OpenRaiser/Intern-Atlas huggingface dataset:
Brazilian License Plate Detection Using Histogram of Oriented Gradients and Sliding Windows
Venue: arXiv cs.CV 2014
Year: 2014

Due to the increasingly need for automatic traffic monitoring, vehicle license plate detection is of high interest to perform automatic toll collection, traffic law enforcement, parking lot access control, among others. In this paper, a sliding window approach based on Histogram of Oriented Gradients (HOG) features is used for Brazilian license plate detection. This approach consists in scanning the whole image in a multiscale fashion such that the license plate is located precisely. The main contribution of this work consists in a deep study of the best setup for HOG descriptors on the detection of Brazilian license plates, in which HOG have never been applied before. We also demonstrate the reliability of this method ensured by a recall higher than 98% (with a precision higher than 78%) in a publicly available data set.
On the Capacity of the Multiuser Vector Adder Channel
Venue: arXiv cs.IT 2014
Year: 2014

We investigate the capacity of the $Q$-frequency $S$-user vector adder channel (channel with intensity information) introduced by Chang and Wolf. Both coordinated and uncoordinated types of transmission are considered. Asymptotic (under the conditions $Q \to \infty$, $S = γQ$ and $0 < γ< \infty$) upper and lower bounds on the relative (per subchannel) capacity are derived. The lower bound for the coordinated case is shown to increase when $γ$ grows. At the same time the relative capacity for the uncoordinated case is upper bounded by a constant.
Maximum Throughput for a Cognitive Radio Multi-Antenna User with Multiple Primary Users
Venue: arXiv cs.IT 2014
Year: 2014

We investigate a cognitive radio scenario involving a single cognitive transmitter equipped with $\mathcal{K}$ antennas sharing the spectrum with $\mathcal{M}$ primary users (PUs) transmitting over orthogonal bands. Each terminal has a queue to store its incoming traffic. We propose a novel protocol where the cognitive user transmits its packet over a channel formed by the aggregate of the inactive primary bands. We study the impact of the number of PUs, sensing errors, and the number of antennas on the maximum secondary stable throughput.
10 Simple Rules for the Care and Feeding of Scientific Data
Venue: arXiv cs.DL 2014
Year: 2014

This article offers a short guide to the steps scientists can take to ensure that their data and associated analyses continue to be of value and to be recognized. In just the past few years, hundreds of scholarly papers and reports have been written on questions of data sharing, data provenance, research reproducibility, licensing, attribution, privacy, and more, but our goal here is not to review that literature. Instead, we present a short guide intended for researchers who want to know why it is important to "care for and feed" data, with some practical advice on how to do that.
A lower bound for metric 1-median selection
Venue: arXiv cs.DS 2014
Year: 2014

Consider the problem of finding a point in an n-point metric space with the minimum average distance to all points. We show that this problem has no deterministic $o(n^2)$-query $(4-Ω(1))$-approximation algorithms.
An ANN Based Call Handoff Management Scheme for Mobile Cellular Network
Venue: arXiv cs.NI 2014
Year: 2014

Handoff decisions are usually signal strength based because of simplicity and effectiveness. Apart from the conventional techniques, such as threshold and hysteresis based schemes, recently many artificial intelligent techniques such as Fuzzy Logic, Artificial Neural Network (ANN) etc. are also used for taking handoff decision. In this paper, an Artificial Neural Network based handoff algorithm is proposed and its performance is studied. We have used ANN here for taking fast and accurate handoff decision. In our proposed handoff algorithm, Backpropagation Neural Network model is used.The advantages of Back propagation method are its simplicity and reasonable speed. The algorithm is designed, tested and found to give optimum results.
Ubiquitous Scaffold Learning Environment Using Problem-based Learning to Enhance Problem-solving Skills and Context Awareness
Venue: arXiv cs.CY 2014
Year: 2014

