Granularity-Adaptive Proof Presentation

Abstract: When mathematicians present proofs they usually adapt their explanations to their didactic goals and to the (assumed) knowledge of their addressees. Modern automated theorem provers, in contrast, present proofs usually at a fixed level of detail (also called granularity). Often these presentations are neither intended nor suitable for human use. A challenge therefore is to develop user- and goal-adaptive proof presentation techniques that obey common mathematical practice. We present a flexible and adaptive approach to proof presentation that exploits machine learning techniques to extract a model of the specific granularity of proof examples and employs this model for the automated generation of further proofs at an adapted level of granularity.


General Game Management Agent

Abstract: The task of managing general game playing in a multi-agent system is the problem addressed in this paper. It is considered to be done by an agent. There are many reasons for constructing such an agent, called general game management agent. This agent manages strategic interactions between other agents - players, natural or also artificial. The agent records the interaction for further benchmarking and analysis. He can also be used for a kind of restricted communications. His behavior is defined by a game description written in a logic-based language. The language, we present for this application, is more expressive than the language GDL, which is already used for such purposes. Our language can represent imperfect information and time dependent elements of a game. Time dependent elements like delays and timeouts are of crucial importance for interactions between players with bounded processing power like humans. We provide examples to show the feasibility of our approach. A way for game theoretical solving of an interaction description in our language is considered as future work.


How to Play Unique Games on Expanders

Abstract: In this note we improve a recent result by Arora, Khot, Kolla, Steurer, Tulsiani, and Vishnoi on solving the Unique Games problem on expanders. Given a $(1-\varepsilon)$-satisfiable instance of Unique Games with the constraint graph $G$, our algorithm finds an assignment satisfying at least a $1- C \varepsilon/h_G$ fraction of all constraints if $\varepsilon < c \lambda_G$ where $h_G$ is the edge expansion of $G$, $\lambda_G$ is the second smallest eigenvalue of the Laplacian of $G$, and $C$ and $c$ are some absolute constants.


De-amortized Cuckoo Hashing: Provable Worst-Case Performance and Experimental Results

Abstract: Cuckoo hashing is a highly practical dynamic dictionary: it provides amortized constant insertion time, worst case constant deletion time and lookup time, and good memory utilization. However, with a noticeable probability during the insertion of n elements some insertion requires \Omega(log n) time. Whereas such an amortized guarantee may be suitable for some applications, in other applications (such as high-performance routing) this is highly undesirable. Recently, Kirsch and Mitzenmacher (Allerton '07) proposed a de-amortization of cuckoo hashing using various queueing techniques that preserve its attractive properties. Kirsch and Mitzenmacher demonstrated a significant improvement to the worst case performance of cuckoo hashing via experimental results, but they left open the problem of constructing a scheme with provable properties. In this work we follow Kirsch and Mitzenmacher and present a de-amortization of cuckoo hashing that provably guarantees constant worst case operations. Specifically, for any sequence of polynomially many operations, with overwhelming probability over the randomness of the initialization phase, each operation is performed in constant time. Our theoretical analysis and experimental results indicate that the scheme is highly efficient, and provides a practical alternative to the only other known dynamic dictionary with such worst case guarantees, due to Dietzfelbinger and Meyer auf der Heide (ICALP '90).


Deductive Inference for the Interiors and Exteriors of Horn Theories

Abstract: In this paper, we investigate the deductive inference for the interiors and exteriors of Horn knowledge bases, where the interiors and exteriors were introduced by Makino and Ibaraki to study stability properties of knowledge bases. We present a linear time algorithm for the deduction for the interiors and show that it is co-NP-complete for the deduction for the exteriors. Under model-based representation, we show that the deduction problem for interiors is NP-complete while the one for exteriors is co-NP-complete. As for Horn envelopes of the exteriors, we show that it is linearly solvable under model-based representation, while it is co-NP-complete under formula-based representation. We also discuss the polynomially solvable cases for all the intractable problems.


Filtering Algorithms for the Multiset Ordering Constraint

Abstract: Constraint programming (CP) has been used with great success to tackle a wide variety of constraint satisfaction problems which are computationally intractable in general. Global constraints are one of the important factors behind the success of CP. In this paper, we study a new global constraint, the multiset ordering constraint, which is shown to be useful in symmetry breaking and searching for leximin optimal solutions in CP. We propose efficient and effective filtering algorithms for propagating this global constraint. We show that the algorithms are sound and complete and we discuss possible extensions. We also consider alternative propagation methods based on existing constraints in CP toolkits. Our experimental results on a number of benchmark problems demonstrate that propagating the multiset ordering constraint via a dedicated algorithm can be very beneficial.


Breaking Value Symmetry

Abstract: Symmetry is an important factor in solving many constraint satisfaction problems. One common type of symmetry is when we have symmetric values. In a recent series of papers, we have studied methods to break value symmetries. Our results identify computational limits on eliminating value symmetry. For instance, we prove that pruning all symmetric values is NP-hard in general. Nevertheless, experiments show that much value symmetry can be broken in practice. These results may be useful to researchers in planning, scheduling and other areas as value symmetry occurs in many different domains.


The Parameterized Complexity of Global Constraints

Abstract: We argue that parameterized complexity is a useful tool with which to study global constraints. In particular, we show that many global constraints which are intractable to propagate completely have natural parameters which make them fixed-parameter tractable and which are easy to compute. This tractability tends either to be the result of a simple dynamic program or of a decomposition which has a strong backdoor of bounded size. This strong backdoor is often a cycle cutset. We also show that parameterized complexity can be used to study other aspects of constraint programming like symmetry breaking. For instance, we prove that value symmetry is fixed-parameter tractable to break in the number of symmetries. Finally, we argue that parameterized complexity can be used to derive results about the approximability of constraint propagation.


Decompositions of Grammar Constraints

Abstract: A wide range of constraints can be compactly specified using automata or formal languages. In a sequence of recent papers, we have shown that an effective means to reason with such specifications is to decompose them into primitive constraints. We can then, for instance, use state of the art SAT solvers and profit from their advanced features like fast unit propagation, clause learning, and conflict-based search heuristics. This approach holds promise for solving combinatorial problems in scheduling, rostering, and configuration, as well as problems in more diverse areas like bioinformatics, software testing and natural language processing. In addition, decomposition may be an effective method to propagate other global constraints.


SLIDE: A Useful Special Case of the CARDPATH Constraint

Abstract: We study the CardPath constraint. This ensures a given constraint holds a number of times down a sequence of variables. We show that SLIDE, a special case of CardPath where the slid constraint must hold always, can be used to encode a wide range of sliding sequence constraints including CardPath itself. We consider how to propagate SLIDE and provide a complete propagator for CardPath. Since propagation is NP-hard in general, we identify special cases where propagation takes polynomial time. Our experiments demonstrate that using SLIDE to encode global constraints can be as efficient and effective as specialised propagators.


Reformulating Global Grammar Constraints

Abstract: An attractive mechanism to specify global constraints in rostering and other domains is via formal languages. For instance, the Regular and Grammar constraints specify constraints in terms of the languages accepted by an automaton and a context-free grammar respectively. Taking advantage of the fixed length of the constraint, we give an algorithm to transform a context-free grammar into an automaton. We then study the use of minimization techniques to reduce the size of such automata and speed up propagation. We show that minimizing such automata after they have been unfolded and domains initially reduced can give automata that are more compact than minimizing before unfolding and reducing. Experimental results show that such transformations can improve the size of rostering problems that we can 'model and run'.


Combining Symmetry Breaking and Global Constraints

Abstract: We propose a new family of constraints which combine together lexicographical ordering constraints for symmetry breaking with other common global constraints. We give a general purpose propagator for this family of constraints, and show how to improve its complexity by exploiting properties of the included global constraints.


Teacher's Evaluation - a Component of Quality Assessment System

Abstract: One of the most important activities to increase the importance and the responsibility of the higher education is the quality management, assessment and evaluation. Starting from 2006, a national mechanism was created in Romania and all the educational institutions have to apply a concrete algorithm to ensure the internal evaluation, the external evaluation and, the most important, to increase the quality of the educational process. This paper presents the implementation of the quality assessment in "Tibiscus" University of Timisoara, particularly at the Faculty of Computers and Applied Computer Science.


MANETS: High mobility can make up for low transmission power

Abstract: We consider a Mobile Ad-hoc NETworks (MANET) formed by "n" nodes that move independently at random over a finite square region of the plane. Nodes exchange data if they are at distance at most "r" within each other, where r>0 is the node transmission radius. The "flooding time" is the number of time steps required to broadcast a message from a source node to every node of the network. Flooding time is an important measure of the speed of information spreading in dynamic networks. We derive a nearly-tight upper bound on the flooding time which is a decreasing function of the maximal "velocity" of the nodes. It turns out that, when the node velocity is sufficiently high, even if the node transmission radius "r" is far below the "connectivity threshold", the flooding time does not asymptotically depend on "r". This implies that flooding can be very fast even though every "snapshot" (i.e. the static random geometric graph at any fixed time) of the MANET is fully disconnected. Data reach all nodes quickly despite these ones use very low transmission power. Our result is the first analytical evidence of the fact that high, random node mobility strongly speed-up information spreading and, at the same time, let nodes save energy.


