A GP-MOEA/D Approach for Modelling Total Electron Content over Cyprus

Abstract: Vertical Total Electron Content (vTEC) is an ionospheric characteristic used to derive the signal delay imposed by the ionosphere on near-vertical trans-ionospheric links. The major aim of this paper is to design a prediction model based on the main factors that influence the variability of this parameter on a diurnal, seasonal and long-term time-scale. The model should be accurate and general (comprehensive) enough for efficiently approximating the high variations of vTEC. However, good approximation and generalization are conflicting objectives. For this reason a Genetic Programming (GP) with Multi-objective Evolutionary Algorithm based on Decomposition characteristics (GP-MOEA/D) is designed and proposed for modeling vTEC over Cyprus. Experimental results show that the Multi-Objective GP-model, considering real vTEC measurements obtained over a period of 11 years, has produced a good approximation of the modeled parameter and can be implemented as a local model to account for the ionospheric imposed error in positioning. Particulary, the GP-MOEA/D approach performs better than a Single Objective Optimization GP, a GP with Non-dominated Sorting Genetic Algorithm-II (NSGA-II) characteristics and the previously proposed Neural Network-based approach in most cases.


MAPSS, a Multi-Aspect Partner and Service Selection Method

Abstract: In Service-Oriented Virtual Organization Breeding Environments (SOVOBEs), services performed by people, organizations and information systems are composed in potentially complex business processes performed by a set of partners. In a SOVOBE, the success of a virtual organization depends largely on the partner and service selection process, which determines the composition of services performed by the VO partners. In this paper requirements for a partner and service selection method for SOVOBEs are defined and a novel Multi-Aspect Partner and Service Selection method, MAPSS, is presented. The MAPSS method allows a VO planner to select appropriate services and partners based on their competences and their relations with other services/partners. The MAPSS method relies on a genetic algorithm to select the most appropriate set of partners and services.


Social Service Brokerage based on UDDI and Social Requirements

Abstract: The choice of a suitable service provider is an important issue often overlooked in existing architectures. Current systems focus mostly on the service itself, paying little (if at all) attention to the service provider. In the Service Oriented Architecture (SOA), Universal Description, Discovery and Integration (UDDI) registries have been proposed as a way to publish and find information about available services. These registries have been criticized for not being completely trustworthy. In this paper, an enhancement of existing mechanisms for finding services is proposed. The concept of Social Service Broker addressing both service and social requirements is proposed. While UDDI registries still provide information about available services, methods from Social Network Analysis are proposed as a way to evaluate and rank the services proposed by a UDDI registry in social terms.


Agile and Pro-Active Public Administration as a Collaborative Networked Organization

Abstract: In highly competitive, globalized economies and societies of always-on-line people intensively using the Internet and mobile phones, public administrations have to adapt to new challenges. Enterprises and citizens expect public administrations to be agile and pro-active to foster development. A way to achieve agility and pro-activity is application of a model of Collaborative Network Organizations in its two forms: Virtual Organizations (VO) and Virtual Organization Breeding Environments (VOBE). In the paper, advantages are shown of public administration playing a role of a Virtual Organization customer on the one hand, and a Virtual Organization member on the other hand. It is also shown how public administration playing a role of a Virtual Organization Breeding Environment may improve its agility and promote advanced technologies and management methods among local organizations. It is argued in the paper that public administration should provide a Virtual Organization Breeding Environment as a part of public services.


Reference Model for Performance Management in Service-Oriented Virtual Organization Breeding Environments

Abstract: Performance management (PM) is a key function of virtual organization (VO) management. A large set of PM indicators has been proposed and evaluated within the context of virtual breeding environments (VBEs). However, it is currently difficult to describe and select suitable PM indicators because of the lack of a common vocabulary and taxonomies of PM indicators. Therefore, there is a need for a framework unifying concepts in the domain of VO PM. In this paper, a reference model for VO PM is presented in the context of service-oriented VBEs. In the proposed reference model, both a set of terms that could be used to describe key performance indicators, and a set of taxonomies reflecting various aspects of PM are proposed. The proposed reference model is a first attempt and a work in progress that should not be supposed exhaustive.


Social Protocols for Agile Virtual Teams

Abstract: Despite many works on collaborative networked organizations (CNOs), CSCW, groupware, workflow systems and social networks, computer support for virtual teams is still insufficient, especially support for agility, i.e. the capability of virtual team members to rapidly and cost efficiently adapt the way they interact to changes. In this paper, requirements for computer support for agile virtual teams are presented. Next, an extension of the concept of social protocol is proposed as a novel model supporting agile interactions within virtual teams. The extended concept of social protocol consists of an extended social network and a workflow model.


PTaCL: A Language for Attribute-Based Access Control in Open Systems

Abstract: Many languages and algebras have been proposed in recent years for the specification of authorization policies. For some proposals, such as XACML, the main motivation is to address real-world requirements, typically by providing a complex policy language with somewhat informal evaluation methods; others try to provide a greater degree of formality (particularly with respect to policy evaluation) but support far fewer features. In short, there are very few proposals that combine a rich set of language features with a well-defined semantics, and even fewer that do this for authorization policies for attribute-based access control in open environments. In this paper, we decompose the problem of policy specification into two distinct sub-languages: the policy target language (PTL) for target specification, which determines when a policy should be evaluated; and the policy composition language (PCL) for building more complex policies from existing ones. We define syntax and semantics for two such languages and demonstrate that they can be both simple and expressive. PTaCL, the language obtained by combining the features of these two sub-languages, supports the specification of a wide range of policies. However, the power of PTaCL means that it is possible to define policies that could produce unexpected results. We provide an analysis of how PTL should be restricted and how policies written in PCL should be evaluated to minimize the likelihood of undesirable results.


Social Requirements for Virtual Organization Breeding Environments

Abstract: The creation of Virtual Breeding Environments (VBE) is a topic which has received too little attention: in most former works, the existence of the VBE is either assumed, or is considered as the result of the voluntary, participatory gathering of a set of candidate companies. In this paper, the creation of a VBE by a third authority is considered: chambers of commerce, as organizations whose goal is to promote and facilitate business interests and activity in the community, could be good candidates for exogenous VBE creators. During VBE planning, there is a need to specify social requirements for the VBE. In this paper, SNA metrics are proposed as a way for a VBE planner to express social requirements for a VBE to be created. Additionally, a set of social requirements for VO planners, VO brokers, and VBE members are proposed.


Partial mutual exclusion for infinitely many processes

Abstract: Partial mutual exclusion is the drinking philosophers problem for complete graphs. It is the problem that a process may enter a critical section CS of its code only when some finite set nbh of other processes are not in their critical sections. For each execution of CS, the set nbh can be given by the environment. We present a starvation free solution of this problem in a setting with infinitely many processes, each with finite memory, that communicate by asynchronous messages. The solution has the property of first-come first-served, in so far as this can be guaranteed by asynchronous messages. For every execution of CS and every process in nbh, between three and six messages are needed. The correctness of the solution is argued with invariants and temporal logic. It has been verified with the proof assistant PVS.


Modeling Virtual Organization Architecture with the Virtual Organization Breeding Methodology

Abstract: While Enterprise Architecture Modeling (EAM) methodologies become more and more popular, an EAM methodology tailored to the needs of virtual organizations (VO) is still to be developed. Among the most popular EAM methodologies, TOGAF has been chosen as the basis for a new EAM methodology taking into account characteristics of VOs presented in this paper. In this new methodology, referred as Virtual Organization Breeding Methodology (VOBM), concepts developed within the ECOLEAD project, e.g. the concept of Virtual Breeding Environment (VBE) or the VO creation schema, serve as fundamental elements for development of VOBM. VOBM is a generic methodology that should be adapted to a given VBE. VOBM defines the structure of VBE and VO architectures in a service-oriented environment, as well as an architecture development method for virtual organizations (ADM4VO). Finally, a preliminary set of tools and methods for VOBM is given in this paper.


Autonomous push-down automaton built on DNA

Abstract: In this paper we propose a biomolecular implementation of the push-down automaton (one of theoretical models of computing device with unbounded memory) using DNA molecules. The idea of this improved implementation was inspired by Cavaliere et al. (2005).


Enhancing LTE-Advanced Relay Deployments via Relay Cell Extension

Abstract: Relaying is a promising enhancement to current radio access networks. Relay enhanced LTE-Advanced networks are expected to fulfill the demanding coverage and capacity requirements in a cost-efficient way. However, due to low transmit power, the coverage areas of the relay nodes will be small. Therefore, the performance of relay deployments may be limited by load imbalances. In this study, we present a practical solution for this problem by introducing a bias to cell selection and handover decisions along with a reduction in eNB transmit power. This method results in an extension of the relay cells and an appropriate load balance can then be achieved. Moreover, it is shown that a proper power control setting is necessary in the uplink and that power control optimization can further enhance the system performance. Comprehensive system level simulations confirm that the proposed solution yields significant user throughput gains both in the uplink and the downlink.


