OpenRaiser/Intern-Atlas huggingface dataset:
Optimal Resource Allocation in Full-Duplex Wireless-Powered Communication Network
Venue: arXiv cs.IT 2014
Year: 2014

This paper studies optimal resource allocation in the wireless-powered communication network (WPCN), where one hybrid access-point (H-AP) operating in full-duplex (FD) broadcasts wireless energy to a set of distributed users in the downlink (DL) and at the same time receives independent information from the users via time-division-multiple-access (TDMA) in the uplink (UL). We design an efficient protocol to support simultaneous wireless energy transfer (WET) in the DL and wireless information transmission (WIT) in the UL for the proposed FD-WPCN. We jointly optimize the time allocations to the H-AP for DL WET and different users for UL WIT as well as the transmit power allocations over time at the H-AP to maximize the users' weighted sum-rate of UL information transmission with harvested energy. We consider both the cases with perfect and imperfect self-interference cancellation (SIC) at the H-AP, for which we obtain optimal and suboptimal time and power allocation solutions, respectively. Furthermore, we consider the half-duplex (HD) WPCN as a baseline scheme and derive its optimal resource allocation solution. Simulation results show that the FD-WPCN outperforms HD-WPCN when effective SIC can be implemented and more stringent peak power constraint is applied at the H-AP.
Interaction and Depth against Nondeterminism in Proof Search
Venue: arXiv cs.LO 2014
Year: 2014

Deep inference is a proof theoretic methodology that generalizes the standard notion of inference of the sequent calculus, whereby inference rules become applicable at any depth inside logical expressions. Deep inference provides more freedom in the design of deductive systems for different logics and a rich combinatoric analysis of proofs. In particular, construction of exponentially shorter analytic proofs becomes possible, however with the cost of a greater nondeterminism than in the sequent calculus. In this paper, we show that the nondeterminism in proof search can be reduced without losing the shorter proofs and without sacrificing proof theoretic cleanliness. For this, we exploit an interaction and depth scheme in the logical expressions. We demonstrate our method on deep inference systems for multiplicative linear logic and classical logic, discuss its proof complexity and its relation to focusing, and present implementations.
Negative Selection Approach Application in Network Intrusion Detection Systems
Venue: arXiv cs.NI 2014
Year: 2014

Nature has always been an inspiration to researchers with its diversity and robustness of its systems, and Artificial Immune Systems are one of them. Many algorithms were inspired by ongoing discoveries of biological immune systems techniques and approaches. One of the basic and most common approach is the Negative Selection Approach, which is simple and easy to implement. It was applied in many fields, but mostly in anomaly detection for the similarity of its basic idea. In this paper, a review is given on the application of negative selection approach in network security, specifically the intrusion detection system. As the work in this field is limited, we need to understand what the challenges of this approach are. Recommendations are given by the end of the paper for future work.
Challenges and complexities in application of LCA approaches in the case of ICT for a sustainable future
Venue: arXiv cs.CY 2014
Year: 2014

In this work, three of many ICT-specific challenges of LCA are discussed. First, the inconsistency versus uncertainty is reviewed with regard to the meta-technological nature of ICT. As an example, the semiconductor technologies are used to highlight the complexities especially with respect to energy and water consumption. The need for specific representations and metric to separately assess products and technologies is discussed. It is highlighted that applying product-oriented approaches would result in abandoning or disfavoring of new technologies that could otherwise help toward a better world. Second, several believed-untouchable hot spots are highlighted to emphasize on their importance and footprint. The list includes, but not limited to, i) User Computer-Interfaces (UCIs), especially screens and displays, ii) Network-Computer Interlaces (NCIs), such as electronic and optical ports, and iii) electricity power interfaces. In addition, considering cross-regional social and economic impacts, and also taking into account the marketing nature of the need for many ICT's product and services in both forms of hardware and software, the complexity of End of Life (EoL) stage of ICT products, technologies, and services is explored. Finally, the impact of smart management and intelligence, and in general software, in ICT solutions and products is highlighted. In particular, it is observed that, even using the same technology, the significance of software could be highly variable depending on the level of intelligence and awareness deployed. With examples from an interconnected network of data centers managed using Dynamic Voltage and Frequency Scaling (DVFS) technology and smart cooling systems, it is shown that the unadjusted assessments could be highly uncertain, and even inconsistent, in calculating the management component's significance on the ICT impacts.
Shape-Based Plagiarism Detection for Flowchart Figures in Texts
Venue: arXiv cs.CV 2014
Year: 2014

