Search results for: network performance

Authors: Said Khelifa, Zoulikha Mekkakia Maaza

Abstract:

In this paper we present a full performance analysis of an energy conserving routing protocol in mobile ad hoc network, named ER-AODV (Energy Reverse Ad-hoc On-demand Distance Vector routing). ER-AODV is a reactive routing protocol based on a policy which combines two mechanisms used in the basic AODV protocol. AODV and most of the on demand ad hoc routing protocols use single route reply along reverse path. Rapid change of topology causes that the route reply could not arrive to the source node, i.e. after a source node sends several route request messages, the node obtains a reply message, and this increases in power consumption. To avoid these problems, we propose a mechanism which tries multiple route replies. The second mechanism proposes a new adaptive approach which seeks to incorporate the metric "residual energy " in the process route selection, Indeed the residual energy of mobile nodes were considered when making routing decisions. The results of simulation show that protocol ER-AODV answers a better energy conservation.

Keywords: Ad hoc mobile networks, Energy AODV, Energy consumption, ER-AODV, Reverse AODV.

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Authors: I. Martins, A. Martins

Abstract:

The European Union supports social and civil competencies as being a core element to develop sustainability of organizations, people and regions. These competencies are fundamental for the well-being of the community because they include interpersonal, intrapersonal as well as their civil, active and democratic participation in organizations. The combination of these competencies reveals the organizational socio-emotional maturity and allows relevant levels of performance. It also allows the development of various capitals, namely, human, structural, relational and social, with direct influence on performance. But along this path, the emotional aspect has not been valued as a capital, given that contemporary society is based on knowledge capital and is flooded with information viewed as a capital. The present study, based on the importance of these socio-emotional capitals, aims to show that the competencies of cooperation, interpersonal understanding, empathy, kindness, ability to listen, and tolerance, to mention a few, are strategic in consolidating knowledge within organizations. This implies that the humanizing processes, both inside and outside the organizations, are revitalized. The question is how to go about doing this and its implementation; as well as, where to begin and which guidelines to take on. These are the foci that guide the present study, bearing in mind the directions of the knowledge economy.

Keywords: Social competencies, civil competencies, humanizing, performance.

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Authors: V. Vicente E. Mujica, Gustavo Gonzalez

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The global coverage of broadband multimedia and internet-based services in terrestrial-satellite networks demand particular interests for satellite providers in order to enhance services with low latencies and high signal quality to diverse users. In particular, the delay of on-board processing is an inherent source of latency in a satellite communication that sometimes is discarded for the end-to-end delay of the satellite link. The frame work for this paper includes modelling of an on-orbit satellite payload using an agent model that can reproduce the properties of processing delays. In essence, a comparison of different spatial interpolation methods is carried out to evaluate physical data obtained by an GEO satellite in order to define a discretization function for determining that delay. Furthermore, the performance of the proposed agent and the development of a delay discretization function are together validated by simulating an hybrid satellite and terrestrial network. Simulation results show high accuracy according to the characteristics of initial data points of processing delay for Ku bands.

Keywords: Terrestrial-satellite networks, latency, on-orbit satellite payload, simulation.

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Authors: Gülfem I. Alptekin, S. Emre Alptekin

Abstract:

The next generation wireless systems, especially the cognitive radio networks aim at utilizing network resources more efficiently. They share a wide range of available spectrum in an opportunistic manner. In this paper, we propose a quality management model for short-term sub-lease of unutilized spectrum bands to different service providers. We built our model on competitive secondary market architecture. To establish the necessary conditions for convergent behavior, we utilize techniques from game theory. Our proposed model is based on potential game approach that is suitable for systems with dynamic decision making. The Nash equilibrium point tells the spectrum holders the ideal price values where profit is maximized at the highest level of customer satisfaction. Our numerical results show that the price decisions of the network providers depend on the price and QoS of their own bands as well as the prices and QoS levels of their opponents- bands.

Keywords: cognitive radio networks, game theory, nextgeneration wireless networks, spectrum management.