Tractability results for the Double-Cut-and-Join circular median problem

Abstract: The circular median problem in the Double-Cut-and-Join (DCJ) distance asks to find, for three given genomes, a fourth circular genome that minimizes the sum of the mutual distances with the three other ones. This problem has been shown to be NP-complete. We show here that, if the number of vertices of degree 3 in the breakpoint graph of the three input genomes is fixed, then the problem is tractable


Robustness Analysis for Battery Supported Cyber-Physical Systems

Abstract: This paper establishes a novel analytical approach to quantify robustness of scheduling and battery management for battery supported cyber-physical systems. A dynamic schedulability test is introduced to determine whether tasks are schedulable within a finite time window. The test is used to measure robustness of a real-time scheduling algorithm by evaluating the strength of computing time perturbations that break schedulability at runtime. Robustness of battery management is quantified analytically by an adaptive threshold on the state of charge. The adaptive threshold significantly reduces the false alarm rate for battery management algorithms to decide when a battery needs to be replaced.


Type inference in mathematics

Abstract: In the theory of programming languages, type inference is the process of inferring the type of an expression automatically, often making use of information from the context in which the expression appears. Such mechanisms turn out to be extremely useful in the practice of interactive theorem proving, whereby users interact with a computational proof assistant to construct formal axiomatic derivations of mathematical theorems. This article explains some of the mechanisms for type inference used by the Mathematical Components project, which is working towards a verification of the Feit-Thompson theorem.


Evolving Chart Pattern Sensitive Neural Network Based Forex Trading Agents

Abstract: Though machine learning has been applied to the foreign exchange market for algorithmic trading for quiet some time now, and neural networks(NN) have been shown to yield positive results, in most modern approaches the NN systems are optimized through traditional methods like the backpropagation algorithm for example, and their input signals are price lists, and lists composed of other technical indicator elements. The aim of this paper is twofold: the presentation and testing of the application of topology and weight evolving artificial neural network (TWEANN) systems to automated currency trading, and to demonstrate the performance when using Forex chart images as input to geometrical regularity aware indirectly encoded neural network systems, enabling them to use the patterns & trends within, when trading. This paper presents the benchmark results of NN based automated currency trading systems evolved using TWEANNs, and compares the performance and generalization capabilities of these direct encoded NNs which use the standard sliding-window based price vector inputs, and the indirect (substrate) encoded NNs which use charts as input. The TWEANN algorithm I will use in this paper to evolve these currency trading agents is the memetic algorithm based TWEANN system called Deus Ex Neural Network (DXNN) platform.


ANN queries: covering Voronoi diagram with hyperboxes

Abstract: Given a set $S$ of $n$ points in $d$-dimensional Euclidean metric space $X$ and a small positive real number $\epsilon$, we present an algorithm to preprocess $S$ and answer queries that require finding a set $S' \subseteq S$ of $\epsilon$-approximate nearest neighbors (ANNs) to a given query point $q \in X$. The following are the characteristics of points belonging to set $S'$: - $\forall s \in S'$, $\exists$ a point $p \in X$ such that $|pq| \le \epsilon$ and the nearest neighbor of $p$ is $s$, and - $\exists$ a $s' \in S'$ such that $s'$ is a nearest neighbor of $q$. During the preprocessing phase, from the Voronoi diagram of $S$ we construct a set of box trees of size $O(4^d\frac{V}{\delta}(\frac{\pi}{\epsilon})^{d-1})$ which facilitate in querying ANNs of any input query point in $O(\frac{1}{d}lg \frac{V}{\delta} + (\frac{\pi}{\epsilon})^{d-1})$ time. Here $\delta$ equals to $(\frac{\epsilon}{2\sqrt{d}})^d$, and $V$ is the volume of a large bounding box that contains all the points of set $S$. The average case cardinality of $S'$ is shown to rely on $S$ and $\epsilon$.


A note on the expressive power of linear orders

Abstract: This article shows that there exist two particular linear orders such that first-order logic with these two linear orders has the same expressive power as first-order logic with the Bit-predicate FO(Bit). As a corollary we obtain that there also exists a built-in permutation such that first-order logic with a linear order and this permutation is as expressive as FO(Bit).


Agent Development Toolkits

Abstract: Development of agents as well as their wide usage requires good underlying infrastructure. Literature indicates scarcity of agent development tools in initial years of research which limited the exploitation of this beneficial technology. However, today a wide variety of tools are available, for developing robust infrastructure. This technical note provides a deep overview of such tools and contrasts features provided by them.


Erd\H{o}s-Szekeres and Testing Weak epsilon-Nets are NP-hard in 3 dimensions - and what now?

Abstract: We consider the computational versions of the Erd\H os-Szekeres theorem and related problems in 3 dimensions. We show that, in constrast to the planar case, no polynomial time algorithm exists for determining the largest (empty) convex subset (unless P=NP) among a set of points, by proving that the corresponding decision problem is NP-hard. This answers a question by Dobkin, Edelsbrunner and Overmars from 1990. As a corollary, we derive a similar result for the closely related problem of testing weak epsilon-nets in R^3. Answering a question by Chazelle et al. from 1995, our reduction shows that the problem is co-NP-hard. This is work in progress - we are still trying to find a smart approximation algorithm for the problems.


The Clique Problem in Ray Intersection Graphs

Abstract: Ray intersection graphs are intersection graphs of rays, or halflines, in the plane. We show that any planar graph has an even subdivision whose complement is a ray intersection graph. The construction can be done in polynomial time and implies that finding a maximum clique in a segment intersection graph is NP-hard. This solves a 21-year old open problem posed by Kratochv\'il and Ne\v{s}et\v{r}il.


An image processing of a Raphael's portrait of Leonardo

Abstract: In one of his paintings, the School of Athens, Raphael is depicting Leonardo da Vinci as the philosopher Plato. Some image processing tools can help us in comparing this portrait with two Leonardo's portraits, considered as self-portraits.


Trading Regret for Efficiency: Online Convex Optimization with Long Term Constraints

Abstract: In this paper we propose a framework for solving constrained online convex optimization problem. Our motivation stems from the observation that most algorithms proposed for online convex optimization require a projection onto the convex set $\mathcal{K}$ from which the decisions are made. While for simple shapes (e.g. Euclidean ball) the projection is straightforward, for arbitrary complex sets this is the main computational challenge and may be inefficient in practice. In this paper, we consider an alternative online convex optimization problem. Instead of requiring decisions belong to $\mathcal{K}$ for all rounds, we only require that the constraints which define the set $\mathcal{K}$ be satisfied in the long run. We show that our framework can be utilized to solve a relaxed version of online learning with side constraints addressed in \cite{DBLP:conf/colt/MannorT06} and \cite{DBLP:conf/aaai/KvetonYTM08}. By turning the problem into an online convex-concave optimization problem, we propose an efficient algorithm which achieves $\tilde{\mathcal{O}}(\sqrt{T})$ regret bound and $\tilde{\mathcal{O}}(T^{3/4})$ bound for the violation of constraints. Then we modify the algorithm in order to guarantee that the constraints are satisfied in the long run. This gain is achieved at the price of getting $\tilde{\mathcal{O}}(T^{3/4})$ regret bound. Our second algorithm is based on the Mirror Prox method \citep{nemirovski-2005-prox} to solve variational inequalities which achieves $\tilde{\mathcal{\mathcal{O}}}(T^{2/3})$ bound for both regret and the violation of constraints when the domain $\K$ can be described by a finite number of linear constraints. Finally, we extend the result to the setting where we only have partial access to the convex set $\mathcal{K}$ and propose a multipoint bandit feedback algorithm with the same bounds in expectation as our first algorithm.


Semantic Query Reformulation in Social PDMS

Abstract: We consider social peer-to-peer data management systems (PDMS), where each peer maintains both semantic mappings between its schema and some acquaintances, and social links with peer friends. In this context, reformulating a query from a peer's schema into other peer's schemas is a hard problem, as it may generate as many rewritings as the set of mappings from that peer to the outside and transitively on, by eventually traversing the entire network. However, not all the obtained rewritings are relevant to a given query. In this paper, we address this problem by inspecting semantic mappings and social links to find only relevant rewritings. We propose a new notion of 'relevance' of a query with respect to a mapping, and, based on this notion, a new semantic query reformulation approach for social PDMS, which achieves great accuracy and flexibility. To find rapidly the most interesting mappings, we combine several techniques: (i) social links are expressed as FOAF (Friend of a Friend) links to characterize peer's friendship and compact mapping summaries are used to obtain mapping descriptions; (ii) local semantic views are special views that contain information about external mappings; and (iii) gossiping techniques improve the search of relevant mappings. Our experimental evaluation, based on a prototype on top of PeerSim and a simulated network demonstrate that our solution yields greater recall, compared to traditional query translation approaches proposed in the literature.


Fast Distributed Computation of Distances in Networks

Abstract: This paper presents a distributed algorithm to simultaneously compute the diameter, radius and node eccentricity in all nodes of a synchronous network. Such topological information may be useful as input to configure other algorithms. Previous approaches have been modular, progressing in sequential phases using building blocks such as BFS tree construction, thus incurring longer executions than strictly required. We present an algorithm that, by timely propagation of available estimations, achieves a faster convergence to the correct values. We show local criteria for detecting convergence in each node. The algorithm avoids the creation of BFS trees and simply manipulates sets of node ids and hop counts. For the worst scenario of variable start times, each node i with eccentricity ecc(i) can compute: the node eccentricity in diam(G)+ecc(i)+2 rounds; the diameter in 2*diam(G)+ecc(i)+2 rounds; and the radius in diam(G)+ecc(i)+2*radius(G) rounds.


Principles of Solomonoff Induction and AIXI

Abstract: We identify principles characterizing Solomonoff Induction by demands on an agent's external behaviour. Key concepts are rationality, computability, indifference and time consistency. Furthermore, we discuss extensions to the full AI case to derive AIXI.


