over heterogeneous sources, and query processing. One traditional approach for dealing with some of the above challenges is to create unified integrated schemas or services to combine the heterogeneous sources. This approach does not scale well when applied in dynamic distributed environments and has many drawbacks related to the large numbers of sources. The main issues in matchmaking are how to represent advertising and request, and how to calculate possibility matching between advertising and request. The advertising and request can represent data or services by using many model of representation. In this paper, we address an approach of matchmaking by considering semantic agreement between sources.


Modeling queuing dynamics of TCP: a simple model and its empirical validation

Abstract: Understanding queuing dynamics of TCP is important for correct router buffer sizing as well as for optimizing the performance of the TCP protocol itself. However, modeling of buffer content dynamics under TCP has received relatively little attention given its importance. Commonly used queuing models are based on overly simplistic assumptions about the packet arrival process. As a consequence, there are no quantitatively accurate closed loop TCP models capable of predicting performance even for a single link shared by multiple flows. Our present paper aims to close this gap by proposing a simple TCP queuing model, which is based on experimental observations and validated by extensive packet level simulations.


Achieving Data Privacy through Secrecy Views and Null-Based Virtual Updates

Abstract: There may be sensitive information in a relational database, and we might want to keep it hidden from a user or group thereof. In this work, sensitive data is characterized as the contents of a set of secrecy views. For a user without permission to access that sensitive data, the database instance he queries is updated to make the contents of the views empty or contain only tuples with null values. In particular, if this user poses a query about any of these views, no meaningful information is returned. Since the database is not expected to be physically changed to produce this result, the updates are only virtual. And also minimal in a precise way. These minimal updates are reflected in the secrecy view contents, and also in the fact that query answers, while being privacy preserving, are also maximally informative. Virtual updates are based on the use of null values as used in the SQL standard. We provide the semantics of secrecy views and the virtual updates. The different ways in which the underlying database is virtually updated are specified as the models of a logic program with stable model semantics. The program becomes the basis for the computation of the "secret answers" to queries, i.e. those that do not reveal the sensitive information.


Evaluating the Efficiency of Asynchronous Systems with FASE

Abstract: In this paper, we present FASE (Faster Asynchronous Systems Evaluation), a tool for evaluating the worst-case efficiency of asynchronous systems. The tool is based on some well-established results in the setting of a timed process algebra (PAFAS: a Process Algebra for Faster Asynchronous Systems). To show the applicability of FASE to concrete meaningful examples, we consider three implementations of a bounded buffer and use FASE to automatically evaluate their worst-case efficiency. We finally contrast our results with previous ones where the efficiency of the same implementations has already been considered.


A Framework for the Evaluation of Worst-Case System Efficiency

Abstract: In this paper we present FASE (Fast Asynchronous Systems Evaluation), a tool for evaluating worst-case efficiency of asynchronous systems. This tool implements some well-established results in the setting of a timed CCS-like process algebra: PAFAS (a Process Algebra for Faster Asynchronous Systems). Moreover, we discuss some new solutions that are useful to improve the applicability of FASE to concrete meaningful examples. We finally use fase to evaluate the efficiency of three different implementations of a bounded buffer and compare our results with previous ones obtained when the same implementations have been contrasted according to an efficiency preorder.


Finitary Deduction Systems

Abstract: Cryptographic protocols are the cornerstone of security in distributed systems. The formal analysis of their properties is accordingly one of the focus points of the security community, and is usually split among two groups. In the first group, one focuses on trace-based security properties such as confidentiality and authentication, and provides decision procedures for the existence of attacks for an on-line attackers. In the second group, one focuses on equivalence properties such as privacy and guessing attacks, and provides decision procedures for the existence of attacks for an offline attacker. In all cases the attacker is modeled by a deduction system in which his possible actions are expressed. We present in this paper a notion of finitary deduction systems that aims at relating both approaches. We prove that for such deduction systems, deciding equivalence properties for on-line attackers can be reduced to deciding reachability properties in the same setting.


Comparison Latent Semantic and WordNet Approach for Semantic Similarity Calculation

Abstract: Information exchange among many sources in Internet is more autonomous, dynamic and free. The situation drive difference view of concepts among sources. For example, word 'bank' has meaning as economic institution for economy domain, but for ecology domain it will be defined as slope of river or lake. In this aper, we will evaluate latent semantic and WordNet approach to calculate semantic similarity. The evaluation will be run for some concepts from different domain with reference by expert or human. Result of the evaluation can provide a contribution for mapping of concept, query rewriting, interoperability, etc.


Design of Thin-Film-Transistor (TFT) arrays using current mirror circuits for Flat Panel Detectors (FPDs)

Abstract: We designed 4x4 matrix TFTs arrays using current mirror amplifiers. Advantages of current mirror amplifiers are they need less requiring switches and the conversion time is short. The TFTs arrays 4x4 matrix using current mirror circuits have been fabricated and tested with success. The TFTs array directly can process signals coming from 16 pixels in the same node. This enables us to make the summation of the light intensities of close pixels during a reading.


