OpenRaiser/Intern-Atlas huggingface dataset:
Asymmetric Distributed Constraint Optimization Problems
Venue: arXiv cs.AI 2014
Year: 2014

Distributed Constraint Optimization (DCOP) is a powerful framework for representing and solving distributed combinatorial problems, where the variables of the problem are owned by different agents. Many multi-agent problems include constraints that produce different gains (or costs) for the participating agents. Asymmetric gains of constrained agents cannot be naturally represented by the standard DCOP model. The present paper proposes a general framework for Asymmetric DCOPs (ADCOPs). In ADCOPs different agents may have different valuations for constraints that they are involved in. The new framework bridges the gap between multi-agent problems which tend to have asymmetric structure and the standard symmetric DCOP model. The benefits of the proposed model over previous attempts to generalize the DCOP model are discussed and evaluated. Innovative algorithms that apply to the special properties of the proposed ADCOP model are presented in detail. These include complete algorithms that have a substantial advantage in terms of runtime and network load over existing algorithms (for standard DCOPs) which use alternative representations. Moreover, standard incomplete algorithms (i.e., local search algorithms) are inapplicable to the existing DCOP representations of asymmetric constraints and when they are applied to the new ADCOP framework they often fail to converge to a local optimum and yield poor results. The local search algorithms proposed in the present paper converge to high quality solutions. The experimental evidence that is presented reveals that the proposed local search algorithms for ADCOPs achieve high quality solutions while preserving a high level of privacy.
Controlling Citizens Cyber Viewing Using Enhanced Internet Content Filters
Venue: arXiv cs.CY 2014
Year: 2014

Information passing through internet is generally unrestricted and uncontrollable and a good web content filter acts very much like a sieve. This paper looks at how citizens internet viewing can be controlled using content filters to prevent access to illegal sites and malicious contents in Nigeria. Primary data were obtained by administering 100 questionnaires. The data was analyzed by a software package called Statistical Package for Social Sciences (SPSS). The result of the study shows that 66.4% of the respondents agreed that the internet is been abused and the abuse can be controlled by the use of content filters. The PHP, MySQL and Apache were used to design a content filter program. It was recommended that a lot still need to be done by public organizations, academic institutions, government and its agencies especially the Economic and Financial Crime Commission (EFCC) in Nigeria to control the internet abuse by the under aged and criminals.
Robotic manipulation of multiple objects as a POMDP
Venue: arXiv cs.RO 2014
Year: 2014

This paper investigates manipulation of multiple unknown objects in a crowded environment. Because of incomplete knowledge due to unknown objects and occlusions in visual observations, object observations are imperfect and action success is uncertain, making planning challenging. We model the problem as a partially observable Markov decision process (POMDP), which allows a general reward based optimization objective and takes uncertainty in temporal evolution and partial observations into account. In addition to occlusion dependent observation and action success probabilities, our POMDP model also automatically adapts object specific action success probabilities. To cope with the changing system dynamics and performance constraints, we present a new online POMDP method based on particle filtering that produces compact policies. The approach is validated both in simulation and in physical experiments in a scenario of moving dirty dishes into a dishwasher. The results indicate that: 1) a greedy heuristic manipulation approach is not sufficient, multi-object manipulation requires multi-step POMDP planning, and 2) on-line planning is beneficial since it allows the adaptation of the system dynamics model based on actual experience.
Loop Unrolling in Multi-pipeline ASIP Design
Venue: arXiv cs.PL 2014
Year: 2014

Application Specific Instruction-set Processor (ASIP) is one of the popular processor design techniques for embedded systems which allows customizability in processor design without overly hindering design flexibility. Multi-pipeline ASIPs were proposed to improve the performance of such systems by compromising between speed and processor area. One of the problems in the multi-pipeline design is the limited inherent instruction level parallelism (ILP) available in applications. The ILP of application programs can be improved via a compiler optimization technique known as loop unrolling. In this paper, we present how loop unrolling effects the performance of multi-pipeline ASIPs. The improvements in performance average around 15% for a number of benchmark applications with the maximum improvement of around 30%. In addition, we analyzed the variable of performance against loop unrolling factor, which is the amount of unrolling we perform.
On-Demand Grid Provisioning Using Cloud Infrastructures and Related Virtualization Tools: A Survey and Taxonomy
Venue: arXiv cs.DC 2014
Year: 2014