Virtual Worlds as a Support to Engineering Teaching

Abstract: Virtual Worlds (VWs) are an emerging technology used by a growing number of educational institutions around the world. It is an environment, a way of learning and an educational tool that allows different levels of online interaction. In the course "Programming I", of the career Informatics Engineering at Universidad de Valpara\'iso, we conducted a pilot experience with the VW of Second Life, in order to evaluate the potential of using VWs in the teaching practice.


Optimal Organizational Hierarchies: Source Coding: Disaster Relief

Abstract: ulticasting is an important communication paradigm for enabling the dissemination of information selectively. This paper considers the problem of optimal secure multicasting in a communication network captured through a graph (optimal is in an interesting sense) and provides a doubly optimal solution using results from source coding. It is realized that the solution leads to optimal design (in a well defined optimality sense) of organizational hierarchies captured through a graph. In this effort two novel concepts : prefix free path, graph entropy are introduced. Some results of graph entropy are provided. Also some results on Kraft inequality are discussed. As an application Hierarchical Hybrid Communication Network is utilized as a model of structured Mobile Adhoc network for utility in Disaster Management. Several new research problems that naturally emanate from this research are summarized.


Greediness and Equilibrium in Congestion Games

Abstract: Rosenthal (1973) introduced the class of congestion games and proved that they always possess a Nash equilibrium in pure strategies. Fotakis et al. (2005) introduce the notion of a greedy strategy tuple, where players sequentially and irrevocably choose a strategy that is a best response to the choice of strategies by former players. Whereas the former solution concept is driven by strong assumptions on the rationality of the players and the common knowledge thereof, the latter assumes very little rationality on the players' behavior. From Fotakis \cite{fotakis10} it follows that for Tree Representable congestion Games greedy behavior leads to a NE. In this paper we obtain necessary and sufficient conditions for the equivalence of these two solution concepts. Such equivalence enhances the viability of these concepts as realistic outcomes of the environment. The conditions for such equivalence to emerge for monotone symmetric games is that the strategy set has a tree-form, or equivalently is a `extension-parallel graph'.


Pattern-Based Classification: A Unifying Perspective

Abstract: The use of patterns in predictive models is a topic that has received a lot of attention in recent years. Pattern mining can help to obtain models for structured domains, such as graphs and sequences, and has been proposed as a means to obtain more accurate and more interpretable models. Despite the large amount of publications devoted to this topic, we believe however that an overview of what has been accomplished in this area is missing. This paper presents our perspective on this evolving area. We identify the principles of pattern mining that are important when mining patterns for models and provide an overview of pattern-based classification methods. We categorize these methods along the following dimensions: (1) whether they post-process a pre-computed set of patterns or iteratively execute pattern mining algorithms; (2) whether they select patterns model-independently or whether the pattern selection is guided by a model. We summarize the results that have been obtained for each of these methods.


An ACO Algorithm for Effective Cluster Head Selection

Abstract: This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.


Threshold phenomena in k-dominant skylines of random samples

Abstract: Skylines emerged as a useful notion in database queries for selecting representative groups in multivariate data samples for further decision making, multi-objective optimization or data processing, and the $k$-dominant skylines were naturally introduced to resolve the abundance of skylines when the dimensionality grows or when the coordinates are negatively correlated. We prove in this paper that the expected number of $k$-dominant skylines is asymptotically zero for large samples when $1\le k\le d-1$ under two reasonable (continuous) probability assumptions of the input points, $d$ being the (finite) dimensionality, in contrast to the asymptotic unboundedness when $k=d$. In addition to such an asymptotic zero-infinity property, we also establish a sharp threshold phenomenon for the expected ($d-1$)-dominant skylines when the dimensionality is allowed to grow with $n$. Several related issues such as the dominant cycle structures and numerical aspects, are also briefly studied.


A Scalable Video Search Engine Based on Audio Content Indexing and Topic Segmentation

Abstract: One important class of online videos is that of news broadcasts. Most news organisations provide near-immediate access to topical news broadcasts over the Internet, through RSS streams or podcasts. Until lately, technology has not made it possible for a user to automatically go to the smaller parts, within a longer broadcast, that might interest them. Recent advances in both speech recognition systems and natural language processing have led to a number of robust tools that allow us to provide users with quicker, more focussed access to relevant segments of one or more news broadcast videos. Here we present our new interface for browsing or searching news broadcasts (video/audio) that exploits these new language processing tools to (i) provide immediate access to topical passages within news broadcasts, (ii) browse news broadcasts by events as well as by people, places and organisations, (iii) perform cross lingual search of news broadcasts, (iv) search for news through a map interface, (v) browse news by trending topics, and (vi) see automatically-generated textual clues for news segments, before listening. Our publicly searchable demonstrator currently indexes daily broadcast news content from 50 sources in English, French, Chinese, Arabic, Spanish, Dutch and Russian.


Improving the Load Balancing Performance of Vlasiator

Abstract: This whitepaper describes the load-balancing performance issues that are observed and tackled during the petascaling of the Vlasiator codes. Vlasiator is a Vlasov-hybrid simulation code developed in Finnish Meteorological Institute (FMI). Vlasiator models the communications associated with the spatial grid operated on as a hypergraph and partitions the grid using the parallel hypergraph partitioning scheme (PHG) of the Zoltan partitioning framework. The result of partitioning determines the distribution of grid cells to processors. It is observed that the partitioning phase takes a substantial percentage of the overall computation time. Alternative (graph-partitioning-based) schemes that perform almost as well as the hypergraph partitioning scheme and that require less preprocessing overhead and better balance are proposed and investigated. A comparison in terms of effect on running time, preprocessing overhead and load-balancing quality of Zoltan's PHG, ParMeTiS, and PT-SCOTCH are presented. Test results on J\"uelich BlueGene/P cluster are presented.


Regret Bound by Variation for Online Convex Optimization

Abstract: In citep{Hazan-2008-extract}, the authors showed that the regret of online linear optimization can be bounded by the total variation of the cost vectors. In this paper, we extend this result to general online convex optimization. We first analyze the limitations of the algorithm in \citep{Hazan-2008-extract} when applied it to online convex optimization. We then present two algorithms for online convex optimization whose regrets are bounded by the variation of cost functions. We finally consider the bandit setting, and present a randomized algorithm for online bandit convex optimization with a variation-based regret bound. We show that the regret bound for online bandit convex optimization is optimal when the variation of cost functions is independent of the number of trials.


XML Information Retrieval Systems: A Survey

Abstract: The continuous growth in the XML information repositories has been matched by increasing efforts in development of XML retrieval systems, in large parts aiming at supporting content-oriented XML retrieval. These systems exploit the available structural information, as market up in XML documents, in order to return documents components- the so called XML elements-instead of the complement documents in repose to the user query. In this paper, we provide an overview of the different XML information retrieval systems and classify them according to their storage and query evaluation strategies.


3D Model Retrieval Based on Semantic and Shape Indexes

Abstract: The size of 3D models used on the web or stored in databases is becoming increasingly high. Then, an efficient method that allows users to find similar 3D objects for a given 3D model query has become necessary. Keywords and the geometry of a 3D model cannot meet the needs of users' retrieval because they do not include the semantic information. In this paper, a new method has been proposed to 3D models retrieval using semantic concepts combined with shape indexes. To obtain these concepts, we use the machine learning methods to label 3D models by k-means algorithm in measures and shape indexes space. Moreover, semantic concepts have been organized and represented by ontology language OWL and spatial relationships are used to disambiguate among models of similar appearance. The SPARQL query language has been used to question the information displayed in this language and to compute the similarity between two 3D models. We interpret our results using the Princeton Shape Benchmark Database and the results show the performance of the proposed new approach to retrieval 3D models. Keywords: 3D Model, 3D retrieval, measures, shape indexes, semantic, ontology


Graph based E-Government web service composition

Abstract: Nowadays, e-government has emerged as a government policy to improve the quality and efficiency of public administrations. By exploiting the potential of new information and communication technologies, government agencies are providing a wide spectrum of online services. These services are composed of several web services that comply with well defined processes. One of the big challenges is the need to optimize the composition of the elementary web services. In this paper, we present a solution for optimizing the computation effort in web service composition. Our method is based on Graph Theory. We model the semantic relationship between the involved web services through a directed graph. Then, we compute all shortest paths using for the first time, an extended version of the Floyd-Warshall algorithm.


Unique decodability of bigram counts by finite automata

Abstract: We revisit the problem of deciding whether a given string is uniquely decodable from its bigram counts by means of a finite automaton. An efficient algorithm for constructing a polynomial-size nondeterministic finite automaton that decides unique decodability is given. Conversely, we show that the minimum deterministic finite automaton for deciding unique decodability has at least exponentially many states in alphabet size.


A Combinatorial Algorithm for All-Pairs Shortest Paths in Directed Vertex-Weighted Graphs with Applications to Disc Graphs

Abstract: We consider the problem of computing all-pairs shortest paths in a directed graph with real weights assigned to vertices. For an $n\times n$ 0-1 matrix $C,$ let $K_{C}$ be the complete weighted graph on the rows of $C$ where the weight of an edge between two rows is equal to their Hamming distance. Let $MWT(C)$ be the weight of a minimum weight spanning tree of $K_{C}.$ We show that the all-pairs shortest path problem for a directed graph $G$ on $n$ vertices with nonnegative real weights and adjacency matrix $A_G$ can be solved by a combinatorial randomized algorithm in time $$\widetilde{O}(n^{2}\sqrt {n + \min\{MWT(A_G), MWT(A_G^t)\}})$$ As a corollary, we conclude that the transitive closure of a directed graph $G$ can be computed by a combinatorial randomized algorithm in the aforementioned time. $\widetilde{O}(n^{2}\sqrt {n + \min\{MWT(A_G), MWT(A_G^t)\}})$ We also conclude that the all-pairs shortest path problem for uniform disk graphs, with nonnegative real vertex weights, induced by point sets of bounded density within a unit square can be solved in time $\widetilde{O}(n^{2.75})$.