Embeddings of Linear Arrays, Rings and 2-D Meshes on Extended Lucas Cube Networks

Abstract: A Fibonacci string is a length n binary string containing no two consecutive 1s. Fibonacci cubes (FC), Extended Fibonacci cubes (ELC) and Lucas cubes (LC) are subgraphs of hypercube defined in terms of Fibonacci strings. All these cubes were introduced in the last ten years as models for interconnection networks and shown that their network topology posseses many interesting properties that are important in parallel processor network design and parallel applications. In this paper, we propose a new family of Fibonacci-like cube, namely Extended Lucas Cube (ELC). We address the following network simulation problem : Given a linear array, a ring or a two-dimensional mesh; how can its nodes be assigned to ELC nodes so as to keep their adjacent nodes near each other in ELC ?. We first show a simple fact that there is a Hamiltonian path and cycle in any ELC. We prove that any linear array and ring network can be embedded into its corresponding optimum ELC (the smallest ELC with at least the number of nodes in the ring) with dilation 1, which is optimum for most cases. Then, we describe dilation 1 embeddings of a class of meshes into their corresponding optimum ELC.


Development of Active Pixel Photodiode Sensors for Gamma Camera Application

Abstract: We designed new photodiodes sensors including current mirror amplifiers. These photodiodes have been fabricated using a CMOS 0.6 micrometers process from Austria Micro System (AMS). The Photodiode areas are respectiveley 1mm x 1mm and 0.4mm x 0.4mm with fill factor 98 % and total chip area is 2 square millimetres. The sensor pixels show a logarithmic response in illumination and are capable of detecting very low blue light (less than 0.5 lux) . These results allow to use our sensor in new Gamma Camera solid-state concept.


Solving Rubik's Cube Using SAT Solvers

Abstract: Rubik's Cube is an easily-understood puzzle, which is originally called the "magic cube". It is a well-known planning problem, which has been studied for a long time. Yet many simple properties remain unknown. This paper studies whether modern SAT solvers are applicable to this puzzle. To our best knowledge, we are the first to translate Rubik's Cube to a SAT problem. To reduce the number of variables and clauses needed for the encoding, we replace a naive approach of 6 Boolean variables to represent each color on each facelet with a new approach of 3 or 2 Boolean variables. In order to be able to solve quickly Rubik's Cube, we replace the direct encoding of 18 turns with the layer encoding of 18-subtype turns based on 6-type turns. To speed up the solving further, we encode some properties of two-phase algorithm as an additional constraint, and restrict some move sequences by adding some constraint clauses. Using only efficient encoding cannot solve this puzzle. For this reason, we improve the existing SAT solvers, and develop a new SAT solver based on PrecoSAT, though it is suited only for Rubik's Cube. The new SAT solver replaces the lookahead solving strategy with an ALO (\emph{at-least-one}) solving strategy, and decomposes the original problem into sub-problems. Each sub-problem is solved by PrecoSAT. The empirical results demonstrate both our SAT translation and new solving technique are efficient. Without the efficient SAT encoding and the new solving technique, Rubik's Cube will not be able to be solved still by any SAT solver. Using the improved SAT solver, we can find always a solution of length 20 in a reasonable time. Although our solver is slower than Kociemba's algorithm using lookup tables, but does not require a huge lookup table.


A Self-Organized Resource Allocation using Inter-Cell Interference Coordination (ICIC) in Relay-Assisted Cellular Networks

Abstract: In a multi-cell scenario, the inter-cell interference (ICI) is detrimental in achieving the intended system performance, in particular for the edge users. There is paucity of work available in literature on ICI coordination (ICIC) for relay-assisted cellular networks (RACN). In this paper, we do a survey on the ICIC schemes in cellular networks and RACN. We then propose a self-organized resource allocation plan for RACN to improve the edge user's performance by ICIC. We compare the performance of reuse-1, reuse-3, soft frequency reuse (SFR) scheme, proposed plan with and without relays. The performance metrics for comparison are edge user's spectral efficiency, their signal-to-interference-and-noise ratio (SINR) and system's area spectral efficiency. We show by the simulation results that our proposed plan performs better than the existing resource allocation schemes in static allocation scenario. Next, we propose to make our resource allocation plan dynamic and self-organized. The distinct features of our proposed plan are: One, it achieves a trade-off between the system's area spectral efficiency and the edge user's spectral efficiency performance. Secondly, it introduces a novel concept of interfering neighbor set to achieve ICIC by local interaction between the entities.


The Ambient Networks Heterogeneous Access Selection Architecture

Abstract: Forthcoming wireless communications will be characterized by the ubiquity of multiaccess. Despite the inherently increased complexity, end-users should be able to take advantage of the most suitable access network. Thus, access selection in an environment with different overlapping radio technologies is of central interest and an architecture is needed that performs equally well on single- and multi-operator scenarios, considers several parameters, and respects the principle of layering. In this paper, we introduce the Ambient Networks heterogeneous access selection architecture explaining how it meets such requirements. We present the essential architectural components and explain their interactions. We illustrate how the proposed architecture works in practice and discuss recent results form our prototype-based validation.


A Generic Signaling Framework for Seamless Mobility in Heterogeneous Wireless Networks

Abstract: In recent years several wireless communication standards have been developed and more are expected, each with different scope in terms of spatial coverage, radio access capabilities, and mobility support. Heterogeneous networks combine multiple of these radio interfaces both in network infrastructure and in user equipment which requires a new multi-radio framework, enabling mobility and handover management for multiple RATs. The use of heterogeneous networks can capitalize on the overlapping coverage and allow user devices to take advantage of the fact that there are multiple radio interfaces. This paper presents the functional architecture for such a framework and proposes a generic signaling exchange applicable to a range of different handover management protocols that enables seamless mobility. The interworking of radio resource management, access selection and mobility management is defined in a generic and modular way, which is extensible for future protocols and standards.