The purpose of this research is to 1) design of an Ubiquitous Scaffold Learning Environment Using Problem-based Learning model to enhance problem-solving skills and context awareness, and 2) evaluate the developed model. The research procedures divide into two phases. The first phase is to design of Ubiquitous Scaffold Learning Environment Using Problem-based Learning model, and the second phase is to evaluate the developed model. The sample group in this study consists of five experts selected by purposive sampling method. Data were analyzed by arithmetic mean and standard deviation. The research findings are as follows: 1. The developed model consist of three components is 1) principles of ubiquitous learning environment (ULE), problem-based learning with scaffolding in ULE, problem solving skill and context awareness 2) objectives of the model are to enhance problem solving skill and context awareness and 3) Process of the instructional model 2. The experts agree Ubiquitous Scaffold Learning Environment Using Problem-based Learning model model is high level of appropriateness.
Self Organizing strategies for enhanced ICIC (eICIC)
Venue: arXiv cs.NI 2014
Year: 2014

Small cells have been identified as an effective solution for coping with the important traffic increase that is expected in the coming years. But this solution is accompanied by additional interference that needs to be mitigated. The enhanced Inter Cell Interference Coordination (eICIC) feature has been introduced to address the interference problem. eICIC involves two parameters which need to be optimized, namely the Cell Range Extension (CRE) of the small cells and the ABS ratio (ABSr) which defines a mute ratio for the macro cell to reduce the interference it produces. In this paper we propose self-optimizing algorithms for the eICIC. The CRE is adjusted by means of load balancing algorithm. The ABSr parameter is optimized by maximizing a proportional fair utility of user throughputs. The convergence of the algorithms is proven using stochastic approximation theorems. Numerical simulations illustrate the important performance gain brought about by the different algorithms.
Dynamic Safety Message Power Control in VANET Using PSO
Venue: arXiv cs.NI 2014
Year: 2014

In the recent years Vehicular Ad hoc Networks (VANET) became one of the most challenging research area in the field of Mobile Ad hoc Networks (MANET). Vehicles in VANET send emergency and safety periodic messages through one control channel having a limited bandwidth, which causes a growing collision to the channel especially in dense traffic situations. In this paper a protocol Particle swarm optimization Beacon Power Control (PBPC) is proposed, which makes dynamic transmission power control to adjust the transmission power of the safety periodic messages that have been aggressively sent by all vehicles on the road 10 times per a second, the proposed protocol aims to decrease the packet collision resulted from periodic safety messages, which leads to control the load on the channel while ensuring a high probability of message reception within the safety distance of the sender vehicle.
Power Allocation for Energy Harvesting Transmitter with Causal Information
Venue: arXiv cs.IT 2014
Year: 2014

We consider power allocation for an access-controlled transmitter with energy harvesting capability based on causal observations of the channel fading state. We assume that the system operates in a time-slotted fashion and the channel gain in each slot is a random variable which is independent across slots. Further, we assume that the transmitter is solely powered by a renewable energy source and the energy harvesting process can practically be predicted. With the additional access control for the transmitter and the maximum power constraint, we formulate the stochastic optimization problem of maximizing the achievable rate as a Markov decision process (MDP) with continuous state. To efficiently solve the problem, we define an approximate value function based on a piecewise linear fit in terms of the battery state. We show that with the approximate value function, the update in each iteration consists of a group of convex problems with a continuous parameter. Moreover, we derive the optimal solution to these convex problems in closed-form. Further, we propose power allocation algorithms for both the finite- and infinite-horizon cases, whose computational complexity is significantly lower than that of the standard discrete MDP method but with improved performance. Extension to the case of a general payoff function and imperfect energy prediction is also considered. Finally, simulation results demonstrate that the proposed algorithms closely approach the optimal performance.
An Online Expectation-Maximisation Algorithm for Nonnegative Matrix Factorisation Models
Venue: arXiv cs.LG 2014
Year: 2014

