OpenRaiser/Intern-Atlas huggingface dataset:
Performance Evaluation of Predictive Classifiers For Knowledge Discovery From Engineering Materials Data Sets
Venue: arXiv cs.LG 2012
Year: 2012

In this paper, naive Bayesian and C4.5 Decision Tree Classifiers(DTC) are successively applied on materials informatics to classify the engineering materials into different classes for the selection of materials that suit the input design specifications. Here, the classifiers are analyzed individually and their performance evaluation is analyzed with confusion matrix predictive parameters and standard measures, the classification results are analyzed on different class of materials. Comparison of classifiers has found that naive Bayesian classifier is more accurate and better than the C4.5 DTC. The knowledge discovered by the naive bayesian classifier can be employed for decision making in materials selection in manufacturing industries.
Implementing A Greedy Chain Routing Technique With Spread Spectrum On Grid-Based WSNs
Venue: arXiv cs.NI 2012
Year: 2012

Wireless Sensor Networks (WSN) are set of energy-limited sensors, which recently have been point of interest due to their vast applications. One of the efficient ways to consume energy in these networks is to utilize optimal routing protocols. In this approach, we proposed a greedy hierarchical chain-based routing method, named, PGC (stands for Persian Greedy Chain) which route the network applying Spread Spectrum codes as a mask given to the grid cells. Due to similarities between the proposed method in this article and LEACH protocol, we compare this routing protocol with the proposed model from diverse aspects in the simulation section such as remaining energy and being fault tolerant and reliable. The results prove that presented method is more robust and efficient.
Energy aware routing scheme for mobile ad hoc network using variable range transmission
Venue: arXiv cs.NI 2012
Year: 2012

This paper discusses a new energy aware routing scheme which uses variable transmission range. The protocol has been incorporated along with the route discovery procedure of AODV as a case study. Both the protocols are simulated using Network Simulator and comparisons are made to analyze their performance based on energy consumption, network lifetime and number of alive nodes metrics for different network scenarios. The results show that EAR makes effective node energy utilization.
Probabilities on Sentences in an Expressive Logic
Venue: arXiv cs.LO 2012
Year: 2012

Automated reasoning about uncertain knowledge has many applications. One difficulty when developing such systems is the lack of a completely satisfactory integration of logic and probability. We address this problem directly. Expressive languages like higher-order logic are ideally suited for representing and reasoning about structured knowledge. Uncertain knowledge can be modeled by using graded probabilities rather than binary truth-values. The main technical problem studied in this paper is the following: Given a set of sentences, each having some probability of being true, what probability should be ascribed to other (query) sentences? A natural wish-list, among others, is that the probability distribution (i) is consistent with the knowledge base, (ii) allows for a consistent inference procedure and in particular (iii) reduces to deductive logic in the limit of probabilities being 0 and 1, (iv) allows (Bayesian) inductive reasoning and (v) learning in the limit and in particular (vi) allows confirmation of universally quantified hypotheses/sentences. We translate this wish-list into technical requirements for a prior probability and show that probabilities satisfying all our criteria exist. We also give explicit constructions and several general characterizations of probabilities that satisfy some or all of the criteria and various (counter) examples. We also derive necessary and sufficient conditions for extending beliefs about finitely many sentences to suitable probabilities over all sentences, and in particular least dogmatic or least biased ones. We conclude with a brief outlook on how the developed theory might be used and approximated in autonomous reasoning agents. Our theory is a step towards a globally consistent and empirically satisfactory unification of probability and logic.
Reliability improvement with PSP of Web-based software application
Venue: arXiv cs.SE 2012
Year: 2012

In diverse industrial and academic environments, the quality of the software has been evaluated using different analytic studies. The contribution of the present work is focused on the development of a methodology in order to improve the evaluation and analysis of the reliability of web-based software applications. The Personal Software Process (PSP) was introduced in our methodology for improving the quality of the process and the product. The Evaluation + Improvement (Ei) process is performed in our methodology to evaluate and improve the quality of the software system. We tested our methodology in a web-based software system and used statistical modeling theory for the analysis and evaluation of the reliability. The behavior of the system under ideal conditions was evaluated and compared against the operation of the system executing under real conditions. The results obtained demonstrated the effectiveness and applicability of our methodology.
A Plan For Curating "Obsolete Data or Resources"
Venue: arXiv cs.DL 2012
Year: 2012

