OpenRaiser/Intern-Atlas huggingface dataset:
Traffic Hotspot localization in 3G and 4G wireless networks using OMC metrics
Venue: arXiv cs.NI 2015
Year: 2015

In recent years, there has been an increasing awareness to traffic localization techniques driven by the emergence of heterogeneous networks (HetNet) with small cells deployment and the green networks. The localization of hotspot data traffic with a very high accuracy is indeed of great interest to know where the small cells should be deployed and how can be managed for sleep mode concept. In this paper, we propose a new traffic localization technique based on the combination of different key performance indicators (KPI) extracted from the operation and maintenance center (OMC). The proposed localization algorithm is composed with five main steps; each one corresponds to the determination of traffic weight per area using only one KPI. These KPIs are Timing Advance (TA), Angle of Arrival (AoA), Neighbor cell level, the load of each cell and the Harmonic mean throughput (HMT) versus the Arithmetic mean throughput (AMT). The five KPIs are finally combined by a function taking as variables the values computed from the five steps. By mixing such KPIs, we show that it is possible to lessen significantly the errors of localization in a high precision attaining small cell dimensions.
Joint Wireless Information and Power Transfer in a Three-Node Autonomous MIMO Relay Network
Venue: arXiv cs.IT 2015
Year: 2015

This paper investigates a three-node amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay network, where an autonomous relay harvests power from the source information flow and is further helped by an energy flow in the form of a wireless power transfer (WPT) at the destination. An energy-flow-assisted two-phase relaying scheme is proposed, where a source and relay joint optimization is formulated to maximize the rate. By diagonalizing the channel, the problem is simplified to a power optimization, where a relay channel pairing problem is solved by an ordering operation. The proposed algorithm, which iteratively optimizes the relay and source power, is shown to converge. Closed-form solutions can be obtained for the separate relay and source optimizations. Besides, a two-phase relaying without energy flow is also studied. Simulation results show that the energy-flow-assisted scheme is beneficial to the rate enhancement, if the transmit power of the energy flow is adequately larger than that of the information flow. Otherwise, the scheme without energy flow would be preferable.
White Paper: Radio y Redes Cognitivas
Venue: arXiv cs.NI 2015
Year: 2015

Traditionally, two different policies to access the radio spectrum have coexisted: licensed regulation, whereby the rights to use specific spectral bands are granted in exclusivity to an individual operator; or unlicensed regulation, according to which certain spectral bands are declared open for free use by any operator or individual following specific rules. While these paradigms have allowed the wireless communications sector to blossom in the past, in recent years they have evidenced shortcomings and given signs of exhaustion. For instance, it is quite usual to encounter fully overloaded mobile communication systems coexisting with unused contiguous spectral bands. This clearly advocates for a more flexible and dynamic allocation of the spectrum resources which can only be achieved with the advent of the so-called cognitive radios and networks. This whitepaper provides an accurate description of priority research activities and open challenges related to the different functionalities of cognitive radios and networks. First, we outline the main open problems related to the theoretical characterization of cognitive radios, spectrum sensing techniques as well as the optimization of physical layer functionalities in these networks. Second, we provide a description of the main research challenges that arise from a system point of view: MAC protocol optimization, traffic modelling, RRM strategies, routing paradigms or security issues. Next, we point out other problems related to the practical hardware implementation of cognitive radios, giving especial emphasis to sensing capabilities, reconfigurability and cognitive control and management. Finally, we succinctly report on a number of current activities related to the standardization of cognitive radio systems.
Tensor SimRank for Heterogeneous Information Networks
Venue: arXiv cs.AI 2015
Year: 2015

We propose a generalization of SimRank similarity measure for heterogeneous information networks. Given the information network, the intraclass similarity score s(a, b) is high if the set of objects that are related with a and the set of objects that are related with b are pair-wise similar according to all imposed relations.
Scale-Adaptive Group Optimization for Social Activity Planning
Venue: arXiv cs.SI 2015
Year: 2015

Studies have shown that each person is more inclined to enjoy a group activity when 1) she is interested in the activity, and 2) many friends with the same interest join it as well. Nevertheless, even with the interest and social tightness information available in online social networks, nowadays many social group activities still need to be coordinated manually. In this paper, therefore, we first formulate a new problem, named Participant Selection for Group Activity (PSGA), to decide the group size and select proper participants so that the sum of personal interests and social tightness of the participants in the group is maximized, while the activity cost is also carefully examined. To solve the problem, we design a new randomized algorithm, named Budget-Aware Randomized Group Selection (BARGS), to optimally allocate the computation budgets for effective selection of the group size and participants, and we prove that BARGS can acquire the solution with a guaranteed performance bound. The proposed algorithm was implemented in Facebook, and experimental results demonstrate that social groups generated by the proposed algorithm significantly outperform the baseline solutions.
An Upper Bound on the Minimum Distance of LDPC Codes over GF(q)
Venue: arXiv cs.IT 2015
Year: 2015