In this paper we formulate the nonnegative matrix factorisation (NMF) problem as a maximum likelihood estimation problem for hidden Markov models and propose online expectation-maximisation (EM) algorithms to estimate the NMF and the other unknown static parameters. We also propose a sequential Monte Carlo approximation of our online EM algorithm. We show the performance of the proposed method with two numerical examples.
Guessing games
Venue: arXiv cs.GT 2014
Year: 2014

In a guessing game, players guess the value of a random real number selected using some probability density function. The winner may be determined in various ways; for example, a winner can be a player whose guess is closest in magnitude to the target or a winner can be a player coming closest without guessing higher than the target. We study optimal strategies for players in these games and determine some of them for two, three, and four players.
Does Restraining End Effect Matter in EMD-Based Modeling Framework for Time Series Prediction? Some Experimental Evidences
Venue: arXiv cs.AI 2014
Year: 2014

Following the "decomposition-and-ensemble" principle, the empirical mode decomposition (EMD)-based modeling framework has been widely used as a promising alternative for nonlinear and nonstationary time series modeling and prediction. The end effect, which occurs during the sifting process of EMD and is apt to distort the decomposed sub-series and hurt the modeling process followed, however, has been ignored in previous studies. Addressing the end effect issue, this study proposes to incorporate end condition methods into EMD-based decomposition and ensemble modeling framework for one- and multi-step ahead time series prediction. Four well-established end condition methods, Mirror method, Coughlin's method, Slope-based method, and Rato's method, are selected, and support vector regression (SVR) is employed as the modeling technique. For the purpose of justification and comparison, well-known NN3 competition data sets are used and four well-established prediction models are selected as benchmarks. The experimental results demonstrated that significant improvement can be achieved by the proposed EMD-based SVR models with end condition methods. The EMD-SBM-SVR model and EMD-Rato-SVR model, in particular, achieved the best prediction performances in terms of goodness of forecast measures and equality of accuracy of competing forecasts test.
Characteristic-Dependent Linear Rank Inequalities with Applications to Network Coding
Venue: arXiv cs.IT 2014
Year: 2014

Two characteristic-dependent linear rank inequalities are given for eight variables. Specifically, the first inequality holds for all finite fields whose characteristic is not three and does not in general hold over characteristic three. The second inequality holds for all finite fields whose characteristic is three and does not in general hold over characteristics other than three. Applications of these inequalities to the computation of capacity upper bounds in network coding are demonstrated.
QoS Constrained Optimal Sink and Relay Placement in Planned Wireless Sensor Networks
Venue: arXiv cs.NI 2014
Year: 2014

We are given a set of sensors at given locations, a set of potential locations for placing base stations (BSs, or sinks), and another set of potential locations for placing wireless relay nodes. There is a cost for placing a BS and a cost for placing a relay. The problem we consider is to select a set of BS locations, a set of relay locations, and an association of sensor nodes with the selected BS locations, so that number of hops in the path from each sensor to its BS is bounded by hmax, and among all such feasible networks, the cost of the selected network is the minimum. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard, and is hard to even approximate within a constant factor. For this problem, we propose a polynomial time approximation algorithm (SmartSelect) based on a relay placement algorithm proposed in our earlier work, along with a modification of the greedy algorithm for weighted set cover. We have analyzed the worst case approximation guarantee for this algorithm. We have also proposed a polynomial time heuristic to improve upon the solution provided by SmartSelect. Our numerical results demonstrate that the algorithms provide good quality solutions using very little computation time in various randomly generated network scenarios.
Parameterized Complexity of Edge Interdiction Problems
Venue: arXiv cs.CC 2014
Year: 2014