Management of Multiple Mobility Protocols and Tools in Dynamically Configurable Networks

Abstract: Solutions for mobility management in wireless networks have been investigated and proposed in various research projects and standardization bodies. With the continuing deployment of different access networks, the wider range of applications tailored for a mobile environment, and a larger diversity of wireless end systems, it emerged that a single mobility protocol (such as Mobile IP) is not sufficient to handle the different requirements adequately. Thus a solution is needed to manage multiple mobility protocols in end systems and network nodes, to detect and select the required protocols, versions and optional features, and enable control on running daemons. For this purpose a mobility toolbox has been developed as part of the EU funded Ambient Networks project. This paper describes this modular management approach and illustrates the additional benefits a mobility protocol can gain by using state transfer as an example.


An Analysis of Routing Disruption Attack on Dynamic Source Routing Protocol

Abstract: Dynamic Source Routing (DSR) is a well known source routing protocol for ad hoc networks. The algorithm depends on the cooperative participation of the nodes that enables route discovery from a source node to a destination node. However, if a group of nodes do not cooperate, the performance of the DSR protocol may be severely degraded. This paper presents a probabilistic attack model on the DSR protocol and analyses its effect on the routing performance. Simulations results of the model show that the effect of the attack is catastrophic only if a large number of nodes are compromised and there is no detection mechanism. As an interesting observation, the analysis also shows that the attack model can also be used to improve the performance of the DSR protocol.


Efficient Image Transmission Through Analog Error Correction

Abstract: This paper presents a new paradigm for image transmission through analog error correction codes. Conventional schemes rely on digitizing images through quantization (which inevitably causes significant bandwidth expansion) and transmitting binary bit-streams through digital error correction codes (which do not automatically differentiate the different levels of significance among the bits). To strike a better overall performance in terms of transmission efficiency and quality, we propose to use a single analog error correction code in lieu of digital quantization, digital code and digital modulation. The key is to get analog coding right. We show that this can be achieved by cleverly exploiting an elegant "butterfly" property of chaotic systems. Specifically, we demonstrate a tail-biting triple-branch baker's map code and its maximum-likelihood decoding algorithm. Simulations show that the proposed analog code can actually outperform digital turbo code, one of the best codes known to date. The results and findings discussed in this paper speak volume for the promising potential of analog codes, in spite of their rather short history.


Complex Adaptive Digital EcoSystems

Abstract: We investigate an abstract conceptualisation of DigitalEcosystems from a computer science perspective. We then provide a conceptual framework for the cross pollination of ideas, concepts and understanding between different classes of ecosystems through the universally applicable principles of Complex Adaptive Systems (CAS) modelling. A framework to assist the cross-disciplinary collaboration of research into Digital Ecosystems, including Digital BusinessEcosystems (DBEs) and Digital Knowledge Ecosystems (DKEs). So, we have defined the key steps towards a theoretical framework for Digital Ecosystems, that is compatible with the diverse theoretical views prevalent. Therefore, a theoretical edifice that can unify the diverse efforts within Digital Ecosystems research.


Practical and theoretical improvements for bipartite matching using the pseudoflow algorithm

Abstract: We show that the pseudoflow algorithm for maximum flow is particularly efficient for the bipartite matching problem both in theory and in practice. We develop several implementations of the pseudoflow algorithm for bipartite matching, and compare them over a wide set of benchmark instances to state-of-the-art implementations of push-relabel and augmenting path algorithms that are specifically designed to solve these problems. The experiments show that the pseudoflow variants are in most cases faster than the other algorithms. We also show that one particular implementation---the matching pseudoflow algorithm---is theoretically efficient. For a graph with $n$ nodes, $m$ arcs, $n_1$ the size of the smaller set in the bipartition, and the maximum matching value $\kappa \leq n_1$, the algorithm's complexity given input in the form of adjacency lists is $O(\min{n_1\kappa,m} + \sqrt{\kappa}\min{\kappa^2,m})$. Similar algorithmic ideas are shown to work for an adaptation of Hopcroft and Karp's bipartite matching algorithm with the same complexity. Using boolean operations on words of size $\lambda$, the complexity of the pseudoflow algorithm is further improved to $O(\min{n_1\kappa, \frac{n_1n_2}{\lambda}, m} + \kappa^2 + \frac{\kappa^{2.5}}{\lambda})$. This run time is faster than for previous algorithms such as Cheriyan and Mehlhorn's algorithm of complexity $O(\frac{n^{2.5}}{\lambda})$.


Some Aspects of Quantum Cryptography and Network Security

Abstract: Quantum mechanics is the current best description of the world as we know it. Experiments have shown that quantum predictions are accurate up ten places of decimal. In quantum cryptography much work has been devoted to the study of Quantum Key Distribution (QKD). The purpose of QKD is to securely distribute secret keys between the users in a network. As a result, several quantum cryptographic protocols have been implemented and tested after the advent of quantum computing. In this paper, we have given a brief overview of QKD, and some practical networks that integrate QKD in the current Internet security architecture. We have also discussed some aspects of quantum network security with particular attention to Byzantine Agreement Protocol.


Computing Majority with Triple Queries

Abstract: Consider a bin containing $n$ balls colored with two colors. In a $k$-query, $k$ balls are selected by a questioner and the oracle's reply is related (depending on the computation model being considered) to the distribution of colors of the balls in this $k$-tuple; however, the oracle never reveals the colors of the individual balls. Following a number of queries the questioner is said to determine the majority color if it can output a ball of the majority color if it exists, and can prove that there is no majority if it does not exist. We investigate two computation models (depending on the type of replies being allowed). We give algorithms to compute the minimum number of 3-queries which are needed so that the questioner can determine the majority color and provide tight and almost tight upper and lower bounds on the number of queries needed in each case.