Secure Geographic Routing Protocols: Issues and Approaches

Abstract: In the years, routing protocols in wireless sensor networks (WSN) have been substantially investigated by researches. Most state-of-the-art surveys have focused on reviewing of wireless sensor network .In this paper we review the existing secure geographic routing protocols for wireless sensor network (WSN) and also provide a qualitative comparison of them.


Nouvelle repr\'esentation concise exacte des motifs corr\'el\'es rares : Application \`a la d\'etection d'intrusions

Abstract: Correlated rare pattern mining is an interesting issue in Data mining. In this respect, the set of correlated rare patterns w.r.t. to the bond correlation measure was studied in a recent work, in which the RCPR concise exact representation of the set of correlated rare patterns was proposed. However, none algorithm was proposed in order to mine this representation and none experiment was carried out to evaluate it. In this paper, we introduce the new RcprMiner algorithm allowing an efficient extraction of RCPR. We also present the IsRCP algorithm allowing the query of the RCPR representation in addition to the RCPRegeneration algorithm allowing the regeneration of the whole set RCP of rare correlated patterns starting from this representation. The carried out experiments highlight interesting compactness rates offered by RCPR. The effectiveness of the proposed classification method, based on generic rare correlated association rules derived from RCPR, has also been proved in the context of intrusion detection.


Exploring Twitter Hashtags

Abstract: Twitter messages often contain so-called hashtags to denote keywords related to them. Using a dataset of 29 million messages, I explore relations among these hashtags with respect to co-occurrences. Furthermore, I present an attempt to classify hashtags into five intuitive classes, using a machine-learning approach. The overall outcome is an interactive Web application to explore Twitter hashtags.


A Diameter-Revealing Proof of the Bondy-Lov\'asz Lemma

Abstract: We present a strengthened version of a lemma due to Bondy and Lov\'asz. This lemma establishes the connectivity of a certain graph whose nodes correspond to the spanning trees of a 2-vertex-connected graph, and implies the k=2 case of the Gy\H{o}ri-Lov\'asz Theorem on partitioning of k-vertex-connected graphs. Our strengthened version constructively proves an asymptotically tight O(|V|^2) bound on the worst-case diameter of this graph of spanning trees.


A Markov Random Field Topic Space Model for Document Retrieval

Abstract: This paper proposes a novel statistical approach to intelligent document retrieval. It seeks to offer a more structured and extensible mathematical approach to the term generalization done in the popular Latent Semantic Analysis (LSA) approach to document indexing. A Markov Random Field (MRF) is presented that captures relationships between terms and documents as probabilistic dependence assumptions between random variables. From there, it uses the MRF-Gibbs equivalence to derive joint probabilities as well as local probabilities for document variables. A parameter learning method is proposed that utilizes rank reduction with singular value decomposition in a matter similar to LSA to reduce dimensionality of document-term relationships to that of a latent topic space. Experimental results confirm the ability of this approach to effectively and efficiently retrieve documents from substantial data sets.


Publishing Location Dataset Differential Privately with Isotonic Regression

Abstract: We consider the problem of publishing location datasets, in particular 2D spatial pointsets, in a differentially private manner. Many existing mechanisms focus on frequency counts of the points in some a priori partition of the domain that is difficult to determine. We propose an approach that adds noise directly to the point, or to a group of neighboring points. Our approach is based on the observation that, the sensitivity of sorting, as a function on sets of real numbers, can be bounded. Together with isotonic regression, the dataset can be accurately reconstructed. To extend the mechanism to higher dimension, we employ locality preserving function to map the dataset to a bounded interval. Although there are fundamental limits on the performance of locality preserving functions, fortunately, our problem only requires distance preservation in the "easier" direction, and the well-known Hilbert space-filling curve suffices to provide high accuracy. The publishing process is simple from the publisher's point of view: the publisher just needs to map the data, sort them, group them, add Laplace noise and publish the dataset. The only parameter to determine is the group size which can be chosen based on predicted generalization errors. Empirical study shows that the published dataset can also exploited to answer other queries, for example, range query and median query, accurately.


Bounding Interference in Wireless Ad Hoc Networks with Nodes in Random Position

Abstract: The interference at a wireless node s can be modelled by the number of wireless nodes whose transmission ranges cover s. Given a set of positions for wireless nodes, the interference minimization problem is to assign a transmission radius (equivalently, a power level) to each node such that the resulting communication graph is connected, while minimizing the maximum interference. We consider the model introduced by von Rickenback et al. (2005), in which each transmission range is represented by a ball and edges in the communication graph are symmetric. The problem is NP-complete in two dimensions (Buchin 2008) and no polynomial-time approximation algorithm is known. Furthermore, even in one dimension (the highway model), the problem's complexity is unknown and the maximum interference of a set of n wireless nodes can be as high as Theta(sqrt(n)) (von Rickenback et al. 2005). In this paper we show how to solve the problem efficiently in settings typical for wireless ad hoc networks. In particular, we show that if node positions are represented by a set P of n points selected uniformly and independently at random over a d-dimensional rectangular region, for any fixed d, then the topology given by the closure of the Euclidean minimum spanning tree of P has maximum interference O(log n) with high probability. We extend this bound to a general class of communication graphs over a broad set of probability distributions. Next we present a local algorithm that constructs a graph from this class; this is the first local algorithm to provide an upper bound on the expected maximum interference. Finally, we discuss an empirical evaluation of our algorithm with a suite of simulation results.


Approximate Aggregate Utility Maximization in Multi-Hop Wireless Networks using Distributed Greedy Scheduling

Abstract: In this paper, we study the performance of greedy scheduling in multihop wireless networks, where the objective is aggregate utility maximization. Following standard approaches, we consider the dual of the original optimization problem. The dual can be solved optimally, only with the knowledge of the maximal independent sets in the network. But computation of maximal independent sets is known to be NP-hard. Motivated by this, we propose a distributed greedy heuristic to address the problem of link scheduling. We evaluate the effect of the distributed greedy heuristic on aggregate utility maximization in detail, for the case of an arbitrary graph. We provide some insights into the factors affecting aggregate utility maximization in a network, by providing bounds on the same. We give simulation results for the approximate aggregate utility maximization achieved under distributed implementation of the greedy heuristic and find them close to the maximum aggregate utility obtained using optimal scheduling.


On the Integrality Gap of the Directed-Component Relaxation for Steiner Tree

Abstract: In this note, we show that the integrality gap of the $k$-Directed-Component- Relaxation($k$-DCR) LP for the Steiner tree problem, introduced by Byrka, Grandoni, Rothvob and Sanita (STOC 2010), is at most $\ln(4)<1.39$. The proof is constructive: we can efficiently find a Steiner tree whose cost is at most $\ln(4)$ times the cost of the optimal fractional $k$-restricted Steiner tree given by the $k$-DCR LP.


An Enhanced Indexing And Ranking Technique On The Semantic Web

Abstract: With the fast growth of the Internet, more and more information is available on the Web. The Semantic Web has many features which cannot be handled by using the traditional search engines. It extracts metadata for each discovered Web documents in RDF or OWL formats, and computes relations between documents. We proposed a hybrid indexing and ranking technique for the Semantic Web which finds relevant documents and computes the similarity among a set of documents. First, it returns with the most related document from the repository of Semantic Web Documents (SWDs) by using a modified version of the ObjectRank technique. Then, it creates a sub-graph for the most related SWDs. Finally, It returns the hubs and authorities of these document by using the HITS algorithm. Our technique increases the quality of the results and decreases the execution time of processing the user's query.


A New Digital Watermarking Algorithm Using Combination of Least Significant Bit (LSB) and Inverse Bit

Abstract: In this paper, we introduce a new digital watermarking algorithm using least significant bit (LSB). LSB is used because of its little effect on the image. This new algorithm is using LSB by inversing the binary values of the watermark text and shifting the watermark according to the odd or even number of pixel coordinates of image before embedding the watermark. The proposed algorithm is flexible depending on the length of the watermark text. If the length of the watermark text is more than ((MxN)/8)-2 the proposed algorithm will also embed the extra of the watermark text in the second LSB. We compare our proposed algorithm with the 1-LSB algorithm and Lee's algorithm using Peak signal-to-noise ratio (PSNR). This new algorithm improved its quality of the watermarked image. We also attack the watermarked image by using cropping and adding noise and we got good results as well.


