Search results for: open innovation networks

Authors: Junghoon Lee, Gyung-Leen Park, Ho-Young Kwak, Cheol Min Kim

Abstract:

This paper presents the design and implements the prototype of an intelligent data processing framework in ubiquitous sensor networks. Much focus is put on how to handle the sensor data stream as well as the interoperability between the low-level sensor data and application clients. Our framework first addresses systematic middleware which mitigates the interaction between the application layer and low-level sensors, for the sake of analyzing a great volume of sensor data by filtering and integrating to create value-added context information. Then, an agent-based architecture is proposed for real-time data distribution to efficiently forward a specific event to the appropriate application registered in the directory service via the open interface. The prototype implementation demonstrates that our framework can host a sophisticated application on the ubiquitous sensor network and it can autonomously evolve to new middleware, taking advantages of promising technologies such as software agents, XML, cloud computing, and the like.

Keywords: sensor network, intelligent farm, middleware, event detection

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Authors: Charles D. Otine, Samuel B. Kucel, Lena Trojer

Abstract:

Selecting the data modeling technique for an information system is determined by the objective of the resultant data model. Dimensional modeling is the preferred modeling technique for data destined for data warehouses and data mining, presenting data models that ease analysis and queries which are in contrast with entity relationship modeling. The establishment of data warehouses as components of information system landscapes in many organizations has subsequently led to the development of dimensional modeling. This has been significantly more developed and reported for the commercial database management systems as compared to the open sources thereby making it less affordable for those in resource constrained settings. This paper presents dimensional modeling of HIV patient information using open source modeling tools. It aims to take advantage of the fact that the most affected regions by the HIV virus are also heavily resource constrained (sub-Saharan Africa) whereas having large quantities of HIV data. Two HIV data source systems were studied to identify appropriate dimensions and facts these were then modeled using two open source dimensional modeling tools. Use of open source would reduce the software costs for dimensional modeling and in turn make data warehousing and data mining more feasible even for those in resource constrained settings but with data available.

Keywords: About Database, Data Mining, Data warehouse, Dimensional Modeling, Open Source.

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Authors: Myungsook Klassen

Abstract:

Training neural networks to capture an intrinsic property of a large volume of high dimensional data is a difficult task, as the training process is computationally expensive. Input attributes should be carefully selected to keep the dimensionality of input vectors relatively small. Technical indexes commonly used for stock market prediction using neural networks are investigated to determine its effectiveness as inputs. The feed forward neural network of Levenberg-Marquardt algorithm is applied to perform one step ahead forecasting of NASDAQ and Dow stock prices.

Keywords: Stock Market Prediction, Neural Networks, Levenberg-Marquadt Algorithm, Technical Indexes

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Authors: J. Kasigwa, V. Baryamureeba, D. Williams

Abstract:

The goal of admission control is to support the Quality of Service demands of real-time applications via resource reservation in IP networks. In this paper we introduce a novel Dynamic Admission Control (DAC) mechanism for IP networks. The DAC dynamically allocates network resources using the previous network pattern for each path and uses the dynamic admission algorithm to improve bandwidth utilization using bandwidth brokers. We evaluate the performance of the proposed mechanism through trace-driven simulation experiments in view point of blocking probability, throughput and normalized utilization.

Keywords: Bandwidth broker, dynamic admission control(DAC), IP networks, quality of service, real-time flows.

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Authors: Yuri Nikitin, Veronika Rukas

Abstract:

Within the framework of the FP7 project "START" the cooperation with European research centres has had a positive impact on raising the level of innovation researches and the introduction of innovations Institute for Superhard Materials of the National Academy of Sciences (ISM NAS) of Ukraine in the economy of Europe and Ukraine, which in turn permits to speeds up the way for Ukrainian science to the European research area through the creation in Ukraine the scientific organizations of innovative type.

Keywords: Programs of the EU, innovative scientific results, innovation competence of the staff, commercialization in business of industry of the Europe and Ukraine.

