Search results for: discrete time systems

Authors: Shinji Kawakura, Ryosuke Shibasaki

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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: Advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis.

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Authors: K. Liagkouras, K. Metaxiotis

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Customer relationship management (CRM) systems in business are a reality of the contemporary business world for the last decade or so. Still, there are grey areas regarding the successful implementation and operation of CRM systems in business. This paper, through the systematic study of the CRM implementation paradigm, attempts to identify the most important challenges and opportunities that the CRM systems face in a rapidly changing business world.

Keywords: Customer Relationship Management, CRM, Business, Information Systems.

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Authors: Taweepol Suesut, Arjin Numsomran, Vittaya Tipsuwanporn

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This paper presents the communication network for machine vision system to implement to control systems and logistics applications in industrial environment. The real-time distributed over the network is very important for communication among vision node, image processing and control as well as the distributed I/O node. A robust implementation both with respect to camera packaging and data transmission has been accounted. This network consists of a gigabit Ethernet network and a switch with integrated fire-wall is used to distribute the data and provide connection to the imaging control station and IEC-61131 conform signal integration comprising the Modbus TCP protocol. The real-time and delay time properties each part on the network were considered and worked out in this paper.

Keywords: Distributed Real-Time Automation, Machine Visionand Ethernet.

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Authors: Zixin Liu, Fangwei Chen

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In this Letter, a class of impulsive switched cellular neural networks with time-varying delays is investigated. At the same time, parametric uncertainties assumed to be norm bounded are considered. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions guaranteeing exponential stability for all admissible parametric uncertainties are derived via constructing appropriate Lyapunov functional. One numerical example is provided to illustrate the validity of the main results obtained in this paper.

Keywords: Switched systems, exponential stability, cellular neural networks.

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled direct normal irradiance field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: Artificial Neural Networks, Resilient Propagation, Solar Radiation, Time Series Forecasting.

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Authors: Ho-Hyun Park, Woosik Kim, Miae Woo

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It is expected that ubiquitous era will come soon. A ubiquitous environment has features like peer-to-peer and nomadic environments. Such features can be represented by peer-to-peer systems and mobile ad-hoc networks (MANETs). The features of P2P systems and MANETs are similar, appealing for implementing P2P systems in MANET environment. It has been shown that, however, the performance of the P2P systems designed for wired networks do not perform satisfactorily in mobile ad-hoc environment. Subsequently, this paper proposes a method to improve P2P performance using cross-layer design and the goodness of a node as a peer. The proposed method uses routing metric as well as P2P metric to choose favorable peers to connect. It also utilizes proactive approach for distributing peer information. According to the simulation results, the proposed method provides higher query success rate, shorter query response time and less energy consumption by constructing an efficient overlay network.

Keywords: Ad-hoc Networks, Cross-layer, Peer-to-Peer, Performance Analysis.

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Authors: Alluri Swaroopa, Lakkakula Venkata Narasimha Prasad

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Alone with fast urbanization in world, traffic control became a big issue in urban construction. Having an efficient and reliable traffic control system is crucial to macro-traffic control. Traffic signal is used to manage conflicting requirement by allocating different sets of mutually compatible traffic movement during distinct time interval. Many approaches have been made proposed to solve this discrete stochastic problem. Recognizing the need to minimize right-of-way impacts while efficiently handling the anticipated high traffic volumes, the proposed alternative system gives effective design. This model allows for increased traffic capacity and reduces delays by eliminating a step in maneuvering through the freeway interchange. The concept proposed in this paper involves construction of bridges and ramps at intersection of four roads to control the vehicular congestion and to prevent traffic breakdown.

Keywords: Bridges, junctions, ramps, urban traffic control.

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Authors: S. Carpintero, R. Barcham

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Light rail systems have proliferated in Spain in the last decade, following a tendency that is common not only in other European countries but also in other parts of the world. This paper reviews the benefits of light rail systems, both related to environmental issues and mobility issues. It analyses the evolution of light rail projects in Spain and shows that light rail systems in this country have evolved towards an extensive use of public-private partnerships. The analysis of the Spanish projects, however, does not contribute any conclusive evidence about whether public-private partnerships have been more efficient than publicly owned enterprises in building and operating light rail systems.