Recent researches have shown that grid resources can be accessed by client on-demand, with the help of virtualization technology in the Cloud. The virtual machines hosted by the hypervisors are being utilized to build the grid network within the cloud environment. The aim of this study is to survey some concepts used for the on-demand grid provisioning using Infrastructure as a Service Cloud and the taxonomy of its related components. This paper, discusses the different approaches for on-demand grid using infrastructural Cloud, the issues it tries to address and the implementation tools. The paper also, proposed an extended classification for the virtualization technology used and a new classification for the Grid-Cloud integration which was based on the architecture, communication flow and the user demand for the Grid resources. This survey, tools and taxonomies presented here will contribute as a guide in the design of future architectures for further researches.
Stability and Performance Issues of a Relay Assisted Multiple Access Scheme with MPR Capabilities
Venue: arXiv cs.IT 2014
Year: 2014

In this work, we study the impact of a relay node to a network with a finite number of users-sources and a destination node. We assume that the users have saturated queues and the relay node does not have packets of its own; we have random access of the medium and the time is slotted. The relay node stores a source packet that it receives successfully in its queue when the transmission to the destination node has failed. The relay and the destination nodes have multi-packet reception capabilities. We obtain analytical equations for the characteristics of the relay's queue such as average queue length, stability conditions etc. We also study the throughput per user and the aggregate throughput for the network.
Graphic-theoretic distributed inference in social networks
Venue: arXiv cs.SI 2014
Year: 2014

We consider distributed inference in social networks where a phenomenon of interest evolves over a given social interaction graph, referred to as the \emph{social digraph}. For inference, we assume that a network of agents monitors certain nodes in the social digraph and no agent may be able to perform inference within its neighborhood; the agents must rely on inter-agent communication. The key contributions of this paper include: (i) a novel construction of the distributed estimator and distributed observability from the first principles; (ii) a graph-theoretic agent classification that establishes the importance and role of each agent towards inference; (iii) characterizing the necessary conditions, based on the classification in (ii), on the agent network to achieve distributed observability. Our results are based on structured systems theory and are applicable to any parameter choice of the underlying system matrix as long as the social digraph remains fixed. In other words, any social phenomena that evolves (linearly) over a structure-invariant social digraph may be considered--we refer to such systems as Liner Structure-Invariant (LSI). The aforementioned contributions, (i)--(iii), thus, only require the knowledge of the social digraph (topology) and are independent of the social phenomena. We show the applicability of the results to several real-wold social networks, i.e. social influence among monks, networks of political blogs and books, and a co-authorship graph.
A Survey on Factors Affecting Iran's Fuel Rationing Smart Card User Acceptance and Security
Venue: arXiv cs.CY 2014
Year: 2014

Smart card technology has resulted in vast developments in many aspects of modern human life. User acceptance of fuel rationing smart cards based on adoption model involves many factors such as: satisfaction, security, external variables, attitude toward using, etc. In this study, user acceptance and security factors for fuel rationing smart cards in Iran have been evaluated based on an adoption model by distributing a questionnaire among UTM (University Technology Malaysia) Iranian students, MMU (Multimedia University) Iranian students, either asking by e-mail from people who are not available.
User-Sensitive Mobile Interfaces: Accounting for Individual Differences amongst the Blind
Venue: arXiv cs.HC 2014
Year: 2014

Mobile phones pervade our daily lives and play ever expanding roles in many contexts. Their ubiquitousness makes them pivotal in empowering disabled people. However, if no inclusive approaches are provided, it becomes a strong vehicle of exclusion. Even though current solutions try to compensate for the lack of sight, not all information reaches the blind user. Good spatial ability is still required to make sense of the device and its interface, as well as the need to memorize positions on screen or keys and associated actions in a keypad. Those problems are compounded by many individual attributes such as age, age of blindness onset or tactile sensitivity which often are forgotten by designers. Worse, the entire blind population is recurrently thought of as homogeneous (often stereotypically so). Thus all users face the same solutions, ignoring their specific capabilities and needs. We usually ignore this diversity as we have the ability to adapt and become experts in interfaces that were probably maladjusted to begin with. This adaptation is not always within reach. Interaction with mobile devices is highly visually demanding which widens this gap amongst blind people. It is paramount to understand the impact of individual differences and their relationship with demands to enable the deployment of more inclusive solutions. We explore individual differences among blind people and assess how they are related with mobile interface demands, both at low (e.g. performing an on-screen gesture) and high level (text-entry) tasks. Results confirmed that different ability levels have significant impact on the performance attained by a blind person. Particularly, otherwise ignored attributes like tactile acuity, pressure sensitivity, spatial ability or verbal IQ have shown to be matched with specific mobile demands and parametrizations.
Compressive Diffusion Strategies Over Distributed Networks for Reduced Communication Load
Venue: arXiv cs.SY 2014
Year: 2014