Computation of WCET using Program Slicing and Real-Time Model-Checking

Abstract: Computing accurate WCET on modern complex architectures is a challenging task. This problem has been devoted a lot of attention in the last decade but there are still some open issues. First, the control flow graph (CFG) of a binary program is needed to compute the WCET and this CFG is built using some internal knowledge of the compiler that generated the binary code; moreover once constructed the CFG has to be manually annotated with loop bounds. Second, the algorithms to compute the WCET (combining Abstract Interpretation and Integer Linear Programming) are tailored for specific architectures: changing the architecture (e.g. replacing an ARM7 by an ARM9) requires the design of a new ad hoc algorithm. Third, the tightness of the computed results (obtained using the available tools) are not compared to actual execution times measured on the real hardware. In this paper we address the above mentioned problems. We first describe a fully automatic method to compute a CFG based solely on the binary program to analyse. Second, we describe the model of the hardware as a product of timed automata, and this model is independent from the program description. The model of a program running on a hardware is obtained by synchronizing (the automaton of) the program with the (timed automata) model of the hardware. Computing the WCET is reduced to a reachability problem on the synchronised model and solved using the model-checker UPPAAL. Finally, we present a rigorous methodology that enables us to compare our computed results to actual execution times measured on a real platform, the ARM920T.


Neural network to identify individuals at health risk

Abstract: The risk of diseases such as heart attack and high blood pressure could be reduced by adequate physical activity. However, even though majority of general population claims to perform some physical exercise, only a minority exercises enough to keep a healthy living style. Thus, physical inactivity has become one of the major concerns of public health in the past decade. Research shows that the highest decrease in physical activity is noticed from high school to college. Thus, it is of great importance to quickly identify college students at health risk due to physical inactivity. Research also shows that the level of physical activity of an individual is highly correlated to demographic features such as race and gender, as well as self motivation and support from family and friends. This information could be collected from each student via a 20 minute questionnaire, but the time needed to distribute and analyze each questionnaire is infeasible on a collegiate campus. Thus, we propose an automatic identifier of students at risk, so that these students could easier be targeted by collegiate campuses and physical activity promotion departments. We present in this paper preliminary results of a supervised backpropagation multilayer neural network for classifying students into at-risk or not at-risk group.


Approximating Petri Net Reachability Along Context-free Traces

Abstract: We investigate the problem asking whether the intersection of a context-free language (CFL) and a Petri net language (PNL) is empty. Our contribution to solve this long-standing problem which relates, for instance, to the reachability analysis of recursive programs over unbounded data domain, is to identify a class of CFLs called the finite-index CFLs for which the problem is decidable. The k-index approximation of a CFL can be obtained by discarding all the words that cannot be derived within a budget k on the number of occurrences of non-terminals. A finite-index CFL is thus a CFL which coincides with its k-index approximation for some k. We decide whether the intersection of a finite-index CFL and a PNL is empty by reducing it to the reachability problem of Petri nets with weak inhibitor arcs, a class of systems with infinitely many states for which reachability is known to be decidable. Conversely, we show that the reachability problem for a Petri net with weak inhibitor arcs reduces to the emptiness problem of a finite-index CFL intersected with a PNL.


Internet of Things: Applications and Challenges in Technology and Standardization

Abstract: The phrase Internet of Things (IoT) heralds a vision of the future Internet where connecting physical things, from banknotes to bicycles, through a network will let them take an active part in the Internet, exchanging information about themselves and their surroundings. This will give immediate access to information about the physical world and the objects in it leading to innovative services and increase in efficiency and productivity. This paper studies the state-of-the-art of IoT and presents the key technological drivers,potential applications, challenges and future research areas in the domain of IoT. IoT definitions from different perspective in academic and industry communities are also discussed and compared. Finally some major issues of future research in IoT are identified and discussed briefly.


Experimental Study of the Shortest Reset Word of Random Automata

Abstract: In this paper we describe an approach to finding the shortest reset word of a finite synchronizing automaton by using a SAT solver. We use this approach to perform an experimental study of the length of the shortest reset word of a finite synchronizing automaton. The largest automata we considered had 100 states. The results of the experiments allow us to formulate a hypothesis that the length of the shortest reset word of a random finite automaton with $n$ states and 2 input letters with high probability is sublinear with respect to $n$ and can be estimated as $1.95 n^{0.55}.$


Priority Based Dynamic Round Robin (PBDRR) Algorithm with Intelligent Time Slice for Soft Real Time Systems

Abstract: In this paper, a new variant of Round Robin (RR) algorithm is proposed which is suitable for soft real time systems. RR algorithm performs optimally in timeshared systems, but it is not suitable for soft real time systems. Because it gives more number of context switches, larger waiting time and larger response time. We have proposed a novel algorithm, known as Priority Based Dynamic Round Robin Algorithm(PBDRR),which calculates intelligent time slice for individual processes and changes after every round of execution. The proposed scheduling algorithm is developed by taking dynamic time quantum concept into account. Our experimental results show that our proposed algorithm performs better than algorithm in [8] in terms of reducing the number of context switches, average waiting time and average turnaround time.