Real-time Texture Error Detection

Abstract: This paper advocates an improved solution for real-time error detection of texture errors that occurs in the production process in textile industry. The research is focused on the mono-color products with 3D texture model (Jaquard fabrics). This is a more difficult task than, for example, 2D multicolor textures.


A constructive proof of the general Lovasz Local Lemma

Abstract: The Lovasz Local Lemma [EL75] is a powerful tool to non-constructively prove the existence of combinatorial objects meeting a prescribed collection of criteria. In his breakthrough paper [Bec91], Beck demonstrated that a constructive variant can be given under certain more restrictive conditions. Simplifications of his procedure and relaxations of its restrictions were subsequently exhibited in several publications [Alo91, MR98, CS00, Mos06, Sri08, Mos08]. In [Mos09], a constructive proof was presented that works under negligible restrictions, formulated in terms of the Bounded Occurrence Satisfiability problem. In the present paper, we reformulate and improve upon these findings so as to directly apply to almost all known applications of the general Local Lemma.


Adaptation of Black-Box Software Components

Abstract: The globalization of the software market leads to crucial problems for software companies. More competition between software companies arises and leads to the force on companies to develop ever newer software products in ever shortened time interval. Therefor the time to market for software systems is shortened and obviously the product life cycle is shortened too[...]The approach introduced here presents the novel technique together with a supportive environment that enables developers to cope with the adaptability of black-box software components. A supported environment will be designed that checks the compatibility of black-box software components with the assistance of their specifications.


Expert Software for the Determination of Juvenile People's Obesity

Abstract: Keeping the health condition at the juvenile population is the concern of both the medical staff and the physical education teachers. Considering the steady tendency of the growth of the number of the youth with excessive weight (overweighted or obese) the intervention to combat this phenomenon must be initiated in the early stage when this condition occurs. The screening method for evaluating the body weight presented in this study uses a calculus program through which, based on the input data (age, sex, weight the width of the skin fold) an evaluation regarding each juvenile's weight and the body structure can be done. This program can be used in schools, high schools, universities, to signal the weight excess and to appreciate the intervention results for getting a normal weight.


About Testing the Speed of Calculating the Shortest Route

Abstract: Applied into a various area of domains, the graph theory and its applications allow the determination of the shortest route. The common algorithm to solve this problem is Bellman-Kalaba, based on the matrix multiplying operation. If the graph is very large (e.g., the dimension of the associated incidence matrix is big) one of the main problems is to reduce the calculus time. This paper presents a testing method able to analyze if an acceleration of the Bellman-Kalaba is possible and able to determine the time efficiency.


Expert System for Quality Assessment in "Tibiscus" University

Abstract: The periodical evaluation of the teaching staff in "Tibiscus" University is based on the specification of the Romanian Agency for Quality Assurance in Higher Education (ARACIS), namely "The quality of teaching and researching staff: The universities must dispose of teaching staff which, as number and functional base must be correctly allocated to the total number of students, depending on the study domain and regarding the qualifications it must depend on the specific of the study program and the proposed quality objectives." This paper presents the implementation of an expert system, offering to the students the possibility to perform the evaluation in a modern way and to the evaluation committee a quick access to all necessary data.


Leveraging Discarded Samples for Tighter Estimation of Multiple-Set Aggregates

Abstract: Many datasets such as market basket data, text or hypertext documents, and sensor observations recorded in different locations or time periods, are modeled as a collection of sets over a ground set of keys. We are interested in basic aggregates such as the weight or selectivity of keys that satisfy some selection predicate defined over keys' attributes and membership in particular sets. This general formulation includes basic aggregates such as the Jaccard coefficient, Hamming distance, and association rules. On massive data sets, exact computation can be inefficient or infeasible. Sketches based on coordinated random samples are classic summaries that support approximate query processing. Queries are resolved by generating a sketch (sample) of the union of sets used in the predicate from the sketches these sets and then applying an estimator to this union-sketch. We derive novel tighter (unbiased) estimators that leverage sampled keys that are present in the union of applicable sketches but excluded from the union sketch. We establish analytically that our estimators dominate estimators applied to the union-sketch for {\em all queries and data sets}. Empirical evaluation on synthetic and real data reveals that on typical applications we can expect a 25%-4 fold reduction in estimation error.


Preserving Individual Privacy in Serial Data Publishing

Abstract: While previous works on privacy-preserving serial data publishing consider the scenario where sensitive values may persist over multiple data releases, we find that no previous work has sufficient protection provided for sensitive values that can change over time, which should be the more common case. In this work we propose to study the privacy guarantee for such transient sensitive values, which we call the global guarantee. We formally define the problem for achieving this guarantee and derive some theoretical properties for this problem. We show that the anonymized group sizes used in the data anonymization is a key factor in protecting individual privacy in serial publication. We propose two strategies for anonymization targeting at minimizing the average group size and the maximum group size. Finally, we conduct experiments on a medical dataset to show that our method is highly efficient and also produces published data of very high utility.


Digital Ecosystems in the Clouds: Towards Community Cloud Computing

Abstract: Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns of privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon, and Microsoft. Community Cloud Computing makes use of the principles of Digital Ecosystems to provide a paradigm for Clouds in the community, offering an alternative architecture for the use cases of Cloud Computing. It is more technically challenging to deal with issues of distributed computing, such as latency, differential resource management, and additional security requirements. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.


Online Estimation of SAT Solving Runtime

Abstract: We present an online method for estimating the cost of solving SAT problems. Modern SAT solvers present several challenges to estimate search cost including non-chronological backtracking, learning and restarts. Our method uses a linear model trained on data gathered at the start of search. We show the effectiveness of this method using random and structured problems. We demonstrate that predictions made in early restarts can be used to improve later predictions. We also show that we can use such cost estimations to select a solver from a portfolio.


Resource Allocation for Multiple Concurrent In-Network Stream-Processing Applications

Abstract: This paper investigates the operator mapping problem for in-network stream-processing applications. In-network stream-processing amounts to applying one or more trees of operators in steady-state, to multiple data objects that are continuously updated at different locations in the network. The goal is to compute some final data at some desired rate. Different operator trees may share common subtrees. Therefore, it may be possible to reuse some intermediate results in different application trees. The first contribution of this work is to provide complexity results for different instances of the basic problem, as well as integer linear program formulations of various problem instances. The second second contribution is the design of several polynomial-time heuristics. One of the primary objectives of these heuristics is to reuse intermediate results shared by multiple applications. Our quantitative comparisons of these heuristics in simulation demonstrates the importance of choosing appropriate processors for operator mapping. It also allow us to identify a heuristic that achieves good results in practice.


Grid Technologies

Abstract: This paper contains the most important aspects of computing grids. Grid computing allows high performance distributed systems to act as a single computer. An overview of grids structure and techniques is given in order to understand the way grids work.


Modeling the Experience of Emotion

Abstract: Affective computing has proven to be a viable field of research comprised of a large number of multidisciplinary researchers resulting in work that is widely published. The majority of this work consists of computational models of emotion recognition, computational modeling of causal factors of emotion and emotion expression through rendered and robotic faces. A smaller part is concerned with modeling the effects of emotion, formal modeling of cognitive appraisal theory and models of emergent emotions. Part of the motivation for affective computing as a field is to better understand emotional processes through computational modeling. One of the four major topics in affective computing is computers that have emotions (the others are recognizing, expressing and understanding emotions). A critical and neglected aspect of having emotions is the experience of emotion (Barrett, Mesquita, Ochsner, and Gross, 2007): what does the content of an emotional episode look like, how does this content change over time and when do we call the episode emotional. Few modeling efforts have these topics as primary focus. The launch of a journal on synthetic emotions should motivate research initiatives in this direction, and this research should have a measurable impact on emotion research in psychology. I show that a good way to do so is to investigate the psychological core of what an emotion is: an experience. I present ideas on how the experience of emotion could be modeled and provide evidence that several computational models of emotion are already addressing the issue.


C# - Connecting a Mobile Application to Oracle Server via Web Services

Abstract: This article is focused on mobile development using Visual Studio 2005, web services and their connection to Oracle server, willing to help programmers to realize simple and useful mobile applications.


Hierarchical neighbor graphs: A low stretch connected structure for points in Euclidean space

Abstract: We introduce hierarchical neighbor graphs, a new architecture for connecting ad hoc wireless nodes distributed in a plane. The structure has the flavor of hierarchical clustering and requires only local knowledge and minimal computation at each node to be formed and repaired. Hence, it is a suitable interconnection model for an ad hoc wireless sensor network. The structure is able to use energy efficiently by reorganizing dynamically when the battery power of heavily utilized nodes degrades and is able to achieve throughput, energy efficiency and network lifetimes that compare favorably with the leading proposals for data collation in sensor networks such as LEACH (Heinzelman et. al., 2002). Additionally, hierarchical neighbor graphs have low power stretch i.e. the power required to connect nodes through the network is a small factor higher than the power required to connect them directly. Our structure also compares favorably to mathematical structures proposed for connecting points in a plane e.g. nearest-neighbor graphs (Ballister et. al., 2005), $\theta$-graphs (Ruppert and Seidel, 1991), in that it has expected constant degree and does not require any significant computation or global information to be formed.