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Authors: Mallikarjun B. Channappagoudar, Pallapa Venkataram

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As a node monitoring protocol, which is a part of network management, operates in distributed manner, conformance testing of such protocols is more tedious than testing a peer-to-peer protocol. Various works carried out to give the methodology to do conformance testing of distributed protocol. In this paper, we have presented a formal approach for conformance testing of a Node Monitoring Protocol, which uses both static and mobile agents, for MANETs. First, we use SDL to obtain MSCs, which represent the scenario descriptions by sequence diagrams, which in turn generate test sequences and test cases. Later, Testing and Test Control Notation Version-3 (TTCN-3) is used to execute test cases with respect to generated test sequences to know the conformance of protocol against the given specification. This approach shows, the effective conformance testing of the distributed protocols for the network with varying node density and complex behavior. Experimental results for the protocol scenario represent the effectiveness of the method used.

Keywords: Conformance Testing, FSM, Mobile agent, TTCN, Test sequence.

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Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

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The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. Previous work established that the Ward-style artificial neural network (ANN) is a suitable tool for developing such models. The current research focused on developing ANN models with reduced average prediction error by increasing the number of distinct observations used in training, adding additional input terms that describe the date of an observation, increasing the duration of prior weather data included in each observation, and reexamining the number of hidden nodes used in the network. Models were created to predict air temperature at hourly intervals from one to 12 hours ahead. Each ANN model, consisting of a network architecture and set of associated parameters, was evaluated by instantiating and training 30 networks and calculating the mean absolute error (MAE) of the resulting networks for some set of input patterns. The inclusion of seasonal input terms, up to 24 hours of prior weather information, and a larger number of processing nodes were some of the improvements that reduced average prediction error compared to previous research across all horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or 12.5%, less than the previous model. Prediction MAEs eight and 12 hours ahead improved by 0.17°C and 0.16°C, respectively, improvements of 7.4% and 5.9% over the existing model at these horizons. Networks instantiating the same model but with different initial random weights often led to different prediction errors. These results strongly suggest that ANN model developers should consider instantiating and training multiple networks with different initial weights to establish preferred model parameters.

Keywords: Decision support systems, frost protection, fruit, time-series prediction, weather modeling

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Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

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The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: Femtocell networks, game theory, interference mitigation, spectrum allocation.

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Authors: Heru Nurwarsito, R. Arief Setyawan, Rakhmadhany Primananda

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Voice Over IP (VoIP) is a technology that could pass the voice traffic and data packet form over an IP network. Network can be used for intranet or Internet. Phone calls using VoIP has advantages in terms of cheaper cost of PSTN phone to more than half, because the cost is calculated by the cost of the global nature of the Internet. Session Initiation Protocol (SIP) is a signaling protocol at the application layer which serves to establish, modify, and terminate a multimedia session involving one or more users. This SIP signaling has SIP message in text form that is used for session management by the SIP components, such as User Agent, Registrar, Redirect Server, and Proxy Server. To build a SIP communication is required SIP Express Router (SER) to be able to receive SIP messages, for handling the basic functions of SIP messages. Problems occur when the NAT through which affects the voice communication will be blocked starting from the sound that is not sent or one side of the sound are sent (half duplex). How that could be used to penetrate NAT is to use a given mediaproxy random RTP port to penetrate NAT.

Keywords: VoIP, SIP, SIP Express Router, NAT, Mediaproxy.

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Authors: Samad Jafarmadar, Amin Habibzadeh, Mohammad Mehdi Rashidi, Sayed Sina Rezaei, Abbas Aghagoli

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In this paper, the ejector-absorption refrigeration cycle is presented. This article deals with the thermodynamic simulation and the first and second law analysis of an ammonia-water. The effects of parameters such as condenser, absorber, generator, and evaporator temperatures have been investigated. The influence of the various operating parameters on the performance coefficient and exergy efficiency of this cycle has been studied. The results show that when the temperature of different parts increases, the performance coefficient and the exergy efficiency of the cycle decrease, except for evaporator and generator, that causes an increase in coefficient of performance (COP). According to the results, absorber and ejector have the highest exergy losses in the studied conditions.

Keywords: Absorption refrigeration, COP, ejector, exergy efficiency.