We study the parameterized complexity of interdiction problems in graphs. For an optimization problem on graphs, one can formulate an interdiction problem as a game consisting of two players, namely, an interdictor and an evader, who compete on an objective with opposing interests. In edge interdiction problems, every edge of the input graph has an interdiction cost associated with it and the interdictor interdicts the graph by modifying the edges in the graph, and the number of such modifications is constrained by the interdictor's budget. The evader then solves the given optimization problem on the modified graph. The action of the interdictor must impede the evader as much as possible. We focus on edge interdiction problems related to minimum spanning tree, maximum matching and shortest paths. These problems arise in different real world scenarios. We derive several fixed-parameter tractability and W[1]-hardness results for these interdiction problems with respect to various parameters. Next, we show close relation between interdiction problems and partial cover problems on bipartite graphs where the goal is not to cover all elements but to minimize/maximize the number of covered elements with specific number of sets. Hereby, we investigate the parameterized complexity of several partial cover problems on bipartite graphs.
Exponential Trust Based Mechanism to Detect Black Hole attack in Wireless Sensor Network
Venue: arXiv cs.NI 2014
Year: 2014

Security is a key feature in Wireless Sensor Networks but they are prone to many kinds of attacks and one of them is Black Hole Attack. In a black hole attack all the packets are consecutively dropped which leads to the decrease in the efficiency of the network and unnecessary wastage of battery life. In this paper, we propose an exponential trust based mechanism to detect the malicious node. In the proposed method a Streak counter is deployed to store the consecutive number of packets dropped and a trust factor is maintained for each node. The trust factor drops exponentially with each consecutive packet dropped which helps in detecting the malicious node. The proposed method show a drastic decrease in the number of packets dropped before the node being detected as a malicious node.
Design and Development of a User Specific Dynamic E-Magazine
Venue: arXiv cs.IR 2014
Year: 2014

Internet and electronic media gaining more popularity due to ease and speed, the count of Internet users has increased tremendously. The world is moving faster each day with several events taking place at once and the Internet is flooded with information in every field. There are categories of information ranging from most relevant to user, to the information totally irrelevant or less relevant to specific users. In such a scenario getting the information which is most relevant to the user is indispensable to save time. The motivation of our solution is based on the idea of optimizing the search for information automatically. This information is delivered to user in the form of an interactive GUI. The optimization of the contents or information served to him is based on his social networking profiles and on his reading habits on the proposed solution. The aim is to get the user's profile information based on his social networking profile considering that almost every Internet user has one. This helps us personalize the contents delivered to the user in order to produce what is most relevant to him, in the form of a personalized e-magazine. Further the proposed solution learns user's reading habits for example the news he saves or clicks the most and makes a decision to provide him with the best contents.
Millimeter Wave Cellular Wireless Networks: Potentials and Challenges
Venue: arXiv cs.NI 2014
Year: 2014

Millimeter wave (mmW) frequencies between 30 and 300 GHz are a new frontier for cellular communication that offers the promise of orders of magnitude greater bandwidths combined with further gains via beamforming and spatial multiplexing from multi-element antenna arrays. This paper surveys measurements and capacity studies to assess this technology with a focus on small cell deployments in urban environments. The conclusions are extremely encouraging; measurements in New York City at 28 and 73 GHz demonstrate that, even in an urban canyon environment, significant non-line-of-sight (NLOS) outdoor, street-level coverage is possible up to approximately 200 m from a potential low power micro- or picocell base station. In addition, based on statistical channel models from these measurements, it is shown that mmW systems can offer more than an order of magnitude increase in capacity over current state-of-the-art 4G cellular networks at current cell densities. Cellular systems, however, will need to be significantly redesigned to fully achieve these gains. Specifically, the requirement of highly directional and adaptive transmissions, directional isolation between links and significant possibilities of outage have strong implications on multiple access, channel structure, synchronization and receiver design. To address these challenges, the paper discusses how various technologies including adaptive beamforming, multihop relaying, heterogeneous network architectures and carrier aggregation can be leveraged in the mmW context.
Multi Terminal Probabilistic Compressed Sensing
Venue: arXiv cs.IT 2014
Year: 2014

