OpenRaiser/Intern-Atlas huggingface dataset:
Quantitative Evaluation of Performance and Validity Indices for Clustering the Web Navigational Sessions
Venue: arXiv cs.LG 2015
Year: 2015

Clustering techniques are widely used in Web Usage Mining to capture similar interests and trends among users accessing a Web site. For this purpose, web access logs generated at a particular web site are preprocessed to discover the user navigational sessions. Clustering techniques are then applied to group the user session data into user session clusters, where intercluster similarities are minimized while the intra cluster similarities are maximized. Since the application of different clustering algorithms generally results in different sets of cluster formation, it is important to evaluate the performance of these methods in terms of accuracy and validity of the clusters, and also the time required to generate them, using appropriate performance measures. This paper describes various validity and accuracy measures including Dunn's Index, Davies Bouldin Index, C Index, Rand Index, Jaccard Index, Silhouette Index, Fowlkes Mallows and Sum of the Squared Error (SSE). We conducted the performance evaluation of the following clustering techniques: k-Means, k-Medoids, Leader, Single Link Agglomerative Hierarchical and DBSCAN. These techniques are implemented and tested against the Web user navigational data. Finally their performance results are presented and compared.
Cyber-physical Control of Road Freight Transport
Venue: arXiv cs.SY 2015
Year: 2015

Freight transportation is of outmost importance for our society and is continuously increasing. At the same time, transporting goods on roads accounts for about 26% of all energy consumption and 18% of all greenhouse gas emissions in the European Union. Despite the influence the transportation system has on our energy consumption and the environment, road transportation is mainly done by individual long-haulage trucks with no real-time coordination or global optimization. In this paper, we review how modern information and communication technology supports a cyber-physical transportation system architecture with an integrated logistic system coordinating fleets of trucks traveling together in vehicle platoons. From the reduced air drag, platooning trucks traveling close together can save about 10% of their fuel consumption. Utilizing road grade information and vehicle-to-vehicle communication, a safe and fuel-optimized cooperative look-ahead control strategy is implemented on top of the existing cruise controller. By optimizing the interaction between vehicles and platoons of vehicles, it is shown that significant improvements can be achieved. An integrated transport planning and vehicle routing in the fleet management system allows both small and large fleet owners to benefit from the collaboration. A realistic case study with 200 heavy-duty vehicles performing transportation tasks in Sweden is described. Simulations show overall fuel savings at more than 5% thanks to coordinated platoon planning. It is also illustrated how well the proposed cooperative look-ahead controller for heavy-duty vehicle platoons manages to optimize the velocity profiles of the vehicles over a hilly segment of the considered road network.
Mechanically Verified Calculational Abstract Interpretation
Venue: arXiv cs.PL 2015
Year: 2015

Calculational abstract interpretation, long advocated by Cousot, is a technique for deriving correct-by-construction abstract interpreters from the formal semantics of programming languages. This paper addresses the problem of deriving correct-by-verified-construction abstract interpreters with the use of a proof assistant. We identify several technical challenges to overcome with the aim of supporting verified calculational abstract interpretation that is faithful to existing pencil-and-paper proofs, supports calculation with Galois connections generally, and enables the extraction of verified static analyzers from these proofs. To meet these challenges, we develop a theory of Galois connections in monadic style that include a specification effect. Effectful calculations may reason classically, while pure calculations have extractable computational content. Moving between the worlds of specification and implementation is enabled by our metatheory. To validate our approach, we give the first mechanically verified proof of correctness for Cousot's "Calculational design of a generic abstract interpreter." Our proof "by calculus" closely follows the original paper-and-pencil proof and supports the extraction of a verified static analyzer.
ARG: Virtual Tool to Teaching Argumentation Theory
Venue: arXiv cs.CY 2015
Year: 2015