Plagiarism detection is well known phenomenon in the academic arena. Copying other people is considered as serious offence that needs to be checked. There are many plagiarism detection systems such as turn-it-in that has been developed to provide this checks. Most, if not all, discard the figures and charts before checking for plagiarism. Discarding the figures and charts results in look holes that people can take advantage. That means people can plagiarized figures and charts easily without the current plagiarism systems detecting it. There are very few papers which talks about flowcharts plagiarism detection. Therefore, there is a need to develop a system that will detect plagiarism in figures and charts. This paper presents a method for detecting flow chart figure plagiarism based on shape-based image processing and multimedia retrieval. The method managed to retrieve flowcharts with ranked similarity according to different matching sets.
Uav Route Planning For Maximum Target Coverage
Venue: arXiv cs.RO 2014
Year: 2014

Utilization of Unmanned Aerial Vehicles (UAVs) in military and civil operations is getting popular. One of the challenges in effectively tasking these expensive vehicles is planning the flight routes to monitor the targets. In this work, we aim to develop an algorithm which produces routing plans for a limited number of UAVs to cover maximum number of targets considering their flight range. The proposed solution for this practical optimization problem is designed by modifying the Max-Min Ant System (MMAS) algorithm. To evaluate the success of the proposed method, an alternative approach, based on the Nearest Neighbour (NN) heuristic, has been developed as well. The results showed the success of the proposed MMAS method by increasing the number of covered targets compared to the solution based on the NN heuristic.
Precise Energy Modeling for the Bluetooth Low Energy Protocol
Venue: arXiv cs.NI 2014
Year: 2014

Bluetooth Low Energy (BLE) is a wireless protocol well suited for ultra-low-power sensors running on small batteries. BLE is described as a new protocol in the official Bluetooth 4.0 specification. To design energy-efficient devices, the protocol provides a number of parameters that need to be optimized within an energy, latency and throughput design space. To minimize power consumption, the protocol parameters have to be optimized for a given application. Therefore, an energy-model that can predict the energy consumption of a BLE-based wireless device for different parameter value settings, is needed. As BLE differs from the original Bluetooth significantly, models for Bluetooth cannot be easily applied to the BLE protocol. Since the last one year, there have been a couple of proposals on energy models for BLE. However, none of them can model all the operating modes of the protocol. This paper presents a precise energy model of the BLE protocol, that allows the computation of a device's power consumption in all possible operating modes. To the best of our knowledge, our proposed model is not only one of the most accurate ones known so far (because it accounts for all protocol parameters), but it is also the only one that models all the operating modes of BLE. Furthermore, we present a sensitivity analysis of the different parameters on the energy consumption and evaluate the accuracy of the model using both discrete event simulation and actual measurements. Based on this model, guidelines for system designers are presented, that help choosing the right parameters for optimizing the energy consumption for a given application.
Adaptive Representations for Tracking Breaking News on Twitter
Venue: arXiv cs.IR 2014
Year: 2014