Abstracting Abstract Machines: A Systematic Approach to Higher-Order Program Analysis

Abstract: Predictive models are fundamental to engineering reliable software systems. However, designing conservative, computable approximations for the behavior of programs (static analyses) remains a difficult and error-prone process for modern high-level programming languages. What analysis designers need is a principled method for navigating the gap between semantics and analytic models: analysis designers need a method that tames the interaction of complex languages features such as higher-order functions, recursion, exceptions, continuations, objects and dynamic allocation. We contribute a systematic approach to program analysis that yields novel and transparently sound static analyses. Our approach relies on existing derivational techniques to transform high-level language semantics into low-level deterministic state-transition systems (with potentially infinite state spaces). We then perform a series of simple machine refactorings to obtain a sound, computable approximation, which takes the form of a non-deterministic state-transition systems with finite state spaces. The approach scales up uniformly to enable program analysis of realistic language features, including higher-order functions, tail calls, conditionals, side effects, exceptions, first-class continuations, and even garbage collection.


A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control

Abstract: Reinforcement Learning (RL) is a method for learning decision-making tasks that could enable robots to learn and adapt to their situation on-line. For an RL algorithm to be practical for robotic control tasks, it must learn in very few actions, while continually taking those actions in real-time. Existing model-based RL methods learn in relatively few actions, but typically take too much time between each action for practical on-line learning. In this paper, we present a novel parallel architecture for model-based RL that runs in real-time by 1) taking advantage of sample-based approximate planning methods and 2) parallelizing the acting, model learning, and planning processes such that the acting process is sufficiently fast for typical robot control cycles. We demonstrate that algorithms using this architecture perform nearly as well as methods using the typical sequential architecture when both are given unlimited time, and greatly out-perform these methods on tasks that require real-time actions such as controlling an autonomous vehicle.


User Mode Memory Page Allocation: A Silver Bullet For Memory Allocation?

Abstract: This paper proposes a novel solution: the elimination of paged virtual memory and partial outsourcing of memory page allocation and manipulation from the operating system kernel into the individual process' user space - a user mode page allocator - which allows an application to have direct, bare metal access to the page mappings used by the hardware Memory Management Unit (MMU) for its part of the overall address space. A user mode page allocator based emulation of the mmap() abstraction layer of dlmalloc is then benchmarked against the traditional kernel mode implemented mmap() in a series of synthetic Monte-Carlo and real world application settings. Given the superb synthetic and positive real world results from the profiling conducted, this paper proposes that with proper operating system and API support one could gain a further order higher performance again while keeping allocator performance invariant to the amount of memory being allocated or freed i.e. a 100x performance improvement or more in some common use cases. It is rare that through a simple and easy to implement API and operating system structure change one can gain a Silver Bullet with the potential for a second one.


User Mode Memory Page Management: An old idea applied anew to the memory wall problem

Abstract: It is often said that one of the biggest limitations on computer performance is memory bandwidth (i.e."the memory wall problem"). In this position paper, I argue that if historical trends in computing evolution (where growth in available capacity is exponential and reduction in its access latencies is linear) continue as they have, then this view is wrong - in fact we ought to be concentrating on reducing whole system memory access latencies wherever possible, and by "whole system" I mean that we ought to look at how software can be unnecessarily wasteful with memory bandwidth due to legacy design decisions. To this end I conduct a feasibility study to determine whether we ought to virtualise the MMU for each application process such that it has direct access to its own MMU page tables and the memory allocated to a process is managed exclusively by the process and not the kernel. I find under typical conditions that nearly scale invariant performance to memory allocation size is possible such that hundreds of megabytes of memory can be allocated, relocated, swapped and deallocated in almost the same time as kilobytes (e.g. allocating 8Mb is 10x quicker under this experimental allocator than a conventional allocator, and resizing a 128Kb block to 256Kb block is 4.5x faster). I find that first time page access latencies are improved tenfold; moreover, because the kernel page fault handler is never called, the lack of cache pollution improves whole application memory access latencies increasing performance by up to 2x. Finally, I try binary patching existing applications to use the experimental allocation technique, finding almost universal performance improvements without having to recompile these applications to make better use of the new facilities.


Individual-based stability in hedonic games depending on the best or worst players

Abstract: We consider coalition formation games in which each player has preferences over the other players and his preferences over coalitions are based on the best player ($\mathcal{B}$-/B-hedonic games) or the worst player ($\mathcal{W}$/W-hedonic games) in the coalition. We show that for $\mathcal{B}$-hedonic games, an individually stable partition is guaranteed to exist and can be computed efficiently. Similarly, there exists a polynomial-time algorithm which returns a Nash stable partition (if one exists) for $\mathcal{B}$-hedonic games with strict preferences. Both $\mathcal{W}$- and W-hedonic games are equivalent if individual rationality is assumed. It is also shown that for B- or $\mathcal{W}$-hedonic games, checking whether a Nash stable partition or an individually stable partition exists is NP-complete even in some cases for strict preferences. We identify a key source of intractability in compact coalition formation games in which preferences over players are extended to preferences over coalitions.


Dissecting a Small InfiniBand Application Using the Verbs API

Abstract: InfiniBand is a switched fabric interconnect. The InfiniBand specification does not define an API. However the OFED package, libibverbs, has become the default API on Linux and Solaris systems. Sparse documentation exists for the verbs API. The simplest InfiniBand program provided by OFED, ibv_rc_pingpong, is about 800 lines long. The semantics of using the verbs API for this program is not obvious to the first time reader. This paper will dissect the ibv_rc_pingpong program in an attempt to make clear to users how to interact with verbs.