On Requirements for Programming Exercises from an E-learning Perspective

Abstract: In this work, we deal with the question of modeling programming exercises for novices pointing to an e-learning scenario. Our purpose is to identify basic requirements, raise some key questions and propose potential answers from a conceptual perspective. Presented as a general picture, we hypothetically situate our work in a general context where e-learning instructional material needs to be adapted to form part of an introductory Computer Science (CS) e-learning course at the CS1-level. Meant is a potential course which aims at improving novices skills and knowledge on the essentials of programming by using e-learning based approaches in connection (at least conceptually) with a general host framework like Activemath (www.activemath.org). Our elaboration covers contextual and, particularly, cognitive elements preparing the terrain for eventual research stages in a derived project, as indicated. We concentrate our main efforts on reasoning mechanisms about exercise complexity that can eventually offer tool support for the task of exercise authoring. We base our requirements analysis on our own perception of the exercise subsystem provided by Activemath especially within the domain reasoner area. We enrich the analysis by bringing to the discussion several relevant contextual elements from the CS1 courses, its definition and implementation. Concerning cognitive models and exercises, we build upon the principles of Bloom's Taxonomy as a relatively standardized basis and use them as a framework for study and analysis of complexity in basic programming exercises. Our analysis includes requirements for the domain reasoner which are necessary for the exercise analysis. We propose for such a purpose a three-layered conceptual model considering exercise evaluation, programming and metaprogramming.


An Epistemic Approach to Coercion-Resistance for Electronic Voting Protocols

Abstract: Coercion resistance is an important and one of the most intricate security requirements of electronic voting protocols. Several definitions of coercion resistance have been proposed in the literature, including definitions based on symbolic models. However, existing definitions in such models are rather restricted in their scope and quite complex. In this paper, we therefore propose a new definition of coercion resistance in a symbolic setting, based on an epistemic approach. Our definition is relatively simple and intuitive. It allows for a fine-grained formulation of coercion resistance and can be stated independently of a specific, symbolic protocol and adversary model. As a proof of concept, we apply our definition to three voting protocols. In particular, we carry out the first rigorous analysis of the recently proposed Civitas system. We precisely identify those conditions under which this system guarantees coercion resistance or fails to be coercion resistant. We also analyze protocols proposed by Lee et al. and Okamoto.


Tagging multimedia stimuli with ontologies

Abstract: Successful management of emotional stimuli is a pivotal issue concerning Affective Computing (AC) and the related research. As a subfield of Artificial Intelligence, AC is concerned not only with the design of computer systems and the accompanying hardware that can recognize, interpret, and process human emotions, but also with the development of systems that can trigger human emotional response in an ordered and controlled manner. This requires the maximum attainable precision and efficiency in the extraction of data from emotionally annotated databases While these databases do use keywords or tags for description of the semantic content, they do not provide either the necessary flexibility or leverage needed to efficiently extract the pertinent emotional content. Therefore, to this extent we propose an introduction of ontologies as a new paradigm for description of emotionally annotated data. The ability to select and sequence data based on their semantic attributes is vital for any study involving metadata, semantics and ontological sorting like the Semantic Web or the Social Semantic Desktop, and the approach described in the paper facilitates reuse in these areas as well.


Algorithms for Weighted Boolean Optimization

Abstract: The Pseudo-Boolean Optimization (PBO) and Maximum Satisfiability (MaxSAT) problems are natural optimization extensions of Boolean Satisfiability (SAT). In the recent past, different algorithms have been proposed for PBO and for MaxSAT, despite the existence of straightforward mappings from PBO to MaxSAT and vice-versa. This papers proposes Weighted Boolean Optimization (WBO), a new unified framework that aggregates and extends PBO and MaxSAT. In addition, the paper proposes a new unsatisfiability-based algorithm for WBO, based on recent unsatisfiability-based algorithms for MaxSAT. Besides standard MaxSAT, the new algorithm can also be used to solve weighted MaxSAT and PBO, handling pseudo-Boolean constraints either natively or by translation to clausal form. Experimental results illustrate that unsatisfiability-based algorithms for MaxSAT can be orders of magnitude more efficient than existing dedicated algorithms. Finally, the paper illustrates how other algorithms for either PBO or MaxSAT can be extended to WBO.


A Domain-Specific Language for Programming in the Tile Assembly Model

Abstract: We introduce a domain-specific language (DSL) for creating sets of tile types for simulations of the abstract Tile Assembly Model. The language defines objects known as tile templates, which represent related groups of tiles, and a small number of basic operations on tile templates that help to eliminate the error-prone drudgery of enumerating such tile types manually or with low-level constructs of general-purpose programming languages. The language is implemented as a class library in Python (a so-called internal DSL), but is presented independently of Python or object-oriented programming, with emphasis on supporting the creation of visual editing tools for programmatically creating large sets of complex tile types without needing to write a program.


Artificial table testing dynamically adaptive systems

Abstract: Dynamically Adaptive Systems (DAS) are systems that modify their behavior and structure in response to changes in their surrounding environment. Critical mission systems increasingly incorporate adaptation and response to the environment; examples include disaster relief and space exploration systems. These systems can be decomposed in two parts: the adaptation policy that specifies how the system must react according to the environmental changes and the set of possible variants to reconfigure the system. A major challenge for testing these systems is the combinatorial explosions of variants and envi-ronment conditions to which the system must react. In this paper we focus on testing the adaption policy and propose a strategy for the selection of envi-ronmental variations that can reveal faults in the policy. Artificial Shaking Table Testing (ASTT) is a strategy inspired by shaking table testing (STT), a technique widely used in civil engineering to evaluate building's structural re-sistance to seismic events. ASTT makes use of artificial earthquakes that simu-late violent changes in the environmental conditions and stresses the system adaptation capability. We model the generation of artificial earthquakes as a search problem in which the goal is to optimize different types of envi-ronmental variations.


Algorithm for Finding $k$-Vertex Out-trees and its Application to $k$-Internal Out-branching Problem

Abstract: An out-tree $T$ is an oriented tree with only one vertex of in-degree zero. A vertex $x$ of $T$ is internal if its out-degree is positive. We design randomized and deterministic algorithms for deciding whether an input digraph contains a given out-tree with $k$ vertices. The algorithms are of runtime $O^*(5.704^k)$ and $O^*(5.704^{k(1+o(1))})$, respectively. We apply the deterministic algorithm to obtain a deterministic algorithm of runtime $O^*(c^k)$, where $c$ is a constant, for deciding whether an input digraph contains a spanning out-tree with at least $k$ internal vertices. This answers in affirmative a question of Gutin, Razgon and Kim (Proc. AAIM'08).


Directing RF Terminals Using TELNET Applications

Abstract: The present study aims to emphasize the way in which the TELNET protocol for directing the mobile terminals is used and works. The paper is structured in three parts: the first two parts are a theoretic presentation of the TELNET protocol, respectively of the mobile terminals. The third part contains an application of the way in which a mobile terminal can be programmed using the TELNET protocol.


Hospital Acquired Infections: Advantages of a Computerized Surveillance

Abstract: To asses the advantages of a computerized surveillance system to detect Healthcare-Associated Infections (HAI). All HAI reported to the Timis County branch of the Romanian National Health Insurance and the Public Health Authority during the year 2007 were collected and assessed for validity


L'entreprise franco-roumaine face au Internet

Abstract: The main goal of the present work is to analyze the activity of the French companies from Romania related to the increasing use of the information and communication technology in the productive field. The convergent assembly of information and communication technologies and the process of economic globalization have led to a profound transformation of the economic activity. The present paper is part of a series of studies made on the French firms from Romania between 2007 and 2008.


How do Wireless Chains Behave? The Impact of MAC Interactions

Abstract: In a Multi-hop Wireless Networks (MHWN), packets are routed between source and destination using a chain of intermediate nodes; chains are a fundamental communication structure in MHWNs whose behavior must be understood to enable building effective protocols. The behavior of chains is determined by a number of complex and interdependent processes that arise as the sources of different chain hops compete to transmit their packets on the shared medium. In this paper, we show that MAC level interactions play the primary role in determining the behavior of chains. We evaluate the types of chains that occur based on the MAC interactions between different links using realistic propagation and packet forwarding models. We discover that the presence of destructive interactions, due to different forms of hidden terminals, does not impact the throughput of an isolated chain significantly. However, due to the increased number of retransmissions required, the amount of bandwidth consumed is significantly higher in chains exhibiting destructive interactions, substantially influencing the overall network performance. These results are validated by testbed experiments. We finally study how different types of chains interfere with each other and discover that well behaved chains in terms of self-interference are more resilient to interference from other chains.


On the Category of Partial Bijections

Abstract: Categories of partial functions have become increasingly important principally because of their applications in theoretical computer science. In this note we prove that the category of partial bijections between sets as an inverse-Baer*-category with closed projections and in which the idempotent split is an exact category. Finally the Noether isomorphism theorems are given for this exact category.


Footprints in Local Reasoning

Abstract: Local reasoning about programs exploits the natural local behaviour common in programs by focussing on the footprint - that part of the resource accessed by the program. We address the problem of formally characterising and analysing the footprint notion for abstract local functions introduced by Calcagno, O Hearn and Yang. With our definition, we prove that the footprints are the only essential elements required for a complete specification of a local function. We formalise the notion of small specifications in local reasoning and show that for well-founded resource models, a smallest specification always exists that only includes the footprints, and also present results for the non-well-founded case. Finally, we use this theory of footprints to investigate the conditions under which the footprints correspond to the smallest safe states. We present a new model of RAM in which, unlike the standard model, the footprints of every program correspond to the smallest safe states, and we also identify a general condition on the primitive commands of a programming language which guarantees this property for arbitrary models.