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Authors: H. Ferfera-Harrar, N. Aiouaz, N. Dairi

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Superabsorbent polymers received much attention and are used in many fields because of their superior characters to traditional absorbents, e.g., sponge and cotton. So, it is very important but challenging to prepare highly and fast-swelling superabsorbents. A reliable, efficient and low-cost technique for removing heavy metal ions from wastewater is the adsorption using bio-adsorbents obtained from biological materials, such as polysaccharides-based hydrogels superabsorbents. In this study, novel multi-functional superabsorbent composites type semi-interpenetrating polymer networks (Semi-IPNs) were prepared via graft polymerization of acrylamide onto chitosan backbone in presence of gelatin, CTS-g-PAAm/Ge, using potassium persulfate and N,N’-methylene bisacrylamide as initiator and crosslinker, respectively. These hydrogels were also partially hydrolyzed to achieve superabsorbents with ampholytic properties and uppermost swelling capacity. The formation of the grafted network was evidenced by Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Thermogravimetric Analysis (TGA). The porous structures were observed by Scanning Electron Microscope (SEM). From TGA analysis, it was concluded that the incorporation of the Ge in the CTS-g-PAAm network has marginally affected its thermal stability. The effect of gelatin content on the swelling capacities of these superabsorbent composites was examined in various media (distilled water, saline and pH-solutions). The water absorbency was enhanced by adding Ge in the network, where the optimum value was reached at 2 wt. % of Ge. Their hydrolysis has not only greatly optimized their absorption capacity but also improved the swelling kinetic.These materials have also showed reswelling ability. We believe that these super-absorbing materials would be very effective for the adsorption of harmful metal ions from wastewater.

Keywords: Chitosan, gelatin, superabsorbent, water absorbency.

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Authors: S. Zappacosta, C. Bove, M. Carmela Marinelli, P. di Lauro, K. Spasenovic, L. Ostano, G. Aiello, M. Pietrosanto

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This paper proposes a neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The classification capability was compared with the flood hazard mapping River Basin Plans (Piani Assetto Idrogeologico, acronimed as PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale), encoding four different increasing flood hazard levels. The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: M. Chobotová, Ž. Rylková

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Time full of changes which is associated with globalization, tougher competition, changes in the structures of markets and economic downturn, that all force companies to think about their competitive advantages. These changes can bring the company a competitive advantage and that can help improve competitive position in the market. Policy of the European Union is focused on the fast growing innovative companies which quickly respond to market demands and consequently increase its competitiveness. To meet those objectives companies need the right conditions and support of their state.

Keywords: Innovation, performance, measurements metrics, indices.

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

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Opportunistic Routing (OR) increases the transmission reliability and network throughput. Traditional routing protocols preselects one or more predetermined nodes before transmission starts and uses a predetermined neighbor to forward a packet in each hop. The opportunistic routing overcomes the drawback of unreliable wireless transmission by broadcasting one transmission can be overheard by manifold neighbors. The first cooperation-optimal protocol for Multirate OR (COMO) used to achieve social efficiency and prevent the selfish behavior of the nodes. The novel link-correlation-aware OR improves the performance by exploiting the miscellaneous low correlated forward links. Context aware Adaptive OR (CAOR) uses active suppression mechanism to reduce packet duplication. The Context-aware OR (COR) can provide efficient routing in mobile networks. By using Cooperative Opportunistic Routing in Mobile Ad hoc Networks (CORMAN), the problem of opportunistic data transfer can be tackled. While comparing to all the protocols, COMO is the best as it achieves social efficiency and prevents the selfish behavior of the nodes.

Keywords: CAOR, COMO, COR, CORMAN, MANET, Opportunistic Routing, Reliability, Throughput.

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Authors: Barzin Gavtash, Khalid Hussain, Mohammad Layeghi, Saeed Sadeghi Lafmejani

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This research aims at modeling and simulating the effects of nanofluids on cylindrical heat pipes thermal performance using the ANSYS-FLUENT CFD commercial software. The heat pipe outer wall temperature distribution, thermal resistance, liquid pressure and axial velocity in presence of suspended nano-scaled solid particle (i.e. Cu, Al2O3 and TiO2) within the fluid (water) were investigated. The effect of particle concentration and size were explored and it is concluded that the thermal performance of the heat pipe is improved when using nanofluid as the system working fluid. Additionally, it was observed that the thermal resistance of the heat pipe drops as the particle concentration level increases and particle radius decreases.

