Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 38

Search results for: updates

38 Principle Components Updates via Matrix Perturbations

Authors: Aiman Elragig, Hanan Dreiwi, Dung Ly, Idriss Elmabrook

Abstract:

This paper highlights a new approach to look at online principle components analysis (OPCA). Given a data matrix X R,^m x n we characterise the online updates of its covariance as a matrix perturbation problem. Up to the principle components, it turns out that online updates of the batch PCA can be captured by symmetric matrix perturbation of the batch covariance matrix. We have shown that as n→ n0 >> 1, the batch covariance and its update become almost similar. Finally, utilize our new setup of online updates to find a bound on the angle distance of the principle components of X and its update.

Keywords: Online data updates, covariance matrix, online principle component analysis (OPCA), matrix perturbation.

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37 QoS Routing in Wired Sensor Networks with Partial Updates

Authors: Arijit Ghos, Tony Gigargis

Abstract:

QoS routing is an important component of Traffic Engineering in networks that provide QoS guarantees. QoS routing is dependent on the link state information which is typically flooded across the network. This affects both the quality of the routing and the utilization of the network resources. In this paper, we examine establishing QoS routes with partial state updates in wired sensor networks.

Keywords:

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36 Continuous FAQ Updating for Service Incident Ticket Resolution

Authors: Kohtaroh Miyamoto

Abstract:

As enterprise computing becomes more and more complex, the costs and technical challenges of IT system maintenance and support are increasing rapidly. One popular approach to managing IT system maintenance is to prepare and use a FAQ (Frequently Asked Questions) system to manage and reuse systems knowledge. Such a FAQ system can help reduce the resolution time for each service incident ticket. However, there is a major problem where over time the knowledge in such FAQs tends to become outdated. Much of the knowledge captured in the FAQ requires periodic updates in response to new insights or new trends in the problems addressed in order to maintain its usefulness for problem resolution. These updates require a systematic approach to define the exact portion of the FAQ and its content. Therefore, we are working on a novel method to hierarchically structure the FAQ and automate the updates of its structure and content. We use structured information and the unstructured text information with the timelines of the information in the service incident tickets. We cluster the tickets by structured category information, by keywords, and by keyword modifiers for the unstructured text information. We also calculate an urgency score based on trends, resolution times, and priorities. We carefully studied the tickets of one of our projects over a 2.5-year time period. After the first 6 months we started to create FAQs and confirmed they improved the resolution times. We continued observing over the next 2 years to assess the ongoing effectiveness of our method for the automatic FAQ updates. We improved the ratio of tickets covered by the FAQ from 32.3% to 68.9% during this time. Also, the average time reduction of ticket resolution was between 31.6% and 43.9%. Subjective analysis showed more than 75% reported that the FAQ system was useful in reducing ticket resolution times.

Keywords: FAQ System, Resolution Time, Service Incident Tickets, IT System Maintenance.

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35 A Study on Neural Network Training Algorithm for Multiface Detection in Static Images

Authors: Zulhadi Zakaria, Nor Ashidi Mat Isa, Shahrel A. Suandi

Abstract:

This paper reports the study results on neural network training algorithm of numerical optimization techniques multiface detection in static images. The training algorithms involved are scale gradient conjugate backpropagation, conjugate gradient backpropagation with Polak-Riebre updates, conjugate gradient backpropagation with Fletcher-Reeves updates, one secant backpropagation and resilent backpropagation. The final result of each training algorithms for multiface detection application will also be discussed and compared.

Keywords: training algorithm, multiface, static image, neural network

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34 Fault Tolerance in Distributed Database Systems

Authors: M. A. Adeboyejo, O. O. Adeosun

Abstract:

Pioneer networked systems assume that connections are reliable, and a faulty operation will be considered in case of losing a connection. Transient connections are typical of mobile devices. Areas of application of data sharing system such as these, lead to the conclusion that network connections may not always be reliable, and that the conventional approaches can be improved. Nigerian commercial banking industry is a critical system whose operation is increasingly becoming dependent on information technology (IT) driven information system. The proposed solution to this problem makes use of a hierarchically clustered network structure which we selected to reflect (as much as possible) the typical organizational structure of the Nigerian commercial banks. Representative transactions such as data updates and replication of the results of such updates were used to simulate the proposed model to show its applicability.

Keywords: Dependability, reliability, data redundancy.

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33 A Logic Approach to Database Dynamic Updating

Authors: Daniel Stamate

Abstract:

We introduce a logic-based framework for database updating under constraints. In our framework, the constraints are represented as an instantiated extended logic program. When performing an update, database consistency may be violated. We provide an approach of maintaining database consistency, and study the conditions under which the maintenance process is deterministic. We show that the complexity of the computations and decision problems presented in our framework is in each case polynomial time.