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Authors: Maninder Kaur Gill, Alpana Agarwal

Abstract:

It is practically not feasible to measure the open-loop voltage gain of the operational amplifier in the open loop configuration. It is because the open-loop voltage gain of the operational amplifier is very large. In order to avoid the saturation of the output voltage, a very small input should be given to operational amplifier which is not possible to be measured practically by a digital multimeter. A test circuit for measurement of open loop voltage gain of an operational amplifier has been proposed and verified using simulation tools as well as by experimental methods on breadboard. The main advantage of this test circuit is that it is simple, fast, accurate, cost effective, and easy to handle even on a breadboard. The test circuit requires only the device under test (DUT) along with resistors. This circuit has been tested for measurement of open loop voltage gain for different operational amplifiers. The underlying goal is to design testable circuits for various analog devices that are simple to realize in VLSI systems, giving accurate results and without changing the characteristics of the original system. The DUTs used are LM741CN and UA741CP. For LM741CN, the simulated gain and experimentally measured gain (average) are calculated as 89.71 dB and 87.71 dB, respectively. For UA741CP, the simulated gain and experimentally measured gain (average) are calculated as 101.15 dB and 105.15 dB, respectively. These values are found to be close to the datasheet values.

Keywords: Device under test, open-loop voltage gain, operational amplifier, test circuit.

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Authors: Ghazi AL-Sukkar, Iyad Jafar, Khalid Darabkh, Raed Al-Zubi, Mohammed Hawa

Abstract:

Smart Grids employ wireless sensor networks for their control and monitoring. Sensors are characterized by limitations in the processing power, energy supply and memory spaces, which require a particular attention on the design of routing and data management algorithms. Since most routing algorithms for sensor networks, focus on finding energy efficient paths to prolong the lifetime of sensor networks, the power of sensors on efficient paths depletes quickly, and consequently sensor networks become incapable of monitoring events from some parts of their target areas. In consequence, the design of routing protocols should consider not only energy efficiency paths, but also energy efficient algorithms in general. In this paper we propose an energy efficient routing protocol for wireless sensor networks without the support of any location information system. The reliability and the efficiency of this protocol have been demonstrated by simulation studies where we compare them to the legacy protocols. Our simulation results show that these algorithms scale well with network size and density.

Keywords: Data-centric storage, Dynamic Address Allocation, Sensor networks, Smart Grid Communications.

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Authors: S. Mousavian, D. Ashouri, F. Mousavian, V. Nikkhah Rashidabad, N. Ghazinia

Abstract:

PH, temperature and time of extraction of each stage,  agitation speed and delay time between stages effect on efficiency of  zinc extraction from concentrate. In this research, efficiency of zinc  extraction was predicted as a function of mentioned variable by  artificial neural networks (ANN). ANN with different layer was  employed and the result show that the networks with 8 neurons in  hidden layer has good agreement with experimental data.

 

Keywords: Zinc extraction, Efficiency, Neural networks, Operating condition.

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Authors: Sorin Valcan, Mihail Găianu

Abstract:

Labeling is a very costly and time consuming process which aims to generate datasets for training neural networks in several functionalities and projects. For driver monitoring system projects, the need of labeled images has a significant impact on the budget and distribution of effort. This paper presents the modifications done to a ground truth data generation algorithm for 2D eyes location on infrared images with drivers in order to improve the quality of the data and performance of the trained neural networks. The algorithm restrictions become tougher which makes it more accurate but also less constant. The resulting dataset becomes smaller and shall not be altered by any kind of manual labels adjustment before being used in the neural networks training process. These changes resulted in a much better performance of the trained neural networks.

Keywords: Labeling automation, infrared camera, driver monitoring, eye detection, Convolutional Neural Networks.

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Authors: Wan Norhayate Wan Daud, Fakhrul Anwar Zainol, Maslina Mansor

Abstract:

The study was conducted to produce case studies from the Malaysian public universities stands point East Coast of Malaysia. The aim of this study is to analyze the effects of knowledge management on human capital toward organizational innovation. The focus point of this study is on the management member in the faculties of these three Malaysian Public Universities in the East Coast state of Peninsular Malaysia. In this case, respondents who agreed to further participate in the research will be invited to a one-hour face-to-face semi-structured, in-depth interview. As a result, the sample size for this study was 3 deans of Faculty of Management. Lastly, this study tries to recommend the framework of organizational innovation in Malaysian Public Universities.

Keywords: Human Capital, Knowledge Management, Organizational Innovation, Public University.

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Authors: Goh Chin Hock, Chandan Kumar Chakrabarty, Mohammad Hadi Badjian, Sanjay Devkumar

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This paper presents a microstrip meandered open circuited stub with bandstop characteristic. The proposed structure is designed on a high frequency laminate with dielectric constant of 4.0 and board thickness of 0.508 millimeters. The scattering parameters and electromagnetic field distributions at various frequencies are investigated by modeling the structure with three dimensional electromagnetic simulation tool. In order to describe the resonant and bandstop characteristic of the meandered open circuited stub, a Smith chart as well as electric field at various frequencies and phases is illustrated accordingly. The structure can be an alternative method in suppressing the harmonic response of a bandpass filter.

