OpenRaiser/Intern-Atlas huggingface dataset:
Game-Theoretic Analysis of the Hegselmann-Krause Model for Opinion Dynamics in Finite Dimensions
Venue: arXiv cs.GT 2014
Year: 2014

We consider the Hegselmann-Krause model for opinion dynamics and study the evolution of the system under various settings. We first analyze the termination time of the synchronous Hegselmann-Krause dynamics in arbitrary finite dimensions and show that the termination time in general only depends on the number of agents involved in the dynamics. To the best of our knowledge, that is the sharpest bound for the termination time of such dynamics that removes dependency of the termination time from the dimension of the ambient space. This answers an open question in [1] on how to obtain a tighter upper bound for the termination time. Furthermore, we study the asynchronous Hegselmann-Krause model from a novel game-theoretic approach and show that the evolution of an asynchronous Hegselmann-Krause model is equivalent to a sequence of best response updates in a well-designed potential game. We then provide a polynomial upper bound for the expected time and expected number of switching topologies until the dynamic reaches an arbitrarily small neighborhood of its equilibrium points, provided that the agents update uniformly at random. This is a step toward analysis of heterogeneous Hegselmann-Krause dynamics. Finally, we consider the heterogeneous Hegselmann-Krause dynamics and provide a necessary condition for the finite termination time of such dynamics. In particular, we sketch some future directions toward more detailed analysis of the heterogeneous Hegselmann-Krause model.
System Architecture and Key Technologies for 5G Heterogeneous Cloud Radio Access Networks
Venue: arXiv cs.IT 2014
Year: 2014

Compared with the fourth generation (4G) cellular systems, the fifth generation wireless communication systems (5G) are anticipated to provide spectral and energy efficiency growth by a factor of at least 10, and the area throughput growth by a factor of at least 25. To achieve these goals, a heterogeneous cloud radio access network (H-CRAN) is presented in this article as the advanced wireless access network paradigm, where cloud computing is used to fulfill the centralized large-scale cooperative processing for suppressing co-channel interferences. The state-of-the-art research achievements in aspects of system architecture and key technologies for H-CRANs are surveyed. Particularly, Node C as a new communication entity is defined to converge the existing ancestral base stations and act as the base band unit (BBU) pool to manage all accessed remote radio heads (RRHs), and the software-defined H-CRAN system architecture is presented to be compatible with software-defined networks (SDN). The principles, performance gains and open issues of key technologies including adaptive large-scale cooperative spatial signal processing, cooperative radio resource management, network function virtualization, and self-organization are summarized. The major challenges in terms of fronthaul constrained resource allocation optimization and energy harvesting that may affect the promotion of H-CRANs are discussed as well.
On the relationship between interdisciplinarity and impact: different modalities of interdisciplinarity lead to different types of impact
Venue: arXiv cs.DL 2014
Year: 2014

There is increasing interest among funding agencies to understand how they can best contribute to enhancing the socio-economic impact of research. Interdisciplinarity is often presented as a research mode that can facilitate impact but there exist a limited number of analytical studies that have attempted to examine whether or how interdisciplinarity can affect the societal relevance of research. We investigate fifteen Social Sciences research investments in the UK to examine how they have achieved impact. We analyse research drivers, cognitive distances, degree of integration, collaborative practices, stakeholder engagement and the type of impact generated. The analysis suggests that interdisciplinarity cannot be associated with a single type of impact mechanism. Also, interdisciplinarity is neither a sufficient nor a necessary condition for achieving societal relevance and impact. However, we identify a specific modality -- "long-range" interdisciplinarity, which appears more likely to be associated with societal impact because of its focused problem-orientation and its strong interaction with stakeholders.
Quantifying Natural and Artificial Intelligence in Robots and Natural Systems with an Algorithmic Behavioural Test
Venue: arXiv cs.AI 2014
Year: 2014

One of the most important aims of the fields of robotics, artificial intelligence and artificial life is the design and construction of systems and machines as versatile and as reliable as living organisms at performing high level human-like tasks. But how are we to evaluate artificial systems if we are not certain how to measure these capacities in living systems, let alone how to define life or intelligence? Here I survey a concrete metric towards measuring abstract properties of natural and artificial systems, such as the ability to react to the environment and to control one's own behaviour.
Temporal effects in trend prediction: identifying the most popular nodes in the future
Venue: arXiv cs.SI 2014
Year: 2014

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes' recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail.
Secrecy Performance Analysis of Location-Based Beamforming in Rician Wiretap Channels
Venue: arXiv cs.IT 2014
Year: 2014