Our cultural discourse is increasingly carried in the web. With the initial emergence of the web many years ago, there was a period where conventional mediums (e.g., music, movies, books, scholarly publications) were primary and the web was a supplementary channel. This has now changed, where the web is often the primary channel, and other publishing mechanisms, if present at all, supplement the web. Unfortunately, the technology for publishing information on the web always outstrips our technology for preservation. My concern is less that we will lose data of known importance (e.g., scientific data, census data), but rather that we will lose data that we do not yet know is important. In this paper I review some of the issues and, where appropriate, proposed solutions for increasing the archivability of the web.
NetSimile: A Scalable Approach to Size-Independent Network Similarity
Venue: arXiv cs.SI 2012
Year: 2012

Given a set of k networks, possibly with different sizes and no overlaps in nodes or edges, how can we quickly assess similarity between them, without solving the node-correspondence problem? Analogously, how can we extract a small number of descriptive, numerical features from each graph that effectively serve as the graph's "signature"? Having such features will enable a wealth of graph mining tasks, including clustering, outlier detection, visualization, etc. We propose NetSimile -- a novel, effective, and scalable method for solving the aforementioned problem. NetSimile has the following desirable properties: (a) It gives similarity scores that are size-invariant. (b) It is scalable, being linear on the number of edges for "signature" vector extraction. (c) It does not need to solve the node-correspondence problem. We present extensive experiments on numerous synthetic and real graphs from disparate domains, and show NetSimile's superiority over baseline competitors. We also show how NetSimile enables several mining tasks such as clustering, visualization, discontinuity detection, network transfer learning, and re-identification across networks.
Multi-track Map Matching
Venue: arXiv cs.LG 2012
Year: 2012

We study algorithms for matching user tracks, consisting of time-ordered location points, to paths in the road network. Previous work has focused on the scenario where the location data is linearly ordered and consists of fairly dense and regular samples. In this work, we consider the \emph{multi-track map matching}, where the location data comes from different trips on the same route, each with very sparse samples. This captures the realistic scenario where users repeatedly travel on regular routes and samples are sparsely collected, either due to energy consumption constraints or because samples are only collected when the user actively uses a service. In the multi-track problem, the total set of combined locations is only partially ordered, rather than globally ordered as required by previous map-matching algorithms. We propose two methods, the iterative projection scheme and the graph Laplacian scheme, to solve the multi-track problem by using a single-track map-matching subroutine. We also propose a boosting technique which may be applied to either approach to improve the accuracy of the estimated paths. In addition, in order to deal with variable sampling rates in single-track map matching, we propose a method based on a particular regularized cost function that can be adapted for different sampling rates and measurement errors. We evaluate the effectiveness of our techniques for reconstructing tracks under several different configurations of sampling error and sampling rate.
Improving Energy Efficiency in Femtocell Networks: A Hierarchical Reinforcement Learning Framework
Venue: arXiv cs.LG 2012
Year: 2012

This paper investigates energy efficiency for two-tier femtocell networks through combining game theory and stochastic learning. With the Stackelberg game formulation, a hierarchical reinforcement learning framework is applied to study the joint average utility maximization of macrocells and femtocells subject to the minimum signal-to-interference-plus-noise-ratio requirements. The macrocells behave as the leaders and the femtocells are followers during the learning procedure. At each time step, the leaders commit to dynamic strategies based on the best responses of the followers, while the followers compete against each other with no further information but the leaders' strategy information. In this paper, we propose two learning algorithms to schedule each cell's stochastic power levels, leading by the macrocells. Numerical experiments are presented to validate the proposed studies and show that the two learning algorithms substantially improve the energy efficiency of the femtocell networks.
Node Coloring in Wireless Networks: Complexity Results and Grid Coloring
Venue: arXiv cs.NI 2012
Year: 2012

Coloring is used in wireless networks to improve communication efficiency, mainly in terms of bandwidth, energy and possibly end-to-end delays. In this paper, we define the h-hop node coloring problem, with h any positive integer, adapted to two types of applications in wireless networks. We specify both general mode for general applications and strategic mode for data gathering applications.We prove that the associated decision problem is NP-complete. We then focus on grid topologies that constitute regular topologies for large or dense wireless networks. We consider various transmission ranges and identify a color pattern that can be reproduced to color the whole grid with the optimal number of colors. We obtain an optimal periodic coloring of the grid for the considered transmission range. We then present a 3-hop distributed coloring algorithm, called SERENA. Through simulation results, we highlight the impact of node priority assignment on the number of colors obtained for any network and grids in particular. We then compare these optimal results on grids with those obtained by SERENA and identify directions to improve SERENA.
Losing My Revolution: How Many Resources Shared on Social Media Have Been Lost?
Venue: arXiv cs.DL 2012
Year: 2012