Keywords: Light rail systems, public-private partnerships, BOT.

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Authors: Debal Saha, NirmalBaranHui

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The present paper discusses the basic concepts and the underlying principles of Multi-Agent Systems (MAS) along with an interdisciplinary exploitation of these principles. It has been found that they have been utilized for lots of research and studies on various systems spanning across diverse engineering and scientific realms showing the need of development of a proper generalized framework. Such framework has been developed for the Multi-Agent Systems and it has been generalized keeping in mind the diverse areas where they find application. All the related aspects have been categorized and a general definition has been given where ever possible.

Keywords: Generalized framework, multiagent systems.

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Authors: Jihad S. Daba, Jean-Pierre Dubois, Georges El Soury

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Fifth generation wireless networks guarantee significant capacity enhancement to suit more clients and services at higher information rates with better reliability while consuming less power. The deployment of massive multiple-input-multiple-output technology guarantees broadband wireless networks with the use of base station antenna arrays to serve a large number of users on the same frequency and time-slot channels. In this work, we evaluate the performance of massive multiple-input-multiple-output systems (MIMO) systems in 5^th generation cellular networks in terms of capacity and bit error rate. Several cases were considered and analyzed to compare the performance of massive MIMO systems while varying the number of antennas at both transmitting and receiving ends. We found that, unlike classical MIMO systems, reducing the number of transmit antennas while increasing the number of antennas at the receiver end provides a better solution to performance enhancement. In addition, enhanced orthogonal frequency division multiplexing and beam division multiple access schemes further improve the performance of massive MIMO systems and make them more reliable.

Keywords: Beam division multiple access, D2D communication, enhanced OFDM, fifth generation broadband, massive MIMO.

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Authors: Elke Mackensen

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Systems Engineering plays a key role during industrial product development of complex technical systems. The need for systems engineers in industry is growing. But there is a gap between the industrial need and the academic education. Normally the academic education is focused on the domain specific design, implementation and testing of technical systems. Necessary systems engineering expertise like knowledge about requirements analysis, product cost estimation, management or social skills are poorly taught. Thus there is the need of new academic concepts for teaching systems engineering skills. This paper presents a project-orientated training concept to prepare students from different technical degree programs for systems engineering activities. The training concept has been initially implemented and applied in the industrial engineering master program of the University of Applied Sciences Offenburg.

Keywords: Educational systems engineering training, requirements analysis, system modelling, SysML.

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: Data mining, hybrid storage system, recurrent neural network, support vector machine.

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Authors: Nyeng P. Gyang

Abstract:

Even though past, current and future trends suggest that multicore and cloud computing systems are increasingly prevalent/ubiquitous, this class of parallel systems is nonetheless underutilized, in general, and barely used for research on employing parallel Delaunay triangulation for parallel surface modeling and generation, in particular. The performances, of actual/physical and virtual/cloud multicore systems/machines, at executing various algorithms, which implement various parallelization strategies of the incremental insertion technique of the Delaunay triangulation algorithm, were evaluated. T-tests were run on the data collected, in order to determine whether various performance metrics differences (including execution time, speedup and efficiency) were statistically significant. Results show that the actual machine is approximately twice faster than the virtual machine at executing the same programs for the various parallelization strategies. Results, which furnish the scalability behaviors of the various parallelization strategies, also show that some of the differences between the performances of these systems, during different runs of the algorithms on the systems, were statistically significant. A few pseudo superlinear speedup results, which were computed from the raw data collected, are not true superlinear speedup values. These pseudo superlinear speedup values, which arise as a result of one way of computing speedups, disappear and give way to asymmetric speedups, which are the accurate kind of speedups that occur in the experiments performed.

Keywords: Cloud computing systems, multicore systems, parallel delaunay triangulation, parallel surface modeling and generation.

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Authors: So Jeong Nam, Seung Woo Lee, Jai-Kyung Lee

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With the globalized production and logistics environment, the need for reducing the product development interval and lead time, having a faster response to orders, conforming to quality standards, fair tracking, and boosting information exchanging activities with customers and partners, and coping with changes in the management environment, manufacturers are in dire need of an information management system in their manufacturing environments. There are lots of information systems that have been designed to manage the condition or operation of equipment in the field but existing systems have a decentralized architecture, which is not unified. Also, these systems cannot effectively handle the status data extraction process upon encountering a problem related to protocols or changes in the equipment or the setting. In this regard, this paper will introduce a system for processing and saving the status info of production equipment, which uses standard representation formats, to enable flexible responses to and support for variables in the field equipment. This system can be used for a variety of manufacturing and equipment settings and is capable of interacting with higher-tier systems such as MES.

