Search results for: international production networks

Authors: Mohsen A. M. El-Bendary, Mostafa A. R. El-Tokhy

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This paper presents an efficient burst error spreading tool. Also, it studies a vital issue in wireless communications, which is the transmission of images over wireless networks. IEEE ZigBee 802.15.4 is a short-range communication standard that could be used for small distance multimedia transmissions. In fact, the ZigBee network is a Wireless Personal Area Network (WPAN), which needs a strong interleaving mechanism for protection against error bursts. Also, it is low power technology and utilized in the Wireless Sensor Networks (WSN) implementation. This paper presents the chaotic interleaving scheme as a data randomization tool for this purpose. This scheme depends on the chaotic Baker map. The mobility effects on the image transmission are studied with different velocity through utilizing the Jakes’ model. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for image transmission over a correlated fading channel is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes.

Keywords: WPANs, Burst Errors, Mobility, Interleaving Techniques, Fading channels.

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Authors: Baghdasaryan Marinka, Ulikyan Azatuhi

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The efficient usage of the compensation abilities of the electrical drive synchronous motors used in production processes can essentially improve the technical and economic indices of the process.  Reducing the flows of the reactive electrical energy due to the compensation of reactive power allows to significantly reduce the load losses of power in the electrical networks. As a result of analyzing the scientific works devoted to the issues of regulating the excitation of the synchronous motors, the need for comprehensive investigation and estimation of the excitation mode has been substantiated. By means of the obtained transmission functions, in the Simulink environment of the software package MATLAB, the transition processes of the excitation mode have been studied. As a result of obtaining and estimating the graph of the Nyquist plot and the transient process, the necessity of developing the Proportional-Integral-Derivative (PID) regulator has been justified. The transient processes of the system of the PID regulator have been investigated, and the amplitude–phase characteristics of the system have been estimated. The analysis of the obtained results has shown that the regulation indices of the developed system have been improved. The developed system can be successfully applied for regulating the excitation voltage of different-power synchronous motors, operating with a changing load, ensuring a value of the power coefficient close to 1.

Keywords: Transient process, synchronous motor, excitation mode, regulator, reactive power.

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: M. Zerikat, S. Chekroun

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This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Keywords: Electric drive, Induction motor, speed control, Adaptive control, neural network, High Performance.

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Authors: Siddhartha Chauhan, Kumar S. Pandey, Prateek Chandra

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One of the key research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we present a Fishnet Based Dispatch Scheme (FiBDS) with energy aware mobility and interest based sensing angle. We propose two algorithms, one is FiBDS centralized algorithm and another is FiBDS distributed algorithm. The centralized algorithm is designed specifically for the non-time critical applications, commonly known as non real-time applications while the distributed algorithm is designed specifically for the time critical applications, commonly known as real-time applications. The proposed dispatch scheme works in a phase-selection manner. In this in each phase a specific constraint is dealt with according to the specified priority and then moved onto the next phase and at the end of each only the best suited nodes for the phase are chosen. Simulation results are presented to verify their effectiveness. 

Keywords: Dispatch Scheme, Energy Aware Mobility, Interest based Sensing, Wireless Sensor Networks (WSNs).

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Authors: Morgan Cheng, Wilson Ho, Max Yiu, Dragon Tsui, Wylog Wong, Yasir A. Naveed, C. S. Loong, Richard Kwan, K. C. Lam, Hannah Lo, C. L. Wong