Keywords: Databases, knowledge bases, constraints, updates, minimal change, consistency.

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32 Variable Regularization Parameter Normalized Least Mean Square Adaptive Filter

Authors: Young-Seok Choi

Abstract:

We present a normalized LMS (NLMS) algorithm with robust regularization. Unlike conventional NLMS with the fixed regularization parameter, the proposed approach dynamically updates the regularization parameter. By exploiting a gradient descent direction, we derive a computationally efficient and robust update scheme for the regularization parameter. In simulation, we demonstrate the proposed algorithm outperforms conventional NLMS algorithms in terms of convergence rate and misadjustment error.

Keywords: Regularization, normalized LMS, system identification, robustness.

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31 New Approach for Manipulation of Stratified Programs

Authors: Amel Grissa-Touzi, Chadlia Jerad, Habib Ounelli

Abstract:

Negation is useful in the majority of the real world applications. However, its introduction leads to semantic and canonical problems. We propose in this paper an approach based on stratification to deal with negation problems. This approach is based on an extension of predicates nets. It is characterized with two main contributions. The first concerns the management of the whole class of stratified programs. The second contribution is related to usual operations optimizations on stratified programs (maximal stratification, incremental updates ...).

Keywords: stratified programs, stratification, standard model, update operations, SEPN formalism.

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30 STRPRO Tool for Manipulation of Stratified Programs Based on SEPN

Authors: Chadlia Jerad, Amel Grissa-Touzi, Habib Ounelli

Abstract:

Negation is useful in the majority of the real world applications. However, its introduction leads to semantic and canonical problems. SEPN nets are well adapted extension of predicate nets for the definition and manipulation of stratified programs. This formalism is characterized by two main contributions. The first concerns the management of the whole class of stratified programs. The second contribution is related to usual operations optimization (maximal stratification, incremental updates ...). We propose, in this paper, useful algorithms for manipulating stratified programs using SEPN. These algorithms were implemented and validated with STRPRO tool.

Keywords: stratified programs, update operations, SEPN formalism, algorithms, STRPRO.

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29 An Android Geofencing App for Autonomous Remote Switch Control

Authors: Jamie Wong, Daisy Sang, Chang-Shyh Peng

Abstract:

Geofence is a virtual fence defined by a preset physical radius around a target location. Geofencing App provides location-based services which define the actionable operations upon the crossing of a geofence. Geofencing requires continual location tracking, which can consume noticeable amount of battery power. Additionally, location updates need to be frequent and accurate or order so that actions can be triggered within an expected time window after the mobile user navigate through the geofence. In this paper, we build an Android mobile geofencing Application to remotely and autonomously control a power switch.

Keywords: Location based service, geofence, autonomous, remote switch.

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28 HTML5 Online Learning Application with Offline Web, Location Based, Animated Web, Multithread, and Real-Time Features

Authors: Sheetal R. Jadhwani, Daisy Sang, Chang-Shyh Peng

Abstract:

Web applications are an integral part of modem life. They are mostly based upon the HyperText Markup Language (HTML). While HTML meets the basic needs, there are some shortcomings. For example, applications can cease to work once user goes offline, real-time updates may be lagging, and user interface can freeze on computationally intensive tasks. The latest language specification HTML5 attempts to rectify the situation with new tools and protocols. This paper studies the new Web Storage, Geolocation, Web Worker, Canvas, and Web Socket APIs, and presents applications to test their features and efficiencies.

Keywords: HTML5, Web Worker, Canvas, Web Socket.

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27 An Estimation of the Performance of HRLS Algorithm

Authors: Shazia Javed, Noor Atinah Ahmad

Abstract:

The householder RLS (HRLS) algorithm is an O(N2) algorithm which recursively updates an arbitrary square-root of the input data correlation matrix and naturally provides the LS weight vector. A data dependent householder matrix is applied for such an update. In this paper a recursive estimate of the eigenvalue spread and misalignment of the algorithm is presented at a very low computational cost. Misalignment is found to be highly sensitive to the eigenvalue spread of input signals, output noise of the system and exponential window. Simulation results show noticeable degradation in the misalignment by increase in eigenvalue spread as well as system-s output noise, while exponential window was kept constant.

Keywords: HRLS algorithm, eigenvalue spread, misalignment.