Keywords: DAS, Equipment Status, Regular Expression

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Authors: Haitham S. Hamza, Mohamed Maher, Shourok Alaa, Aya Khattab, Hadeal Ismail, Kamilia Hosny

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Radio Frequency Identification (RFID) has become a key technology in the emerging concept of Internet of Things (IoT). Naturally, business applications would require the deployment of various RFID systems developed by different vendors that use different data formats and structures. This heterogeneity poses a challenge in developing real-life IoT systems with RFID, as integration is becoming very complex and challenging. Semantic integration is a key approach to deal with this challenge. To do so, ontology for RFID systems need to be developed in order to annotated semantically RFID systems, and hence, facilitate their integration. Accordingly, in this paper, we propose ontology for RFID systems. The proposed ontology can be used to semantically enrich RFID systems, and hence, improve their usage and reasoning.

Keywords: IoT, RFID, Semantic, sparql, Ontology.

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Authors: A. M. Sagir

Abstract:

In this paper, linear multistep technique using power series as the basis function is used to develop the block methods which are suitable for generating direct solution of the special second order ordinary differential equations with associated initial or boundary conditions. The continuous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain two different four discrete schemes, each of order (5,5,5,5)T, which were used in block form for parallel or sequential solutions of the problems. The computational burden and computer time wastage involved in the usual reduction of second order problem into system of first order equations are avoided by this approach. Furthermore, a stability analysis and efficiency of the block methods are tested on linear and non-linear ordinary differential equations and the results obtained compared favorably with the exact solution.

Keywords: Block Method, Hybrid, Linear Multistep Method, Self – starting, Special Second Order.

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Authors: V. Venkatachalam, S. Selvan

Abstract:

The security of computer networks plays a strategic role in modern computer systems. Intrusion Detection Systems (IDS) act as the 'second line of defense' placed inside a protected network, looking for known or potential threats in network traffic and/or audit data recorded by hosts. We developed an Intrusion Detection System using LAMSTAR neural network to learn patterns of normal and intrusive activities, to classify observed system activities and compared the performance of LAMSTAR IDS with other classification techniques using 5 classes of KDDCup99 data. LAMSAR IDS gives better performance at the cost of high Computational complexity, Training time and Testing time, when compared to other classification techniques (Binary Tree classifier, RBF classifier, Gaussian Mixture classifier). we further reduced the Computational Complexity of LAMSTAR IDS by reducing the dimension of the data using principal component analysis which in turn reduces the training and testing time with almost the same performance.

Keywords: Binary Tree Classifier, Gaussian Mixture, IntrusionDetection System, LAMSTAR, Radial Basis Function.

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Authors: Koudjo M. Koumadi, Kester Quist-Aphetsi, Robert A. Sowah, Amevi Acakpovi

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Downlink/Uplink (DL/UL) time slot allocation (TSA) in time division duplex (TDD) systems is generally uniform for all the cells. This TSA however is not efficient in case of different traffic asymmetry ratios in different cells. We first propose a new 3-coordinate architecture to identify cells in an orthogonal frequency division multiple access (OFDMA) system where each cell is divided into three sectors. Then, this coordinate system is used to derive a TSA for symmetric traffic. Mathematical analysis and simulations are used to show that the proposed TSA outperforms the traditional all uniform type of TSA in terms of total intercellular interference, even under uniform symmetrical traffic. Two adaptation strategies are further proposed to adjust the proposed TSA to asymmetrical traffic with different DL/UL traffic ratios in different cells. Further simulation results show that the adaptation strategies also yield higher signal-to-interference ratio (SIR).