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Hong Kong is known worldwide for high density living and the ability to thrive under trying circumstances. The 7.5 million residents of this busy metropolis live primarily in high-rise buildings which are built and demolished incessantly. Hong Kong residents are therefore affected continuously by numerous construction activities. In 2020, the Hong Kong Environmental Protection Department (EPD) commissioned a feasibility study on the management of construction noise, including those associated with renovation of domestic premises. A key component of the study focused on the review of practices concerning the management and control of construction noise in metropolitans in other parts of the world. To benefit from international best practices, this extensive review aimed at identifying possible areas of improvement in Hong Kong. The study first referred to the United Nations “The World’s Cities in 2016” Report and examined the top 100 cities therein. The 20 most suitable cities were then chosen for further review. Upon further screening, 12 cities with more relevant management practices were selected for further scrutiny. These 12 cities include: Asia – Tokyo, Seoul, Taipei, Guangzhou, Singapore; Europe – City of Westminster (London), Berlin; North America – Toronto, New York City, San Francisco; Oceania – Sydney, Melbourne. Subsequently, three cities, namely Sydney, City of Westminster, and New York City, were selected for in-depth review. These three were chosen primarily because of the maturity, success, and effectiveness of their construction noise management and control measures, as well as their similarity to Hong Kong in certain key aspects. One of the more important findings of the review is the importance of early focus on potential noise issues, with the objective of designing the noise away wherever practicable. The study examined the similar yet different construction noise early focus mechanisms of these three cities. This paper describes this landmark, worldwide and extensive review on international best construction noise management and control practices at the source, along the noise transmission path and at the receiver end. The methodology, approach, and key findings are presented succinctly in this paper. By sharing the findings with the acoustics professionals worldwide, it is hoped that more advanced and mature construction noise management practices can be developed to attain urban sustainability.

Keywords: construction noise, international best practices, noise control and noise management

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Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller

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Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.

Keywords: Multi-agent system, safety analysis, safety model.

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Authors: R. Usubamatov, A. Usubamatova, S. Hussain

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Modern highly automated production systems faces problems of reliability. Machine function reliability results in changes of productivity rate and efficiency use of expensive industrial facilities. Predicting of reliability has become an important research and involves complex mathematical methods and calculation. The reliability of high productivity technological automatic machines that consists of complex mechanical, electrical and electronic components is important. The failure of these units results in major economic losses of production systems. The reliability of transport and feeding systems for automatic technological machines is also important, because failure of transport leads to stops of technological machines. This paper presents reliability engineering on the feeding system and its components for transporting a complex shape parts to automatic machines. It also discusses about the calculation of the reliability parameters of the feeding unit by applying the probability theory. Equations produced for calculating the limits of the geometrical sizes of feeders and the probability of sticking the transported parts into the chute represents the reliability of feeders as a function of its geometrical parameters.

Keywords: Chute-feeder, parts, reliability.

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Authors: J. Zambujal-Oliveira

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The relation between taxation states and foreign direct investment has been studied for several perspectives and with states of different levels of development. Usually it's only considered the impact of tax level on the foreign direct investment volume. This paper enhances this view by assuming that multinationals companies (MNC) can use transfer prices systems and have got investment timing flexibility. Thus, it evaluates the impact of the use of international transfer pricing systems on the states- policy and on the investment timing of the multinational companies. In uncertain business environments (with periodical release of news), the investment can increase if MNC detain investment delay options. This paper shows how tax differentials can attract foreign direct investments (FDI) and influence MNC behavior. The equilibrium is set in a global environment where MNC can shift their profits between states depending on the corporate tax rates. Assuming the use of transfer pricing schemes, this paper confirms the relationship between MNC behavior and the release of new business news.

Keywords: Corporate Taxation, International Profit Shifting, Real Options

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Authors: Rawya Rizk, Rehab Abdel-Kader, Rabab Ramadan

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Unlike the best effort service provided by the internet today, next-generation wireless networks will support real-time applications. This paper proposes an adaptive early packet discard (AEPD) policy to improve the performance of the real time TCP traffic over ATM networks and avoid the fragmentation problem. Three main aspects are incorporated in the proposed policy. First, providing quality-of-service (QoS) guaranteed for real-time applications by implementing a priority scheduling. Second, resolving the partially corrupted packets problem by differentiating the buffered cells of one packet from another. Third, adapting a threshold dynamically using Fuzzy logic based on the traffic behavior to maintain a high throughput under a variety of load conditions. The simulation is run for two priority classes of the input traffic: real time and non-real time classes. Simulation results show that the proposed AEPD policy improves throughput and fairness over that using static threshold under the same traffic conditions.