Securing The Kernel via Static Binary Rewriting and Program Shepherding

Abstract: Recent Microsoft security bulletins show that kernel vulnerabilities are becoming more and more important security threats. Despite the pretty extensive security mitigations many of the kernel vulnerabilities are still exploitable. Successful kernel exploitation typically grants the attacker maximum privilege level and results in total machine compromise. To protect against kernel exploitation, we have developed a tool which statically rewrites the Microsoft Windows kernel as well as other kernel level modules. Such rewritten binary files allow us to monitor control flow transfers during operating system execution. At this point we are able to detect whether selected control transfer flow is valid or should be considered as an attack attempt. Our solution is especially directed towards preventing remote kernel exploitation attempts. Additionally, many of the local privilege escalation attacks are also blocked (also due to additional mitigation techniques we have implemented). Our tool was tested with Microsoft Windows XP, Windows Vista and Windows 7 (under both virtual and physical machines) on IA-32 compatible processors. Our apparatus is also completely standalone and does not require any third party software.


"Eppur si muove", Software Libero e Ricerca Riproducibile

Abstract: This article describes similarities of the scientific method and the free open source software development, and how reproducibility is the key of an healthy scientific production.


Chebyshev Polynomial Approximation for Distributed Signal Processing

Abstract: Unions of graph Fourier multipliers are an important class of linear operators for processing signals defined on graphs. We present a novel method to efficiently distribute the application of these operators to the high-dimensional signals collected by sensor networks. The proposed method features approximations of the graph Fourier multipliers by shifted Chebyshev polynomials, whose recurrence relations make them readily amenable to distributed computation. We demonstrate how the proposed method can be used in a distributed denoising task, and show that the communication requirements of the method scale gracefully with the size of the network.


Convergence Analysis of Differential Evolution Variants on Unconstrained Global Optimization Functions

Abstract: In this paper, we present an empirical study on convergence nature of Differential Evolution (DE) variants to solve unconstrained global optimization problems. The aim is to identify the competitive nature of DE variants in solving the problem at their hand and compare. We have chosen fourteen benchmark functions grouped by feature: unimodal and separable, unimodal and nonseparable, multimodal and separable, and multimodal and nonseparable. Fourteen variants of DE were implemented and tested on fourteen benchmark problems for dimensions of 30. The competitiveness of the variants are identified by the Mean Objective Function value, they achieved in 100 runs. The convergence nature of the best and worst performing variants are analyzed by measuring their Convergence Speed (Cs) and Quality Measure (Qm).


The Hidden Web, XML and Semantic Web: A Scientific Data Management Perspective

Abstract: The World Wide Web no longer consists just of HTML pages. Our work sheds light on a number of trends on the Internet that go beyond simple Web pages. The hidden Web provides a wealth of data in semi-structured form, accessible through Web forms and Web services. These services, as well as numerous other applications on the Web, commonly use XML, the eXtensible Markup Language. XML has become the lingua franca of the Internet that allows customized markups to be defined for specific domains. On top of XML, the Semantic Web grows as a common structured data source. In this work, we first explain each of these developments in detail. Using real-world examples from scientific domains of great interest today, we then demonstrate how these new developments can assist the managing, harvesting, and organization of data on the Web. On the way, we also illustrate the current research avenues in these domains. We believe that this effort would help bridge multiple database tracks, thereby attracting researchers with a view to extend database technology.


Emerging multidisciplinary research across database management systems

Abstract: The database community is exploring more and more multidisciplinary avenues: Data semantics overlaps with ontology management; reasoning tasks venture into the domain of artificial intelligence; and data stream management and information retrieval shake hands, e.g., when processing Web click-streams. These new research avenues become evident, for example, in the topics that doctoral students choose for their dissertations. This paper surveys the emerging multidisciplinary research by doctoral students in database systems and related areas. It is based on the PIKM 2010, which is the 3rd Ph.D. workshop at the International Conference on Information and Knowledge Management (CIKM). The topics addressed include ontology development, data streams, natural language processing, medical databases, green energy, cloud computing, and exploratory search. In addition to core ideas from the workshop, we list some open research questions in these multidisciplinary areas.


Classification and Evaluation the Privacy Preserving Data Mining Techniques by using a Data Modification-based Framework

Abstract: In recent years, the data mining techniques have met a serious challenge due to the increased concerning and worries of the privacy, that is, protecting the privacy of the critical and sensitive data. Different techniques and algorithms have been already presented for Privacy Preserving data mining, which could be classified in three common approaches: Data modification approach, Data sanitization approach and Secure Multi-party Computation approach. This paper presents a Data modification- based Framework for classification and evaluation of the privacy preserving data mining techniques. Based on our framework the techniques are divided into two major groups, namely perturbation approach and anonymization approach. Also in proposed framework, eight functional criteria will be used to analyze and analogically assessment of the techniques in these two major groups. The proposed framework provides a good basis for more accurate comparison of the given techniques to privacy preserving data mining. In addition, this framework allows recognizing the overlapping amount for different approaches and identifying modern approaches in this field.


Analytical Classification of Multimedia Index Structures by Using a Partitioning Method-Based Framework

Abstract: Due to the advances in hardware technology and increase in production of multimedia data in many applications, during the last decades, multimedia databases have become increasingly important. Contentbased multimedia retrieval is one of an important research area in the field of multimedia databases. Lots of research on this field has led to proposition of different kinds of index structures to support fast and efficient similarity search to retrieve multimedia data from these databases. Due to variety and plenty of proposed index structures, we suggest a systematic framework based on partitioning method used in these structures to classify multimedia index structures, and then we evaluated these structures based on important functional measures. We hope this proposed framework will lead to empirical and technical comparison of multimedia index structures and development of more efficient structures at future.