We propose a new optimal Location-Based Beamforming (LBB) scheme for the wiretap channel, where both the main channel and the eavesdropper's channel are subject to Rician fading. In our LBB scheme the two key inputs are the location of the legitimate receiver and the location of the potential eavesdropper. Notably, our scheme does not require as direct inputs any channel state information of the main channel or the eavesdropper's channel, making it easy to deploy in a host of application settings in which the location inputs are known. Our beamforming solution assumes a multiple-antenna transmitter, a multiple-antenna eavesdropper, and a single-antenna receiver, and its aim is to maximize the physical layer security of the channel. To obtain our solution we first derive the secrecy outage probability of the LBB scheme in a closed-form expression that is valid for arbitrary values of the Rician K-factors of the main channel and the eavesdropper's channel. Using this expression we then determine the location-based beamformer solution that minimizes the secrecy outage probability. To assess the usefulness of our new scheme, and to quantify the value of the location information to the beamformer, we compare our scheme to other schemes, some of which do not utilize any location information. Our new beamformer solution provides optimal physical layer security for a wide range of location-based applications.
Comparing the sensitivity of social networks, web graphs, and random graphs with respect to vertex removal
Venue: arXiv cs.SI 2014
Year: 2014

The sensitivity of networks regarding the removal of vertices has been studied extensively within the last 15 years. A common approach to measure this sensitivity is (i) removing successively vertices by following a specific removal strategy and (ii) comparing the original and the modified network using a specific comparison method. In this paper we apply a wide range of removal strategies and comparison methods in order to study the sensitivity of medium-sized networks from real world and randomly generated networks. In the first part of our study we observe that social networks and web graphs differ in sensitivity. When removing vertices, social networks are robust, web graphs are not. This effect is conclusive with the work of Boldi et al. who analyzed very large networks. For similarly generated random graphs we find that the sensitivity highly depends on the comparison method. The choice of the removal strategy has surprisingly marginal impact on the sensitivity as long as we consider removal strategies implied by common centrality measures. However, it has a strong effect when removing the vertices in random order.
Decision-theoretic rough sets-based three-way approximations of interval-valued fuzzy sets
Venue: arXiv cs.AI 2014
Year: 2014

In practical situations, interval-valued fuzzy sets are frequently encountered. In this paper, firstly, we present shadowed sets for interpreting and understanding interval fuzzy sets. We also provide an analytic solution to computing the pair of thresholds by searching for a balance of uncertainty in the framework of shadowed sets. Secondly, we construct errors-based three-way approximations of interval-valued fuzzy sets. We also provide an alternative decision-theoretic formulation for calculating the pair of thresholds by transforming interval-valued loss functions into single-valued loss functions, in which the required thresholds are computed by minimizing decision costs. Thirdly, we compute errors-based three-way approximations of interval-valued fuzzy sets by using interval-valued loss functions. Finally, we employ several examples to illustrate that how to take an action for an object with interval-valued membership grade by using interval-valued loss functions.
Layered Interference Alignment: Achieving the Total DoF of MIMO X Channels
Venue: arXiv cs.IT 2014
Year: 2014

The $K\times 2$ and $2\times K$, Multiple-Input Multiple-Output (MIMO) X channel with constant channel coefficients available at all transmitters and receivers is considered. A new alignment scheme, named \emph{layered interference alignment}, is proposed in which both vector and real interference alignment are exploited, in conjunction with joint processing at receiver sides. Data streams with fractional multiplexing gains are sent in the desired directions to align the interfering signals at receivers. To decode the intended messages at receivers, a joint processing/simultaneous decoding technique, which exploits the availability of several receive antennas, is proposed. This analysis is subsequently backed up by metrical results for systems of linear forms. In particular, for such linear forms, Khintchine--Groshev type theorems are proved over real and complex numbers. It is observed that $K\times 2$ and $2\times K$, X channels with $M$ antennas at all transmitters/receivers enjoy duality in Degrees of Freedom (DoF). It is shown that incorporating the layered interference alignment is essential to characterize the total DoF of $\frac{2KM}{K+1}$ in the $K\times 2$ and $2\times K$, $M$ antenna X channels.
Audio Source Separation Using a Deep Autoencoder
Venue: arXiv cs.SD 2014
Year: 2014

This paper proposes a novel framework for unsupervised audio source separation using a deep autoencoder. The characteristics of unknown source signals mixed in the mixed input is automatically by properly configured autoencoders implemented by a network with many layers, and separated by clustering the coefficient vectors in the code layer. By investigating the weight vectors to the final target, representation layer, the primitive components of the audio signals in the frequency domain are observed. By clustering the activation coefficients in the code layer, the previously unknown source signals are segregated. The original source sounds are then separated and reconstructed by using code vectors which belong to different clusters. The restored sounds are not perfect but yield promising results for the possibility in the success of many practical applications.
5G Wireless Backhaul Networks: Challenges and Research Advance
Venue: arXiv cs.NI 2014
Year: 2014