Keywords: Early packet discard, Fuzzy logic, packet dropping policies, quality-of-service (QoS), TCP over ATM

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Authors: M.Rajasimman, S.Subathra

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In this work, statistical experimental design was applied for the optimization of medium constituents for Gentamicin production by Micromsonospora echinospora subs pallida (MTCC 708) in a batch reactor and the results are compared with the ANN predicted values. By central composite design, 50 experiments are carried out for five test variables: Starch, Soya bean meal, K2HPO4, CaCO3 and FeSO4. The optimum condition was found to be: Starch (8.9,g/L), Soya bean meal (3.3 g/L), K2HPO4 (0.8 g/L), CaCO3 (4 g/L) and FeSO4 (0.03 g/L). At these optimized conditions, the yield of gentamicin was found to be 1020 mg/L. The R2 values were found to be 1 for ANN training set, 0.9953 for ANN test set, and 0.9286 for RSM.

Keywords: Gentamicin, optimization, Micromonospora echinospora, ANN, RSM

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Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, Meisam Babaie

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Gas lift optimization is becoming more important now a day in petroleum industry. A proper lift optimization can reduce the operating cost, increase the net present value (NPV) and maximize the recovery from the asset. A widely accepted definition of gas lift optimization is to obtain the maximum output under specified operating conditions. In addition, gas lift, a costly and indispensable means to recover oil from high depth reservoir entails solving the gas lift optimization problems. Gas lift optimization is a continuous process; there are two levels of production optimization. The total field optimization involves optimizing the surface facilities and the injection rate that can be achieved by standard tools softwares. Well level optimization can be achieved by optimizing the well parameters such as point of injection, injection rate, and injection pressure. All these aspects have been investigated and presented in this study by using experimental data and PROSPER simulation program. The results show that the well head pressure has a large influence on the gas lift performance and also proved that smart gas lift valve can be used to improve gas lift performance by controlling gas injection from down hole. Obtaining the optimum gas injection rate is important because excessive gas injection reduces production rate and consequently increases the operation cost.

Keywords: Optimization, production rate, reservoir pressure effect, gas injection rate effect, gas injection pressure.

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Authors: Maja Ruzic-Baf, Vedrana Keteles, Andrea Debeljuh

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Younger and younger children are now using a smartphone, a device which has become ‘a must have’ and the life of children would be almost ‘unthinkable’ without one. Devices are becoming lighter and lighter but offering an array of options and applications as well as the unavoidable access to the Internet, without which it would be almost unusable. Numerous features such as taking of photographs, listening to music, information search on the Internet, access to social networks, usage of some of the chatting and messaging services, are only some of the numerous features offered by ‘smart’ devices. They have replaced the alarm clock, home phone, camera, tablet and other devices. Their use and possession have become a part of the everyday image of young people. Apart from the positive aspects, the use of smartphones has also some downsides. For instance, free time was usually spent in nature, playing, doing sports or other activities enabling children an adequate psychophysiological growth and development. The greater usage of smartphones during classes to check statuses on social networks, message your friends, play online games, are just some of the possible negative aspects of their application. Considering that the age of the population using smartphones is decreasing and that smartphones are no longer ‘foreign’ to children of pre-school age (smartphones are used at home or in coffee shops or shopping centers while waiting for their parents, playing video games often inappropriate to their age), particular attention must be paid to a very sensitive group, the teenagers who almost never separate from their ‘pets’. This paper is divided into two sections, theoretical and empirical ones. The theoretical section gives an overview of the pros and cons of the usage of smartphones, while the empirical section presents the results of a research conducted in three elementary schools regarding the usage of smartphones and, specifically, their usage during classes, during breaks and to search information on the Internet, check status updates and 'likes’ on the Facebook social network.

Keywords: Education, smartphone, social networks, teenagers.

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Authors: Shin-Shin Kao

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This paper reviews the crucial situation in higher education in Taiwan due to the rapid decline of the birth rate in the past three decades, and how the government and local colleges/universities work to face the challenge. Recruiting international students is one of the possible ways to resolve the problem, but offering enough courses in English is one of the main obstacles when the majority of learners are still Taiwanese students. In the academic year of 2012, Chung Yuan Christian University determined to make its campus international and began to enforce two required courses for freshmen taught in English. It failed in the beginning, but succeeded in the following academic year of 2013. Using the teaching evaluations accumulated in the past three years, this paper aims to clarify the myths which had been bothering most faculties. It also offers some suggestions for college/university teachers interested in giving lectures in English to English as Second Language (ESL) learners. A conclusion is presented at the end of the paper, in which the author explained why Taiwanese students could learn their profession in English.