In [1] a syndrome counting based upper bound on the minimum distance of regular binary LDPC codes is given. In this paper we extend the bound to the case of irregular and generalized LDPC codes over GF(q). The comparison to the lower bound for LDPC codes over GF(q) and to the upper bound for non-binary codes is done. The new bound is shown to lie under the Gilbert-Varshamov bound at high rates.
Smart Socket for Activity Monitoring
Venue: arXiv cs.CY 2015
Year: 2015

In this short paper we consider the problem of monitoring physical activity in the smart house. The authors suggested a simple device that allows medical staff and relatives to monitor the activity for older adults living alone. This sensor monitors the switching-on of electrical devices. The fact of switching is seen as confirmation of physical activity. It is confirmed by SMS notifications to observers.
Growth rate of binary words avoiding $xxx^R$
Venue: arXiv cs.FL 2015
Year: 2015

Consider the set of those binary words with no non-empty factors of the form $xxx^R$. Du, Mousavi, Schaeffer, and Shallit asked whether this set of words grows polynomially or exponentially with length. In this paper, we demonstrate the existence of upper and lower bounds on the number of such words of length $n$, where each of these bounds is asymptotically equivalent to a (different) function of the form $Cn^{\lg n+c}$, where $C$, $c$ are constants.
Undergraduate Signal Processing Laboratories for the Android Operating System
Venue: arXiv cs.CY 2015
Year: 2015

We present a DSP simulation environment that will enable students to perform laboratory exercises using Android mobile devices and tablets. Due to the pervasive nature of the mobile technology, education applications designed for mobile devices have the potential to stimulate student interest in addition to offering convenient access and interaction capabilities. This paper describes a portable signal processing laboratory for the Android platform. This software is intended to be an educational tool for students and instructors in DSP, and signals and systems courses. The development of Android JDSP (A-JDSP) is carried out using the Android SDK, which is a Java-based open source development platform. The proposed application contains basic DSP functions for convolution, sampling, FFT, filtering and frequency domain analysis, with a convenient graphical user interface. A description of the architecture, functions and planned assessments are presented in this paper.
A Novel Architecture of Area Efficient FFT Algorithm for FPGA Implementation
Venue: arXiv cs.AR 2015
Year: 2015

Fast Fourier transform (FFT) of large number of samples requires huge hardware resources of field programmable gate arrays (FPGA), which needs more area and power. In this paper, we present an area efficient architecture of FFT processor that reuses the butterfly elements several times. The FFT processor is simulated using VHDL and the results are validated on a Virtex-6 FPGA. The proposed architecture outperforms the conventional architecture of a $N$-point FFT processor in terms of area which is reduced by a factor of $log_N 2$ with negligible increase in processing time.
An approximation algorithm for the longest cycle problem in solid grid graphs
Venue: arXiv cs.DS 2015
Year: 2015

Although, the Hamiltonicity of solid grid graphs are polynomial-time decidable, the complexity of the longest cycle problem in these graphs is still open. In this paper, by presenting a linear-time constant-factor approximation algorithm, we show that the longest cycle problem in solid grid graphs is in APX. More precisely, our algorithm finds a cycle of length at least $\frac{2n}{3}+1$ in 2-connected $n$-node solid grid graphs. Keywords: Longest cycle, Hamiltonian cycle, Approximation algorithm, Solid grid graph.
Measuring Online Social Bubbles
Venue: arXiv cs.SI 2015
Year: 2015

Social media have quickly become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view, and even foster polarization and misinformation. Here we explore and validate this hypothesis quantitatively for the first time, at the collective and individual levels, by mining three massive datasets of web traffic, search logs, and Twitter posts. Our analysis shows that collectively, people access information from a significantly narrower spectrum of sources through social media and email, compared to search. The significance of this finding for individual exposure is revealed by investigating the relationship between the diversity of information sources experienced by users at the collective and individual level. There is a strong correlation between collective and individual diversity, supporting the notion that when we use social media we find ourselves inside "social bubbles". Our results could lead to a deeper understanding of how technology biases our exposure to new information.
Open Source Remote Monitoring for Rural Solar Electrification Projects
Venue: arXiv cs.CY 2015
Year: 2015