Keywords: Crossed TSA, different-entity interference, same-entity interference, uniform TSA

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Authors: Emrah Bulut, Okan Duru, Shigeru Yoshida

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In this study, a fuzzy integrated logical forecasting method (FILF) is extended for multi-variate systems by using a vector autoregressive model. Fuzzy time series forecasting (FTSF) method was recently introduced by Song and Chissom [1]-[2] after that Chen improved the FTSF method. Rather than the existing literature, the proposed model is not only compared with the previous FTS models, but also with the conventional time series methods such as the classical vector autoregressive model. The cluster optimization is based on the C-means clustering method. An empirical study is performed for the prediction of the chartering rates of a group of dry bulk cargo ships. The root mean squared error (RMSE) metric is used for the comparing of results of methods and the proposed method has superiority than both traditional FTS methods and also the classical time series methods.

Keywords: C-means clustering, Fuzzy time series, Multi-variate design

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Authors: Mubina Nazmeen, Iram Rubab

Abstract:

Formal Specification languages are being widely used for system specification and testing. Highly critical systems such as real time systems, avionics, and medical systems are represented using Formal specification languages. Formal specifications based testing is mostly performed using black box testing approaches thus testing only the set of inputs and outputs of the system. The formal specification language such as VDMµ can be used for white box testing as they provide enough constructs as any other high level programming language. In this work, we perform data and control flow analysis of VDMµ class specifications. The proposed work is discussed with an example of SavingAccount.

Keywords: VDM-SL, VDMµ, data flow graph, control flowgraph, testing, formal specification.

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Authors: Nunziata Ivana Guarneri, Arcangelo Bruna, Giuseppe Spampinato, Antonio Buemi

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In the last decade, automotive companies have invested a lot in terms of innovation about many aspects regarding the automatic driver assistance systems. One innovation regards the usage of a smart camera placed on the car’s side mirror for monitoring the back and lateral road situation. A common road scenario is the overtaking of the preceding car and, in this case, a brief distraction or a loss of concentration can lead the driver to undertake this action, even if there is an already overtaking vehicle, leading to serious accidents. A valid support for a secure drive can be a smart camera system, which is able to automatically analyze the road scenario and consequentially to warn the driver when another vehicle is overtaking. This paper describes a method for monitoring the side view of a vehicle by using camera optical flow motion vectors. The proposed solution detects the presence of incoming vehicles, assesses their distance from the host car, and warns the driver through different levels of alert according to the estimated distance. Due to the low complexity and computational cost, the proposed system ensures real time performances.

Keywords: Camera calibration, ego motion, kalman filters, object tracking, real time systems.

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Authors: Marlene Weber, Joseph Giacomin, Alessio Malizia, Lee Skrypchuk, Voula Gkatzidou

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Technological and sociological developments in the automotive sector are shifting the focus of design towards developing a better understanding of driver needs, desires and emotions. Human centred design methods are being more frequently applied to automotive research, including the use of systems to detect human emotions in real-time. One method for a non-contact measurement of emotion with low intrusiveness is Facial-Expression Analysis (FEA). This paper describes a research study investigating emotional responses of 22 participants in a naturalistic driving environment by applying a multi-method approach. The research explored the possibility to investigate emotional responses and their frequencies during naturalistic driving through real-time FEA. Observational analysis was conducted to assign causes to the collected emotional responses. In total, 730 emotional responses were measured in the collective study time of 440 minutes. Causes were assigned to 92% of the measured emotional responses. This research establishes and validates a methodology for the study of emotions and their causes in the driving environment through which systems and factors causing positive and negative emotional effects can be identified.

Keywords: Affective computing, case study, emotion recognition, human computer interaction.

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Authors: Joseph C. Chen, Venkata Mohan Kudapa

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Development of two real-time surface roughness (Ra) prediction systems for milling operations was attempted. The systems used not only cutting parameters, such as feed rate and spindle speed, but also the cutting current generated and corrected by a clamp type energy sensor. Two different approaches were developed. First, a fuzzy inference system (FIS), in which the fuzzy logic rules are generated by experts in the milling processes, was used to conduct prediction modeling using current cutting data. Second, a neuro-fuzzy system (ANFIS) was explored. Neuro-fuzzy systems are adaptive techniques in which data are collected on the network, processed, and rules are generated by the system. The inference system then uses these rules to predict Ra as the output. Experimental results showed that the parameters of spindle speed, feed rate, depth of cut, and input current variation could predict Ra. These two systems enable the prediction of Ra during the milling operation with an average of 91.83% and 94.48% accuracy by FIS and ANFIS systems, respectively. Statistically, the ANFIS system provided better prediction accuracy than that of the FIS system.