Social media content has grown exponentially in the recent years and the role of social media has evolved from just narrating life events to actually shaping them. In this paper we explore how many resources shared in social media are still available on the live web or in public web archives. By analyzing six different event-centric datasets of resources shared in social media in the period from June 2009 to March 2012, we found about 11% lost and 20% archived after just a year and an average of 27% lost and 41% archived after two and a half years. Furthermore, we found a nearly linear relationship between time of sharing of the resource and the percentage lost, with a slightly less linear relationship between time of sharing and archiving coverage of the resource. From this model we conclude that after the first year of publishing, nearly 11% of shared resources will be lost and after that we will continue to lose 0.02% per day.
A Simultaneous-Movement Mobile Multiplayer Game Design based on Adaptive Background Partitioning Technique
Venue: arXiv cs.GT 2012
Year: 2012

Implementations of mobile games have become prevalent industrial technology due to the ubiquitous nature of mobile devices. However, simultaneous-movement multiplayer games, games that a player competes simultaneously with other players, are usually affected by such parameters as latency, type of game architecture and type of communication technology. This paper makes a review of the above parameters, considering the pros and cons of the various techniques used in addressing each parameter. It then goes ahead to propose an enhanced mechanism for dealing with packet delays based on partitioning the game background into grids. The proposed design is implemented and tested using Bluetooth and Wi-Fi communication technologies. The efficiency and effectiveness of the design are also analyzed.
Improved Algorithm for Throughput Maximization in MC-CDMA
Venue: arXiv cs.NI 2012
Year: 2012

The Multi-Carrier Code Division Multiple Access (MC-CDMA) is becoming a very significant downlink multiple access technique for high-rate data transmission in the fourth generation wireless communication systems. By means of efficient resource allocation higher data rate i.e. throughput can be achieved. This paper evaluates the performance of criteria used for group (subchannel) allocation employed in downlink transmission, which results in throughput maximization. Proposed algorithm gives the modified technique of sub channel allocation in the downlink transmission of MC-CDMA systems. Simulation are carried out for all the three combining schemes, results shows that for the given power and BER proposed algorithm comparatively gives far better results
Augmenting Customer Journey Maps with quantitative empirical data: a case on EEG and eye tracking
Venue: arXiv cs.HC 2012
Year: 2012

This paper introduces the use of electroencephalography (EEG) and eye tracking in exploring customer experiences in service design. These tools are expected to allow designers to generate customer journeys from empirical data leading to new visualization methods and therefore improvements in service design deliverables.
High-throughput Execution of Hierarchical Analysis Pipelines on Hybrid Cluster Platforms
Venue: arXiv cs.DC 2012
Year: 2012

We propose, implement, and experimentally evaluate a runtime middleware to support high-throughput execution on hybrid cluster machines of large-scale analysis applications. A hybrid cluster machine consists of computation nodes which have multiple CPUs and general purpose graphics processing units (GPUs). Our work targets scientific analysis applications in which datasets are processed in application-specific data chunks, and the processing of a data chunk is expressed as a hierarchical pipeline of operations. The proposed middleware system combines a bag-of-tasks style execution with coarse-grain dataflow execution. Data chunks and associated data processing pipelines are scheduled across cluster nodes using a demand driven approach, while within a node operations in a given pipeline instance are scheduled across CPUs and GPUs. The runtime system implements several optimizations, including performance aware task scheduling, architecture aware process placement, data locality conscious task assignment, and data prefetching and asynchronous data copy, to maximize utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. The application and performance benefits of the runtime middleware are demonstrated using an image analysis application, which is employed in a brain cancer study, on a state-of-the-art hybrid cluster in which each node has two 6-core CPUs and three GPUs. Our results show that implementing and scheduling application data processing as a set of fine-grain operations provide more opportunities for runtime optimizations and attain better performance than a coarser-grain, monolithic implementation. The proposed runtime system can achieve high-throughput processing of large datasets - we were able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles at about 150 tiles/second rate on 100 nodes.
EBCD: a routing algorithm based on bee colony for energy consumption reduction in wireless relay networks
Venue: arXiv cs.NI 2012
Year: 2012

One of the important issues in wireless networks is the Routing problem that is effective on system performance, in this article the attempt is made to propose a routing algorithm using the bee colony in order to reduce energy consumption in wireless relay networks. In EBCD algorithm, through combined of energy, distance and traffic parameters a routing algorithm for wireless networks is presented with more efficiency than its predecessor. Applying the bee colony method would allow the placement of the parameters under conventional conditions and to get closer to a mechanism with a better adaptability than that of the existing algorithm. According to the parameters considered, the proposed algorithm provides a fitness function that can be applied as a multi-hop. Unlike other algorithms of its kind this can increase service quality based on environmental conditions through its multiple services. This new method can store the energy accumulated in the nodes and reduce the hop restrictions.
Deadlock Recovery Technique in Bus Enhanced NoC Architecture
Venue: arXiv cs.AR 2012
Year: 2012