Keywords: Calculus, English, teaching evaluation, teaching strategy, vocabulary.

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Authors: Zelmina Lubovac, Björn Olsson, Jonas Gamalielsson

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This paper describes a novel approach for deriving modules from protein-protein interaction networks, which combines functional information with topological properties of the network. This approach is based on weighted clustering coefficient, which uses weights representing the functional similarities between the proteins. These weights are calculated according to the semantic similarity between the proteins, which is based on their Gene Ontology terms. We recently proposed an algorithm for identification of functional modules, called SWEMODE (Semantic WEights for MODule Elucidation), that identifies dense sub-graphs containing functionally similar proteins. The rational underlying this approach is that each module can be reduced to a set of triangles (protein triplets connected to each other). Here, we propose considering semantic similarity weights of all triangle-forming edges between proteins. We also apply varying semantic similarity thresholds between neighbours of each node that are not neighbours to each other (and hereby do not form a triangle), to derive new potential triangles to include in module-defining procedure. The results show an improvement of pure topological approach, in terms of number of predicted modules that match known complexes.

Keywords: Modules, systems biology, protein interactionnetworks, yeast.

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Authors: Dariush Semnani, Mehdi Ahangareianabhari, Hossein Ghayoor

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In recent five decades, textured yarns of polyester fiber produced by false twist method are the most important and mass-produced manmade fibers. There are many parameters of cross section which affect the physical and mechanical properties of textured yarns. These parameters are surface area, perimeter, equivalent diameter, large diameter, small diameter, convexity, stiffness, eccentricity, and hydraulic diameter. These parameters were evaluated by digital image processing techniques. To find trends between production criteria and evaluated parameters of cross section, three criteria of production line have been adjusted and different types of yarns were produced. These criteria are temperature, drafting ratio, and D/Y ratio. Finally the relations between production criteria and cross section parameters were considered. The results showed that the presented technique can recognize and measure the parameters of fiber cross section in acceptable accuracy. Also, the optimum condition of adjustments has been estimated from results of image analysis evaluation.

Keywords: Computer Vision, Cross Section Analysis, Fibers Deformation, Textured Yarn

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Authors: Maassoumeh Javadi Baygi, Abdul Rahman B Ramli, Borhanuddin Mohd Ali, Syamsiah Mashohor

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The expectation of network performance from the early days of ARPANET until now has been changed significantly. Every day, new advancement in technological infrastructure opens the doors for better quality of service and accordingly level of perceived quality of network services have been increased over the time. Nowadays for many applications, late information has no value or even may result in financial or catastrophic loss, on the other hand, demands for some level of guarantee in providing and maintaining quality of service are ever increasing. Based on this history, having a QoS aware routing system which is able to provide today's required level of quality of service in the networks and effectively adapt to the future needs, seems as a key requirement for future Internet. In this work we have extended the traditional AntNet routing system to support QoS with multiple metrics such as bandwidth and delay which is named Q-Net. This novel scalable QoS routing system aims to provide different types of services in the network simultaneously. Each type of service can be provided for a period of time in the network and network nodes do not need to have any previous knowledge about it. When a type of quality of service is requested, Q-Net will allocate required resources for the service and will guarantee QoS requirement of the service, based on target objectives.

Keywords: Quality of Service, Routing, Ant Colony Optimization, Ant-based algorithms.

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Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw

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This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.

Keywords: Neural network, Load forecast, Time series, wavelettransform.