Twitter is often the most up-to-date source for finding and tracking breaking news stories. Therefore, there is considerable interest in developing filters for tweet streams in order to track and summarize stories. This is a non-trivial text analytics task as tweets are short, and standard retrieval methods often fail as stories evolve over time. In this paper we examine the effectiveness of adaptive mechanisms for tracking and summarizing breaking news stories. We evaluate the effectiveness of these mechanisms on a number of recent news events for which manually curated timelines are available. Assessments based on ROUGE metrics indicate that an adaptive approaches are best suited for tracking evolving stories on Twitter.
3D Well-composed Polyhedral Complexes
Venue: arXiv cs.CV 2014
Year: 2014

A binary three-dimensional (3D) image $I$ is well-composed if the boundary surface of its continuous analog is a 2D manifold. Since 3D images are not often well-composed, there are several voxel-based methods ("repairing" algorithms) for turning them into well-composed ones but these methods either do not guarantee the topological equivalence between the original image and its corresponding well-composed one or involve sub-sampling the whole image. In this paper, we present a method to locally "repair" the cubical complex $Q(I)$ (embedded in $\mathbb{R}^3$) associated to $I$ to obtain a polyhedral complex $P(I)$ homotopy equivalent to $Q(I)$ such that the boundary of every connected component of $P(I)$ is a 2D manifold. The reparation is performed via a new codification system for $P(I)$ under the form of a 3D grayscale image that allows an efficient access to cells and their faces.
Evaluation of Image Segmentation and Filtering With ANN in the Papaya Leaf
Venue: arXiv cs.NE 2014
Year: 2014

Precision agriculture is area with lack of cheap technology. The refinement of the production system brings large advantages to the producer and the use of images makes the monitoring a more cheap methodology. Macronutrients monitoring can to determine the health and vulnerability of the plant in specific stages. In this paper is analyzed the method based on computational intelligence to work with image segmentation in the identification of symptoms of plant nutrient deficiency. Artificial neural networks are evaluated for image segmentation and filtering, several variations of parameters and insertion impulsive noise were evaluated too. Satisfactory results are achieved with artificial neural for segmentation same with high noise levels.
A Comparative Study of Audio Compression Based on Compressed Sensing and Sparse Fast Fourier Transform (SFFT): Performance and Challenges
Venue: arXiv cs.IT 2014
Year: 2014

Audio compression has become one of the basic multimedia technologies. Choosing an efficient compression scheme that is capable of preserving the signal quality while providing a high compression ratio is desirable in the different standards worldwide. In this paper we study the application of two highly acclaimed sparse signal processing algorithms, namely, Compressed Sensing (CS) and Sparse Fart Fourier transform, to audio compression. In addition, we present a Sparse Fast Fourier transform (SFFT)-based framework to compress audio signal. This scheme embeds the K-largest frequencies indices as part of the transmitted signal and thus saves in the bandwidth required for transmission
Readout Optical System of Sapphire Disks intended for Long-Term Data Storage
Venue: arXiv cs.ET 2014
Year: 2014

The development of long-term data storage technology is one of the urging problems of our time. This paper presents the results of implementation of technical solution for long-term data storage technology proposed a few years ago on the basis of single crystal sapphire. It is shown that the problem of reading data through a substrate of negative single crystal sapphire can be solved by using for reading a special optical system with a plate of positive single crystal quartz. The experimental results confirm the efficiency of the proposed method of compensation.
Noise Facilitation in Associative Memories of Exponential Capacity
Venue: arXiv cs.NE 2014
Year: 2014

Recent advances in associative memory design through structured pattern sets and graph-based inference algorithms have allowed reliable learning and recall of an exponential number of patterns. Although these designs correct external errors in recall, they assume neurons that compute noiselessly, in contrast to the highly variable neurons in brain regions thought to operate associatively such as hippocampus and olfactory cortex. Here we consider associative memories with noisy internal computations and analytically characterize performance. As long as the internal noise level is below a specified threshold, the error probability in the recall phase can be made exceedingly small. More surprisingly, we show that internal noise actually improves the performance of the recall phase while the pattern retrieval capacity remains intact, i.e., the number of stored patterns does not reduce with noise (up to a threshold). Computational experiments lend additional support to our theoretical analysis. This work suggests a functional benefit to noisy neurons in biological neuronal networks.
Minimal TSP Tour is coNP-Complete
Venue: arXiv cs.CC 2014
Year: 2014