Increase in the speed of processors has led to crucial role of communication in the performance of systems. As a result, routing is taken into consideration as one of the most important subjects of the Network on Chip architecture. Routing algorithms to deadlock avoidance prevent packets route completely based on network traffic condition by means of restricting the route of packets. This action leads to less performance especially in non-uniform traffic patterns. On the other hand True Fully Adoptive Routing algorithm provides routing of packets completely based on traffic condition. However, deadlock detection and recovery mechanisms are needed to handle deadlocks. Use of global bus beside NoC as a parallel supportive environment, provide platform to offer advantages of both features of bus and NoC. This bus is useful for broadcast and multicast operations, sending delay sensitive signals, system management and other services. In this research, we use this bus as an escaping path for deadlock recovery technique. According to simulation results, this bus is suitable platform for deadlock recovery technique.
Output Feedback H_2 Model Matching for Decentralized Systems with Delays
Venue: arXiv cs.SY 2012
Year: 2012

This paper gives a new solution to the output feedback H_2 model matching problem for a large class of delayed information sharing patterns. Existing methods for such problems typically reduce the decentralized problem to a centralized problem of higher state dimension. In contrast, the controller given in this paper is constructed from the solutions to the centralized control and estimation Riccati equations for the original system. The problem is solved by decomposing the controller into two components. One is centralized, but delayed, while the other is decentralized with finite impulse response (FIR). It is then shown that the optimal controller can be constructed through a combination of centralized spectral factorization and quadratic programming.
Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields
Venue: arXiv cs.LG 2012
Year: 2012

Many real-world datasets can be represented in the form of a graph whose edge weights designate similarities between instances. A discrete Gaussian random field (GRF) model is a finite-dimensional Gaussian process (GP) whose prior covariance is the inverse of a graph Laplacian. Minimizing the trace of the predictive covariance Sigma (V-optimality) on GRFs has proven successful in batch active learning classification problems with budget constraints. However, its worst-case bound has been missing. We show that the V-optimality on GRFs as a function of the batch query set is submodular and hence its greedy selection algorithm guarantees an (1-1/e) approximation ratio. Moreover, GRF models have the absence-of-suppressor (AofS) condition. For active survey problems, we propose a similar survey criterion which minimizes 1'(Sigma)1. In practice, V-optimality criterion performs better than GPs with mutual information gain criteria and allows nonuniform costs for different nodes.
Minimal realization of the dynamical structure function and its application to network reconstruction
Venue: arXiv cs.SY 2012
Year: 2012

Network reconstruction, i.e., obtaining network structure from data, is a central theme in systems biology, economics and engineering. In some previous work, we introduced dynamical structure functions as a tool for posing and solving the problem of network reconstruction between measured states. While recovering the network structure between hidden states is not possible since they are not measured, in many situations it is important to estimate the minimal number of hidden states in order to understand the complexity of the network under investigation and help identify potential targets for measurements. Estimating the minimal number of hidden states is also crucial to obtain the simplest state-space model that captures the network structure and is coherent with the measured data. This paper characterizes minimal order state-space realizations that are consistent with a given dynamical structure function by exploring properties of dynamical structure functions and developing an algorithm to explicitly obtain such a minimal realization.
Interference Mitigation via Interference-Aware Successive Decoding
Venue: arXiv cs.IT 2012
Year: 2012

In modern wireless networks, interference is no longer negligible since each cell becomes smaller to support high throughput. The reduced size of each cell forces to install many cells, and consequently causes to increase inter-cell interference at many cell edge areas. This paper considers a practical way of mitigating interference at the receiver equipped with multiple antennas in interference channels. Recently, it is shown that the capacity region of interference channels over point-to-point codes could be established with a combination of two schemes: treating interference as noise and jointly decoding both desired and interference signals. In practice, the first scheme is straightforwardly implementable, but the second scheme needs impractically huge computational burden at the receiver. Within a practical range of complexity, this paper proposes the interference-aware successive decoding (IASD) algorithm which successively decodes desired and interference signals while updating a priori information of both signals. When multiple decoders are allowed to be used, the proposed IASD can be extended to interference-aware parallel decoding (IAPD). The proposed algorithm is analyzed with extrinsic information transfer (EXIT) chart so as to show that the interference decoding is advantageous to improve the performance. Simulation results demonstrate that the proposed algorithm significantly outperforms interference non-decoding algorithms.