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Authors: Wahidul K. Biswas

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Perth will run out of available sustainable natural water resources by 2015 if nothing is done to slow usage rates, according to a Western Australian study [1]. Alternative water technology options need to be considered for the long-term guaranteed supply of water for agricultural, commercial, domestic and industrial purposes. Seawater is an alternative source of water for human consumption, because seawater can be desalinated and supplied in large quantities to a very high quality. While seawater desalination is a promising option, the technology requires a large amount of energy which is typically generated from fossil fuels. The combustion of fossil fuels emits greenhouse gases (GHG) and, is implicated in climate change. In addition to environmental emissions from electricity generation for desalination, greenhouse gases are emitted in the production of chemicals and membranes for water treatment. Since Australia is a signatory to the Kyoto Protocol, it is important to quantify greenhouse gas emissions from desalinated water production. A life cycle assessment (LCA) has been carried out to determine the greenhouse gas emissions from the production of 1 gigalitre (GL) of water from the new plant. In this LCA analysis, a new desalination plant that will be installed in Bunbury, Western Australia, and known as Southern Seawater Desalinization Plant (SSDP), was taken as a case study. The system boundary of the LCA mainly consists of three stages: seawater extraction, treatment and delivery. The analysis found that the equivalent of 3,890 tonnes of CO2 could be emitted from the production of 1 GL of desalinated water. This LCA analysis has also identified that the reverse osmosis process would cause the most significant greenhouse emissions as a result of the electricity used if this is generated from fossil fuels

Keywords: Desalinization, Greenhouse gas emissions, life cycle assessment.

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Authors: N. Mahendran, R. Madhuranthi

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Wireless sensor networks (WSNs), are constantly in demand to process information more rapidly with less energy and area cost. Presently, processor based solutions have difficult to achieve high processing speed with low-power consumption. This paper presents a simple and accurate data processing scheme for low power wireless sensor node, based on reduced number of processing element (PE). The presented model provides a simple recursive structure (SRS) to process the sampled data in the wireless sensor environment and to reduce the power consumption in wireless sensor node. Based on this model, to process the incoming samples and produce a smaller amount of data sufficient to reconstruct the original signal. The ModelSim simulator used to simulate SRS structure. Functional simulation is carried out for the validation of the presented architecture. Xilinx Power Estimator (XPE) tool is used to measure the power consumption. The experimental results show the average power consumption of 91 mW; this is 42% improvement compared to the folded tree architecture.

Keywords: Power consumption, energy efficiency, low power WSN node, recursive structure, sleep/wake scheduling.

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Authors: Mustafa Elfituri, Jonathan Cook

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Recently, graph-based computations have become more important in large-scale scientific computing as they can provide a methodology to model many types of relations between independent objects. They are being actively used in fields as varied as biology, social networks, cybersecurity, and computer networks. At the same time, graph problems have some properties such as irregularity and poor locality that make their performance different than regular applications performance. Therefore, parallelizing graph algorithms is a hard and challenging task. Initial evidence is that standard computer architectures do not perform very well on graph algorithms. Little is known exactly what causes this. The Graph500 benchmark is a representative application for parallel graph-based computations, which have highly irregular data access and are driven more by traversing connected data than by computation. In this paper, we present results from analyzing the performance of various example implementations of Graph500, including a shared memory (OpenMP) version, a distributed (MPI) version, and a hybrid version. We measured and analyzed all the factors that affect its performance in order to identify possible changes that would improve its performance. Results are discussed in relation to what factors contribute to performance degradation.

Keywords: Graph computation, Graph500 benchmark, parallel architectures, parallel programming, workload characterization.

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Authors: Ammar Elyas babiker, M.Nordin B. Zakaria, Hassan Yosif, Samir B. Ibrahim

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Variable channel conditions in underwater networks, and variable distances between sensors due to water current, leads to variable bit error rate (BER). This variability in BER has great effects on energy efficiency of error correction techniques used. In this paper an efficient energy adaptive hybrid error correction technique (AHECT) is proposed. AHECT adaptively changes error technique from pure retransmission (ARQ) in a low BER case to a hybrid technique with variable encoding rates (ARQ & FEC) in a high BER cases. An adaptation algorithm depends on a precalculated packet acceptance rate (PAR) look-up table, current BER, packet size and error correction technique used is proposed. Based on this adaptation algorithm a periodically 3-bit feedback is added to the acknowledgment packet to state which error correction technique is suitable for the current channel conditions and distance. Comparative studies were done between this technique and other techniques, and the results show that AHECT is more energy efficient and has high probability of success than all those techniques.