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26 A Preemptive Link State Spanning Tree Source Routing Scheme for Opportunistic Data Forwarding in MANET

Authors: R. Poonkuzhali, M. Y. Sanavullah, A. Sabari

Abstract:

Opportunistic Data Forwarding (ODF) has drawn much attention in mobile adhoc networking research in recent years. The effectiveness of ODF in MANET depends on a suitable routing protocol which provides a powerful source routing services. PLSR is featured by source routing, loop free and small routing overhead. The update messages in PLSR are integrated into a tree structure and no need to time stamp routing updates which reduces the routing overhead.

Keywords: Mobile ad hoc network (MANET), Opportunistic data forwarding (ODF), Preemptive link state spanning tree routing (PLSR), Depth First Search (DFS).

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25 Evolution, Tendencies and Impact of Standardization of Input/Output Platforms in Full Scale Simulators for Training Power Plant Operators

Authors: Zabre Eric, Román Rafael

Abstract:

This article presents the evolution and technological changes implemented on the full scale simulators developed by the Simulation Department of the Instituto de Investigaciones Eléctricas1 (Mexican Electric Research Institute) and located at different training centers around the Mexican territory, and allows US to know the last updates, basically from the input/output view point, of the current simulators at some facilities of the electrical sector as well as the compatible industry of the electrical manufactures and industries such as Comision Federal de Electricidad (CFE*, The utility Mexican company). Tendencies of these developments and impact within the operators- scope are also presented.

Keywords: Control room, communication protocol, instructor console, modeling, controller, training simulator

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24 On the Sphere Method of Linear Programming Using Multiple Interior Points Approach

Authors: Job H. Domingo, Carolina Bancayrin-Baguio

Abstract:

The Sphere Method is a flexible interior point algorithm for linear programming problems. This was developed mainly by Professor Katta G. Murty. It consists of two steps, the centering step and the descent step. The centering step is the most expensive part of the algorithm. In this centering step we proposed some improvements such as introducing two or more initial feasible solutions as we solve for the more favorable new solution by objective value while working with the rigorous updates of the feasible region along with some ideas integrated in the descent step. An illustration is given confirming the advantage of using the proposed procedure.

Keywords: Interior point, linear programming, sphere method, initial feasible solution, feasible region, centering and descent steps, optimal solution.

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23 CBCTL: A Reasoning System of TemporalEpistemic Logic with Communication Channel

Authors: Suguru Yoshioka, Satoshi Tojo

Abstract:

This paper introduces a temporal epistemic logic CBCTL that updates agent-s belief states through communications in them, based on computational tree logic (CTL). In practical environments, communication channels between agents may not be secure, and in bad cases agents might suffer blackouts. In this study, we provide inform* protocol based on ACL of FIPA, and declare the presence of secure channels between two agents, dependent on time. Thus, the belief state of each agent is updated along with the progress of time. We show a prover, that is a reasoning system for a given formula in a given a situation of an agent ; if it is directly provable or if it could be validated through the chains of communications, the system returns the proof.

Keywords: communication channel, computational tree logic, reasoning system, temporal epistemic logic.

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22 Incremental Learning of Independent Topic Analysis

Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

Abstract:

In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: Text mining, topic extraction, independent, incremental, independent component analysis.

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21 Qmulus – A Cloud Driven GPS Based Tracking System for Real-Time Traffic Routing

Authors: Niyati Parameswaran, Bharathi Muthu, Madiajagan Muthaiyan

Abstract:

This paper presents Qmulus- a Cloud Based GPS Model. Qmulus is designed to compute the best possible route which would lead the driver to the specified destination in the shortest time while taking into account real-time constraints. Intelligence incorporated to Qmulus-s design makes it capable of generating and assigning priorities to a list of optimal routes through customizable dynamic updates. The goal of this design is to minimize travel and cost overheads, maintain reliability and consistency, and implement scalability and flexibility. The model proposed focuses on reducing the bridge between a Client Application and a Cloud service so as to render seamless operations. Qmulus-s system model is closely integrated and its concept has the potential to be extended into several other integrated applications making it capable of adapting to different media and resources.

Keywords: Cloud Services, GPS, Real-Time Constraints, Shortest Path, System Management and Traffic Routing

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20 Precombining Adaptive LMMSE Detection for DS-CDMA Systems in Time Varying Channels: Non Blind and Blind Approaches

Authors: M. D. Kokate, T. R. Sontakke, P. W. Wani

Abstract:

This paper deals with an adaptive multiuser detector for direct sequence code division multiple-access (DS-CDMA) systems. A modified receiver, precombinig LMMSE is considered under time varying channel environment. Detector updating is performed with two criterions, mean square estimation (MSE) and MOE optimization technique. The adaptive implementation issues of these two schemes are quite different. MSE criterion updates the filter weights by minimizing error between data vector and adaptive vector. MOE criterion together with canonical representation of the detector results in a constrained optimization problem. Even though the canonical representation is very complicated under time varying channels, it is analyzed with assumption of average power profile of multipath replicas of user of interest. The performance of both schemes is studied for practical SNR conditions. Results show that for poor SNR, MSE precombining LMMSE is better than the blind precombining LMMSE but for greater SNR, MOE scheme outperforms with better result.