An analytical framework for data stream mining techniques based on challenges and requirements

Abstract: A growing number of applications that generate massive streams of data need intelligent data processing and online analysis. Real-time surveillance systems, telecommunication systems, sensor networks and other dynamic environments are such examples. The imminent need for turning such data into useful information and knowledge augments the development of systems, algorithms and frameworks that address streaming challenges. The storage, querying and mining of such data sets are highly computationally challenging tasks. Mining data streams is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information. Generally, two main challenges are designing fast mining methods for data streams and need to promptly detect changing concepts and data distribution because of highly dynamic nature of data streams. The goal of this article is to analyze and classify the application of diverse data mining techniques in different challenges of data stream mining. In this paper, we present the theoretical foundations of data stream analysis and propose an analytical framework for data stream mining techniques.


Algebra-Logical Repair Method for FPGA Logic Blocks

Abstract: An algebra-logical repair method for FPGA functional logic blocks on the basis of solving the coverage problem is proposed. It is focused on implementation into Infrastructure IP for system-on-a chip and system-in-package. A method is designed for providing the operability of FPGA blocks and digital system as a whole. It enables to obtain exact and optimal solution associated with the minimum number of spares needed to repair the FPGA logic components with multiple faults.


Brain-like infrastructure for embedded SoC diagnosis

Abstract: This article describes high-speed multiprocessor architecture for the concurrent analyzing information represented in analytic, graph- and table forms of associative relations to search, recognize and make a decision in n-dimensional vector discrete space. Vector-logical process models of actual applications,for which the quality of solution is estimated by the proposed integral non-arithmetical metric of the interaction between Boolean vectors, are described.


Secure Data Processing in a Hybrid Cloud

Abstract: Cloud computing has made it possible for a user to be able to select a computing service precisely when needed. However, certain factors such as security of data and regulatory issues will impact a user's choice of using such a service. A solution to these problems is the use of a hybrid cloud that combines a user's local computing capabilities (for mission- or organization-critical tasks) with a public cloud (for less influential tasks). We foresee three challenges that must be overcome before the adoption of a hybrid cloud approach: 1) data design: How to partition relations in a hybrid cloud? The solution to this problem must account for the sensitivity of attributes in a relation as well as the workload of a user; 2) data security: How to protect a user's data in a public cloud with encryption while enabling query processing over this encrypted data? and 3) query processing: How to execute queries efficiently over both, encrypted and unencrypted data? This paper addresses these challenges and incorporates their solutions into an add-on tool for a Hadoop and Hive based cloud computing infrastructure.


A Step-indexed Semantic Model of Types for the Call-by-Name Lambda Calculus

Abstract: Step-indexed semantic models of types were proposed as an alternative to purely syntactic safety proofs using subject-reduction. Building upon the work by Appel and others, we introduce a generalized step-indexed model for the call-by-name lambda calculus. We also show how to prove type safety of general recursion in our call-by-name model.


New Heuristic Rounding Approaches to the Quadratic Assignment Problem

Abstract: Quadratic assignment problem is one of the great challenges in combinatorial optimization. It has many applications in Operations research and Computer Science. In this paper, the author extends the most-used rounding approach to a one-parametric optimization model for the quadratic assignment problems. A near-optimum parameter is also predestinated. The numerical experiments confirm the efficiency.


Security Risks and Modern Cyber Security Technologies for Corporate Networks

Abstract: This article aims to highlight current trends on the market of corporate antivirus solutions. Brief overview of modern security threats that can destroy IT environment is provided as well as a typical structure and features of antivirus suits for corporate users presented on the market. The general requirements for corporate products are determined according to the last report from av-comparatives.org [1]. The detailed analysis of new features is provided based on an overview of products available on the market nowadays. At the end, an enumeration of modern trends in antivirus industry for corporate users completes this article. Finally, the main goal of this article is to stress an attention about new trends suggested by AV vendors in their solutions in order to protect customers against newest security threats.


Practical Verified Computation with Streaming Interactive Proofs

Abstract: When delegating computation to a service provider, as in cloud computing, we seek some reassurance that the output is correct and complete. Yet recomputing the output as a check is inefficient and expensive, and it may not even be feasible to store all the data locally. We are therefore interested in proof systems which allow a service provider to prove the correctness of its output to a streaming (sublinear space) user, who cannot store the full input or perform the full computation herself. Our approach is two-fold. First, we describe a carefully chosen instantiation of one of the most efficient general-purpose constructions for arbitrary computations (streaming or otherwise), due to Goldwasser, Kalai, and Rothblum. This requires several new insights to make the methodology more practical. Our main contribution is in achieving a prover who runs in time O(S(n) log S(n)), where S(n) is the size of an arithmetic circuit computing the function of interest. Our experimental results demonstrate that a practical general-purpose protocol for verifiable computation may be significantly closer to reality than previously realized. Second, we describe techniques that achieve genuine scalability for protocols fine-tuned for specific important problems in streaming and database processing. Focusing in particular on non-interactive protocols for problems ranging from matrix-vector multiplication to bipartite perfect matching, we build on prior work to achieve a prover who runs in nearly linear-time, while obtaining optimal tradeoffs between communication cost and the user's working memory. Existing techniques required (substantially) superlinear time for the prover. We argue that even if general-purpose methods improve, fine-tuned protocols will remain valuable in real-world settings for key problems, and hence special attention to specific problems is warranted.