Keywords: Surface roughness, input current, fuzzy logic, neuro-fuzzy, milling operations.

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Authors: Giovanni Incerti

Abstract:

The motion planning procedure described in this paper has been developed in order to eliminate or reduce the residual vibrations of electromechanical positioning systems, without augmenting the motion time (usually imposed by production requirements), nor introducing overtime for vibration damping. The proposed technique is based on a suitable choice of the motion law assigned to the servomotor that drives the mechanism. The reference profile is defined by a Bezier curve, whose shape can be easily changed by modifying some numerical parameters. By means of an optimization technique these parameters can be modified without altering the continuity conditions imposed on the displacement and on its time derivatives at the initial and final time instants.

Keywords: Servomechanism, residual vibrations, motion optimization.

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Authors: H. Y. Jung, Ju H. Park, S. M. Lee

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Sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: Sampled-data control, Sector bound, Solid oxide fuel cell, Time-delay.

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Authors: R. Sahraian, A. Karampour Haghighi, E. Ghasemi

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Process planning and production scheduling play important roles in manufacturing systems. In this paper a multiobjective mixed integer linear programming model is presented for the integrated planning and scheduling of multi-product. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimization problem with substantially large solution space, suggesting that it is highly difficult to find the best solutions with the exact search method. To account for it, a PSO-based algorithm is proposed by fully utilizing the capability of the exploration search and fast convergence. To fit the continuous PSO in the discrete modeled problem, a solution representation is used in the algorithm. The numerical experiments have been performed to demonstrate the effectiveness of the proposed algorithm.

Keywords: Integrated process planning and scheduling, multi objective, MILP, Particle swarm optimization

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Authors: Neeraj Mohan, Parvinder S. Sandhu, Hardeep Singh

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Software maintenance is extremely important activity in software development life cycle. It involves a lot of human efforts, cost and time. Software maintenance may be further subdivided into different activities such as fault prediction, fault detection, fault prevention, fault correction etc. This topic has gained substantial attention due to sophisticated and complex applications, commercial hardware, clustered architecture and artificial intelligence. In this paper we surveyed the work done in the field of software maintenance. Software fault prediction has been studied in context of fault prone modules, self healing systems, developer information, maintenance models etc. Still a lot of things like modeling and weightage of impact of different kind of faults in the various types of software systems need to be explored in the field of fault severity.

Keywords: Fault prediction, Software Maintenance, Automated Fault Prediction, and Failure Mode Analysis

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Authors: Carsten Röcker

Abstract:

This paper presents a set of guidelines for the design of multi-user awareness systems. In a first step, general requirements for team awareness systems are analyzed. In the second part of the paper, the identified requirements are aggregated and transformed into concrete design guidelines for the development of team awareness systems.

Keywords: User Interface Design, Awareness Systems, User- Centered Design, Human Factors.

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Authors: Chee Peng Lim, Wei Yee Goh

Abstract:

In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.

Keywords: AdaBoost, Elman network, neural network ensemble, time series regression.

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Authors: Yan Yu, Wang Yu, Chen Xintong, Liu Yi, Zhang Yanzhong, Wang Yanji, Chen Xingyu, Zhang Miaocheng, Tong Yi

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Neuromorphic computing based on spiking neural networks (SNNs) has emerged as a promising avenue for building the next generation of intelligent computing systems. Owing to their high-density integration, low power, and outstanding nonlinearity, memristors have attracted emerging attention on achieving SNNs. However, fabricating a low-power and robust memristor-based spiking neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a TiO2-based threshold switching (TS) memristor to emulate a leaky integrate-and-fire (LIF) neuron without auxiliary circuits, used to realize single layer fully connected (FC) SNNs. Moreover, our TiO2-based resistive switching (RS) memristors realize spiking-time-dependent-plasticity (STDP), originating from the Ag diffusion-based filamentary mechanism. This work demonstrates that TiO2-based memristors may provide an efficient method to construct hardware neuromorphic computing systems.

Keywords: Leaky integrate-and-fire, memristor, spiking neural networks, spiking-time-dependent-plasticity.

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