Researchers look for new virtual instruments that can improve and maximize traditional forms of teaching and learning. In this paper, we present the ARG system, a virtual tool developed to help the teaching/learning process in argumentation theory, especially in the field of Law. ARG was developed based on Araucaria by Reed and Rowe, Room 5 by Ronald P. Loui, as well on systems such as Argue!-System and ArguMed by Bart Verheij. ARG is a platform for online collaboration and applies the theory of Stephen Toulmin to produce arguments that are more concise, precise, minimally structured and more resistant to criticism.
Euler diagrams as an introduction to set-theoretical models
Venue: arXiv cs.CY 2015
Year: 2015

Understanding the notion of a model is not always easy in logic courses. Hence, tools such as Euler diagrams are frequently applied as informal illustrations of set-theoretical models. We formally investigate Euler diagrams as an introduction to set-theoretical models. We show that the model-theoretic notions of validity and invalidity are characterized by Euler diagrams, and, in particular, that model construction can be described as a manipulation of Euler diagrams.
TryLogic tutorial: an approach to Learning Logic by proving and refuting
Venue: arXiv cs.CY 2015
Year: 2015

Aiming to offer a framework for blended learning to the teaching of proof theory, the present paper describes an interactive tutorial, called \textsc{TryLogic}, teaching how to solve logical conjectures either by proofs or refutations. The paper also describes the integration of our infrastructure with the Virtual Learning Environment \texttt{Moodle} through the IMS Learning Tools Interoperability specification, and evaluates the tool we have developed.
Logic Modelling
Venue: arXiv cs.CY 2015
Year: 2015

This is a reflection on the author's experience in teaching logic at the graduate level in a computer science department. The main lesson is that model building and the process of modelling must be placed at the centre stage of logic teaching. Furthermore, effective use must be supported with adequate tools. Finally, logic is the methodology underlying many applications, it is hence paramount to pass on its principles, methods and concepts to computer science audiences.
Teaching Logic to Information Systems Students: Challenges and Opportunities
Venue: arXiv cs.CY 2015
Year: 2015

In contrast to Computer Science, where the fundamental role of Logic is widely recognized, it plays a practically non-existent role in Information Systems curricula. In this paper we argue that instead of Logic's exclusion from the IS curriculum, a significant adaptation of the contents, as well as teaching methodologies, is required for an alignment with the needs of IS practitioners. We present our vision for such adaptation and report on concrete steps towards its implementation in the design and teaching of a course for graduate IS students at the University of Haifa. We discuss the course plan and present some data on the students' feedback on the course.
A New Method for Triangular Mesh Generation
Venue: arXiv cs.CG 2015
Year: 2015

Computational mathematics plays an increasingly important role in computational fluid dynamics (CFD). The aeronautics and aerospace re- search community is working on next generation of CFD capacity that is accurate, automatic, and fast. A key component of the next generation of CFD is a greatly enhanced capacity for mesh generation and adaptivity of the mesh according to solution and geometry. In this paper, we propose a new method that generates triangular meshes on domains of curved boundary. The method deforms a Cartesian mesh that covers the domain to generate a mesh with prescribed boundary nodes. The deformation fields are generated by a system of divergence and curl equations which are solved effectively by the least square finite element method.
Projected Wirtinger Gradient Descent for Low-Rank Hankel Matrix Completion in Spectral Compressed Sensing
Venue: arXiv cs.IT 2015
Year: 2015

This paper considers reconstructing a spectrally sparse signal from a small number of randomly observed time-domain samples. The signal of interest is a linear combination of complex sinusoids at $R$ distinct frequencies. The frequencies can assume any continuous values in the normalized frequency domain $[0,1)$. After converting the spectrally sparse signal recovery into a low rank structured matrix completion problem, we propose an efficient feasible point approach, named projected Wirtinger gradient descent (PWGD) algorithm, to efficiently solve this structured matrix completion problem. We further accelerate our proposed algorithm by a scheme inspired by FISTA. We give the convergence analysis of our proposed algorithms. Extensive numerical experiments are provided to illustrate the efficiency of our proposed algorithm. Different from earlier approaches, our algorithm can solve problems of very large dimensions very efficiently.
Computational Capacity and Energy Consumption of Complex Resistive Switch Networks
Venue: arXiv cs.ET 2015
Year: 2015