Keywords: Bandstop, Equivalent Lumped Element Model, Electromagnetic Model, Meandered Open Circuited Stub

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Authors: A. U. Haque, W. Asrar, A. A. Omar, E. Sulaeman, J. S Mohamed Ali

Abstract:

Open jet testing is a valuable testing technique which provides the desired results with reasonable accuracy. It has been used in past for the airships and now has recently been applied for the hybrid ones, having more non-buoyant force coming from the wings, empennage and the fuselage. In the present review work, an effort has been done to review the challenges involved in open jet testing. In order to shed light on the application of this technique, the experimental results of two different configurations are presented. Although, the aerodynamic results of such vehicles are unique to its own design; however, it will provide a starting point for planning any future testing. Few important testing areas which need more attention are also highlighted. Most of the hybrid buoyant aerial vehicles are unconventional in shape and there experimental data is generated, which is unique to its own design.

Keywords: Open jet testing, aerodynamics, hybrid buoyant aerial vehicles, airships.

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

Abstract:

Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution [(γ)_i^∞] for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.

Keywords: Ionic liquid, Neural networks, VLE, Dilute solution.

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Authors: JooHyung Oh, Dongwan Kang, Sekwon Kim, ChaeTae Im

Abstract:

Currently, there has been a 3G mobile networks data traffic explosion due to the large increase in the number of smartphone users. Unlike a traditional wired infrastructure, 3G mobile networks have limited wireless resources and signaling procedures for complex wireless resource management. And mobile network security for various abnormal and malicious traffic technologies was not ready. So Malicious or potentially malicious traffic originating from mobile malware infected smart devices can cause serious problems to the 3G mobile networks, such as DoS and scanning attack in wired networks. This paper describes the DoS security threat in the 3G mobile network and proposes a detection technology.

Keywords: 3G, WCDMA, DoS, Security Threat

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Authors: Shai Sarussi

Abstract:

Let S be an integral domain with field of fractions F and let A be an F-algebra. An S-subalgebra R of A is called S-nice if R∩F = S and the localization of R with respect to S \{0} is A. Denoting by W the set of all S-nice subalgebras of A, and defining a notion of open sets on W, one can view W as a T0-Alexandroff space. A characterization of the property of immediate neighbors in an Alexandroff topological space is given, in terms of closed and open subsets of appropriate subspaces. Moreover, two special subspaces of W are introduced, and a way in which their closed and open subsets induce W is presented.

Keywords: Algebras over integral domains, Alexandroff topology, immediate neighbors, integral domains.

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Authors: Farhad Asadi, S. Hossein Sadati

Abstract:

This paper presents a prediction performance of feedforward Multilayer Perceptron (MLP) and Echo State Networks (ESN) trained with extended Kalman filter. Feedforward neural networks and ESN are powerful neural networks which can track and predict nonlinear signals. However, their tracking performance depends on the specific signals or data sets, having the risk of instability accompanied by large error. In this study we explore this process by applying different network size and leaking rate for prediction of nonlinear or chaotic signals in MLP neural networks. Major problems of ESN training such as the problem of initialization of the network and improvement in the prediction performance are tackled. The influence of coefficient of activation function in the hidden layer and other key parameters are investigated by simulation results. Extended Kalman filter is employed in order to improve the sequential and regulation learning rate of the feedforward neural networks. This training approach has vital features in the training of the network when signals have chaotic or non-stationary sequential pattern. Minimization of the variance in each step of the computation and hence smoothing of tracking were obtained by examining the results, indicating satisfactory tracking characteristics for certain conditions. In addition, simulation results confirmed satisfactory performance of both of the two neural networks with modified parameterization in tracking of the nonlinear signals.

Keywords: Feedforward neural networks, nonlinear signal prediction, echo state neural networks approach, leaking rates, capacity of neural networks.

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Authors: Liping Zhang, Kelin Li

Abstract:

In this paper, a class of impulsive BAM fuzzy cellular neural networks with time delays in the leakage terms is formulated and investigated. By establishing a delay differential inequality and M-matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with time delays in the leakage terms are obtained. In particular, a precise estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive perturbation intention. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.