Minimizing the Risk of Architectural Decay by using Architecture-Centric Evolution Process

Abstract: Software systems endure many noteworthy changes throughout their life-cycle in order to follow the evolution of the problem domains. Generally, the software system architecture cannot follow the rapid evolution of a problem domain which results in the discrepancies between the implemented and designed architecture. Software architecture illustrates a system's structure and global properties and consequently determines not only how the system should be constructed but also leads its evolution. Architecture plays an important role to ensure that a system satisfies its business and mission goals during implementation and evolution. However, the capabilities of the designed architecture may possibly be lost when the implementation does not conform to the designed architecture. Such a loss of consistency causes the risk of architectural decay. The architectural decay can be avoided if architectural changes are made as early as possible. The paper presents the Process Model for Architecture-Centric Evolution which improves the quality of software systems through maintaining consistency between designed architecture and implementation. It also increases architecture awareness of developers which assists in minimizing the risk of architectural decay. In the proposed approach consistency checks are performed before and after the change implementation.


Peer-to-Peer Live Streaming and Video On Demand Design Issues and its Challenges

Abstract: Peer-to-Peer Live streaming and Video on Demand is the most popular media applications over the Internet in recent years. These systems reduce the load on the server and provide a scalable content distribution. A new paradigm of P2P network collaborates to build large distributed video applications on existing networks .But, the problem of designing the system are at par with the P2P media streaming, live and Video on demand systems. Hence a comprehensive design comparison is needed to build such kind of system architecture. Therefore, in this paper we elaborately studied the traditional approaches for P2P streaming architectures, and its critical design issues, as well as practicable challenges. Thus, our studies in this paper clearly point the tangible design issues and its challenges, and other intangible issues for providing P2P VoD services.


Fast Balanced Partitioning is Hard, Even on Grids and Trees

Abstract: Two kinds of approximation algorithms exist for the k-BALANCED PARTITIONING problem: those that are fast but compute unsatisfying approximation ratios, and those that guarantee high quality ratios but are slow. In this paper we prove that this tradeoff between runtime and solution quality is necessary. For the problem a minimum number of edges in a graph need to be found that, when cut, partition the vertices into k equal-sized sets. We develop a reduction framework which identifies some necessary conditions on the considered graph class in order to prove the hardness of the problem. We focus on two combinatorially simple but very different classes, namely trees and solid grid graphs. The latter are finite connected subgraphs of the infinite 2D grid without holes. First we use the framework to show that for solid grid graphs it is NP-hard to approximate the optimum number of cut edges within any satisfying ratio. Then we consider solutions in which the sets may deviate from being equal-sized. Our framework is used on grids and trees to prove that no fully polynomial time algorithm exists that computes solutions in which the sets are arbitrarily close to equal-sized. This is true even if the number of edges cut is allowed to increase the more stringent the limit on the set sizes is. These are the first bicriteria inapproximability results for the problem.


The Potential of Synergistic Static, Dynamic and Speculative Loop Nest Optimizations for Automatic Parallelization

Abstract: Research in automatic parallelization of loop-centric programs started with static analysis, then broadened its arsenal to include dynamic inspection-execution and speculative execution, the best results involving hybrid static-dynamic schemes. Beyond the detection of parallelism in a sequential program, scalable parallelization on many-core processors involves hard and interesting parallelism adaptation and mapping challenges. These challenges include tailoring data locality to the memory hierarchy, structuring independent tasks hierarchically to exploit multiple levels of parallelism, tuning the synchronization grain, balancing the execution load, decoupling the execution into thread-level pipelines, and leveraging heterogeneous hardware with specialized accelerators. The polyhedral framework allows to model, construct and apply very complex loop nest transformations addressing most of the parallelism adaptation and mapping challenges. But apart from hardware-specific, back-end oriented transformations (if-conversion, trace scheduling, value prediction), loop nest optimization has essentially ignored dynamic and speculative techniques. Research in polyhedral compilation recently reached a significant milestone towards the support of dynamic, data-dependent control flow. This opens a large avenue for blending dynamic analyses and speculative techniques with advanced loop nest optimizations. Selecting real-world examples from SPEC benchmarks and numerical kernels, we make a case for the design of synergistic static, dynamic and speculative loop transformation techniques. We also sketch the embedding of dynamic information, including speculative assumptions, in the heart of affine transformation search spaces.


Enhancing Information Systems Security in Educational Organizations in KSA through proposing security model

Abstract: It is well known that technology utilization is not restricted for one sector than the other anymore, Educational organizations share many parts of their information systems with commercial organizations. In this paper we will try to identify the main characteristics of information systems in educational organizations, then we will propose a model of two parts to enhance the information systems security, the first part of the model will handle the policy and laws of the information system, the second part will provide a technical approach on how to audit and subsequently maintain the security of information system.


Autonomic Management for Multi-agent Systems

Abstract: Autonomic computing is a computing system that can manage itself by self-configuration, self-healing, self-optimizing and self-protection. Researchers have been emphasizing the strong role that multi agent systems can play progressively towards the design and implementation of complex autonomic systems. The important of autonomic computing is to create computing systems capable of managing themselves to a far greater extent than they do today. With the nature of autonomy, reactivity, sociality and pro-activity, software agents are promising to make autonomic computing system a reality. This paper mixed multi-agent system with autonomic feature that completely hides its complexity from users/services. Mentioned Java Application Development Framework as platform example of this environment, could applied to web services as front end to users. With multi agent support it also provides adaptability, intelligence, collaboration, goal oriented interactions, flexibility, mobility and persistence in software systems


Constraining the Size Growth of the Task Space with Socially Guided Intrinsic Motivation using Demonstrations

Abstract: This paper presents an algorithm for learning a highly redundant inverse model in continuous and non-preset environments. Our Socially Guided Intrinsic Motivation by Demonstrations (SGIM-D) algorithm combines the advantages of both social learning and intrinsic motivation, to specialise in a wide range of skills, while lessening its dependence on the teacher. SGIM-D is evaluated on a fishing skill learning experiment.


Packet flow analysis in IP networks via abstract interpretation

Abstract: Static analysis (aka offline analysis) of a model of an IP network is useful for understanding, debugging, and verifying packet flow properties of the network. There have been static analysis approaches proposed in the literature for networks based on model checking as well as graph reachability. Abstract interpretation is a method that has typically been applied to static analysis of programs. We propose a new, abstract-interpretation based approach for analysis of networks. We formalize our approach, mention its correctness guarantee, and demonstrate its flexibility in addressing multiple network-analysis problems that have been previously solved via tailor-made approaches. Finally, we investigate an application of our analysis to a novel problem -- inferring a high-level policy for the network -- which has been addressed in the past only in the restricted single-router setting.


A Fuzzy Realistic Mobility Model For Ad hoc Networks

Abstract: Realistic mobility models can demonstrate more precise evaluation results because their parameters are closer to the reality. In this paper a realistic Fuzzy Mobility Model has been proposed. This model has rules which is changeable depending on nodes and environment conditions. This model is more complete and precise than the other mobility models and this is the advantage of this model. After simulation, it was found out that not only considering nodes movement as being imprecise (fuzzy) has a positive effects on most of ad hoc network parameters, but also, more importantly as they are closer to the real world condition, they can have a more positive effect on the implementation of ad hoc network protocols.


Fast Private Data Release Algorithms for Sparse Queries

Abstract: We revisit the problem of accurately answering large classes of statistical queries while preserving differential privacy. Previous approaches to this problem have either been very general but have not had run-time polynomial in the size of the database, have applied only to very limited classes of queries, or have relaxed the notion of worst-case error guarantees. In this paper we consider the large class of sparse queries, which take non-zero values on only polynomially many universe elements. We give efficient query release algorithms for this class, in both the interactive and the non-interactive setting. Our algorithms also achieve better accuracy bounds than previous general techniques do when applied to sparse queries: our bounds are independent of the universe size. In fact, even the runtime of our interactive mechanism is independent of the universe size, and so can be implemented in the "infinite universe" model in which no finite universe need be specified by the data curator.


Understanding the Social Cascading of Geekspeak and the Upshots for Social Cognitive Systems

Abstract: Barring swarm robotics, a substantial share of current machine-human and machine-machine learning and interaction mechanisms are being developed and fed by results of agent-based computer simulations, game-theoretic models, or robotic experiments based on a dyadic communication pattern. Yet, in real life, humans no less frequently communicate in groups, and gain knowledge and take decisions basing on information cumulatively gleaned from more than one single source. These properties should be taken into consideration in the design of autonomous artificial cognitive systems construed to interact with learn from more than one contact or 'neighbour'. To this end, significant practical import can be gleaned from research applying strict science methodology to human and social phenomena, e.g. to discovery of realistic creativity potential spans, or the 'exposure thresholds' after which new information could be accepted by a cognitive agent. The results will be presented of a project analysing the social propagation of neologisms in a microblogging service. From local, low-level interactions and information flows between agents inventing and imitating discrete lexemes we aim to describe the processes of the emergence of more global systemic order and dynamics, using the latest methods of complexity science. Whether in order to mimic them, or to 'enhance' them, parameters gleaned from complexity science approaches to humans' social and humanistic behaviour should subsequently be incorporated as points of reference in the field of robotics and human-machine interaction.


Neuropsychological constraints to human data production on a global scale

Abstract: Which are the factors underlying human information production on a global level? In order to gain an insight into this question we study a corpus of 252-633 Million publicly available data files on the Internet corresponding to an overall storage volume of 284-675 Terabytes. Analyzing the file size distribution for several distinct data types we find indications that the neuropsychological capacity of the human brain to process and record information may constitute the dominant limiting factor for the overall growth of globally stored information, with real-world economic constraints having only a negligible influence. This supposition draws support from the observation that the files size distributions follow a power law for data without a time component, like images, and a log-normal distribution for multimedia files, for which time is a defining qualia.