Resistive switches are a class of emerging nanoelectronics devices that exhibit a wide variety of switching characteristics closely resembling behaviors of biological synapses. Assembled into random networks, such resistive switches produce emerging behaviors far more complex than that of individual devices. This was previously demonstrated in simulations that exploit information processing within these random networks to solve tasks that require nonlinear computation as well as memory. Physical assemblies of such networks manifest complex spatial structures and basic processing capabilities often related to biologically-inspired computing. We model and simulate random resistive switch networks and analyze their computational capacities. We provide a detailed discussion of the relevant design parameters and establish the link to the physical assemblies by relating the modeling parameters to physical parameters. More globally connected networks and an increased network switching activity are means to increase the computational capacity linearly at the expense of exponentially growing energy consumption. We discuss a new modular approach that exhibits higher computational capacities and energy consumption growing linearly with the number of networks used. The results show how to optimize the trade-off between computational capacity and energy efficiency and are relevant for the design and fabrication of novel computing architectures that harness random assemblies of emerging nanodevices.
Optimization of Code Rates in SISOME Wiretap Channels
Venue: arXiv cs.IT 2015
Year: 2015

We propose a new framework for determining the wiretap code rates of single-input single-output multi-antenna eavesdropper (SISOME) wiretap channels when the capacity of the eavesdropper's channel is not available at the transmitter. In our framework we introduce the effective secrecy throughput (EST) as a new performance metric that explicitly captures the two key features of wiretap channels, namely, reliability and secrecy. Notably, the EST measures the average rate of the confidential information transmitted from the transmitter to the intended receiver without being eavesdropped on. We provide easy-to-implement methods to determine the wiretap code rates for two transmission schemes: 1) adaptive transmission scheme in which the capacity of the main channel is available at the transmitter and 2) fixed-rate transmission scheme in which the capacity of the main channel is not available at the transmitter. Such determinations are further extended into an absolute-passive eavesdropping scenario where even the average signal-to-noise ratio of the eavesdropper's channel is not available at the transmitter. Notably, our solutions for the wiretap code rates do not require us to set reliability or secrecy constraints for the transmission within wiretap channels.
Tight Bounds for Subgraph Isomorphism and Graph Homomorphism
Venue: arXiv cs.DS 2015
Year: 2015

We prove that unless Exponential Time Hypothesis (ETH) fails, deciding if there is a homomorphism from graph $G$ to graph $H$ cannot be done in time $|V(H)|^{o(|V(G)|)}$. Combined with the reduction of Cygan, Pachocki, and Socała, our result rules out (subject to ETH) a possibility of $|V(G)|^{o(|V(G)|)}$-time algorithm deciding if graph $H$ is a subgraph of $G$. For both problems our lower bounds asymptotically match the running time of brute-force algorithms trying all possible mappings of one graph into another. Thus, our work closes the gap in the known complexity of these fundamental problems.
Contention-based Geographic Forwarding Strategies for Wireless Sensors Networks
Venue: arXiv cs.IT 2015
Year: 2015

This paper studies combined relay selection and opportunistic geographic routing strategies for autonomous wireless sensor networks where transmissions occur over multiple hops. The proposed solution is built upon three constituent parts: (i) relay selection algorithm, (ii) contention resolution mechanism, and (iii) geographic forwarding strategy. Using probability generating function and spatial point process as the theoretic background, we propose an auction-based algorithm for selecting the relay node that relies on the network topology as side-information. Our results show that geographic solutions that iteratively exploit the local knowledge of the topology to ponder the algorithm operation outperforms established random approaches.
Pilot Clustering in Asymmetric Massive MIMO Networks
Venue: arXiv cs.IT 2015
Year: 2015