Home Heating Systems Design using PHP and MySQL Databases

Abstract: This paper presents the use of a computer application based on a MySQL database, managed by PHP programs, allowing the selection of a heating device using coefficient-based calculus.


Application for Evaluation of the Professional Competencies of the Teaching Staff

Abstract: The goal of the presented application is to offer a full support for universities in retrieving the feedback from their students with regard to their teachers. This is the main reason we described it in this paper. To build this application the following tools have been used: Microsoft Notepad 5.1 (to make the source files), Adobe Photoshop CS3 (to make the background image) and Adobe Flash Media Encoder 8 (to render the video clips).


Decomposition, Reformulation, and Diving in University Course Timetabling

Abstract: In many real-life optimisation problems, there are multiple interacting components in a solution. For example, different components might specify assignments to different kinds of resource. Often, each component is associated with different sets of soft constraints, and so with different measures of soft constraint violation. The goal is then to minimise a linear combination of such measures. This paper studies an approach to such problems, which can be thought of as multiphase exploitation of multiple objective-/value-restricted submodels. In this approach, only one computationally difficult component of a problem and the associated subset of objectives is considered at first. This produces partial solutions, which define interesting neighbourhoods in the search space of the complete problem. Often, it is possible to pick the initial component so that variable aggregation can be performed at the first stage, and the neighbourhoods to be explored next are guaranteed to contain feasible solutions. Using integer programming, it is then easy to implement heuristics producing solutions with bounds on their quality. Our study is performed on a university course timetabling problem used in the 2007 International Timetabling Competition, also known as the Udine Course Timetabling Problem. In the proposed heuristic, an objective-restricted neighbourhood generator produces assignments of periods to events, with decreasing numbers of violations of two period-related soft constraints. Those are relaxed into assignments of events to days, which define neighbourhoods that are easier to search with respect to all four soft constraints. Integer programming formulations for all subproblems are given and evaluated using ILOG CPLEX 11. The wider applicability of this approach is analysed and discussed.


Efficient Human Computation

Abstract: Collecting large labeled data sets is a laborious and expensive task, whose scaling up requires division of the labeling workload between many teachers. When the number of classes is large, miscorrespondences between the labels given by the different teachers are likely to occur, which, in the extreme case, may reach total inconsistency. In this paper we describe how globally consistent labels can be obtained, despite the absence of teacher coordination, and discuss the possible efficiency of this process in terms of human labor. We define a notion of label efficiency, measuring the ratio between the number of globally consistent labels obtained and the number of labels provided by distributed teachers. We show that the efficiency depends critically on the ratio alpha between the number of data instances seen by a single teacher, and the number of classes. We suggest several algorithms for the distributed labeling problem, and analyze their efficiency as a function of alpha. In addition, we provide an upper bound on label efficiency for the case of completely uncoordinated teachers, and show that efficiency approaches 0 as the ratio between the number of labels each teacher provides and the number of classes drops (i.e. alpha goes to 0).


Symmetry Breaking Using Value Precedence

Abstract: We present a comprehensive study of the use of value precedence constraints to break value symmetry. We first give a simple encoding of value precedence into ternary constraints that is both efficient and effective at breaking symmetry. We then extend value precedence to deal with a number of generalizations like wreath value and partial interchangeability. We also show that value precedence is closely related to lexicographical ordering. Finally, we consider the interaction between value precedence and symmetry breaking constraints for variable symmetries.


Complexity of Terminating Preference Elicitation

Abstract: Complexity theory is a useful tool to study computational issues surrounding the elicitation of preferences, as well as the strategic manipulation of elections aggregating together preferences of multiple agents. We study here the complexity of determining when we can terminate eliciting preferences, and prove that the complexity depends on the elicitation strategy. We show, for instance, that it may be better from a computational perspective to elicit all preferences from one agent at a time than to elicit individual preferences from multiple agents. We also study the connection between the strategic manipulation of an election and preference elicitation. We show that what we can manipulate affects the computational complexity of manipulation. In particular, we prove that there are voting rules which are easy to manipulate if we can change all of an agent's vote, but computationally intractable if we can change only some of their preferences. This suggests that, as with preference elicitation, a fine-grained view of manipulation may be informative. Finally, we study the connection between predicting the winner of an election and preference elicitation. Based on this connection, we identify a voting rule where it is computationally difficult to decide the probability of a candidate winning given a probability distribution over the votes.


The Complexity of Reasoning with Global Constraints

Abstract: Constraint propagation is one of the techniques central to the success of constraint programming. To reduce search, fast algorithms associated with each constraint prune the domains of variables. With global (or non-binary) constraints, the cost of such propagation may be much greater than the quadratic cost for binary constraints. We therefore study the computational complexity of reasoning with global constraints. We first characterise a number of important questions related to constraint propagation. We show that such questions are intractable in general, and identify dependencies between the tractability and intractability of the different questions. We then demonstrate how the tools of computational complexity can be used in the design and analysis of specific global constraints. In particular, we illustrate how computational complexity can be used to determine when a lesser level of local consistency should be enforced, when constraints can be safely generalized, when decomposing constraints will reduce the amount of pruning, and when combining constraints is tractable.


Breaking Value Symmetry

Abstract: One common type of symmetry is when values are symmetric. For example, if we are assigning colours (values) to nodes (variables) in a graph colouring problem then we can uniformly interchange the colours throughout a colouring. For a problem with value symmetries, all symmetric solutions can be eliminated in polynomial time. However, as we show here, both static and dynamic methods to deal with symmetry have computational limitations. With static methods, pruning all symmetric values is NP-hard in general. With dynamic methods, we can take exponential time on problems which static methods solve without search.


Tetravex is NP-complete

Abstract: Tetravex is a widely played one person computer game in which you are given $n^2$ unit tiles, each edge of which is labelled with a number. The objective is to place each tile within a $n$ by $n$ square such that all neighbouring edges are labelled with an identical number. Unfortunately, playing Tetravex is computationally hard. More precisely, we prove that deciding if there is a tiling of the Tetravex board is NP-complete. Deciding where to place the tiles is therefore NP-hard. This may help to explain why Tetravex is a good puzzle. This result compliments a number of similar results for one person games involving tiling. For example, NP-completeness results have been shown for: the offline version of Tetris, KPlumber (which involves rotating tiles containing drawings of pipes to make a connected network), and shortest sliding puzzle problems. It raises a number of open questions. For example, is the infinite version Turing-complete? How do we generate Tetravex problems which are truly puzzling as random NP-complete problems are often surprising easy to solve? Can we observe phase transition behaviour? What about the complexity of the problem when it is guaranteed to have an unique solution? How do we generate puzzles with unique solutions?


Stochastic Constraint Programming: A Scenario-Based Approach

Abstract: To model combinatorial decision problems involving uncertainty and probability, we introduce scenario based stochastic constraint programming. Stochastic constraint programs contain both decision variables, which we can set, and stochastic variables, which follow a discrete probability distribution. We provide a semantics for stochastic constraint programs based on scenario trees. Using this semantics, we can compile stochastic constraint programs down into conventional (non-stochastic) constraint programs. This allows us to exploit the full power of existing constraint solvers. We have implemented this framework for decision making under uncertainty in stochastic OPL, a language which is based on the OPL constraint modelling language [Hentenryck et al., 1999]. To illustrate the potential of this framework, we model a wide range of problems in areas as diverse as portfolio diversification, agricultural planning and production/inventory management.


Stochastic Constraint Programming

Abstract: To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a probability distribution). They combine together the best features of traditional constraint satisfaction, stochastic integer programming, and stochastic satisfiability. We give a semantics for stochastic constraint programs, and propose a number of complete algorithms and approximation procedures. Finally, we discuss a number of extensions of stochastic constraint programming to relax various assumptions like the independence between stochastic variables, and compare with other approaches for decision making under uncertainty.


The structure of finite meadows

Abstract: A meadow is a commutative ring with a total inverse operator satisfying 0^{-1}=0. We show that the class of finite meadows is the closure of the class of Galois fields under finite products. As a corollary, we obtain a unique representation of minimal finite meadows in terms of finite prime fields.


The Omega Rule is $\mathbf{\Pi_{1}^{1}}$-Complete in the $\lambda\beta$-Calculus

Abstract: In a functional calculus, the so called \Omega-rule states that if two terms P and Q applied to any closed term <i>N</i> return the same value (i.e. PN = QN), then they are equal (i.e. P = Q holds). As it is well known, in the \lambda\beta-calculus the \Omega-rule does not hold, even when the \eta-rule (weak extensionality) is added to the calculus. A long-standing problem of H. Barendregt (1975) concerns the determination of the logical power of the \Omega-rule when added to the \lambda\beta-calculus. In this paper we solve the problem, by showing that the resulting theory is \Pi\_{1}^{1}-complete.