Workbook Structure Analysis - "Coping with the Imperfect"

Abstract: This Paper summarises the operation of software developed for the analysis of workbook structure. This comprises: the identification of layout in terms of filled areas formed into "Stripes", the identification of all the Formula Blocks/Cells and the identification of Data Blocks/Cells referenced by those formulas. This development forms part of our FormulaDataSleuth toolset. It is essential for the initial "Watching" of an existing workbook and enables the workbook to be subsequently managed and protected from damage.


Modelling the Delay Distribution of Binary Spray and Wait Routing Protocol

Abstract: This article proposes a stochastic model to obtain the end-to-end delay law between two nodes of a Delay Tolerant Network (DTN). We focus on the commonly used Binary Spray and Wait (BSW) routing protocol and propose a model that can be applied to homogeneous or heterogeneous networks (i.e. when the inter-contact law parameter takes one or several values). To the best of our knowledge, this is the first model allowing to estimate the delay distribution of Binary Spray and Wait DTN protocol in heterogeneous networks. We first detail the model and propose a set of simulations to validate the theoretical results.


Spreadsheets in Financial Departments: An Automated Analysis of 65,000 Spreadsheets using the Luminous Technology

Abstract: Spreadsheet technology is a cornerstone of IT systems in most organisations. It is often the glue that binds more structured transaction-based systems together. Financial operations are a case in point where spreadsheets fill the gaps left by dedicated accounting systems, particularly covering reporting and business process operations. However, little is understood as to the nature of spreadsheet usage in organisations and the contents and structure of these spreadsheets as they relate to key business functions with few, if any, comprehensive analyses of spreadsheet repositories in real organisations. As such this paper represents an important attempt at profiling real and substantial spreadsheet repositories. Using the Luminous technology an analysis of 65,000 spreadsheets for the financial departments of both a government and a private commercial organisation was conducted. This provides an important insight into the nature and structure of these spreadsheets, the links between them, the existence and nature of macros and the level of repetitive processes performed through the spreadsheets. Furthermore it highlights the organisational dependence on spreadsheets and the range and number of spreadsheets dealt with by individuals on a daily basis. In so doing, this paper prompts important questions that can frame future research in the domain.


Beyond The Desktop Spreadsheet

Abstract: Hypernumbers is a new commercial web-based spreadsheet. It addresses several risk factors in deploying spreadsheets.


Effect of Range Naming Conventions on Reliability and Development Time for Simple Spreadsheet Formulas

Abstract: Practitioners often argue that range names make spreadsheets easier to understand and use, akin to the role of good variable names in traditional programming languages, yet there is no supporting scientific evidence. The authors previously published experiments that disproved this theory in relation to debugging, and now turn their focus to development. This paper presents the results of two iterations of a new experiment, which measure the effect of range names on the correctness of, and the time it takes to develop, simple summation formulas. Our findings, supported by statistically significant results, show that formulas developed by non-experts using range names are more likely to contain errors and take longer to develop. Taking these findings with the findings from previous experiments, we conclude that range names do not improve the quality of spreadsheets developed by novice and intermediate users. This paper is important in that it finds that the choice of naming convention can have a significant impact on novice and intermediate users' performance in formula development, with less structured naming conventions resulting in poorer performance by users.


From Good Practices to Effective Policies for Preventing Errors in Spreadsheets

Abstract: Thanks to the enormous flexibility they provide, spreadsheets are considered a priceless blessing by many end-users. Many spreadsheets, however, contain errors which can lead to severe consequences in some cases. To manage these risks, quality managers in companies are often asked to develop appropriate policies for preventing spreadsheet errors. Good policies should specify rules which are based on "known-good" practices. While there are many proposals for such practices in literature written by practitioners and researchers, they are often not consistent with each other. Therefore no general agreement has been reached yet and no science-based "golden rules" have been published. This paper proposes an expert-based, retrospective approach to the identification of good practices for spreadsheets. It is based on an evaluation loop that cross-validates the findings of human domain experts against rules implemented in a semi-automated spreadsheet workbench, taking into account the context in which the spreadsheets are used.


Dynamics of Knowledge in DeLP through Argument Theory Change

Abstract: This article is devoted to the study of methods to change defeasible logic programs (de.l.p.s) which are the knowledge bases used by the Defeasible Logic Programming (DeLP) interpreter. DeLP is an argumentation formalism that allows to reason over potentially inconsistent de.l.p.s. Argument Theory Change (ATC) studies certain aspects of belief revision in order to make them suitable for abstract argumentation systems. In this article, abstract arguments are rendered concrete by using the particular rule-based defeasible logic adopted by DeLP. The objective of our proposal is to define prioritized argument revision operators \`a la ATC for de.l.p.s, in such a way that the newly inserted argument ends up undefeated after the revision, thus warranting its conclusion. In order to ensure this warrant, the de.l.p. has to be changed in concordance with a minimal change principle. To this end, we discuss different minimal change criteria that could be adopted. Finally, an algorithm is presented, implementing the argument revision operations.


A Platform for Spreadsheet Composition

Abstract: A huge amount of data is everyday managed in large organizations in many critical business sectors with the support of spreadsheet applications. The process of elaborating spreadsheet data is often performed in a distributed, collaborative way, where many actors enter data belonging to their local business domain to contribute to a global business view. The manual fusion of such data may lead to errors in copy-paste operations, loss of alignment and coherency due to multiple spreadsheet copies in circulation, as well as loss of data due to broken cross-spreadsheet links. In this paper we describe a methodology, based on a Spreadsheet Composition Platform, which greatly reduces these risks. The proposed platform seamlessly integrates the distributed spreadsheet elaboration, supports the commonly known spreadsheet tools for data processing and helps organizations to adopt a more controlled and secure environment for data fusion.


Controls over Spreadsheets for Financial Reporting in Practice

Abstract: Past studies show that only a small percent of organizations implement and enforce formal rules or informal guidelines for the designing, testing, documenting, using, modifying, sharing and archiving of spreadsheet models. Due to lack of such policies, there has been little research on how companies can effectively govern spreadsheets throughout their life cycle. This paper describes a survey involving 38 participants from the United States, representing companies that were working on compliance with the Sarbanes-Oxley Act of 2002 (SOX) as it relates to spreadsheets for financial reporting. The findings of this survey describe specific controls organizations have implemented to manage spreadsheets for financial reporting throughout the spreadsheet's lifecycle. Our findings indicate that there are problems in all stages of a spreadsheet's life cycle and suggest several important areas for future research.


Breviz: Visualizing Spreadsheets using Dataflow Diagrams

Abstract: Spreadsheets are used extensively in industry, often for business critical purposes. In previous work we have analyzed the information needs of spreadsheet professionals and addressed their need for support with the transition of a spreadsheet to a colleague with the generation of data flow diagrams. In this paper we describe the application of these data flow diagrams for the purpose of understanding a spreadsheet with three example cases. We furthermore suggest an additional application of the data flow diagrams: the assessment of the quality of the spreadsheet's design.


The M4RIE library for dense linear algebra over small fields with even characteristic

Abstract: In this work, we present the M4RIE library which implements efficient algorithms for linear algebra with dense matrices over GF(2^e) for 2 <= 2 <= 10. As the name of the library indicates, it makes heavy use of the M4RI library both directly (i.e., by calling it) and indirectly (i.e., by using its concepts). We provide an open-source GPLv2+ C library for efficient linear algebra over GF(2^e) for e small. In this library we implemented an idea due to Bradshaw and Boothby which reduces matrix multiplication over GF(p^k) to a series of matrix multiplications over GF(p). Furthermore, we propose a caching technique - Newton-John tables - to avoid finite field multiplications which is inspired by Kronrod's method ("M4RM") for matrix multiplication over GF(2). Using these two techniques we provide asymptotically fast triangular solving with matrices (TRSM) and PLE-based Gaussian elimination. As a result, we are able to significantly improve upon the state of the art in dense linear algebra over GF(2^e) with 2 <= e <= 10.


Requirements for Automated Assessment of Spreadsheet Maintainability

Abstract: The use of spreadsheets is widespread. Be it in business, finance, engineering or other areas, spreadsheets are created for their flexibility and ease to quickly model a problem. Very often they evolve from simple prototypes to implementations of crucial business logic. Spreadsheets that play a crucial role in an organization will naturally have a long lifespan and will be maintained and evolved by several people. Therefore, it is important not only to look at their reliability, i.e., how well is the intended functionality implemented, but also at their maintainability, i.e., how easy it is to diagnose a spreadsheet for deficiencies and modify it without degrading its quality. In this position paper we argue for the need to create a model to estimate the maintainability of a spreadsheet based on (automated) measurement. We propose to do so by applying a structured methodology that has already shown its value in the estimation of maintainability of software products. We also argue for the creation of a curated, community-contributed repository of spreadsheets.


Towards Evaluating the Quality of a Spreadsheet: The Case of the Analytical Spreadsheet Model

Abstract: We consider the challenge of creating guidelines to evaluate the quality of a spreadsheet model. We suggest four principles. First, state the domain-the spreadsheets to which the guidelines apply. Second, distinguish between the process by which a spreadsheet is constructed from the resulting spreadsheet artifact. Third, guidelines should be written in terms of the artifact, independent of the process. Fourth, the meaning of "quality" must be defined. We illustrate these principles with an example. We define the domain of "analytical spreadsheet models", which are used in business, finance, engineering, and science. We propose for discussion a framework and terminology for evaluating the quality of analytical spreadsheet models. This framework categorizes and generalizes the findings of previous work on the more narrow domain of financial spreadsheet models. We suggest that the ultimate goal is a set of guidelines for an evaluator, and a checklist for a developer.