We study the compressive diffusion strategies over distributed networks based on the diffusion implementation and adaptive extraction of the information from the compressed diffusion data. We demonstrate that one can achieve a comparable performance with the full information exchange configurations, even if the diffused information is compressed into a scalar or a single bit. To this end, we provide a complete performance analysis for the compressive diffusion strategies. We analyze the transient, steady-state and tracking performance of the configurations in which the diffused data is compressed into a scalar or a single-bit. We propose a new adaptive combination method improving the convergence performance of the compressive diffusion strategies further. In the new method, we introduce one more freedom-of-dimension in the combination matrix and adapt it by using the conventional mixture approach in order to enhance the convergence performance for any possible combination rule used for the full diffusion configuration. We demonstrate that our theoretical analysis closely follow the ensemble averaged results in our simulations. We provide numerical examples showing the improved convergence performance with the new adaptive combination method.
Levels of Abstraction and the Apparent Contradictory Philosophical Legacy of Turing and Shannon
Venue: arXiv cs.GL 2014
Year: 2014

In a recent article, Luciano Floridi explains his view of Turing's legacy in connection to the philosophy of information. I will very briefly survey one of Turing's other contributions to the philosophy of information and computation, including similarities to Shannon's own methodological approach to information through communication, showing how crucial they are and have been as methodological strategies to understanding key aspects of these concepts. While Floridi's concept of Levels of Abstraction is related to the novel methodology of Turing's imitation game for tackling the question of machine intelligence, Turing's other main contribution to the philosophy of information runs contrary to it. Indeed, the seminal concept of computation universality strongly suggests the deletion of fundamental differences among seemingly different levels of description. How might we reconcile these apparently contradictory contributions? I will argue that Turing's contribution should prompt us to plot some directions for a philosophy of information and computation, one that closely parallels the most important developments in computer science, one that understands the profound implications of the works of Turing, Shannon and others.
Long Short-Term Memory Based Recurrent Neural Network Architectures for Large Vocabulary Speech Recognition
Venue: arXiv cs.NE 2014
Year: 2014

Long Short-Term Memory (LSTM) is a recurrent neural network (RNN) architecture that has been designed to address the vanishing and exploding gradient problems of conventional RNNs. Unlike feedforward neural networks, RNNs have cyclic connections making them powerful for modeling sequences. They have been successfully used for sequence labeling and sequence prediction tasks, such as handwriting recognition, language modeling, phonetic labeling of acoustic frames. However, in contrast to the deep neural networks, the use of RNNs in speech recognition has been limited to phone recognition in small scale tasks. In this paper, we present novel LSTM based RNN architectures which make more effective use of model parameters to train acoustic models for large vocabulary speech recognition. We train and compare LSTM, RNN and DNN models at various numbers of parameters and configurations. We show that LSTM models converge quickly and give state of the art speech recognition performance for relatively small sized models.
Compressing IP Forwarding Tables: Towards Entropy Bounds and Beyond
Venue: arXiv cs.DS 2014
Year: 2014

Lately, there has been an upsurge of interest in compressed data structures, aiming to pack ever larger quantities of information into constrained memory without sacrificing the efficiency of standard operations, like random access, search, or update. The main goal of this paper is to demonstrate how data compression can benefit the networking community, by showing how to squeeze the IP Forwarding Information Base (FIB), the giant table consulted by IP routers to make forwarding decisions, into information-theoretical entropy bounds, with essentially zero cost on longest prefix match and FIB update. First, we adopt the state-of-the-art in compressed data structures, yielding a static entropy-compressed FIB representation with asymptotically optimal lookup. Then, we re-design the venerable prefix tree, used commonly for IP lookup for at least 20 years in IP routers, to also admit entropy bounds and support lookup in optimal time and update in nearly optimal time. Evaluations on a Linux kernel prototype indicate that our compressors encode a FIB comprising more than 440K prefixes to just about 100--400 KBytes of memory, with a threefold increase in lookup throughput and no penalty on FIB updates. This technical report contains a number of important corrections and revisions to the original manuscript.
TouchIn: Sightless Two-factor Authentication on Multi-touch Mobile Devices
Venue: arXiv cs.CR 2014
Year: 2014

Mobile authentication is indispensable for preventing unauthorized access to multi-touch mobile devices. Existing mobile authentication techniques are often cumbersome to use and also vulnerable to shoulder-surfing and smudge attacks. This paper focuses on designing, implementing, and evaluating TouchIn, a two-factor authentication system on multi-touch mobile devices. TouchIn works by letting a user draw on the touchscreen with one or multiple fingers to unlock his mobile device, and the user is authenticated based on the geometric properties of his drawn curves as well as his behavioral and physiological characteristics. TouchIn allows the user to draw on arbitrary regions on the touchscreen without looking at it. This nice sightless feature makes TouchIn very easy to use and also robust to shoulder-surfing and smudge attacks. Comprehensive experiments on Android devices confirm the high security and usability of TouchIn.
Constructing Performance Models for Dense Linear Algebra Algorithms on Cray XE Systems
Venue: arXiv cs.DC 2014
Year: 2014