Renewable energy systems are an increasingly popular way to generate electricity around the world. As wind and solar technologies gradually begin to supplant the use of fossil fuels as preferred means of energy production, new challenges are emerging which are unique to the experience of decentralized power generation. One such challenge is the development of effective monitoring technologies to relay diagnostic information from remote energy systems to data analysis centers. The ability to easily obtain, synthesize, and evaluate data pertaining to the behavior of a potentially vast number of individual power sources is of critical importance to the maintainability of the next generation of intelligent grid infrastructure. However, the application space of remote monitoring extends well beyond this. This paper details the development and implementation of an open-source monitoring framework for remote solar energy systems. The necessity for such a framework to be open is much better understood when considered through the lens of the theoretical potential for remote monitoring technologies in developing countries. The United States and other industrialized nations in the so-called 'first world' are likely to be slow to seriously adopt renewable energy on account of the massive investment and infrastructural changes required for its integration into the existing electrical grid. In countries where grid infrastructure is generally inadequate or nonexistent, this barrier is far less of a concern, and renewable energy technologies are viewed more as an enabling tool for progress than as a disruptive and expensive technological tangent. In this context as well, remote monitoring has a role to play.
Analysis and Optimization of Interference Nulling in Downlink Multi-Antenna HetNets with Offloading
Venue: arXiv cs.IT 2015
Year: 2015

Heterogeneous networks (HetNets) with offloading is considered as an effective way to meet the high data rate demand of future wireless service. However, the offloaded users suffer from strong inter-tier interference, which reduces the benefits of offloading and is one of the main limiting factors of the system performance. In this paper, we investigate the use of an interference nulling (IN) beamforming scheme to improve the system performance by carefully managing the inter-tier interference to the offloaded users in downlink two-tier HetNets with multi-antenna base stations. Utilizing tools from stochastic geometry, we derive a tractable expression for the rate coverage probability of the IN scheme. Then, we optimize the design parameter, i.e., the degrees of freedom that can be used for IN, to maximize the rate coverage probability. Specifically, in the asymptotic scenario where the rate threshold is small, by studying the order behavior of the rate coverage probability, we characterize the optimal design parameter. For the general scenario, we show some properties of the optimal design parameter. Finally, by numerical simulations, we show the IN scheme can outperform both the simple offloading scheme without interference management and the almost blank subframes scheme in 3GPP LTE, especially in large antenna regime.
Estimating the Potential Speedup of Computer Vision Applications on Embedded Multiprocessors
Venue: arXiv cs.CV 2015
Year: 2015

Computer vision applications constitute one of the key drivers for embedded multicore architectures. Although the number of available cores is increasing in new architectures, designing an application to maximize the utilization of the platform is still a challenge. In this sense, parallel performance prediction tools can aid developers in understanding the characteristics of an application and finding the most adequate parallelization strategy. In this work, we present a method for early parallel performance estimation on embedded multiprocessors from sequential application traces. We describe its implementation in Parana, a fast trace-driven simulator targeting OpenMP applications on the STMicroelectronics' STxP70 Application-Specific Multiprocessor (ASMP). Results for the FAST key point detector application show an error margin of less than 10% compared to the reference cycle-approximate simulator, with lower modeling effort and up to 20x faster execution time.
SAT problem and statistical distance
Venue: arXiv cs.CC 2015
Year: 2015

In this paper with two equivalent representations of the information contained by a SAT formula, the reason why string generated by succinct SAT formula can be greatly compressed is firstly presented based on Kolmogorov complexity theory. Then what strings can be greatly compressed were classified and discussed. In this way we discovered the SAT problem was composed of a basic distinguish problem: distinguish two different distributions induced under the computer with certain SAT formula ensemble. We then tried to map this problem into quantum mechanics, or the quantum version basic distinguish problem: this time two different distributions are induced under quantum mechanics. Based on the equivalence of statistical distance between probability space and Hilbert space, in the same time this distance is invariant under all unitary transformations. The quantum version basic problem cannot be efficiently solved by any quantum computer. In the worst case, any quantum computer must perform exponential times measurement in order to solve it. In the end we proposed the main theorem : The statistical distance in program space and probability space are identical. We tried to prove it using the relationship of Kolmogorov complexity and entropy. It showed there is no difference to solve the basic problem in SAT formula space or probability space. In the worst case, exponential trials must be performed to solve it. NP!=P.
Data Driven Validation Framework for Multi-agent Activity-based Models
Venue: arXiv cs.MA 2015
Year: 2015

Activity-based models, as a specific instance of agent-based models, deal with agents that structure their activity in terms of (daily) activity schedules. An activity schedule consists of a sequence of activity instances, each with its assigned start time, duration and location, together with transport modes used for travel between subsequent activity locations. A critical step in the development of simulation models is validation. Despite the growing importance of activity-based models in modelling transport and mobility, there has been so far no work focusing specifically on statistical validation of such models. In this paper, we propose a six-step Validation Framework for Activity-based Models (VALFRAM) that allows exploiting historical real-world data to assess the validity of activity-based models. The framework compares temporal and spatial properties and the structure of activity schedules against real-world travel diaries and origin-destination matrices. We confirm the usefulness of the framework on three real-world activity-based transport models.
Online Learning with Feedback Graphs: Beyond Bandits
Venue: arXiv cs.LG 2015
Year: 2015