The problem of deciding if a Traveling Salesman Problem (TSP) tour is minimal was proved to be coNP-complete by Papadimitriou and Steiglitz. We give an alternative proof based on a polynomial time reduction from 3SAT. Like the original proof, our reduction also shows that given a graph $G$ and an Hamiltonian path of $G$, it is NP-complete to check if $G$ contains an Hamiltonian cycle (Restricted Hamiltonian Cycle problem).
Coloring Large Complex Networks
Venue: arXiv cs.SI 2014
Year: 2014

Given a large social or information network, how can we partition the vertices into sets (i.e., colors) such that no two vertices linked by an edge are in the same set while minimizing the number of sets used. Despite the obvious practical importance of graph coloring, existing works have not systematically investigated or designed methods for large complex networks. In this work, we develop a unified framework for coloring large complex networks that consists of two main coloring variants that effectively balances the tradeoff between accuracy and efficiency. Using this framework as a fundamental basis, we propose coloring methods designed for the scale and structure of complex networks. In particular, the methods leverage triangles, triangle-cores, and other egonet properties and their combinations. We systematically compare the proposed methods across a wide range of networks (e.g., social, web, biological networks) and find a significant improvement over previous approaches in nearly all cases. Additionally, the solutions obtained are nearly optimal and sometimes provably optimal for certain classes of graphs (e.g., collaboration networks). We also propose a parallel algorithm for the problem of coloring neighborhood subgraphs and make several key observations. Overall, the coloring methods are shown to be (i) accurate with solutions close to optimal, (ii) fast and scalable for large networks, and (iii) flexible for use in a variety of applications.
Scalable and Robust Construction of Topical Hierarchies
Venue: arXiv cs.LG 2014
Year: 2014

Automated generation of high-quality topical hierarchies for a text collection is a dream problem in knowledge engineering with many valuable applications. In this paper a scalable and robust algorithm is proposed for constructing a hierarchy of topics from a text collection. We divide and conquer the problem using a top-down recursive framework, based on a tensor orthogonal decomposition technique. We solve a critical challenge to perform scalable inference for our newly designed hierarchical topic model. Experiments with various real-world datasets illustrate its ability to generate robust, high-quality hierarchies efficiently. Our method reduces the time of construction by several orders of magnitude, and its robust feature renders it possible for users to interactively revise the hierarchy.
A delay-based routing metric
Venue: arXiv cs.NI 2014
Year: 2014

In overlay networks, both local and long-distance links appear as a single hop to a routing protocol. Traditional routing metrics (based on hop count or packet loss) fail to take the differences between such links into account. In this paper, we study a metric based on packet delay that has been designed to improve routing in overlay networks. We show a lightweight technique for measuring delay asynchronously, and show how to use the data it provides for constructing a routing metric. Using delay naively leads to persistent routing oscillations, so our routing protocol implements a number of features to bound the frequency of oscillations. We show that our protocol causes no oscillations in real-world tests, and has oscillations with a period on the order of minutes in artificially constructed worst-case setups.
Analyzing Large Biological Datasets with an Improved Algorithm for MIC
Venue: arXiv cs.DB 2014
Year: 2014

A computational framework utilizes the traditional similarity measures for mining the significant relationships in biological annotations is recently proposed by Tatiana V. Karpinets et al. [2]. In this paper, an improved approximation algorithm for MIC (maximal information coefficient) named IAMIC is suggested to perfect this framework for discovering the hidden regularities between biological annotations. Further, IAMIC is the enhanced algorithm for approximating a novel similarity coefficient MIC with generality and equitability, which makes it more appropriate for data exploration. Here it is shown that IAMIC is also applicable for identify the associations between biological annotations.
Using Cluster Curves to Control Software Development Projects
Venue: arXiv cs.SE 2014
Year: 2014