Multi-Objective Problem Solving With Offspring on Enterprise Clouds

Abstract: In this paper, we present a distributed implementation of a network based multi-objective evolutionary algorithm, called EMO, by using Offspring. Network based evolutionary algorithms have proven to be effective for multi-objective problem solving. They feature a network of connections between individuals that drives the evolution of the algorithm. Unfortunately, they require large populations to be effective and a distributed implementation can leverage the computation time. Most of the existing frameworks are limited to providing solutions that are basic or specific to a given algorithm. Our Offspring framework is a plug-in based software environment that allows rapid deployment and execution of evolutionary algorithms on distributed computing environments such as Enterprise Clouds. Its features and benefits are presented by describing the distributed implementation of EMO.


Jeeva: Enterprise Grid-enabled Web Portal for Protein Secondary Structure Prediction

Abstract: This paper presents a Grid portal for protein secondary structure prediction developed by using services of Aneka, a .NET-based enterprise Grid technology. The portal is used by research scientists to discover new prediction structures in a parallel manner. An SVM (Support Vector Machine)-based prediction algorithm is used with 64 sample protein sequences as a case study to demonstrate the potential of enterprise Grids.


A Linear Programming Driven Genetic Algorithm for Meta-Scheduling on Utility Grids

Abstract: The user-level brokers in grids consider individual application QoS requirements and minimize their cost without considering demands from other users. This results in contention for resources and sub-optimal schedules. Meta-scheduling in grids aims to address this scheduling problem, which is NP hard due to its combinatorial nature. Thus, many heuristic-based solutions using Genetic Algorithm (GA) have been proposed, apart from traditional algorithms such as Greedy and FCFS. We propose a Linear Programming/Integer Programming model (LP/IP) for scheduling these applications to multiple resources. We also propose a novel algorithm LPGA (Linear programming driven Genetic Algorithm) which combines the capabilities of LP and GA. The aim of this algorithm is to obtain the best metaschedule for utility grids which minimize combined cost of all users in a coordinated manner. Simulation results show that our proposed integrated algorithm offers the best schedule having the minimum processing cost with negligible time overhead.


A Lagrangian Relaxation for the Maximum Stable Set Problem

Abstract: We propose a new integer programming formulation for the problem of finding a maximum stable set of a graph based on representatives of stable sets. In addition, we investigate exact solutions provided by a Lagrangian decomposition of this formulation in which only one constraint is relaxed. Some computational experiments were carried out with an effective multi-threaded implementation of our algorithm in a multi-core system, and their results are presented.


The Digital Restoration of Da Vinci's Sketches

Abstract: A sketch, found in one of Leonardo da Vinci's notebooks and covered by the written notes of this genius, has been recently restored. The restoration reveals a possible self-portrait of the artist, drawn when he was young. Here, we discuss the discovery of this self-portrait and the procedure used for restoration. Actually, this is a restoration performed on the digital image of the sketch, a procedure that can easily extended and applied to ancient documents for studies of art and palaeography.


Multi-unit Auctions with Budget Constraints

Abstract: Motivated by sponsored search auctions, we study multi-unit auctions with budget constraints. In the mechanism we propose, Sort-Cut, understating budgets or values is weakly dominated. Since Sort-Cut's revenue is increasing in budgets and values, all kinds of equilibrium deviations from true valuations turn out to be beneficial to the auctioneer. We show that the revenue of Sort-Cut can be an order of magnitude greater than that of the natural Market Clearing Price mechanism, and we discuss the efficiency properties of its ex-post Nash equilibrium.


Wi-Fi, WiMax and WCDMA A comparative study based on Channel Impairments and Equalization method used

Abstract: In this paper we describe the channel impairments and equalization methods currently used in WiFi, WiMax and WCDMA. After a review of channel model for Intelligent Transportation System (ITS), we proposed an equalization method which will be useful for the estimation of strong multipath channel at a high velocity.


Digital Radar for Collision Avoidance and Automatic Cruise Control in Transportation

Abstract: A proper remote sensing device is required for automatic cruise control (ACC) to avoid collision in transportation system. In this paper we proposed a direct sequence spread spectrum (DSSS) radar for remote sensing in intelligent transporation system(ITS). We have successfully detected single target and through 1D radar imaging we are capable to separate multiple targets. We have also implemented DSSS radar using software defined radio (SDR) and successfully detected a single target.


MIMO Based Multimedia Communication System

Abstract: High data rate is required for multimedia communication. But the communication at high data rate is always challenging. In this work we have successfully performed data chatting, Voice chatting and high quality video transmission between two distant units using MIMO adapter, Direct sequence spread spectrum system and MATLAB/SIMULINK platform.


18th Workshop on Logic-based methods in Programming Environments (WLPE 2008)

Abstract: This volume contains the papers presented at WLPE 2008: the 18th Workshop on Logic-based Methods in Programming Environments held on 12th December, 2008 in Udine, Italy. It was held as a satellite workshop of ICLP 2008, the 24th International Conference on Logic Programming.


On the Morse-Hedlund complexity gap

Abstract: In 1938, Morse and Hedlund proved that the subword complexity function of an infinite word is either bounded or at least linearly growing. In 1982, Ehrenfeucht and Rozenberg proved that this gap property holds for the subword complexity function of any language. The aim of the present paper is to present a self-contained, compact proof of Ehrenfeucht and Rozenberg's result.


Heuristic Reasoning on Graph and Game Complexity of Sudoku

Abstract: The Sudoku puzzle has achieved worldwide popularity recently, and attracted great attention of the computational intelligence community. Sudoku is always considered as Satisfiability Problem or Constraint Satisfaction Problem. In this paper, we propose to focus on the essential graph structure underlying the Sudoku puzzle. First, we formalize Sudoku as a graph. Then a solving algorithm based on heuristic reasoning on the graph is proposed. The related r-Reduction theorem, inference theorem and their properties are proved, providing the formal basis for developments of Sudoku solving systems. In order to evaluate the difficulty levels of puzzles, a quantitative measurement of the complexity level of Sudoku puzzles based on the graph structure and information theory is proposed. Experimental results show that all the puzzles can be solved fast using the proposed heuristic reasoning, and that the proposed game complexity metrics can discriminate difficulty levels of puzzles perfectly.


Faceted Exploration of Emerging Resource Spaces

Abstract: Humans have the ability to regcognize the real world from different facets. Faceted exploration is a mechanism for browsing and understanding large-scale resources in information network by multiple facets. This paper proposes an Emerging Resource Space Model, whose schema is a partially ordered set of concepts with subclassOf relation and each resource is categorized by multiple concepts. Emering Resource Space (ERS) is a class of resources characterized by a concept set. ERSes compose a lattice (ERSL) via concept association. A series of exploration operations is proposed to guide users to explore through ERSL with more demanding and richer semantics than current faceted navigation. To fulfill instant response during faceted exploration, we devise an efficient algorithm for mining and indexing ERSL. The proposed model can effectively support faceted exploration in various applications from personal information management to large-scale information sharing.


Connectivity of Heterogeneous Wireless Networks

Abstract: We address the connectivity of large-scale ad hoc heterogeneous wireless networks, where secondary users exploit channels temporarily unused by primary users and the existence of a communication link between two secondary users depends on not only the distance between them but also the transmitting and receiving activities of nearby primary users. We introduce the concept of connectivity region defined as the set of density pairs -- the density of secondary users and the density of primary transmitters -- under which the secondary network is connected. Using theories and techniques from continuum percolation, we analytically characterize the connectivity region of the secondary network and reveal the tradeoff between proximity (the number of neighbors) and the occurrence of spectrum opportunities. Specifically, we establish three basic properties of the connectivity region -- contiguity, monotonicity of the boundary, and uniqueness of the infinite connected component, where the uniqueness implies the occurrence of a phase transition phenomenon in terms of the almost sure existence of either zero or one infinite connected component; we identify and analyze two critical densities which jointly specify the profile as well as an outer bound on the connectivity region; we study the impacts of secondary users' transmission power on the connectivity region and the conditional average degree of a secondary user, and demonstrate that matching the interference ranges of the primary and the secondary networks maximizes the tolerance of the secondary network to the primary traffic load. Furthermore, we establish a necessary condition and a sufficient condition for connectivity, which lead to an outer bound and an inner bound on the connectivity region.


Review of Replication Schemes for Unstructured P2P Networks

Abstract: To improve unstructured P2P system performance, one wants to minimize the number of peers that have to be probed for the shortening of the search time. A solution to the problem is to employ a replication scheme, which provides high hit rate for target files. Replication can also provide load balancing and reduce access latency if the file is accessed by a large population of users. This paper briefly describes various replication schemes that have appeared in the literature and also focuses on a novel replication technique called Q-replication to increase availability of objects in unstructured P2P networks. The Q-replication technique replicates objects autonomously to suitable sites based on object popularity and site selection logic by extensively employing Q-learning concept.


The Role of Tag Suggestions in Folksonomies

Abstract: Most tagging systems support the user in the tag selection process by providing tag suggestions, or recommendations, based on a popularity measurement of tags other users provided when tagging the same resource. In this paper we investigate the influence of tag suggestions on the emergence of power law distributions as a result of collaborative tag behavior. Although previous research has already shown that power laws emerge in tagging systems, the cause of why power law distributions emerge is not understood empirically. The majority of theories and mathematical models of tagging found in the literature assume that the emergence of power laws in tagging systems is mainly driven by the imitation behavior of users when observing tag suggestions provided by the user interface of the tagging system. This imitation behavior leads to a feedback loop in which some tags are reinforced and get more popular which is also known as the `rich get richer' or a preferential attachment model. We present experimental results that show that the power law distribution forms regardless of whether or not tag suggestions are presented to the users. Furthermore, we show that the real effect of tag suggestions is rather subtle; the resulting power law distribution is `compressed' if tag suggestions are given to the user, resulting in a shorter long tail and a `compressed' top of the power law distribution. The consequences of this experiment show that tag suggestions by themselves do not account for the formation of power law distributions in tagging systems.