Submodular Cost Allocation Problem and Applications

Abstract: We study the Minimum Submodular-Cost Allocation problem (MSCA). In this problem we are given a finite ground set $V$ and $k$ non-negative submodular set functions $f_1 ,..., f_k$ on $V$. The objective is to partition $V$ into $k$ (possibly empty) sets $A_1 ,..., A_k$ such that the sum $\sum_{i=1}^k f_i(A_i)$ is minimized. Several well-studied problems such as the non-metric facility location problem, multiway-cut in graphs and hypergraphs, and uniform metric labeling and its generalizations can be shown to be special cases of MSCA. In this paper we consider a convex-programming relaxation obtained via the Lov\'asz-extension for submodular functions. This allows us to understand several previous relaxations and rounding procedures in a unified fashion and also develop new formulations and approximation algorithms for several problems. In particular, we give a $(1.5 - 1/k)$-approximation for the hypergraph multiway partition problem. We also give a $\min\{2(1-1/k), H_{\Delta}\}$-approximation for the hypergraph multiway cut problem when $\Delta$ is the maximum hyperedge size. Both problems generalize the multiway cut problem in graphs and the hypergraph cut problem is approximation equivalent to the node-weighted multiway cut problem in graphs.


Approximation Algorithms for Submodular Multiway Partition

Abstract: We study algorithms for the Submodular Multiway Partition problem (SubMP). An instance of SubMP consists of a finite ground set $V$, a subset of $k$ elements $S = \{s_1,s_2,...,s_k\}$ called terminals, and a non-negative submodular set function $f:2^V\rightarrow \mathbb{R}_+$ on $V$ provided as a value oracle. The goal is to partition $V$ into $k$ sets $A_1,...,A_k$ such that for $1 \le i \le k$, $s_i \in A_i$ and $\sum_{i=1}^k f(A_i)$ is minimized. SubMP generalizes some well-known problems such as the Multiway Cut problem in graphs and hypergraphs, and the Node-weighed Multiway Cut problem in graphs. SubMP for arbitrarysubmodular functions (instead of just symmetric functions) was considered by Zhao, Nagamochi and Ibaraki \cite{ZhaoNI05}. Previous algorithms were based on greedy splitting and divide and conquer strategies. In very recent work \cite{ChekuriE11} we proposed a convex-programming relaxation for SubMP based on the Lov\'asz-extension of a submodular function and showed its applicability for some special cases. In this paper we obtain the following results for arbitrary submodular functions via this relaxation. (i) A 2-approximation for SubMP. This improves the $(k-1)$-approximation from \cite{ZhaoNI05} and (ii) A $(1.5-1/k)$-approximation for SubMP when $f$ is symmetric. This improves the $2(1-1/k)$-approximation from \cite{Queyranne99,ZhaoNI05}.


In Search of Autocorrelation Based Vocal Cord Cues for Speaker Identification

Abstract: In this paper we investigate a technique to find out vocal source based features from the LP residual of speech signal for automatic speaker identification. Autocorrelation with some specific lag is computed for the residual signal to derive these features. Compared to traditional features like MFCC, PLPCC which represent vocal tract information, these features represent complementary vocal cord information. Our experiment in fusing these two sources of information in representing speaker characteristics yield better speaker identification accuracy. We have used Gaussian mixture model (GMM) based speaker modeling and results are shown on two public databases to validate our proposition.


On relaxing the constraints in pairwise compatibility graphs

Abstract: A graph $G$ is called a pairwise compatibility graph (PCG) if there exists an edge weighted tree $T$ and two non-negative real numbers $d_{min}$ and $d_{max}$ such that each leaf $l_u$ of $T$ corresponds to a vertex $u \in V$ and there is an edge $(u,v) \in E$ if and only if $d_{min} \leq d_T (l_u, l_v) \leq d_{max}$ where $d_T (l_u, l_v)$ is the sum of the weights of the edges on the unique path from $l_u$ to $l_v$ in $T$. In this paper we analyze the class of PCG in relation with two particular subclasses resulting from the the cases where $\dmin=0$ (LPG) and $\dmax=+\infty$ (mLPG). In particular, we show that the union of LPG and mLPG does not coincide with the whole class PCG, their intersection is not empty, and that neither of the classes LPG and mLPG is contained in the other. Finally, as the graphs we deal with belong to the more general class of split matrogenic graphs, we focus on this class of graphs for which we try to establish the membership to the PCG class.


A Cloud-based Approach for Context Information Provisioning

Abstract: As a result of the phenomenal proliferation of modern mobile Internet-enabled devices and the widespread utilization of wireless and cellular data networks, mobile users are increasingly requiring services tailored to their current context. High-level context information is typically obtained from context services that aggregate raw context information sensed by various sensors and mobile devices. Given the massive amount of sensed data, traditional context services are lacking the necessary resources to store and process these data, as well as to disseminate high-level context information to a variety of potential context consumers. In this paper, we propose a novel framework for context information provisioning, which relies on deploying context services on the cloud and using context brokers to mediate between context consumers and context services using a publish/subscribe model. Moreover, we describe a multi-attributes decision algorithm for the selection of potential context services that can fulfill context consumers' requests for context information. The algorithm calculates the score of each context service, per context information type, based on the quality-of-service (QoS) and quality-of-context information (QoC) requirements expressed by the context consumer. One of the benefits of the approach is that context providers can scale up and down, in terms of cloud resources they use, depending on current demand for context information. Besides, the selection algorithm allows ranking context services by matching their QoS and QoC offers against the QoS and QoC requirements of the context consumer.