5G networks are expected to achieve gigabit-level throughput in future cellular networks. However, it is a great challenge to treat 5G wireless backhaul traffic in an effective way. In this article, we analyze the wireless backhaul traffic in two typical network architectures adopting small cell and millimeter wave commmunication technologies. Furthermore, the energy efficiency of wireless backhaul networks is compared for different network architectures and frequency bands. Numerical comparison results provide some guidelines for deploying future 5G wireless backhaul networks in economical and highly energy-efficient ways.
A connective differentiation of textual production in interaction networks
Venue: arXiv cs.SI 2014
Year: 2014

This paper explores textual production in interaction networks, with special emphasis on its relation to topological measures. Four email lists were selected, in which measures were taken from the texts participants wrote. Peripheral, intermediary and hub sectors of these networks were observed to have discrepant linguistic elaborations. For completeness of exposition, correlation of textual and topological measures were observed for the entire network and for each connective sector. The formation of principal components is used for further insights of how measures are related.
Saving fractional bits: A practical entropy efficient code for fair die rolls
Venue: arXiv cs.IT 2014
Year: 2014

We give an implementation of an algorithm that uses fair coin flips to simulate fair rolls of an $n$-sided die. A register plays the role of an entropy pool and holds entropy that is generated as a by-product during each die roll and that is usually discarded. The entropy stored in this register is completely reused during the next rolls. Consequently, we can achieve an almost negligible loss of entropy per roll. The algorithm allows to change the number of sides of the die in each round. We prove that the entropy loss is monotone decreasing with increasing entropy pool size (register length).
DMARF AND GIPSY High Level Architecture and Requirements Analysis
Venue: arXiv cs.SE 2014
Year: 2014

In the current scenario, many organizations invest on open-source systems which are becoming popular and result in rapid growth, where in many of them have not met the quality standards which resulted in need for assessing quality. Initially we represent our work by analyzing the two open source case studies which are (1) Distributed Modular Audio Recognition Framework (DMARF) is an open-source framework which consists of Natural Language Processing (NLP) implemented using Java which facilitates extensibility by adding new algorithms, (2) General Intensional Programming System (GIPSY) is a platform designed to support intensional programming languages which are built using intensional logic and their imperative counter-parts for the intensional execution model. During this background study we identified few metrics which are used to assess the quality characteristics of a software product defined by ISO standards. Among the metrics, we identified the number of the java classes and methods using SonarQube. Followed by that, the actors and stakeholders have been categorized and focused on the evolution of fully dressed use cases. Besides, we analyzed the requirements and compiled the conceptual UML domain model diagrams with the responsibilities and relationships based on the functionalities, which leads to the creation of the class diagrams. Later the analysis and interpretation of results has been done using the metric tools to verify results which have been implemented and to identify the code smells accordingly. Finally the implication is towards performing the system level refactoring by applying appropriate refactoring methods to enhance the quality and performance of the open source systems. Besides, the respective test cases have been portrayed to ensure that there is not much behavioral change with the existing architecture.
Hete-CF: Social-Based Collaborative Filtering Recommendation using Heterogeneous Relations
Venue: arXiv cs.IR 2014
Year: 2014

Collaborative filtering algorithms haven been widely used in recommender systems. However, they often suffer from the data sparsity and cold start problems. With the increasing popularity of social media, these problems may be solved by using social-based recommendation. Social-based recommendation, as an emerging research area, uses social information to help mitigate the data sparsity and cold start problems, and it has been demonstrated that the social-based recommendation algorithms can efficiently improve the recommendation performance. However, few of the existing algorithms have considered using multiple types of relations within one social network. In this paper, we investigate the social-based recommendation algorithms on heterogeneous social networks and proposed Hete-CF, a Social Collaborative Filtering algorithm using heterogeneous relations. Distinct from the exiting methods, Hete-CF can effectively utilize multiple types of relations in a heterogeneous social network. In addition, Hete-CF is a general approach and can be used in arbitrary social networks, including event based social networks, location based social networks, and any other types of heterogeneous information networks associated with social information. The experimental results on two real-world data sets, DBLP (a typical heterogeneous information network) and Meetup (a typical event based social network) show the effectiveness and efficiency of our algorithm.
On the Power Allocation for Hybrid DF and CF Protocol with Auxiliary Parameter in Fading Relay Channels
Venue: arXiv cs.IT 2014
Year: 2014