Reconstructing Curves from Points and Tangents

Abstract: Reconstructing a finite set of curves from an unordered set of sample points is a well studied topic. There has been less effort that considers how much better the reconstruction can be if tangential information is given as well. We show that if curves are separated from each other by a distance D, then the sampling rate need only be O(sqrt(D)) for error-free reconstruction. For the case of point data alone, O(D) sampling is required.


Strict Self-Assembly of Discrete Sierpinski Triangles

Abstract: Winfree (1998) showed that discrete Sierpinski triangles can self-assemble in the Tile Assembly Model. A striking molecular realization of this self-assembly, using DNA tiles a few nanometers long and verifying the results by atomic-force microscopy, was achieved by Rothemund, Papadakis, and Winfree (2004). Precisely speaking, the above self-assemblies tile completely filled-in, two-dimensional regions of the plane, with labeled subsets of these tiles representing discrete Sierpinski triangles. This paper addresses the more challenging problem of the strict self-assembly of discrete Sierpinski triangles, i.e., the task of tiling a discrete Sierpinski triangle and nothing else. We first prove that the standard discrete Sierpinski triangle cannot strictly self-assemble in the Tile Assembly Model. We then define the fibered Sierpinski triangle, a discrete Sierpinski triangle with the same fractal dimension as the standard one but with thin fibers that can carry data, and show that the fibered Sierpinski triangle strictly self-assembles in the Tile Assembly Model. In contrast with the simple XOR algorithm of the earlier, non-strict self-assemblies, our strict self-assembly algorithm makes extensive, recursive use of optimal counters, coupled with measured delay and corner-turning operations. We verify our strict self-assembly using the local determinism method of Soloveichik and Winfree (2007).


Continuation-Passing Style and Strong Normalisation for Intuitionistic Sequent Calculi

Abstract: The intuitionistic fragment of the call-by-name version of Curien and Herbelin's \lambda\_mu\_{\~mu}-calculus is isolated and proved strongly normalising by means of an embedding into the simply-typed lambda-calculus. Our embedding is a continuation-and-garbage-passing style translation, the inspiring idea coming from Ikeda and Nakazawa's translation of Parigot's \lambda\_mu-calculus. The embedding strictly simulates reductions while usual continuation-passing-style transformations erase permutative reduction steps. For our intuitionistic sequent calculus, we even only need "units of garbage" to be passed. We apply the same method to other calculi, namely successive extensions of the simply-typed λ-calculus leading to our intuitionistic system, and already for the simplest extension we consider (λ-calculus with generalised application), this yields the first proof of strong normalisation through a reduction-preserving embedding. The results obtained extend to second and higher-order calculi.


Limitations of Self-Assembly at Temperature 1

Abstract: We prove that if a set $X \subseteq \Z^2$ weakly self-assembles at temperature 1 in a deterministic tile assembly system satisfying a natural condition known as \emph{pumpability}, then $X$ is a finite union of semi-doubly periodic sets. This shows that only the most simple of infinite shapes and patterns can be constructed using pumpable temperature 1 tile assembly systems, and gives evidence for the thesis that temperature 2 or higher is required to carry out general-purpose computation in a tile assembly system. Finally, we show that general-purpose computation \emph{is} possible at temperature 1 if negative glue strengths are allowed in the tile assembly model.


Contracting preference relations for database applications

Abstract: The binary relation framework has been shown to be applicable to many real-life preference handling scenarios. Here we study preference contraction: the problem of discarding selected preferences. We argue that the property of minimality and the preservation of strict partial orders are crucial for contractions. Contractions can be further constrained by specifying which preferences should be protected. We consider two classes of preference relations: finite and finitely representable. We present algorithms for computing minimal and preference-protecting minimal contractions for finite as well as finitely representable preference relations. We study relationships between preference change in the binary relation framework and belief change in the belief revision theory. We also introduce some preference query optimization techniques which can be used in the presence of contraction. We evaluate the proposed algorithms experimentally and present the results.


Laconic schema mappings: computing core universal solutions by means of SQL queries

Abstract: We present a new method for computing core universal solutions in data exchange settings specified by source-to-target dependencies, by means of SQL queries. Unlike previously known algorithms, which are recursive in nature, our method can be implemented directly on top of any DBMS. Our method is based on the new notion of a laconic schema mapping. A laconic schema mapping is a schema mapping for which the canonical universal solution is the core universal solution. We give a procedure by which every schema mapping specified by FO s-t tgds can be turned into a laconic schema mapping specified by FO s-t tgds that may refer to a linear order on the domain of the source instance. We show that our results are optimal, in the sense that the linear order is necessary and the method cannot be extended to schema mapping involving target constraints.


Partitions versus sets : a case of duality

Abstract: In a recent paper, Amini et al. introduce a general framework to prove duality theorems between special decompositions and their dual combinatorial object. They thus unify all known ad-hoc proofs in one single theorem. While this unification process is definitely good, their main theorem remains quite technical and does not give a real insight of why some decompositions admit dual objects and why others do not. The goal of this paper is both to generalise a little this framework and to give an enlightening simple proof of its central theorem.


A new universal cellular automaton on the ternary heptagrid

Abstract: In this paper, we construct a new weakly universal cellular automaton on the ternary heptagrid. The previous result, obtained by the same author and Y. Song required six states only. This time, the number of states is four. This is the best result up to date for cellular automata in the hyperbolic plane.


Adaptive Mesh Approach for Predicting Algorithm Behavior with Application to Visibility Culling in Computer Graphics

Abstract: We propose a concise approximate description, and a method for efficiently obtaining this description, via adaptive random sampling of the performance (running time, memory consumption, or any other profileable numerical quantity) of a given algorithm on some low-dimensional rectangular grid of inputs. The formal correctness is proven under reasonable assumptions on the algorithm under consideration; and the approach's practical benefit is demonstrated by predicting for which observer positions and viewing directions an occlusion culling algorithm yields a net performance benefit or loss compared to a simple brute force renderer.


Analysis of a Bloom Filter Algorithm via the Supermarket Model

Abstract: This paper deals with the problem of identifying elephants in the Internet Traffic. The aim is to analyze a new adaptive algorithm based on a Bloom Filter. This algorithm uses a so-called min-rule which can be described as in the supermarket model. This model consists of joining the shortest queue among d queues selected at random in a large number of m queues. In case of equality, one of the shortest queues is chosen at random. An analysis of a simplified model gives an insight of the error generated by the algorithm on the estimation of the number of the elephants. The main conclusion is that, as m gets large, there is a deterministic limit for the empirical distribution of the filter counters. Limit theorems are proved and the limit is identified. It depends on key parameters. The condition for the algorithm to perform well is discussed. Theoretical results are validated by experiments on a traffic trace from France Telecom and by simulations.


Supernodal Analysis Revisited

Abstract: In this paper we show how to extend the known algorithm of nodal analysis in such a way that, in the case of circuits without nullors and controlled sources (but allowing for both, independent current and voltage sources), the system of nodal equations describing the circuit is partitioned into one part, where the nodal variables are explicitly given as linear combinations of the voltage sources and the voltages of certain reference nodes, and another, which contains the node variables of these reference nodes only and which moreover can be read off directly from the given circuit. Neither do we need preparational graph transformations, nor do we need to introduce additional current variables (as in MNA). Thus this algorithm is more accessible to students, and consequently more suitable for classroom presentations.


Better Termination for Prolog with Constraints

Abstract: Termination properties of actual Prolog systems with constraints are fragile and difficult to analyse. The lack of the occurs-check, moded and overloaded arithmetical evaluation via is/2 and the occasional nontermination of finite domain constraints are all sources for invalidating termination results obtained by current termination analysers that rely on idealized assumptions. In this paper, we present solutions to address these problems on the level of the underlying Prolog system. Improved unification modes meet the requirements of norm based analysers by offering dynamic occurs-check detection. A generalized finite domain solver overcomes the shortcomings of conventional arithmetic without significant runtime overhead. The solver offers unbounded domains, yet propagation always terminates. Our work improves Prolog's termination and makes Prolog a more reliable target for termination and type analysis. It is part of SWI-Prolog since version 5.6.50.


Role-Based Access Controls

Abstract: While Mandatory Access Controls (MAC) are appropriate for multilevel secure military applications, Discretionary Access Controls (DAC) are often perceived as meeting the security processing needs of industry and civilian government. This paper argues that reliance on DAC as the principal method of access control is unfounded and inappropriate for many commercial and civilian government organizations. The paper describes a type of non-discretionary access control - role-based access control (RBAC) - that is more central to the secure processing needs of non-military systems than DAC.


On the (semi)lattices induced by continuous reducibilities

Abstract: Continuous reducibilities are a proven tool in computable analysis, and have applications in other fields such as constructive mathematics or reverse mathematics. We study the order-theoretic properties of several variants of the two most important definitions, and especially introduce suprema for them. The suprema are shown to commutate with several characteristic numbers.