Keywords: Global exponential stability, bidirectional associative memory, fuzzy cellular neural networks, leakage delays, impulses.

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Authors: Kanittha Kanokkanjana, Savitri Garivait

Abstract:

This study focuses on emission of black carbon (BC) from field open burning of corn residues. Real-time BC concentration was measured by Micro Aethalometer from field burning and simulated open burning in a chamber (SOC) experiments. The average concentration of BC was 1.18±0.47 mg/m3 in the field and 0.89±0.63 mg/m3 in the SOC. The deduced emission factor from field experiments was 0.50±0.20 gBC/kgdm, and 0.56±0.33 gBC/kgdm from SOC experiment, which are in good agreement with other studies. In 2007, the total burned area of corn crop was 8,000 ha, resulting in an emission load of BC 20 ton corresponding to 44.5 million kg CO2 equivalent. Therefore, the control of open burning in corn field represents a significant global warming reduction option.

Keywords: Black carbon, corn field residues, global warming, mitigation option

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Authors: Z. Shaaban

Abstract:

This paper presents a new approach to tackle the problem of recognizing machine-printed Arabic texts. Because of the difficulty of recognizing cursive Arabic words, the text has to be normalized and segmented to be ready for the recognition stage. The new scheme for recognizing Arabic characters depends on multiple parallel neural networks classifier. The classifier has two phases. The first phase categories the input character into one of eight groups. The second phase classifies the character into one of the Arabic character classes in the group. The system achieved high recognition rate.

Keywords: Neural Networks, character recognition, feature extraction, multiple networks, Arabic text.

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Authors: Lili Wang

Abstract:

By using the estimation of the Cauchy matrix of linear impulsive differential equations and Banach fixed point theorem as well as Gronwall-Bellman’s inequality, some sufficient conditions are obtained for the existence and exponential stability of almost periodic solution for an impulsive neural networks with distributed delays. An example is presented to illustrate the feasibility and  effectiveness of the results.

Keywords: Almost periodic solution, Exponential stability, Neural networks, Impulses.

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Authors: Jung-Hyun Kim, Jihyung Kim, Kwangjae Lim, Dong Seung Kwon

Abstract:

In this paper, our focus is to assure a global frequency synchronization in OFDMA-based wireless mesh networks with local information. To acquire the global synchronization in distributed manner, we propose a novel distributed frequency synchronization (DFS) method. DFS is a method that carrier frequencies of distributed nodes converge to a common value by repetitive estimation and averaging step and sharing step. Experimental results show that DFS achieves noteworthy better synchronization success probability than existing schemes in OFDMA-based mesh networks where the estimation error is presented.

Keywords: OFDMA systems, Frequency synchronization, Distributed networks, Multiple groups.

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Authors: J.H. Park, S. Lakshmanan, H.Y. Jung, S.M. Lee

Abstract:

This paper is concerned with the delay-distributiondependent stability criteria for bidirectional associative memory (BAM) neural networks with time-varying delays. Based on the Lyapunov-Krasovskii functional and stochastic analysis approach, a delay-probability-distribution-dependent sufficient condition is derived to achieve the globally asymptotically mean square stable of the considered BAM neural networks. The criteria are formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages. Finally, a numerical example and its simulation is given to demonstrate the usefulness and effectiveness of the proposed results.

Keywords: BAM neural networks, Probabilistic time-varying delays, Stability criteria.

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Authors: Guang Zhou, Shouming Zhong

Abstract:

In this paper, we investigate the problem of the existence, uniqueness and global asymptotic stability of the equilibrium point for a class of neural networks, the neutral system has mixed time delays and parameter uncertainties. Under the assumption that the activation functions are globally Lipschitz continuous, we drive a new criterion for the robust stability of a class of neural networks with time delays by utilizing the Lyapunov stability theorems and the Homomorphic mapping theorem. Numerical examples are given to illustrate the effectiveness and the advantage of the proposed main results.

Keywords: Neural networks, Delayed systems, Lyapunov function, Stability analysis.

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Authors: P. Vazan, P. Tanuska, M. Kebisek, S. Duchovicova

Abstract:

The paper deals with communication standards for control and production system. The authors formulate the requirements for communication security protection. The paper is focused on application protocols of the industrial networks and their basic classification. The typical attacks are analysed and the safety protection, based on requirements for specific industrial network is suggested and defined in this paper.

Keywords: Application protocols, communication standards, industrial networks.