In Search of a Taxonomy for Classifying Qualitative Spreadsheet Errors

Abstract: Most organizations use large and complex spreadsheets that are embedded in their mission-critical processes and are used for decision-making purposes. Identification of the various types of errors that can be present in these spreadsheets is, therefore, an important control that organizations can use to govern their spreadsheets. In this paper, we propose a taxonomy for categorizing qualitative errors in spreadsheet models that offers a framework for evaluating the readiness of a spreadsheet model before it is released for use by others in the organization. The classification was developed based on types of qualitative errors identified in the literature and errors committed by end-users in developing a spreadsheet model for Panko's (1996) "Wall problem". Closer inspection of the errors reveals four logical groupings of the errors creating four categories of qualitative errors. The usability and limitations of the proposed taxonomy and areas for future extension are discussed.


Abstract: Medicinal plants are increasingly recognized worldwide as an alternative source of efficacious and inexpensive medications to synthetic chemo-therapeutic compound. Rapid declining wild stocks of medicinal plants accompanied by adulteration and species substitutions reduce their efficacy, quality and safety. Consequently, the low accessibility to and non-affordability of orthodox medicine costs by rural dwellers to be healthy and economically productive further threaten their life expectancy. Finding comprehensive information on medicinal plants of conservation concern at a global level has been difficult. This has created a gap between computing technologies' promises and expectations in the healing process under complementary and alternative medicine. This paper presents the design and implementation of a Multimedia-based Medicinal Plants Sustainability Management System addressing these concerns. Medicinal plants' details for designing the system were collected through semi-structured interviews and databases. Unified Modelling Language, Microsoft-Visual-Studio.Net, C#3.0, Microsoft-Jet-Engine4.0, MySQL, Loquendo Multilingual Text-to-Speech Software, YouTube, and VLC Media Player were used. Keywords: Complementary and Alternative Medicine, conservation, extinction, medicinal plant, multimedia, phytoconstituents, rural dwellers


Spreadsheet on Cloud -- Framework for Learning and Health Management System

Abstract: Cloud Computing has caused a paradigm shift in the world of computing. Several use case scenarios have been floating around the programming world in relation to this. Applications such as Spreadsheets have the capability to use the Cloud framework to create complex web based applications. In our effort to do the same, we have proposed a Spreadsheet on the cloud as the framework for building new web applications, which will be useful in various scenarios, specifically a School administration system and governance scenarios, such as Health and Administration. This paper is a manifestation of this work, and contains some use cases and architectures which can be used to realize these scenarios in the most efficient manner.


Hardness of Mastermind

Abstract: Mastermind is a popular board game released in 1971, where a codemaker chooses a secret pattern of colored pegs, and a codebreaker has to guess it in several trials. After each attempt, the codebreaker gets a response from the codemaker containing some information on the number of correctly guessed pegs. The search space is thus reduced at each turn, and the game continues until the codebreaker is able to find the correct code, or runs out of trials. In this paper we study several variations of #MSP, the problem of computing the size of the search space resulting from a given (possibly fictitious) sequence of guesses and responses. Our main contribution is a proof of the #P-completeness of #MSP under parsimonious reductions, which settles an open problem posed by Stuckman and Zhang in 2005, concerning the complexity of deciding if the secret code is uniquely determined by the previous guesses and responses. Similarly, #MSP stays #P-complete under Turing reductions even with the promise that the search space has at least k elements, for any constant k. (In a regular game of Mastermind, k=1.) All our hardness results hold even in the most restrictive setting, in which there are only two available peg colors, and also if the codemaker's responses contain less information, for instance like in the so-called single-count (black peg) Mastermind variation.


Architecture of a Conference Management System Providing Advanced Paper Assignment Features

Abstract: This paper proposes an architecture and assignment management model of a conference management system that performs a precise and accurate automatic assignment of reviewers to papers. The system relies on taxonomy of keywords to describe papers and reviewers' competences. The implied hierarchical structure of the taxonomy provides important additional information - the semantic relationships between the separate keywords. It allows similarity measures to take into account not only the number of exactly matching keywords between a paper and a reviewer, but in case of non-matching ones to calculate how semantically close they are. Reviewers are allowed to bid on the papers they would like to (or not like to) review and to explicitly state conflicts of interest (CoI) with papers. An automatic CoI detection is checking for additional conflicts based on institutional affiliation, co-authorship (within the local database) and previous co-authorship in the past (within the major bibliographic indexes and digital libraries). The algorithm for automatic assignment takes into account all - selected keywords, reviewers' bids and conflicts of interest and tries to find the most accurate assignment while maintaining load balancing among reviewers.


Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees

Abstract: The tasks of extracting (top-$K$) Frequent Itemsets (FI's) and Association Rules (AR's) are fundamental primitives in data mining and database applications. Exact algorithms for these problems exist and are widely used, but their running time is hindered by the need of scanning the entire dataset, possibly multiple times. High quality approximations of FI's and AR's are sufficient for most practical uses, and a number of recent works explored the application of sampling for fast discovery of approximate solutions to the problems. However, these works do not provide satisfactory performance guarantees on the quality of the approximation, due to the difficulty of bounding the probability of under- or over-sampling any one of an unknown number of frequent itemsets. In this work we circumvent this issue by applying the statistical concept of \emph{Vapnik-Chervonenkis (VC) dimension} to develop a novel technique for providing tight bounds on the sample size that guarantees approximation within user-specified parameters. Our technique applies both to absolute and to relative approximations of (top-$K$) FI's and AR's. The resulting sample size is linearly dependent on the VC-dimension of a range space associated with the dataset to be mined. The main theoretical contribution of this work is a proof that the VC-dimension of this range space is upper bounded by an easy-to-compute characteristic quantity of the dataset which we call \emph{d-index}, and is the maximum integer $d$ such that the dataset contains at least $d$ transactions of length at least $d$ such that no one of them is a superset of or equal to another. We show that this bound is strict for a large class of datasets.


Reflexivity and the diagonal argument in proofs of limitative theorems

Abstract: This paper discusses limitations of reflexive and diagonal arguments as methods of proof of limitative theorems (e.g. G\"odel's theorem on Entscheidungsproblem, Turing's halting problem or Chaitin-G\"odel's theorem). The fact, that a formal system contains a sentence, which introduces reflexitivity, does not imply, that the same system does not contain a sentence or a proof procedure which solves this problem. Second basic method of proof - diagonal argument (i.e. showing non-eqiunumerosity of a program set with the set of real numbers) does not exclude existance of a single program, capable of computing all real numbers. In this work, we suggest an algorithm generating real numbers (arbitrary, infinite in the limit, binary strings), and we speculate it's meaning for theoretical computer science.


Shortest Non-trivial Cycles in Directed and Undirected Surface Graphs

Abstract: Let G be a graph embedded on a surface of genus g with b boundary cycles. We describe algorithms to compute multiple types of non-trivial cycles in G, using different techniques depending on whether or not G is an undirected graph. If G is undirected, then we give an algorithm to compute a shortest non-separating cycle in 2^O(g) n log log n time. Similar algorithms are given to compute a shortest non-contractible or non-null-homologous cycle in 2^O(g+b) n log log n time. Our algorithms for undirected G combine an algorithm of Kutz with known techniques for efficiently enumerating homotopy classes of curves that may be shortest non-trivial cycles. Our main technical contributions in this work arise from assuming G is a directed graph with possibly asymmetric edge weights. For this case, we give an algorithm to compute a shortest non-contractible cycle in G in O((g^3 + g b)n log n) time. In order to achieve this time bound, we use a restriction of the infinite cyclic cover that may be useful in other contexts. We also describe an algorithm to compute a shortest non-null-homologous cycle in G in O((g^2 + g b)n log n) time, extending a known algorithm of Erickson to compute a shortest non-separating cycle. In both the undirected and directed cases, our algorithms improve the best time bounds known for many values of g and b.


Task Interaction in an HTN Planner

Abstract: Hierarchical Task Network (HTN) planning uses task decomposition to plan for an executable sequence of actions as a solution to a problem. In order to reason effectively, an HTN planner needs expressive domain knowledge. For instance, a simplified HTN planning system such as JSHOP2 uses such expressivity and avoids some task interactions due to the increased complexity of the planning process. We address the possibility of simplifying the domain representation needed for an HTN planner to find good solutions, especially in real-world domains describing home and building automation environments. We extend the JSHOP2 planner to reason about task interaction that happens when task's effects are already achieved by other tasks. The planner then prunes some of the redundant searches that can occur due to the planning process's interleaving nature. We evaluate the original and our improved planner on two benchmark domains. We show that our planner behaves better by using simplified domain knowledge and outperforms JSHOP2 in a number of relevant cases.