Rfuzzy framework

Abstract: Fuzzy reasoning is a very productive research field that during the last years has provided a number of theoretical approaches and practical implementation prototypes. Nevertheless, the classical implementations, like Fril, are not adapted to the latest formal approaches, like multi-adjoint logic semantics. Some promising implementations, like Fuzzy Prolog, are so general that the regular user/programmer does not feel comfortable because either representation of fuzzy concepts is complex or the results difficult to interpret. In this paper we present a modern framework, Rfuzzy, that is modelling multi-adjoint logic. It provides some extensions as default values (to represent missing information, even partial default values) and typed variables. Rfuzzy represents the truth value of predicates through facts, rules and functions. Rfuzzy answers queries with direct results (instead of constraints) and it is easy to use for any person that wants to represent a problem using fuzzy reasoning in a simple way (by using the classical representation with real numbers).


On the Generation of Test Data for Prolog by Partial Evaluation

Abstract: In recent work, we have proposed an approach to Test Data Generation (TDG) of imperative bytecode by partial evaluation (PE) of CLP which consists in two phases: (1) the bytecode program is first transformed into an equivalent CLP program by means of interpretive compilation by PE, (2) a second PE is performed in order to supervise the generation of test-cases by execution of the CLP decompiled program. The main advantages of TDG by PE include flexibility to handle new coverage criteria, the possibility to obtain test-case generators and its simplicity to be implemented. The approach in principle can be directly applied for TDG of any imperative language. However, when one tries to apply it to a declarative language like Prolog, we have found as a main difficulty the generation of test-cases which cover the more complex control flow of Prolog. Essentially, the problem is that an intrinsic feature of PE is that it only computes non-failing derivations while in TDG for Prolog it is essential to generate test-cases associated to failing computations. Basically, we propose to transform the original Prolog program into an equivalent Prolog program with explicit failure by partially evaluating a Prolog interpreter which captures failing derivations w.r.t. the input program. Another issue that we discuss in the paper is that, while in the case of bytecode the underlying constraint domain only manipulates integers, in Prolog it should properly handle the symbolic data manipulated by the program. The resulting scheme is of interest for bringing the advantages which are inherent in TDG by PE to the field of logic programming.


Improving Size-Change Analysis in Offline Partial Evaluation

Abstract: Some recent approaches for scalable offline partial evaluation of logic programs include a size-change analysis for ensuring both so called local and global termination. In this work|inspired by experimental evaluation|we introduce several improvements that may increase the accuracy of the analysis and, thus, the quality of the associated specialized programs. We aim to achieve this while maintaining the same complexity and scalability of the recent works.


A Lightweight Combination of Semantics for Non-deterministic Functions

Abstract: The use of non-deterministic functions is a distinctive feature of modern functional logic languages. The semantics commonly adopted is call-time choice, a notion that at the operational level is related to the sharing mechanism of lazy evaluation in functional languages. However, there are situations where run-time choice, closer to ordinary rewriting, is more appropriate. In this paper we propose an extension of existing call-time choice based languages, to provide support for run-time choice in localized parts of a program. The extension is remarkably simple at three relevant levels: syntax, formal operational calculi and implementation, which is based on the system Toy.


Prolog Visualization System Using Logichart Diagrams

Abstract: We have developed a Prolog visualization system that is intended to support Prolog programming education. The system uses Logichart diagrams to visualize Prolog programs. The Logichart diagram is designed to visualize the Prolog execution flow intelligibly and to enable users to easily correlate the Prolog clauses with its parts. The system has the following functions. (1) It visually traces Prolog execution (goal calling, success, and failure) on the Logichart diagram. (2) Dynamic change in a Prolog program by calling extra-logical predicates, such as `assertz' and `retract', is visualized in real time. (3) Variable substitution processes are displayed in a text widget in real time.


Constraint solving for high-level WCET analysis

Abstract: The safety of our day-to-day life depends crucially on the correct functioning of embedded software systems which control the functioning of more and more technical devices. Many of these software systems are time-critical. Hence, computations performed need not only to be correct, but must also be issued in a timely fashion. Worst case execution time (WCET) analysis is concerned with computing tight upper bounds for the execution time of a system in order to provide formal guarantees for the proper timing behaviour of a system. Central for this is to compute safe and tight bounds for loops and recursion depths. In this paper, we highlight the TuBound approach to this challenge at whose heart is a constraint logic based approach for loop analysis.


A Semantics-Aware Editing Environment for Prolog in Eclipse

Abstract: In this paper we present a Prolog plugin for Eclipse based upon BE4, and providing many features such as semantic-aware syntax highlighting, outline view, error marking, content assist, hover information, documentation generation, and quick fixes. The plugin makes use of a Java parser for full Prolog with an integrated Prolog engine, and can be extended with further semantic analyses, e.g., based on abstract interpretation.


An Absolute 2-Approximation Algorithm for Two-Dimensional Bin Packing

Abstract: We consider the problem of packing rectangles into bins that are unit squares, where the goal is to minimize the number of bins used. All rectangles have to be packed non-overlapping and orthogonal, i.e., axis-parallel. We present an algorithm for this problem with an absolute worst-case ratio of 2, which is optimal provided P != NP.


A Novel Approach for Compression of Images Captured using Bayer Color Filter Arrays

Abstract: We propose a new approach for image compression in digital cameras, where the goal is to achieve better quality at a given rate by using the characteristics of a Bayer color filter array. Most digital cameras produce color images by using a single CCD plate, so that each pixel in an image has only one color component and therefore an interpolation method is needed to produce a full color image. After the image processing stage, in order to reduce the memory requirements of the camera, a lossless or lossy compression stage often follows. But in this scheme, before decreasing redundancy through compression, redundancy is increased in an interpolation stage. In order to avoid increasing the redundancy before compression, we propose algorithms for image compression in which the order of the compression and interpolation stages is reversed. We introduce image transform algorithms, since non interpolated images cannot be directly compressed with general image coders. The simulation results show that our algorithm outperforms conventional methods with various color interpolation methods in a wide range of compression ratios. Our proposed algorithm provides not only better quality but also lower encoding complexity because the amount of luminance data used is only half of that in conventional methods.


Manipulating Scrip Systems: Sybils and Collusion

Abstract: Game-theoretic analyses of distributed and peer-to-peer systems typically use the Nash equilibrium solution concept, but this explicitly excludes the possibility of strategic behavior involving more than one agent. We examine the effects of two types of strategic behavior involving more than one agent, sybils and collusion, in the context of scrip systems where agents provide each other with service in exchange for scrip. Sybils make an agent more likely to be chosen to provide service, which generally makes it harder for agents without sybils to earn money and decreases social welfare. Surprisingly, in certain circumstances it is possible for sybils to make all agents better off. While collusion is generally bad, in the context of scrip systems it actually tends to make all agents better off, not merely those who collude. These results also provide insight into the effects of allowing agents to advertise and loan money. While many extensions of Nash equilibrium have been proposed that address collusion and other issues relevant to distributed and peer-to-peer systems, our results show that none of them adequately address the issues raised by sybils and collusion in scrip systems.


Multiagent Learning in Large Anonymous Games

Abstract: In large systems, it is important for agents to learn to act effectively, but sophisticated multi-agent learning algorithms generally do not scale. An alternative approach is to find restricted classes of games where simple, efficient algorithms converge. It is shown that stage learning efficiently converges to Nash equilibria in large anonymous games if best-reply dynamics converge. Two features are identified that improve convergence. First, rather than making learning more difficult, more agents are actually beneficial in many settings. Second, providing agents with statistical information about the behavior of others can significantly reduce the number of observations needed.


Differential Contrastive Divergence

Abstract: This paper has been retracted.


Relations, Constraints and Abstractions: Using the Tools of Logic Programming in the Security Industry

Abstract: Logic programming is sometimes described as relational programming: a paradigm in which the programmer specifies and composes n-ary relations using systems of constraints. An advanced logic programming environment will provide tools that abstract these relations to transform, optimise, or even verify the correctness of a logic program. This talk will show that these concepts, namely relations, constraints and abstractions, turn out to also be important in the reverse engineer process that underpins the discovery of bugs within the security industry.


Infinite words without palindrome

Abstract: We show that there exists an uniformly recurrent infinite word whose set of factors is closed under reversal and which has only finitely many palindromic factors.


On tiered small jump operators

Abstract: Predicative analysis of recursion schema is a method to characterize complexity classes like the class FPTIME of polynomial time computable functions. This analysis comes from the works of Bellantoni and Cook, and Leivant by data tiering. Here, we refine predicative analysis by using a ramified Ackermann's construction of a non-primitive recursive function. We obtain a hierarchy of functions which characterizes exactly functions, which are computed in O(n^k) time over register machine model of computation. For this, we introduce a strict ramification principle. Then, we show how to diagonalize in order to obtain an exponential function and to jump outside deterministic polynomial time. Lastly, we suggest a dependent typed lambda-calculus to represent this construction.