Online interpretation and visualization of project data are gaining increasing importance on the long road towards predictable and controllable software project execution. This paper sketches the Sprint I controlling approach for software development projects and gives first evaluation results. The approach is grounded on the usage of context-oriented cluster curves and integrated in the framework of software project control centers.
A Systematic Methodology for Developing Discrete Event Simulation Models of Software Development Processes
Venue: arXiv cs.SE 2014
Year: 2014

So far there have been several efforts for developing software process simulators. However, the approaches for developing the simulators seem to have been ad-hoc and no systematic methodology exists. Since modeling and simulation in support of software development should become more popular (and there are signs that it does), there is a need for migrating modeling from craft to engineering. This article proposes such a systematic method, focused on the development of discrete simulation-based decision models, but extensible to other modeling approaches as well.
Proving Security Goals With Shape Analysis Sentences
Venue: arXiv cs.CR 2014
Year: 2014

The paper that introduced shape analysis sentences presented a method for extracting a sentence in first-order logic that completely characterizes a run of CPSA. Logical deduction can then be used to determine if a security goal is satisfied. This paper presents a method for importing shape analysis sentences into a proof assistant on top of a detailed theory of strand spaces. The result is a semantically rich environment in which the validity of a security goal can be determined using shape analysis sentences and the foundation on which they are based.
Applying mathematical models in cloud computing: A survey
Venue: arXiv cs.DC 2014
Year: 2014

As more and more information on individuals and companies are placed in the cloud, concerns are beginning to grow about just how safe an environment it is. It is better to prevent security threats before they enter into the systems and there is no way how this can be prevented without knowing where they come from. The issue of resource allocation and revenue maximization is also equally important especially when it comes to cloud security. This brings about the necessity of different modelling techniques including but not limited; security threat, resource allocation and revenue maximization models. This survey paper will try to analyse security threats and risk mitigation in cloud computing. It gives introduction of how viral attack can invade the virtual machines on the cloud, discusses the top security threats and countermeasures by providing the viral threat modelling in virtual machines and risk mitigation. Resource allocation models and revenue maximization techniques are also discussed.
A CCA secure cryptosystem using matrices over group rings
Venue: arXiv cs.CR 2014
Year: 2014

We propose a cryptosystem based on matrices over group rings and claim that it is secure against adaptive chosen ciphertext attack.
A Low-Complexity Algorithm for Throughput Maximization in Wireless Powered Communication Networks
Venue: arXiv cs.IT 2014
Year: 2014

This paper investigates a wireless powered communication network (WPCN) under the protocol of harvest-then-transmit,where a hybrid access point with constant power supply replenishes the passive user nodes by wireless power transfer in the downlink,then each user node transmit independent information to the hybrid AP in a time division multiple access (TDMA) scheme in the uplink.The sum-throughput maximization and min-throughput maximization problems are considered in this paper.The optimal time allocation for the sum-throughput maximization is proposed based on the Jensen's inequality,which provides more insight into the design of WPCNs.A low-complexity fixed-point iteration algorithm for the min-throughput maximization problem,which promises a much better computation complexity than the state-of-the-art algorithm.Simulation results confirm the effectiveness of the proposed algorithm.
Removal and Contraction Operations in $n$D Generalized Maps for Efficient Homology Computation
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, we show that contraction operations preserve the homology of $n$D generalized maps, under some conditions. Removal and contraction operations are used to propose an efficient algorithm that compute homology generators of $n$D generalized maps. Its principle consists in simplifying a generalized map as much as possible by using removal and contraction operations. We obtain a generalized map having the same homology than the initial one, while the number of cells decreased significantly. Keywords: $n$D Generalized Maps; Cellular Homology; Homology Generators; Contraction and Removal Operations.