We consider the uplink of a cellular massive MIMO network. Since the spectral efficiency of these networks is limited by pilot contamination, the pilot allocation across cells is of paramount importance. However, finding efficient pilot reuse patterns is non-trivial especially in practical asymmetric base station deployments. In this paper, we approach this problem using coalitional game theory. Each cell has its own unique pilots and can form coalitions with other cells to gain access to more pilots. We develop a low-complexity distributed algorithm and prove convergence to an individually stable coalition structure. Simulations reveal fast algorithmic convergence and substantial performance gains over one-cell coalitions and full pilot reuse.
Rewriting recursive aggregates in answer set programming: back to monotonicity
Venue: arXiv cs.AI 2015
Year: 2015

Aggregation functions are widely used in answer set programming for representing and reasoning on knowledge involving sets of objects collectively. Current implementations simplify the structure of programs in order to optimize the overall performance. In particular, aggregates are rewritten into simpler forms known as monotone aggregates. Since the evaluation of normal programs with monotone aggregates is in general on a lower complexity level than the evaluation of normal programs with arbitrary aggregates, any faithful translation function must introduce disjunction in rule heads in some cases. However, no function of this kind is known. The paper closes this gap by introducing a polynomial, faithful, and modular translation for rewriting common aggregation functions into the simpler form accepted by current solvers. A prototype system allows for experimenting with arbitrary recursive aggregates, which are also supported in the recent version 4.5 of the grounder \textsc{gringo}, using the methods presented in this paper. To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 2015.
Hyper Heterogeneous Cloud-based IMS Software Architecture: A Proof-of-Concept and Empirical Analysis
Venue: arXiv cs.DC 2015
Year: 2015

The IP Multimedia Subsystem (IMS) defined by the 3GPP has been mainly developed and deployed by telephony vendors on vendor-specific hardware. Recent advances in Network Function Virtualisation (NFV) technology paved the way for virtualized hardware and telephony function elasticity. As such, Telecom vendors have started to embrace the cloud as a deployment platform, usually selecting a privileged virtualization platform. Operators would like to deploy telecom functionality on their already existing IT cloud platforms. Achieving such flexibility would require the telecom vendors to adopt a software architecture allowing deployment on many cloud platforms or even heterogeneous cloud platforms. We propose a distributed software architecture enabling the deployment of a single software version on multiple cloud platforms thus allowing for a solution-based deployment. We also present a prototype we developed to study the characteristics of this architecture.
Unsupervised Decision Forest for Data Clustering and Density Estimation
Venue: arXiv cs.CV 2015
Year: 2015

An algorithm to improve performance parameter for unsupervised decision forest clustering and density estimation is presented. Specifically, a dual assignment parameter is introduced as a density estimator by combining Random Forest and Gaussian Mixture Model. The Random Forest method has been specifically applied to construct a robust affinity graph that provides information on the underlying structure of data objects used in clustering. The proposed algorithm differs from the commonly used spectral clustering methods where the computed distance metric is used to find similarities between data points. Experiments were conducted using five datasets. A comparison with six other state-of-the-art methods shows that our model is superior to existing approaches. Efficiency of the proposed model is in capturing the underlying structure for a given set of data points. The proposed method is also robust, and can discriminate between the complex features of data points among different clusters.
False shares in verifiable secret sharing with finite field commitments
Venue: arXiv cs.CR 2015
Year: 2015

Verifiable secret sharing (VSS) is designed to allow parties to collaborate to keep secrets. We describe here a method of fabricating false secret shares that appear to other parties to be legitimate, which can prevent assembly of the decryption key. This vulnerability affects VSS schemes using verification commitments bounded to a finite field.
Evidential relational clustering using medoids
Venue: arXiv cs.AI 2015
Year: 2015