Keywords: LMMSE, MOE, MUD.

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19 ‘The Right to Information’: A Malaysian Political Blog Readers’ Perspective

Authors: Norraihan Zakaria, Abdul Rahman Othman

Abstract:

Political blogs are one of the pivotal alternative communication channels for political news in Malaysia. Many have argued that the mushrooming of political blogs nurtures the effective realization of human rights in the country. The paper studies the ‘Malaysian political blog readers–human rights’ relationship by exploring these questions: Has traditional mainstream media become obsolete with the rise of political blogosphere? Why do blog readers visit political blogs? A survey was conducted and the findings revealed that traditional mainstream media is still a pertinent source for political news in the country. Apart from acquiring the latest political updates quickly and at anytime, blog readers compare the news published in political blogs with the ones reported in traditional mainstream media. This suggests that freedom of information is deemed as one of the prime motives for Malaysian blog readers clinging to political blogosphere.

Keywords: Freedom of information, Human rights, Malaysian political blog readers, Malaysian political blogosphere.

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18 A Study of Adaptive Fault Detection Method for GNSS Applications

Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

Abstract:

This study is purposed to develop an efficient fault detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive noise covariance estimation. Due to the dependence on radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. In the proposed method, the pseudorange and carrier-phase measurement noise covariances are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. The test statistics for fault detection are generated by the estimated measurement noise covariances. To evaluate the fault detection capability, intentional faults were added to the filed-collected measurements. The experiment result shows that the proposed method is efficient in detecting unhealthy measurements and improves GNSS positioning accuracy against fault occurrences.

Keywords: Adaptive estimation, fault detection, GNSS, residual.

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17 Dynamic Process Monitoring of an Ammonia Synthesis Fixed-Bed Reactor

Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

Abstract:

This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: Ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling.

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16 DACS3: Embedding Individual Ant Behavior in Ant Colony System

Authors: Zulaiha Ali Othman, Helmi Md Rais, Abdul Razak Hamdan

Abstract:

Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). Ants communicate to each other through chemical substances called pheromones. Modeling individual ants- ability to manipulate this substance can help an ACS find the best solution. This paper introduces a Dynamic Ant Colony System with threelevel updates (DACS3) that enhance an existing ACS. Experiments were conducted to observe single ant behavior in a colony of Malaysian House Red Ants. Such behavior was incorporated into the DACS3 algorithm. We benchmark the performance of DACS3 versus DACS on TSP instances ranging from 14 to 100 cities. The result shows that the DACS3 algorithm can achieve shorter distance in most cases and also performs considerably faster than DACS.

Keywords: Dynamic Ant Colony System (DACS), TravelingSalesmen Problem (TSP), Optimization, Swarm Intelligent.

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15 Dynamic Background Updating for Lightweight Moving Object Detection

Authors: Kelemewerk Destalem, Jungjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo

Abstract:

Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a simple moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Keywords: Background subtraction, background updating, real time and lightweight algorithm, temporal difference.

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14 DACS3:Embedding Individual Ant Behavior in Ant Colony System

Authors: Zulaiha Ali Othman, Helmi Md Rais, Abdul Razak Hamdan

Abstract:

Ants are fascinating creatures that demonstrate the ability to find food and bring it back to their nest. Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). Ants communicate to each other through chemical substances called pheromones. Modeling individual ants- ability to manipulate this substance can help an ACS find the best solution. This paper introduces a Dynamic Ant Colony System with threelevel updates (DACS3) that enhance an existing ACS. Experiments were conducted to observe single ant behavior in a colony of Malaysian House Red Ants. Such behavior was incorporated into the DACS3 algorithm. We benchmark the performance of DACS3 versus DACS on TSP instances ranging from 14 to 100 cities. The result shows that the DACS3 algorithm can achieve shorter distance in most cases and also performs considerably faster than DACS.

Keywords: Dynamic Ant Colony System (DACS), Traveling Salesmen Problem (TSP), Optimization, Swarm Intelligent.