Qualitative Logics and Equivalences for Probabilistic Systems

Abstract: We investigate logics and equivalence relations that capture the qualitative behavior of Markov Decision Processes (MDPs). We present Qualitative Randomized CTL (QRCTL): formulas of this logic can express the fact that certain temporal properties hold over all paths, or with probability 0 or 1, but they do not distinguish among intermediate probability values. We present a symbolic, polynomial time model-checking algorithm for QRCTL on MDPs. The logic QRCTL induces an equivalence relation over states of an MDP that we call qualitative equivalence: informally, two states are qualitatively equivalent if the sets of formulas that hold with probability 0 or 1 at the two states are the same. We show that for finite alternating MDPs, where nondeterministic and probabilistic choices occur in different states, qualitative equivalence coincides with alternating bisimulation, and can thus be computed via efficient partition-refinement algorithms. On the other hand, in non-alternating MDPs the equivalence relations cannot be computed via partition-refinement algorithms, but rather, they require non-local computation. Finally, we consider QRCTL*, that extends QRCTL with nested temporal operators in the same manner in which CTL* extends CTL. We show that QRCTL and QRCTL* induce the same qualitative equivalence on alternating MDPs, while on non-alternating MDPs, the equivalence arising from QRCTL* can be strictly finer. We also provide a full characterization of the relation between qualitative equivalence, bisimulation, and alternating bisimulation, according to whether the MDPs are finite, and to whether their transition relations are finitely-branching.


Positive Logic with Adjoint Modalities: Proof Theory, Semantics and Reasoning about Information

Abstract: We consider a simple modal logic whose non-modal part has conjunction and disjunction as connectives and whose modalities come in adjoint pairs, but are not in general closure operators. Despite absence of negation and implication, and of axioms corresponding to the characteristic axioms of (e.g.) T, S4 and S5, such logics are useful, as shown in previous work by Baltag, Coecke and the first author, for encoding and reasoning about information and misinformation in multi-agent systems. For such a logic we present an algebraic semantics, using lattices with agent-indexed families of adjoint pairs of operators, and a cut-free sequent calculus. The calculus exploits operators on sequents, in the style of "nested" or "tree-sequent" calculi; cut-admissibility is shown by constructive syntactic methods. The applicability of the logic is illustrated by reasoning about the muddy children puzzle, for which the calculus is augmented with extra rules to express the facts of the muddy children scenario.


Parking functions, labeled trees and DCJ sorting scenarios

Abstract: In genome rearrangement theory, one of the elusive questions raised in recent years is the enumeration of rearrangement scenarios between two genomes. This problem is related to the uniform generation of rearrangement scenarios, and the derivation of tests of statistical significance of the properties of these scenarios. Here we give an exact formula for the number of double-cut-and-join (DCJ) rearrangement scenarios of co-tailed genomes. We also construct effective bijections between the set of scenarios that sort a cycle and well studied combinatorial objects such as parking functions and labeled trees.


Effect of Degree Distribution on Evolutionary Search

Abstract: This paper introduces a method to generate hierarchically modular networks with prescribed node degree list and proposes a metric to measure network modularity based on the notion of edge distance. The generated networks are used as test problems to explore the effect of modularity and degree distribution on evolutionary algorithm performance. Results from the experiments (i) confirm a previous finding that modularity increases the performance advantage of genetic algorithms over hill climbers, and (ii) support a new conjecture that test problems with modularized constraint networks having heavy-tailed right-skewed degree distributions are more easily solved than test problems with modularized constraint networks having bell-shaped normal degree distributions.


CloudSim: A Novel Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services

Abstract: Cloud computing focuses on delivery of reliable, secure, fault-tolerant, sustainable, and scalable infrastructures for hosting Internet-based application services. These applications have different composition, configuration, and deployment requirements. Quantifying the performance of scheduling and allocation policy on a Cloud infrastructure (hardware, software, services) for different application and service models under varying load, energy performance (power consumption, heat dissipation), and system size is an extremely challenging problem to tackle. To simplify this process, in this paper we propose CloudSim: a new generalized and extensible simulation framework that enables seamless modelling, simulation, and experimentation of emerging Cloud computing infrastructures and management services. The simulation framework has the following novel features: (i) support for modelling and instantiation of large scale Cloud computing infrastructure, including data centers on a single physical computing node and java virtual machine; (ii) a self-contained platform for modelling data centers, service brokers, scheduling, and allocations policies; (iii) availability of virtualization engine, which aids in creation and management of multiple, independent, and co-hosted virtualized services on a data center node; and (iv) flexibility to switch between space-shared and time-shared allocation of processing cores to virtualized services.


Airport Gate Assignment A Hybrid Model and Implementation

Abstract: With the rapid development of airlines, airports today become much busier and more complicated than previous days. During airlines daily operations, assigning the available gates to the arriving aircrafts based on the fixed schedule is a very important issue, which motivates researchers to study and solve Airport Gate Assignment Problems (AGAP) with all kinds of state-of-the-art combinatorial optimization techniques. In this paper, we study the AGAP and propose a novel hybrid mathematical model based on the method of constraint programming and 0 - 1 mixed-integer programming. With the objective to minimize the number of gate conflicts of any two adjacent aircrafts assigned to the same gate, we build a mathematical model with logical constraints and the binary constraints. For practical considerations, the potential objective of the model is also to minimize the number of gates that airlines must lease or purchase in order to run their business smoothly. We implement the model in the Optimization Programming Language (OPL) and carry out empirical studies with the data obtained from online timetable of Continental Airlines, Houston Gorge Bush Intercontinental Airport IAH, which demonstrate that our model can provide an efficient evaluation criteria for the airline companies to estimate the efficiency of their current gate assignments.


Multi-Agent Crisis Response systems - Design Requirements and Analysis of Current Systems

Abstract: Crisis response is a critical area of research, with encouraging progress in the past view yeas. The aim of the research is to contribute to building future crisis environment where software agents, robots, responders, crisis managers, and crisis organizations interact to provide advice, protection and aid. This paper discusses the crisis response domain requirements, and provides analysis of five crisis response systems namely: DrillSim [2], DEFACTO [15], ALADDIN [1], RoboCup Rescue [18], and FireGrid [3]. Analysis of systems includes systems architecture and methodology. In addition, we identified features and limitations of systems based on crisis response domain requirements.


To Click or not to Click? The Role of Contextualized and User-Centric Web Snippets

Abstract: When searching the web, it is often possible that there are too many results available for ambiguous queries. Text snippets, extracted from the retrieved pages, are an indicator of the pages' usefulness to the query intention and can be used to focus the scope of search results. In this paper, we propose a novel method for automatically extracting web page snippets that are highly relevant to the query intention and expressive of the pages' entire content. We show that the usage of semantics, as a basis for focused retrieval, produces high quality text snippet suggestions. The snippets delivered by our method are significantly better in terms of retrieval performance compared to those derived using the pages' statistical content. Furthermore, our study suggests that semantically-driven snippet generation can also be used to augment traditional passage retrieval algorithms based on word overlap or statistical weights, since they typically differ in coverage and produce different results. User clicks on the query relevant snippets can be used to refine the query results and promote the most comprehensive among the relevant documents.


Bottom-up rewriting for words and terms

Abstract: For the whole class of linear term rewriting systems, we define \emph{bottom-up rewriting} which is a restriction of the usual notion of rewriting. We show that bottom-up rewriting effectively inverse-preserves recognizability and analyze the complexity of the underlying construction. The Bottom-Up class (BU) is, by definition, the set of linear systems for which every derivation can be replaced by a bottom-up derivation. Membership to BU turns out to be undecidable, we are thus lead to define more restricted classes: the classes SBU(k), k in N of Strongly Bottom-Up(k) systems for which we show that membership is decidable. We define the class of Strongly Bottom-Up systems by SBU = U_{k in \} SBU(k). We give a polynomial sufficient condition for a system to be in $\SBU$. The class SBU contains (strictly) several classes of systems which were already known to inverse preserve recognizability: the inverse left-basic semi-Thue systems (viewed as unary term rewriting systems), the linear growing term rewriting systems, the inverse Linear-Finite-Path-Ordering systems.


Generating Hierarchically Modular Networks via Link Switching

Abstract: This paper introduces a method to generate hierarchically modular networks with prescribed node degree list by link switching. Unlike many existing network generating models, our method does not use link probabilities to achieve modularity. Instead, it utilizes a user-specified topology to determine relatedness between pairs of nodes in terms of edge distances and links are switched to increase edge distances. To measure the modular-ness of a network as a whole, a new metric called Q2 is proposed. Comparisons are made between the Q [15] and Q2 measures. We also comment on the effect of our modularization method on other network characteristics such as clustering, hierarchy, average path length, small-worldness, degree correlation and centrality. An application of this method is reported elsewhere [12]. Briefly, the generated networks are used as test problems to explore the effect of modularity and degree distribution on evolutionary search algorithms.


Privacy in Location Based Services: Primitives Toward the Solution

Abstract: Location based services (LBS) are one of the most promising and innovative directions of convergence technologies resulting of emergence of several fields including database systems, mobile communication, Internet technology, and positioning systems. Although being initiated as early as middle of 1990's, it is only recently that the LBS received a systematic profound research interest due to its commercial and technological impact. As the LBS is related to the user's location which can be used to trace the user's activities, a strong privacy concern has been raised. To preserve the user's location, several intelligent works have been introduced though many challenges are still awaiting solutions. This paper introduces a survey on LBS systems considering both localization technologies, model and architectures guaranteeing privacy. We also overview cryptographic primitive to possibly use in preserving LBS's privacy followed by fruitful research directions basically concerned with the privacy issue.