Hiding or minimizing the communication cost is key in order to obtain good performance on large-scale systems. While communication overlapping attempts to hide communications cost, 2.5D communication avoiding algorithms improve performance scalability by reducing the volume of data transfers at the cost of extra memory usage. Both approaches can be used together or separately and the best choice depends on the machine, the algorithm and the problem size. Thus, the development of performance models is crucial to determine the best option for each scenario. In this paper, we present a methodology for constructing performance models for parallel numerical routines on Cray XE systems. Our models use portable benchmarks that measure computational cost and network characteristics, as well as performance degradation caused by simultaneous accesses to the network. We validate our methodology by constructing the performance models for the 2D and 2.5D approaches, with and without overlapping, of two matrix multiplication algorithms (Cannon's and SUMMA), triangular solve (TRSM) and Cholesky. We compare the estimations provided by these models with the experimental results using up to 24,576 cores of a Cray XE6 system and predict the performance of the algorithms on larger systems. Results prove that the estimations significantly improve when taking into account network contention.
Tracking via Motion Estimation with Physically Motivated Inter-Region Constraints
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, we propose a method for tracking structures (e.g., ventricles and myocardium) in cardiac images (e.g., magnetic resonance) by propagating forward in time a previous estimate of the structures via a new deformation estimation scheme that is motivated by physical constraints of fluid motion. The method employs within structure motion estimation (so that differing motions among different structures are not mixed) while simultaneously satisfying the physical constraint in fluid motion that at the interface between a fluid and a medium, the normal component of the fluid's motion must match the normal component of the motion of the medium. We show how to estimate the motion according to the previous considerations in a variational framework, and in particular, show that these conditions lead to PDEs with boundary conditions at the interface that resemble Robin boundary conditions and induce coupling between structures. We illustrate the use of this motion estimation scheme in propagating a segmentation across frames and show that it leads to more accurate segmentation than traditional motion estimation that does not make use of physical constraints. Further, the method is naturally suited to interactive segmentation methods, which are prominently used in practice in commercial applications for cardiac analysis, where typically a segmentation from the previous frame is used to predict a segmentation in the next frame. We show that our propagation scheme reduces the amount of user interaction by predicting more accurate segmentations than commonly used and recent interactive commercial techniques.
Generalized Signal Alignment For MIMO Two-Way X Relay Channels
Venue: arXiv cs.IT 2014
Year: 2014

We study the degrees of freedom (DoF) of MIMO two-way X relay channels. Previous work studied the case $N < 2M$, where $N$ and $M$ denote the number of antennas at the relay and each source, respectively, and showed that the maximum DoF of $2N$ is achievable when $N \leq \lfloor\frac{8M}{5}\rfloor$ by applying signal alignment (SA) for network coding and interference cancelation. This work considers the case $N>2M$ where the performance is limited by the number of antennas at each source node and conventional SA is not feasible. We propose a \textit{generalized signal alignment} (GSA) based transmission scheme. The key is to let the signals to be exchanged between every source node align in a transformed subspace, rather than the direct subspace, at the relay so as to form network-coded signals. This is realized by jointly designing the precoding matrices at all source nodes and the processing matrix at the relay. Moreover, the aligned subspaces are orthogonal to each other. By applying the GSA, we show that the DoF upper bound $4M$ is achievable when $M \leq \lfloor\frac{2N}{5}\rfloor$ ($M$ is even) or $M \leq \lfloor\frac{2N-1}{5}\rfloor$ ($M$ is odd). Numerical results also demonstrate that our proposed transmission scheme is feasible and effective.
A note on 'Exact and approximate methods for a one-dimensional minimax bin-packing problem' [Annals of Operations Research (2013) 206:611-626]
Venue: arXiv cs.DS 2014
Year: 2014

In a recent paper, Brusco, Köhn and Steinley [Ann. Oper. Res. 206:611-626 (2013)] conjecture that the 2 bins special case of the one-dimensional minimax bin-packing problem with bin size constraints might be solvable in polynomial time. In this note, we show that this problem is NP-hard for the special case and that it is strongly NP-hard for the general problem. We also propose a pseudo-polynomial algorithm for the special case and a constructive heuristic for the general problem.