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13 An Efficient MIPv6 Return Routability Scheme Based on Geometric Computing

Authors: Yen-Cheng Chen, Fu-Chen Yang

Abstract:

IETF defines mobility support in IPv6, i.e. MIPv6, to allow nodes to remain reachable while moving around in the IPv6 internet. When a node moves and visits a foreign network, it is still reachable through the indirect packet forwarding from its home network. This triangular routing feature provides node mobility but increases the communication latency between nodes. This deficiency can be overcome by using a Binding Update (BU) scheme, which let nodes keep up-to-date IP addresses and communicate with each other through direct IP routing. To further protect the security of BU, a Return Routability (RR) procedure was developed. However, it has been found that RR procedure is vulnerable to many attacks. In this paper, we will propose a lightweight RR procedure based on geometric computing. In consideration of the inherent limitation of computing resources in mobile node, the proposed scheme is developed to minimize the cost of computations and to eliminate the overhead of state maintenance during binding updates. Compared with other CGA-based BU schemes, our scheme is more efficient and doesn-t need nonce tables in nodes.

Keywords: Mobile IPv6, Binding update, Geometric computing.

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12 The Most Secure Smartphone Operating System: A Survey

Authors: Sundus Ayyaz, Saad Rehman

Abstract:

In the recent years, a fundamental revolution in the Mobile Phone technology from just being able to provide voice and short message services to becoming the most essential part of our lives by connecting to network and various app stores for downloading software apps of almost every activity related to our life from finding location to banking from getting news updates to downloading HD videos and so on. This progress in Smart Phone industry has modernized and transformed our way of living into a trouble-free world. The smart phone has become our personal computers with the addition of significant features such as multi core processors, multi-tasking, large storage space, bluetooth, WiFi, including large screen and cameras. With this evolution, the rise in the security threats have also been amplified. In Literature, different threats related to smart phones have been highlighted and various precautions and solutions have been proposed to keep the smart phone safe which carries all the private data of a user. In this paper, a survey has been carried out to find out the most secure and the most unsecure smart phone operating system among the most popular smart phones in use today.

Keywords: Smart phone, operating system, security threats, Android, iOS, Balckberry, Windows.

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11 Environmentally Adaptive Acoustic Echo Suppression for Barge-in Speech Recognition

Authors: Jong Han Joo, Jeong Hun Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

Abstract:

In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. However, the effects of echo path changes should be considered for eliminating the undesired echoes. We describe a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: Acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector.

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10 Inelastic Strength of Laterally Unsupported Top- Loaded Built-Up Slender Beams

Authors: M. Massoud El Sa'adawy, F. F. F. El Dib

Abstract:

Lateral-torsional buckling (LTB) is one of the phenomenae controlling the ultimate bending strength of steel Ibeams carrying distributed loads on top flange. Built-up I-sections are used as main beams and distributors. This study investigates the ultimate bending strength of such beams with sections of different classes including slender elements. The nominal strengths of the selected beams are calculated for different unsupported lengths according to the Provisions of the American Institute of Steel Constructions (AISC-LRFD). These calculations are compared with results of a nonlinear inelastic study using accurate FE model for this type of loading. The goal is to investigate the performance of the provisions for the selected sections. Continuous distributed load at the top flange of the beams was applied at the FE model. Imperfections of different values are implemented to the FE model to examine their effect on the LTB of beams at failure, and hence, their effect on the ultimate strength of beams. The study also introduces a procedure for evaluating the performance of the provisions compared with the accurate FEA results of the selected sections. A simplified design procedure is given and recommendations for future code updates are made.

Keywords: Lateral buckling, Top Loading, Ultimate load, Slender Sections.

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9 Optimizing Dialogue Strategy Learning Using Learning Automata

Authors: G. Kumaravelan, R. Sivakumar

Abstract:

Modeling the behavior of the dialogue management in the design of a spoken dialogue system using statistical methodologies is currently a growing research area. This paper presents a work on developing an adaptive learning approach to optimize dialogue strategy. At the core of our system is a method formalizing dialogue management as a sequential decision making under uncertainty whose underlying probabilistic structure has a Markov Chain. Researchers have mostly focused on model-free algorithms for automating the design of dialogue management using machine learning techniques such as reinforcement learning. But in model-free algorithms there exist a dilemma in engaging the type of exploration versus exploitation. Hence we present a model-based online policy learning algorithm using interconnected learning automata for optimizing dialogue strategy. The proposed algorithm is capable of deriving an optimal policy that prescribes what action should be taken in various states of conversation so as to maximize the expected total reward to attain the goal and incorporates good exploration and exploitation in its updates to improve the naturalness of humancomputer interaction. We test the proposed approach using the most sophisticated evaluation framework PARADISE for accessing to the railway information system.

Keywords: Dialogue management, Learning automata, Reinforcement learning, Spoken dialogue system

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