Keywords: CFD, Heat Pipe, Nanofluid, Thermal resistance

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Authors: K. Ramasamy, B. Balamuralithara, Mohammad Umar Siddiqi

Abstract:

We proposed a new class of asymmetric turbo encoder for 3G systems that performs well in both “water fall" and “error floor" regions in [7]. In this paper, a modified (optimal) power allocation scheme for the different bits of new class of asymmetric turbo encoder has been investigated to enhance the performance. The simulation results and performance bound for proposed asymmetric turbo code with modified Unequal Power Allocation (UPA) scheme for the frame length, N=400, code rate, r=1/3 with Log-MAP decoder over Additive White Gaussian Noise (AWGN) channel are obtained and compared with the system with typical UPA and without UPA. The performance tests are extended over AWGN channel for different frame size to verify the possibility of implementation of the modified UPA scheme for the proposed asymmetric turbo code. From the performance results, it is observed that the proposed asymmetric turbo code with modified UPA performs better than the system without UPA and with typical UPA and it provides a coding gain of 0.4 to 0.52dB.

Keywords: Asymmetric turbo code, Generator polynomial, Interleaver, UPA, WCDMA, cdma2000.

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Authors: Lewis E. Hibell, Honghai Liu, David J. Brown

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This paper presents the use of a newly created network structure known as a Self-Delaying Dynamic Network (SDN) to create a high resolution image from a set of time stepped input frames. These SDNs are non-recurrent temporal neural networks which can process time sampled data. SDNs can store input data for a lifecycle and feature dynamic logic based connections between layers. Several low resolution images and one high resolution image of a scene were presented to the SDN during training by a Genetic Algorithm. The SDN was trained to process the input frames in order to recreate the high resolution image. The trained SDN was then used to enhance a number of unseen noisy image sets. The quality of high resolution images produced by the SDN is compared to that of high resolution images generated using Bi-Cubic interpolation. The SDN produced images are superior in several ways to the images produced using Bi-Cubic interpolation.

Keywords: Image Enhancement, Neural Networks, Multi-Frame.

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: Distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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Authors: Salim Ouchtati, Bedda Mouldi, Abderrazak Lachouri

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In this paper we present an off line system for the recognition of the handwritten numeric chains. Our work is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this case the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: the distribution sequence, the Barr features and the centred moments of the different projections and profiles. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.

Keywords: Optical Characters Recognition, Neural networks, Barr features, Image processing, Pattern Recognition, Featuresextraction.

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Authors: Wanda Luen-Wun Siu, Xiaowen Zhang

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This paper offered the primary methodical proof on how Corporate Social Responsibility (CSR) reporting related to enterprise earnings in listed firms in China in light of most evidence focusing on cross-sectional data or data in a short span of time. Using full economic and business panel data on China’s publicly listed enterprises from 2006 to 2020 over two decades in the China Stock Market & Accounting Research database, we found initial evidence of significant direct relations between CSR reporting and firm corporate performance in both state-owned and privately-owned firms over this period, supporting the stakeholder theory. Results also revealed that state-owned enterprises performed as well as private enterprises in the current period. But private enterprises performed better than state-owned enterprises in the subsequent years. Moreover, the release of social responsibility reports had the more significant impact on the financial performance of state-owned and private enterprises in the current period than in the subsequent periods. Specifically, CSR release was not significantly associated to the financial performance of state-owned enterprises on the lag of the first, second, and third periods. But it had an impact on the lag of the first, second, and third periods among private enterprises. Such findings suggested that CSR reporting helped improve the corporate financial performance of state-owned and private enterprises in the current period, but this kind of effect was more significant among private enterprises in the lag periods.

Keywords: China’s Listed Firm, CSR reporting, financial performance, panel analysis.

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Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt

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To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.

Keywords: 100% renewable electricity, California, capacity expansion, binary quadratic programming.

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Authors: Ming-Hui Cheng, Jyh-Horng Jeng

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In this study, a classification-based video super-resolution method using artificial neural network (ANN) is proposed to enhance low-resolution (LR) to high-resolution (HR) frames. The proposed method consists of four main steps: classification, motion-trace volume collection, temporal adjustment, and ANN prediction. A classifier is designed based on the edge properties of a pixel in the LR frame to identify the spatial information. To exploit the spatio-temporal information, a motion-trace volume is collected using motion estimation, which can eliminate unfathomable object motion in the LR frames. In addition, temporal lateral process is employed for volume adjustment to reduce unnecessary temporal features. Finally, ANN is applied to each class to learn the complicated spatio-temporal relationship between LR and HR frames. Simulation results show that the proposed method successfully improves both peak signal-to-noise ratio and perceptual quality.

Keywords: Super-resolution, classification, spatio-temporal information, artificial neural network.