Keywords: Underwater communication, wireless sensornetworks, error correction technique, energy efficiency

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Authors: P. Luangpaiboon, P. Aungkulanon

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This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.

Keywords: Aggregate Production Planning, Desirability Function Approach, Improved Harmony Search Algorithm, Hunting Search Algorithm and Firefly Algorithm.

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Authors: B. Mendonça, D. Sandwell

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The Metropolitan Region of Sao Paulo (MRSP) has suffered from serious water scarcity. Consequently, the most convenient solution has been building wells to extract groundwater from local aquifers. However, it requires constant vigilance to prevent over extraction and future events that can pose serious threat to the population, such as subsidence. Radar imaging techniques (InSAR) have allowed continuous investigation of such phenomena. The analysis of data in the present study consists of 23 SAR images dated from October 2007 to March 2011, obtained by the ALOS-1 spacecraft. Data processing was made with the software GMTSAR, by using the InSAR technique to create pairs of interferograms with ground displacement during different time spans. First results show a correlation between the location of 102 wells registered in 2009 and signals of ground displacement equal or lower than -90 millimeters (mm) in the region. The longest time span interferogram obtained dates from October 2007 to March 2010. As a result, from that interferogram, it was possible to detect the average velocity of displacement in millimeters per year (mm/y), and which areas strong signals have persisted in the MRSP. Four specific areas with signals of subsidence of 28 mm/y to 40 mm/y were chosen to investigate the phenomenon: Guarulhos (Sao Paulo International Airport), the Greater Sao Paulo, Itaquera and Sao Caetano do Sul. The coverage area of the signals was between 0.6 km and 1.65 km of length. All areas are located above a sedimentary type of aquifer. Itaquera and Sao Caetano do Sul showed signals varying from 28 mm/y to 32 mm/y. On the other hand, the places most likely to be suffering from stronger subsidence are the ones in the Greater Sao Paulo and Guarulhos, right beside the International Airport of Sao Paulo. The rate of displacement observed in both regions goes from 35 mm/y to 40 mm/y. Previous investigations of the water use at the International Airport highlight the risks of excessive water extraction that was being done through 9 deep wells. Therefore, it is affirmed that subsidence events are likely to occur and to cause serious damage in the area. This study could show a situation that has not been explored with proper importance in the city, given its social and economic consequences. Since the data were only available until 2011, the question that remains is if the situation still persists. It could be reaffirmed, however, a scenario of risk at the International Airport of Sao Paulo that needs further investigation.

Keywords: Ground subsidence, interferometric satellite aperture radar (InSAR), metropolitan region of Sao Paulo, water extraction.

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Authors: Olga Velts, Mai Uibu, Juha Kallas, Rein Kuusik

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An innovative approach utilizing highly alkaline oil shale waste ash and carbon dioxide gas (CO2), associated with power production, as a resource for production of precipitated calcium carbonate (PCC) is introduced in this paper. The specifics and feasibility of the integrated ash valorization and CO2 sequestration process by indirect aqueous carbonation of lime-consisting ash were elaborated and the main parameters established. Detailed description of the formed precipitates was included. Complimentary carbonation experiments with commercial CaO fine powder were conducted for comparative characterization of the final products obtained on the basis of two different raw materials. Finally, the expected CO2 uptake was evaluated.

Keywords: Calcium Carbonate, Carbon Dioxide Sequestration, Oil Shale Ash, Waste Valorization.

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Authors: S. Padmapriya, M. Tamilarasi

Abstract:

Femtocells are regarded as a milestone for next generation cellular networks. As femtocells are deployed in an unplanned manner, there is a chance of assigning same resource to neighboring femtocells. This scenario may induce co-channel interference and may seriously affect the service quality of neighboring femtocells. In addition, the dominant transmit power of a femtocell will induce co-tier interference to neighboring femtocells. Thus to jointly handle co-tier and co-channel interference, we propose an interference-free power and resource block allocation (IFPRBA) algorithm for closely located, closed access femtocells. Based on neighboring list, inter-femto-base station distance and uplink noise power, the IFPRBA algorithm assigns non-interfering power and resource to femtocells. The IFPRBA algorithm also guarantees the quality of service to femtouser based on the knowledge of resource requirement, connection type, and the tolerable delay budget. Simulation result shows that the interference power experienced in IFPRBA algorithm is below the tolerable interference power and hence the overall service success ratio, PRB efficiency and network throughput are maximum when compared to conventional resource allocation framework for femtocell (RAFF) algorithm.