In real clustering applications, proximity data, in which only pairwise similarities or dissimilarities are known, is more general than object data, in which each pattern is described explicitly by a list of attributes. Medoid-based clustering algorithms, which assume the prototypes of classes are objects, are of great value for partitioning relational data sets. In this paper a new prototype-based clustering method, named Evidential C-Medoids (ECMdd), which is an extension of Fuzzy C-Medoids (FCMdd) on the theoretical framework of belief functions is proposed. In ECMdd, medoids are utilized as the prototypes to represent the detected classes, including specific classes and imprecise classes. Specific classes are for the data which are distinctly far from the prototypes of other classes, while imprecise classes accept the objects that may be close to the prototypes of more than one class. This soft decision mechanism could make the clustering results more cautious and reduce the misclassification rates. Experiments in synthetic and real data sets are used to illustrate the performance of ECMdd. The results show that ECMdd could capture well the uncertainty in the internal data structure. Moreover, it is more robust to the initializations compared with FCMdd.
Stream Verification
Venue: arXiv cs.DS 2015
Year: 2015

We survey models and algorithms for stream verification.
Combinatorial Cascading Bandits
Venue: arXiv cs.LG 2015
Year: 2015

We propose combinatorial cascading bandits, a class of partial monitoring problems where at each step a learning agent chooses a tuple of ground items subject to constraints and receives a reward if and only if the weights of all chosen items are one. The weights of the items are binary, stochastic, and drawn independently of each other. The agent observes the index of the first chosen item whose weight is zero. This observation model arises in network routing, for instance, where the learning agent may only observe the first link in the routing path which is down, and blocks the path. We propose a UCB-like algorithm for solving our problems, CombCascade; and prove gap-dependent and gap-free upper bounds on its $n$-step regret. Our proofs build on recent work in stochastic combinatorial semi-bandits but also address two novel challenges of our setting, a non-linear reward function and partial observability. We evaluate CombCascade on two real-world problems and show that it performs well even when our modeling assumptions are violated. We also demonstrate that our setting requires a new learning algorithm.
IP Over ICN - The Better IP? An Unusual Take on Information-Centric Networking
Venue: arXiv cs.NI 2015
Year: 2015

This paper presents a proposition for informationcentric networking (ICN) that lies outside the typical trajectory of aiming for a wholesale replacement of IP as the internetworking layer of the Internet. Instead, we propose that a careful exploitation of key ICN benefits, expanding previously funded ICN efforts, will enable individual operators to improve the performance of their IP-based services along many dimensions. Alongside the main motivation for our work, we present an early strawman architecture for such an IP-over-ICN proposition, which will ultimately be implemented and trialed in a recently started H2020 research effort.
A bi-criteria approximation algorithm for $k$ Means
Venue: arXiv cs.DS 2015
Year: 2015

We consider the classical $k$-means clustering problem in the setting bi-criteria approximation, in which an algoithm is allowed to output $βk > k$ clusters, and must produce a clustering with cost at most $α$ times the to the cost of the optimal set of $k$ clusters. We argue that this approach is natural in many settings, for which the exact number of clusters is a priori unknown, or unimportant up to a constant factor. We give new bi-criteria approximation algorithms, based on linear programming and local search, respectively, which attain a guarantee $α(β)$ depending on the number $βk$ of clusters that may be opened. Our gurantee $α(β)$ is always at most $9 + ε$ and improves rapidly with $β$ (for example: $α(2)<2.59$, and $α(3) < 1.4$). Moreover, our algorithms have only polynomial dependence on the dimension of the input data, and so are applicable in high-dimensional settings.
Resistance against brute-force attacks on stateless forwarding in information centric networking
Venue: arXiv cs.NI 2015
Year: 2015

Line Speed Publish/Subscribe Inter-networking (LIPSIN) is one of the proposed forwarding mechanisms in Information Centric Networking (ICN). It is a stateless source-routing approach based on Bloom filters. However, it has been shown that LIPSIN is vulnerable to brute-force attacks which may lead to distributed denial-of-service (DDoS) attacks and unsolicited messages. In this work, we propose a new forwarding approach that maintains the advantages of Bloom filter based forwarding while allowing forwarding nodes to statelessly verify if packets have been previously authorized, thus preventing attacks on the forwarding mechanism. Analysis of the probability of attack, derived analytically, demonstrates that the technique is highly-resistant to brute-force attacks.