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Authors: D. Vlachopoulos, G. Tsokkas

Abstract:

Although it is not intended to identify distance education students as a homogeneous group, recent research has demonstrated that there are some demographic and personality common traits among most of them that provide the basis for the description of a typical distance learning student. The purpose of this paper is to describe these common traits and to facilitate their learning journey within a distance education program. The described research is an initiative of the Distance Education Unit at the European University Cyprus (Laureate International Universities) in the context of its action for the improvement of the students’ performance.

Keywords: Distance education students, successful student performance, European University Cyprus, common traits.

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Authors: Oluwaseyi O. Taiwo, Adeolu A. Adediran, Abayomi A. Akinwande, Frank C. Okoyeh

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The use of fuel fired crucible furnace is essential in the foundries of developing countries owing to the luxury of electricity. Fuel fired crucible furnace are commonly used in recycling, casting, research and training activities in tertiary institutions, therefore, several attempts are being made to improve the performance and service life of fuel fired crucible. The current study reviews the sequential stages involved in the designs and fabrication of fuel fired crucible furnace which include; design, material selection, modelling and simulation as well as performance evaluation. The study shows that selecting appropriate materials for the different units in the fabrication process is important to the efficiency and service life of fuel fired crucible furnaces. Also, efficiency and performance of fuel fired furnaces are independent of cost of fabrication and their capacity. The importance of modelling and simulation tools in the fabrication process are identified while their non-frequent usage in several works is observed. The need to widen performance evaluations in further studies beyond efficiency determination to give a more detailed assessment of fuel fired crucible furnaces is also observed.

Keywords: Crucible furnace, furnace design, fabrication, fuel.

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Authors: T.P. Andamuthu, Dr. P. Balasubramanie

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The intermittent connectivity modifies the “always on" network assumption made by all the distributed query processing systems. In modern- day systems, the absence of network connectivity is considered as a fault. Since the last upload, it might not be feasible to transmit all the data accumulated right away over the available connection. It is possible that vital information may be delayed excessively when the less important information takes place of the vital information. Owing to the restricted and uneven bandwidth, it is vital that the mobile nodes make the most advantageous use of the connectivity when it arrives. Hence, in order to select the data that needs to be transmitted first, some sort of data prioritization is essential. A continuous query processing system for intermittently connected mobile networks that comprises of a delaytolerant continuous query processor distributed across the mobile hosts has been proposed in this paper. In addition, a mechanism for prioritizing query results has been designed that guarantees enhanced accuracy and reduced delay. It is illustrated that our architecture reduces the client power consumption, increases query efficiency by the extensive simulation results.

Keywords: Broadcast, Location, Mobile host, Mobility, Query.

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Authors: Shan Gao, Zaiming Liu

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This paper treats a discrete-time batch arrival queue with single working vacation. The main purpose of this paper is to present a performance analysis of this system by using the supplementary variable technique. For this purpose, we first analyze the Markov chain underlying the queueing system and obtain its ergodicity condition. Next, we present the stationary distributions of the system length as well as some performance measures at random epochs by using the supplementary variable method. Thirdly, still based on the supplementary variable method we give the probability generating function (PGF) of the number of customers at the beginning of a busy period and give a stochastic decomposition formulae for the PGF of the stationary system length at the departure epochs. Additionally, we investigate the relation between our discretetime system and its continuous counterpart. Finally, some numerical examples show the influence of the parameters on some crucial performance characteristics of the system.

Keywords: Discrete-time queue, batch arrival, working vacation, supplementary variable technique, stochastic decomposition.

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Authors: Diego Felix, Eugene Hyun, Michael McGuire, Mihai Sima

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Terminal localization for indoor Wireless Local Area Networks (WLANs) is critical for the deployment of location-aware computing inside of buildings. A major challenge is obtaining high localization accuracy in presence of fluctuations of the received signal strength (RSS) measurements caused by multipath fading. This paper focuses on reducing the effect of the distance-varying noise by spatial filtering of the measured RSS. Two different survey point geometries are tested with the noise reduction technique: survey points arranged in sets of clusters and survey points uniformly distributed over the network area. The results show that the location accuracy improves by 16% when the filter is used and by 18% when the filter is applied to a clustered survey set as opposed to a straight-line survey set. The estimated locations are within 2 m of the true location, which indicates that clustering the survey points provides better localization accuracy due to superior noise removal.