Keywords: Co-channel interference, co-tier interference, femtocells, guaranteed QoS, power optimization, resource assignment.

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Authors: Federico Cabitza, Bernardo Dal Seno

Abstract:

In this paper DJess is presented, a novel distributed production system that provides an infrastructure for factual and procedural knowledge sharing. DJess is a Java package that provides programmers with a lightweight middleware by which inference systems implemented in Jess and running on different nodes of a network can communicate. Communication and coordination among inference systems (agents) is achieved through the ability of each agent to transparently and asynchronously reason on inferred knowledge (facts) that might be collected and asserted by other agents on the basis of inference code (rules) that might be either local or transmitted by any node to any other node.

Keywords: Knowledge-Based Systems, Expert Systems, Distributed Inference Systems, Parallel Production Systems, Ambient Intelligence, Mobile Agents.

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Authors: Lillian Gungat, Meor Othman Hamzah, Mohd Rosli Mohd Hasan, Jan Valentin

Abstract:

Utilization of a high percentage of reclaimed asphalt pavement (RAP) requires higher production temperatures and consumes more energy. High production temperature expedites the aging of bitumen in RAP, which could affect the mixture performance. Warm mix asphalt (WMA) additive enables reduced production temperatures as a result of viscosity reduction. This paper evaluates the integration of a high percentage of RAP with a WMA additive known as RH-WMA. The optimum dosage of RH-WMA was determined from basic properties tests. A total of 0%, 30% and 50% RAP contents from two roads sources were modified with RH-WMA. The modified RAP bitumen were examined for viscosity, stiffness, rutting resistance and greenhouse gas emissions. The addition of RH-WMA improved the flow of bitumen by reducing the viscosity, and thus, decreased the construction temperature. The stiffness of the RAP modified bitumen reduced with the incorporation of RH-WMA. The positive improvement in rutting resistance was observed on bitumen with the addition of RAP and RH-WMA in comparison with control. It was estimated that the addition of RH-WMA could potentially reduce fuel usage and GHG emissions by 22 %. Hence, the synergy of RAP and WMA technology can be an alternative in green road construction.

Keywords: Reclaimed asphalt pavement, WMA additive, viscosity, stiffness, emissions.

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Authors: A. T. Asutosh, J. Woo, M. Kouhirostami, M. Sam, A. Khantawang, C. Cuales, W. Ryor, C. Kibert

Abstract:

Climate change and global warming vortex have grown to alarming proportions. Therefore, the need for a shift in the conceptualization of energy production is paramount. Energy practices have been created in the current situation. Fossil fuels continue their prominence, at the expense of renewable sources. Despite this abundance, a large percentage of the world population still has no access to electricity but there have been encouraging signs in global movement from nonrenewable to renewable energy but means to reverse climate change have been elusive. Worldwide, organizations have put tremendous effort into innovation. Conferences and exhibitions act as a platform that allows a broad exchange of information regarding trends in the renewable energy field. The Solar Power International (SPI) conference and exhibition is a gathering of concerned activists, and probably the largest convention of its kind. This study investigates current development in the renewable energy field, analyzing means by which industry is being applied to the issue. In reviewing the 2019 SPI conference, it was found innovations in recycling and assessing the environmental impacts of the solar products that need critical attention. There is a huge movement in the electrical storage but there exists a large gap in the development of security systems. This research will focus on solar energy, but impacts will be relevant to the entire renewable energy market.

Keywords: Climate change, renewable energy, solar, trends, research, SPI.

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Authors: Anchana Khemphila, Veera Boonjing

Abstract:

In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.

Keywords: Data mining, classification, Parkinson disease, artificial neural networks, feature selection, information gain.

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