In fading channels, power allocation over channel state may bring a rate increment compared to the fixed constant power mode. Such a rate increment is referred to power allocation gain. It is expected that the power allocation gain varies for different relay protocols. In this paper, Decode-and-Forward (DF) and Compress-and-Forward (CF) protocols are considered. We first establish a general framework for relay power allocation of DF and CF over channel state in half-duplex relay channels and present the optimal solution for relay power allocation with auxiliary parameters, respectively. Then, we reconsider the power allocation problem for one hybrid scheme which always selects the better one between DF and CF and obtain a near optimal solution for the hybrid scheme by introducing an auxiliary rate function as well as avoiding the non-concave rate optimization problem.
A Fuzzy Based Model to Identify Printed Sinhala Characters (ICIAfS14)
Venue: arXiv cs.CV 2014
Year: 2014

Character recognition techniques for printed documents are widely used for English language. However, the systems that are implemented to recognize Asian languages struggle to increase the accuracy of recognition. Among other Asian languages (such as Arabic, Tamil, Chinese), Sinhala characters are unique, mainly because they are round in shape. This unique feature makes it a challenge to extend the prevailing techniques to improve recognition of Sinhala characters. Therefore, a little attention has been given to improve the accuracy of Sinhala character recognition. A novel method, which makes use of this unique feature, could be advantageous over other methods. This paper describes the use of a fuzzy inference system to recognize Sinhala characters. Feature extraction is mainly focused on distance and intersection measurements in different directions from the center of the letter making use of the round shape of characters. The results showed an overall accuracy of 90.7% for 140 instances of letters tested, much better than similar systems.
Efficient Switch Architectures for Pre-configured Backup Protection with Sharing in Elastic Optical Networks (EON)
Venue: arXiv cs.NI 2014
Year: 2014

In this paper, we address the problem of providing survivability in elastic optical networks (EONs). EONs use fine granular frequency slots or flexible grids, when compared to the conventional fixed grid networks and therefore utilize the frequency spectrum efficiently. For providing survivability in EONs, we consider a recently proposed survivability method for conventional fixed grid networks, known as pre-configured backup protection with sharing (PBPS), because of its benefits over the traditional survivability approaches such as dedicated and shared protection. In PBPS, backup paths can be pre-configured and at the same time they can share resources. Therefore, both short recovery time and efficient resource usage can be achieved. We find that the existing switch architectures do not support both PBPS and EONs. Specifically, we identify and illustrate that, if a switch architecture is not carefully designed, several key problems/issues might arise in certain scenarios. Such problems include unnecessary resource consumption, inability of using existing free resources, and incapability of sharing backup paths. These problems appear when PBPS is adopted in EONs and they do not arise in fixed grid networks. In this paper, we propose new switch architectures which support both PBPS and EONs. Particularly, we illustrate that, our switch architectures avoid the specific problems/issues mentioned above. Therefore, our switch architectures support using resources more efficiently and reducing blocking of requests.
A Game-Theoretic Framework for Studying Dynamics of Multi Decision-maker Systems
Venue: arXiv cs.GT 2014
Year: 2014

System Dynamics (SD) main aim is to study dynamic behavior of systems based on causal relations. The other purpose of the science is to design policies, both in initial values and causal relation, to change system behavior as we desire. Especially we are interested in making systems behavior a convergent one. Although now SD is mainly used in situations of single policy maker, there are major parts of situations in which there are multi policy makers playing role. Game Theory (GT) is an appropriate tool for studying such cases.GT is the theory of studying multi decision-maker conditions. In this paper we will introduce GT and explain how to apply it in SD. Also we will provide some examples of microeconomic systems and show how to use GT for studying and simulating dynamics of these example systems. We will also have a short discuss on how SD can help GT studies.
Improved Parameter Identification Method Based on Moving Rate
Venue: arXiv cs.NE 2014
Year: 2014

To improve the problem that the parameter identification for fuzzy neural network has many time complexities in calculating, an improved T-S fuzzy inference method and an parameter identification method for fuzzy neural network are proposed. It mainly includes three parts. First, improved fuzzy inference method based on production term for T-S Fuzzy model is explained. Then, compared with existing Sugeno fuzzy inference based on Compositional rules and type-distance fuzzy inference method, the proposed fuzzy inference algorithm has a less amount of complexity in calculating and the calculating process is simple. Next, a parameter identification method for FNN based on production inference is proposed. Finally, the proposed method is applied for the precipitation forecast and security situation prediction. Test results showed that the proposed method significantly improved the effectiveness of identification, reduced the learning order, time complexity and learning error.