Keywords: Position measurement, Wireless LAN, Radio navigation, Filtering

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Authors: Muhammad Faisal Zafar, Dzulkifli Mohamad, Razib M. Othman

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On-line handwritten scripts are usually dealt with pen tip traces from pen-down to pen-up positions. Time evaluation of the pen coordinates is also considered along with trajectory information. However, the data obtained needs a lot of preprocessing including filtering, smoothing, slant removing and size normalization before recognition process. Instead of doing such lengthy preprocessing, this paper presents a simple approach to extract the useful character information. This work evaluates the use of the counter- propagation neural network (CPN) and presents feature extraction mechanism in full detail to work with on-line handwriting recognition. The obtained recognition rates were 60% to 94% using the CPN for different sets of character samples. This paper also describes a performance study in which a recognition mechanism with multiple thresholds is evaluated for counter-propagation architecture. The results indicate that the application of multiple thresholds has significant effect on recognition mechanism. The method is applicable for off-line character recognition as well. The technique is tested for upper-case English alphabets for a number of different styles from different peoples.

Keywords: On-line character recognition, character digitization, counter-propagation neural networks, extreme coordinates.

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Authors: Ramaswamy Palaniappan

Abstract:

In this paper, a second order autoregressive (AR) model is proposed to discriminate alcoholics using single trial gamma band Visual Evoked Potential (VEP) signals using 3 different classifiers: Simplified Fuzzy ARTMAP (SFA) neural network (NN), Multilayer-perceptron-backpropagation (MLP-BP) NN and Linear Discriminant (LD). Electroencephalogram (EEG) signals were recorded from alcoholic and control subjects during the presentation of visuals from Snodgrass and Vanderwart picture set. Single trial VEP signals were extracted from EEG signals using Elliptic filtering in the gamma band spectral range. A second order AR model was used as gamma band VEP exhibits pseudo-periodic behaviour and second order AR is optimal to represent this behaviour. This circumvents the requirement of having to use some criteria to choose the correct order. The averaged discrimination errors of 2.6%, 2.8% and 11.9% were given by LD, MLP-BP and SFA classifiers. The high LD discrimination results show the validity of the proposed method to discriminate between alcoholic subjects.

Keywords: Linear Discriminant, Neural Network, VisualEvoked Potential.

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Authors: Shakirat Abimbola Adesola, Shuaib Akintunde Asifat, Jelili Olalekan Amoo

Abstract:

This paper presented the impact of students’ emotions on learning when receiving lectures and when taking tests. It was observed during the study that students experience different types of emotions, and this was found to have a significant effect on their academic performance. A total of 1675 students from the department of Computer Science in two Colleges of Education in South-West Nigeria took part in this study. The students were randomly selected for the research. The sample comprises of 968 males representing 58%, and 707 females representing 42%. A structured questionnaire, of Motivated Strategies for Learning Questionnaire (MSLQ) was distributed to the participants to obtain their opinions. Data gathered were analyzed using the IBM SPSS 20 to obtain ANOVA, descriptive analysis, stepwise regression, and reliability tests. The results revealed that emotion moderately shape students’ motivation and engagement in learning; and that self-regulation and self-determination do have significant impact on academic performance. It was further revealed that test anxiety has a significant correlation with academic performance.

Keywords: Motivation, self-determination, test anxiety, academic performance, academic engagement.

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Authors: Shan-Jen Cheng, Jr-Ming Miao, Sheng-Ju Wu

Abstract:

The purpose of this paper is applied Taguchi method on the optimization for PEMFC performance, and a representative Computational Fluid Dynamics (CFD) model is selectively performed for statistical analysis. The studied factors in this paper are pressure of fuel cell, operating temperature, the relative humidity of anode and cathode, porosity of gas diffusion electrode (GDE) and conductivity of GDE. The optimal combination for maximum power density is gained by using a three-level statistical method. The results confirmed that the robustness of the optimum design parameters influencing the performance of fuel cell are founded by pressure of fuel cell, 3atm; operating temperature, 353K; the relative humidity of anode, 50%; conductivity of GDE, 1000 S/m, but the relative humidity of cathode and porosity of GDE are pooled as error due to a small sum of squares. The present simulation results give designers the ideas ratify the effectiveness of the proposed robust design methodology for the performance of fuel cell.

Keywords: PEMFC, numerical simulation, optimization, Taguchi method.

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