Stability of Evolving Multi-Agent Systems

Abstract: A Multi-Agent System is a distributed system where the agents or nodes perform complex functions that cannot be written down in analytic form. Multi-Agent Systems are highly connected, and the information they contain is mostly stored in the connections. When agents update their state, they take into account the state of the other agents, and they have access to those states via the connections. There is also external, user-generated input into the Multi-Agent System. As so much information is stored in the connections, agents are often memory-less. This memory-less property, together with the randomness of the external input, has allowed us to model Multi-Agent Systems using Markov chains. In this paper, we look at Multi-Agent Systems that evolve, i.e. the number of agents varies according to the fitness of the individual agents. We extend our Markov chain model, and define stability. This is the start of a methodology to control Multi-Agent Systems. We then build upon this to construct an entropy-based definition for the degree of instability (entropy of the limit probabilities), which we used to perform a stability analysis. We then investigated the stability of evolving agent populations through simulation, and show that the results are consistent with the original definition of stability in non-evolving Multi-Agent Systems, proposed by Chli and De Wilde. This paper forms the theoretical basis for the construction of Digital Business Ecosystems, and applications have been reported elsewhere.


Design of Image Cryptosystem by Simultaneous VQ-Compression and Shuffling of Codebook and Index Matrix

Abstract: The popularity of Internet usage although increases exponentially, it is incapable of providing the security for exchange of confidential data between the users. As a result, several cryptosystems for encryption of data and images have been developed for secured transmission over Internet. In this work, a scheme for Image encryption/decryption based on Vector Quantization (VQ) has been proposed that concurrently encodes the images for compression and shuffles the codebook and the index matrix using pseudorandom sequences for encryption. The processing time of the proposed scheme is much less than the other cryptosystems, because it does not use any traditional cryptographic operations, and instead it performs swapping between the contents of the codebook with respect to a random sequence, which resulted an indirect shuffling of the contents of the index matrix. It may be noted that the security of the proposed cryptosystem depends on the generation and the exchange of the random sequences used. Since the generation of truly random sequences are not practically feasible, we simulate the proposed scheme using MATLAB, where its operators like rand(method, seed), randperm(n) has been used to generate pseudorandom sequences and it has been seen that the proposed cryptosystem shows the expected performance.


Correlation Decay up to Uniqueness in Spin Systems

Abstract: We give a complete characterization of the two-state anti-ferromagnetic spin systems which are of strong spatial mixing on general graphs. We show that a two-state anti-ferromagnetic spin system is of strong spatial mixing on all graphs of maximum degree at most $\Delta$ if and only if the system has a unique Gibbs measure on infinite regular trees of degree up to $\Delta$, where $\Delta$ can be either bounded or unbounded. As a consequence, there exists an FPTAS for the partition function of a two-state anti-ferromagnetic spin system on graphs of maximum degree at most $\Delta$ when the uniqueness condition is satisfied on infinite regular trees of degree up to $\Delta$. In particular, an FPTAS exists for arbitrary graphs if the uniqueness is satisfied on all infinite regular trees. This covers as special cases all previous algorithmic results for two-state anti-ferromagnetic systems on general-structure graphs. Combining with the FPRAS for two-state ferromagnetic spin systems of Jerrum-Sinclair and Goldberg-Jerrum-Paterson, and the hardness results of Sly-Sun and independently of Galanis-Stefankovic-Vigoda, this gives a complete classification, except at the phase transition boundary, of the approximability of all two-state spin systems, on either degree-bounded families of graphs or family of all graphs.


Non-cooperative Feedback Rate Control Game for Channel State Information in Wireless Networks

Abstract: It has been well recognized that channel state information (CSI) feedback is of great importance for dowlink transmissions of closed-loop wireless networks. However, the existing work typically researched the CSI feedback problem for each individual mobile station (MS), and thus, cannot efficiently model the interactions among self-interested mobile users in the network level. To this end, in this paper, we propose an alternative approach to investigate the CSI feedback rate control problem in the analytical setting of a game theoretic framework, in which a multiple-antenna base station (BS) communicates with a number of co-channel MSs through linear precoder. Specifically, we first present a non-cooperative feedback-rate control game (NFC), in which each MS selects the feedback rate to maximize its performance in a distributed way. To improve efficiency from a social optimum point of view, we then introduce pricing, called the non-cooperative feedback-rate control game with price (NFCP). The game utility is defined as the performance gain by CSI feedback minus the price as a linear function of the CSI feedback rate. The existence of the Nash equilibrium of such games is investigated, and two types of feedback protocols (FDMA and CSMA) are studied. Simulation results show that by adjusting the pricing factor, the distributed NFCP game results in close optimal performance compared with that of the centralized scheme.


PARIS: Probabilistic Alignment of Relations, Instances, and Schema

Abstract: One of the main challenges that the Semantic Web faces is the integration of a growing number of independently designed ontologies. In this work, we present PARIS, an approach for the automatic alignment of ontologies. PARIS aligns not only instances, but also relations and classes. Alignments at the instance level cross-fertilize with alignments at the schema level. Thereby, our system provides a truly holistic solution to the problem of ontology alignment. The heart of the approach is probabilistic, i.e., we measure degrees of matchings based on probability estimates. This allows PARIS to run without any parameter tuning. We demonstrate the efficiency of the algorithm and its precision through extensive experiments. In particular, we obtain a precision of around 90% in experiments with some of the world's largest ontologies.


Answering Top-k Queries Over a Mixture of Attractive and Repulsive Dimensions

Abstract: In this paper, we formulate a top-k query that compares objects in a database to a user-provided query object on a novel scoring function. The proposed scoring function combines the idea of attractive and repulsive dimensions into a general framework to overcome the weakness of traditional distance or similarity measures. We study the properties of the proposed class of scoring functions and develop efficient and scalable index structures that index the isolines of the function. We demonstrate various scenarios where the query finds application. Empirical evaluation demonstrates a performance gain of one to two orders of magnitude on querying time over existing state-of-the-art top-k techniques. Further, a qualitative analysis is performed on a real dataset to highlight the potential of the proposed query in discovering hidden data characteristics.


PIQL: Success-Tolerant Query Processing in the Cloud

Abstract: Newly-released web applications often succumb to a "Success Disaster," where overloaded database machines and resulting high response times destroy a previously good user experience. Unfortunately, the data independence provided by a traditional relational database system, while useful for agile development, only exacerbates the problem by hiding potentially expensive queries under simple declarative expressions. As a result, developers of these applications are increasingly abandoning relational databases in favor of imperative code written against distributed key/value stores, losing the many benefits of data independence in the process. Instead, we propose PIQL, a declarative language that also provides scale independence by calculating an upper bound on the number of key/value store operations that will be performed for any query. Coupled with a service level objective (SLO) compliance prediction model and PIQL's scalable database architecture, these bounds make it easy for developers to write success-tolerant applications that support an arbitrarily large number of users while still providing acceptable performance. In this paper, we present the PIQL query processing system and evaluate its scale independence on hundreds of machines using two benchmarks, TPC-W and SCADr.


gSketch: On Query Estimation in Graph Streams

Abstract: Many dynamic applications are built upon large network infrastructures, such as social networks, communication networks, biological networks and the Web. Such applications create data that can be naturally modeled as graph streams, in which edges of the underlying graph are received and updated sequentially in a form of a stream. It is often necessary and important to summarize the behavior of graph streams in order to enable effective query processing. However, the sheer size and dynamic nature of graph streams present an enormous challenge to existing graph management techniques. In this paper, we propose a new graph sketch method, gSketch, which combines well studied synopses for traditional data streams with a sketch partitioning technique, to estimate and optimize the responses to basic queries on graph streams. We consider two different scenarios for query estimation: (1) A graph stream sample is available; (2) Both a graph stream sample and a query workload sample are available. Algorithms for different scenarios are designed respectively by partitioning a global sketch to a group of localized sketches in order to optimize the query estimation accuracy. We perform extensive experimental studies on both real and synthetic data sets and demonstrate the power and robustness of gSketch in comparison with the state-of-the-art global sketch method.


Indexing the Earth Mover's Distance Using Normal Distributions

Abstract: Querying uncertain data sets (represented as probability distributions) presents many challenges due to the large amount of data involved and the difficulties comparing uncertainty between distributions. The Earth Mover's Distance (EMD) has increasingly been employed to compare uncertain data due to its ability to effectively capture the differences between two distributions. Computing the EMD entails finding a solution to the transportation problem, which is computationally intensive. In this paper, we propose a new lower bound to the EMD and an index structure to significantly improve the performance of EMD based K-nearest neighbor (K-NN) queries on uncertain databases. We propose a new lower bound to the EMD that approximates the EMD on a projection vector. Each distribution is projected onto a vector and approximated by a normal distribution, as well as an accompanying error term. We then represent each normal as a point in a Hough transformed space. We then use the concept of stochastic dominance to implement an efficient index structure in the transformed space. We show that our method significantly decreases K-NN query time on uncertain databases. The index structure also scales well with database cardinality. It is well suited for heterogeneous data sets, helping to keep EMD based queries tractable as uncertain data sets become larger and more complex.


Size-l Object Summaries for Relational Keyword Search

Abstract: A previously proposed keyword search paradigm produces, as a query result, a ranked list of Object Summaries (OSs). An OS is a tree structure of related tuples that summarizes all data held in a relational database about a particular Data Subject (DS). However, some of these OSs are very large in size and therefore unfriendly to users that initially prefer synoptic information before proceeding to more comprehensive information about a particular DS. In this paper, we investigate the effective and efficient retrieval of concise and informative OSs. We argue that a good size-l OS should be a stand-alone and meaningful synopsis of the most important information about the particular DS. More precisely, we define a size-l OS as a partial OS composed of l important tuples. We propose three algorithms for the efficient generation of size-l OSs (in addition to the optimal approach which requires exponential time). Experimental evaluation on DBLP and TPC-H databases verifies the effectiveness and efficiency of our approach.