We study a general class of online learning problems where the feedback is specified by a graph. This class includes online prediction with expert advice and the multi-armed bandit problem, but also several learning problems where the online player does not necessarily observe his own loss. We analyze how the structure of the feedback graph controls the inherent difficulty of the induced $T$-round learning problem. Specifically, we show that any feedback graph belongs to one of three classes: strongly observable graphs, weakly observable graphs, and unobservable graphs. We prove that the first class induces learning problems with $\widetildeΘ(α^{1/2} T^{1/2})$ minimax regret, where $α$ is the independence number of the underlying graph; the second class induces problems with $\widetildeΘ(δ^{1/3}T^{2/3})$ minimax regret, where $δ$ is the domination number of a certain portion of the graph; and the third class induces problems with linear minimax regret. Our results subsume much of the previous work on learning with feedback graphs and reveal new connections to partial monitoring games. We also show how the regret is affected if the graphs are allowed to vary with time.
The $k$-Leaf Spanning Tree Problem Admits a Klam Value of 39
Venue: arXiv cs.DS 2015
Year: 2015

Given an undirected graph $G$ and a parameter $k$, the $k$-Leaf Spanning Tree ($k$-LST) problem asks if $G$ contains a spanning tree with at least $k$ leaves. This problem has been extensively studied over the past three decades. In 2000, Fellows et al. [FSTTCS'00] explicitly asked whether it admits a klam value of 50. A steady progress towards an affirmative answer continued until 5 years ago, when an algorithm of klam value 37 was discovered. In this paper, we present an $O^*(3.188^k)$-time parameterized algorithm for $k$-LST, which shows that the problem admits a klam value of 39. Our algorithm is based on an interesting application of the well-known bounded search trees technique, where the correctness of rules crucially depends on the history of previously applied rules in a non-standard manner.
Efficient Geometric-based Computation of the String Subsequence Kernel
Venue: arXiv cs.LG 2015
Year: 2015

Kernel methods are powerful tools in machine learning. They have to be computationally efficient. In this paper, we present a novel Geometric-based approach to compute efficiently the string subsequence kernel (SSK). Our main idea is that the SSK computation reduces to range query problem. We started by the construction of a match list $L(s,t)=\{(i,j):s_{i}=t_{j}\}$ where $s$ and $t$ are the strings to be compared; such match list contains only the required data that contribute to the result. To compute efficiently the SSK, we extended the layered range tree data structure to a layered range sum tree, a range-aggregation data structure. The whole process takes $ O(p|L|\log|L|)$ time and $O(|L|\log|L|)$ space, where $|L|$ is the size of the match list and $p$ is the length of the SSK. We present empiric evaluations of our approach against the dynamic and the sparse programming approaches both on synthetically generated data and on newswire article data. Such experiments show the efficiency of our approach for large alphabet size except for very short strings. Moreover, compared to the sparse dynamic approach, the proposed approach outperforms absolutely for long strings.
Visualizing Cartograms: Goals and Task Taxonomy
Venue: arXiv cs.HC 2015
Year: 2015

Cartograms are maps in which areas of geographic regions (countries, states) appear in proportion to some variable of interest (population, income). Cartograms are popular visualizations for geo-referenced data that have been around for over a century. Newspapers, magazines, textbooks, blogs, and presentations frequently employ cartograms to show voting results, popularity, and in general, geographic patterns. Despite the popularity of cartograms and the large number of cartogram variants, there are very few studies evaluating the effectiveness of cartograms in conveying information. In order to design cartograms as a useful visualization tool and to be able to compare the effectiveness of cartograms generated by different methods, we need to study the nature of information conveyed and the specific tasks that can be performed on cartograms. In this paper we consider a set of cartogram visualization tasks, based on standard taxonomies from cartography and information visualization. We then propose a cartogram task taxonomy that can be used to organize not only the tasks considered here but also other tasks that might be added later.
Document Clustering using K-Means and K-Medoids
Venue: arXiv cs.IR 2015
Year: 2015

With the huge upsurge of information in day-to-days life, it has become difficult to assemble relevant information in nick of time. But people, always are in dearth of time, they need everything quick. Hence clustering was introduced to gather the relevant information in a cluster. There are several algorithms for clustering information out of which in this paper, we accomplish K-means and K-Medoids clustering algorithm and a comparison is carried out to find which algorithm is best for clustering. On the best clusters formed, document summarization is executed based on sentence weight to focus on key point of the whole document, which makes it easier for people to ascertain the information they want and thus read only those documents which is relevant in their point of view.