In this paper, the `Approximate Message Passing' (AMP) algorithm, initially developed for compressed sensing of signals under i.i.d. Gaussian measurement matrices, has been extended to a multi-terminal setting (MAMP algorithm). It has been shown that similar to its single terminal counterpart, the behavior of MAMP algorithm is fully characterized by a `State Evolution' (SE) equation for large block-lengths. This equation has been used to obtain the rate-distortion curve of a multi-terminal memoryless source. It is observed that by spatially coupling the measurement matrices, the rate-distortion curve of MAMP algorithm undergoes a phase transition, where the measurement rate region corresponding to a low distortion (approximately zero distortion) regime is fully characterized by the joint and conditional Renyi information dimension (RID) of the multi-terminal source. This measurement rate region is very similar to the rate region of the Slepian-Wolf distributed source coding problem where the RID plays a role similar to the discrete entropy. Simulations have been done to investigate the empirical behavior of MAMP algorithm. It is observed that simulation results match very well with predictions of SE equation for reasonably large block-lengths.
Repair Locality From a Combinatorial Perspective
Venue: arXiv cs.IT 2014
Year: 2014

Repair locality is a desirable property for erasure codes in distributed storage systems. Recently, different structures of local repair groups have been proposed in the definitions of repair locality. In this paper, the concept of regenerating set is introduced to characterize the local repair groups. A definition of locality $r^{(δ-1)}$ (i.e., locality $r$ with repair tolerance $δ-1$) under the most general structure of regenerating sets is given. All previously studied locality turns out to be special cases of this definition. Furthermore, three representative concepts of locality proposed before are reinvestigated under the framework of regenerating sets, and their respective upper bounds on the minimum distance are reproved in a uniform and brief form. Additionally, a more precise distance bound is derived for the square code which is a class of linear codes with locality $r^{(2)}$ and high information rate, and an explicit code construction attaining the optimal distance bound is obtained.
The Missing Ones: Key Ingredients Towards Effective Ambient Assisted Living Systems
Venue: arXiv cs.CY 2014
Year: 2014

The population of elderly people keeps increasing rapidly, which becomes a predominant aspect of our societies. As such, solutions both efficacious and cost-effective need to be sought. Ambient Assisted Living (AAL) is a new approach which promises to address the needs from elderly people. In this paper, we claim that human participation is a key ingredient towards effective AAL systems, which not only saves social resources, but also has positive relapses on the psychological health of the elderly people. Challenges in increasing the human participation in ambient assisted living are discussed in this paper and solutions to meet those challenges are also proposed. We use our proposed mutual assistance community, which is built with service oriented approach, as an example to demonstrate how to integrate human tasks in AAL systems. Our preliminary simulation results are presented, which support the effectiveness of human participation.
Distance Landmarks Revisited for Road Graphs
Venue: arXiv cs.DB 2014
Year: 2014

Computing shortest distances is one of the fundamental problems on graphs, and remains a {\em challenging} task today. {\em Distance} {\em landmarks} have been recently studied for shortest distance queries with an auxiliary data structure, referred to as {\em landmark} {\em covers}. This paper studies how to apply distance landmarks for fast {\em exact} shortest distance query answering on large road graphs. However, the {\em direct} application of distance landmarks is {\em impractical} due to the high space and time cost. To rectify this problem, we investigate novel techniques that can be seamlessly combined with distance landmarks. We first propose a notion of {\em hybrid landmark covers}, a revision of landmark covers. Second, we propose a notion of {\em agents}, each of which represents a small subgraph and holds good properties for fast distance query answering. We also show that agents can be computed in {\em linear time}. Third, we introduce graph partitions to deal with the remaining subgraph that cannot be captured by agents. Fourth, we develop a unified framework that seamlessly integrates our proposed techniques and existing optimization techniques, for fast shortest distance query answering. Finally, we experimentally verify that our techniques significantly improve the efficiency of shortest distance queries, using real-life road graphs.