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Authors: Harri Jalonen

Abstract:

Faced with social and health system capacity constraints and rising and changing demand for welfare services, governments and welfare providers are increasingly relying on innovation to help support and enhance services. However, the evidence reported by several studies indicates that the realization of that potential is not an easy task. Innovations can be deemed inherently complex to implement and operate, because many of them involve a combination of technological and organizational renewal within an environment featuring a diversity of stakeholders. Many public welfare service innovations are markedly systemic in their nature, which means that they emerge from, and must address, the complex interplay between political, administrative, technological, institutional and legal issues. This paper suggests that stakeholders dealing with systemic innovation in welfare services must deal with ambiguous and incomplete information in circumstances of uncertainty. Employing a literature review methodology and case study, this paper identifies, categorizes and discusses different aspects of the uncertainty of systemic innovation in public welfare services, and argues that uncertainty can be classified into eight categories: technological uncertainty, market uncertainty, regulatory/institutional uncertainty, social/political uncertainty, acceptance/legitimacy uncertainty, managerial uncertainty, timing uncertainty and consequence uncertainty.

Keywords: Systemic innovation, uncertainty, welfare services

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Authors: Hazem M. El-Bakry, Nikos Mastorakis

Abstract:

Fast forecasting of stock market prices is very important for strategic planning. In this paper, a new approach for fast forecasting of stock market prices is presented. Such algorithm uses new high speed time delay neural networks (HSTDNNs). The operation of these networks relies on performing cross correlation in the frequency domain between the input data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented HSTDNNs is less than that needed by traditional time delay neural networks (TTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Fast Forecasting, Stock Market Prices, Time Delay NeuralNetworks, Cross Correlation, Frequency Domain.

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Authors: Vrince Vimal, Madhav J. Nigam

Abstract:

Wireless sensor networks have enticed much of the spotlight from researchers all around the world, owing to its extensive applicability in agricultural, industrial and military fields. Energy conservation node deployment stratagems play a notable role for active implementation of Wireless Sensor Networks. Clustering is the approach in wireless sensor networks which improves energy efficiency in the network. The clustering algorithm needs to have an optimum size and number of clusters, as clustering, if not implemented properly, cannot effectively increase the life of the network. In this paper, an algorithm has been proposed to address connectivity issues with the aim of ensuring the uniform energy consumption of nodes in every part of the network. The results obtained after simulation showed that the proposed algorithm has an edge over existing algorithms in terms of throughput and networks lifetime.

Keywords: WSN, random deployment, clustering, isolated nodes, network lifetime.

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Authors: Lili Wang, Meng Hu

Abstract:

In this paper, based on almost periodic functional hull theory and M-matrix theory, some sufficient conditions are established for the existence and uniqueness of positive almost periodic solution for a class of BAM neural networks with time-varying delays. An example is given to illustrate the main results.

Keywords: Delayed BAM neural networks, Hull theorem, Mmatrix, Almost periodic solution, Global exponential stability.

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Authors: Weifeng Pan

Abstract:

The stability of a software system is one of the most important quality attributes affecting the maintenance effort. Many techniques have been proposed to support the analysis of software stability at the architecture, file, and class level of software systems, but little effort has been made for that at the feature (i.e., method and attribute) level. And the assumptions the existing techniques based on always do not meet the practice to a certain degree. Considering that, in this paper, we present a novel metric, Stability of Software (SoS), to measure the stability of object-oriented software systems by software change propagation analysis using a simulation way in software dependency networks at feature level. The approach is evaluated by case studies on eight open source Java programs using different software structures (one employs design patterns versus one does not) for the same object-oriented program. The results of the case studies validate the effectiveness of the proposed metric. The approach has been fully automated by a tool written in Java.

Keywords: Software stability, change propagation, design pattern, software maintenance, object-oriented (OO) software.

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Authors: Biao Qin, Jin Huang, Jiaojiao Ren, Wei Kang

Abstract:

This paper deals with the problem of passivity analysis for stochastic neural networks with leakage, discrete and distributed delays. By using delay partitioning technique, free weighting matrix method and stochastic analysis technique, several sufficient conditions for the passivity of the addressed neural networks are established in terms of linear matrix inequalities (LMIs), in which both the time-delay and its time derivative can be fully considered. A numerical example is given to show the usefulness and effectiveness of the obtained results.

Keywords: Passivity, Stochastic neural networks, Multiple time delays, Linear matrix inequalities (LMIs).

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