Search results for: planning navigational ability

Authors: J. Radojicic, D. Surdilovic, G. Schreck

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The paper considers a novel modular and intrinsically safe redundant robotic system with biologically inspired actuators (pneumatic artificial muscles and rubber bellows actuators). Similarly to the biological systems, the stiffness of the internal parallel modules, representing 2 DOF joints in the serial robotic chains, is controlled by co-activation of opposing redundant actuator groups in the null-space of the module Jacobian, without influencing the actual robot position. The decoupled position/stiffness control allows the realization of variable joint stiffness according to different force-displacement relationships. The variable joint stiffness, as well as limited pneumatic muscle/bellows force ability, ensures internal system safety that is crucial for development of human-friendly robots intended for human-robot collaboration. The initial experiments with the system prototype demonstrate the capabilities of independently, simultaneously controlling both joint (Cartesian) motion and joint stiffness. The paper also presents the possible industrial applications of snake-like robots built using the new modules.

Keywords: bellows actuator, human-robot interaction, hyper redundant robot, pneumatic muscle.

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Authors: Sunita Jahirabadkar, Parag Kulkarni

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Many real-world data sets consist of a very high dimensional feature space. Most clustering techniques use the distance or similarity between objects as a measure to build clusters. But in high dimensional spaces, distances between points become relatively uniform. In such cases, density based approaches may give better results. Subspace Clustering algorithms automatically identify lower dimensional subspaces of the higher dimensional feature space in which clusters exist. In this paper, we propose a new clustering algorithm, ISC – Intelligent Subspace Clustering, which tries to overcome three major limitations of the existing state-of-art techniques. ISC determines the input parameter such as є – distance at various levels of Subspace Clustering which helps in finding meaningful clusters. The uniform parameters approach is not suitable for different kind of databases. ISC implements dynamic and adaptive determination of Meaningful clustering parameters based on hierarchical filtering approach. Third and most important feature of ISC is the ability of incremental learning and dynamic inclusion and exclusions of subspaces which lead to better cluster formation.

Keywords: Density based clustering, high dimensional data, subspace clustering, dynamic parameter setting.

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Authors: Mariyam Arif, Ye Liu, Israr Ul Haq, Ahsan Ashfaq

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High cost of fossil fuels and intensifying installations of alternate energy generation sources are intimidating main challenges in power systems. Making accurate load forecasting an important and challenging task for optimal energy planning and management at both distribution and generation side. There are many techniques to forecast load but each technique comes with its own limitation and requires data to accurately predict the forecast load. Artificial Neural Network (ANN) is one such technique to efficiently forecast the load. Comparison between two different ranges of input datasets has been applied to dynamic ANN technique using MATLAB Neural Network Toolbox. It has been observed that selection of input data on training of a network has significant effects on forecasted results. Day-wise input data forecasted the load accurately as compared to year-wise input data. The forecasted load is then distributed among the six generators by using the linear programming to get the optimal point of generation. The algorithm is then verified by comparing the results of each generator with their respective generation limits.

Keywords: Artificial neural networks, demand-side management, economic dispatch, linear programming, power generation dispatch.

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Authors: Davinder Singh, Jaimal Singh Khamba, Tarun Nanda

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MSMEs are regarded as the sunrise sector of the Indian economy in view of its large potential for growth and likely socio economic impact specifically on employment and income generation. In today’s competitive business environment, global competition forces companies to continuously seek ways of improving their products and services. The pressure on organizations to adapt to new technologies and external threats requires resourcefulness, creativity and innovation. Market has become more open, competitive and customers more demanding. Without continuous technology innovation, no organization can ever remain competitive. Innovations reflect a critical way in which organizations respond to either technological or market challenges. The need of the market is to deliver high quality products through continuous changing in features in product, improve existing products, reduce their cost, and improve employee skills, training, technology infrastructure and financial policies. Therefore, the key factor of organization’s ability to change is innovation. The study presents a detailed review of literature on the role of technology innovation in improving manufacturing performance of industries.

Keywords: Competitive, Manufacturing performance, MSMEs, Technological Innovation.

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Authors: Héctor Rivera-Gómez, Eva Selene Hernández-Gress, Oscar Montaño-Arango, Jose Ramon Corona-Armenta

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This research studies the joint production, maintenance and subcontracting control policy for an unreliable deteriorating manufacturing system. Production activities are controlled by a derivation of the Hedging Point Policy, and given that the system is subject to deterioration, it reduces progressively its capacity to satisfy product demand. Multiple deterioration effects are considered, reflected mainly in the quality of the parts produced and the reliability of the machine. Subcontracting is available as support to satisfy product demand; also, overhaul maintenance can be conducted to reduce the effects of deterioration. The main objective of the research is to determine simultaneously the production, maintenance and subcontracting rate, which minimize the total, incurred cost. A stochastic dynamic programming model is developed and solved through a simulation-based approach composed of statistical analysis and optimization with the response surface methodology. The obtained results highlight the strong interactions between production, deterioration and quality, which justify the development of an integrated model. A numerical example and a sensitivity analysis are presented to validate our results.

Keywords: Deterioration, simulation, subcontracting, production planning.

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Authors: Yih-Ferng Peng

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In this paper, the local grid refinement is focused by using a nested grid technique. The Cartesian grid numerical method is developed for simulating unsteady, viscous, incompressible flows with complex immersed boundaries. A finite volume method is used in conjunction with a two-step fractional-step procedure. The key aspects that need to be considered in developing such a nested grid solver are imposition of interface conditions on the inter-block and accurate discretization of the governing equation in cells that are with the inter-block as a control surface. A new interpolation procedure is presented which allows systematic development of a spatial discretization scheme that preserves the spatial accuracy of the underlying solver. The present nested grid method has been tested by two numerical examples to examine its performance in the two dimensional problems. The numerical examples include flow past a circular cylinder symmetrically installed in a Channel and flow past two circular cylinders with different diameters. From the numerical experiments, the ability of the solver to simulate flows with complicated immersed boundaries is demonstrated and the nested grid approach can efficiently speed up the numerical solutions.

Keywords: local grid refinement, Cartesian grid, nested grid, fractional-step method.

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Authors: A. Zeynolabedin, M. A. Olyaei, B. Ghiasi

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Drought is an inevitable part of the earth’s climate. It occurs regularly with no clear warning and without recognizing borders. In addition, its impact is cumulative and not immediately discernible. Iran is located in a semi-arid region where droughts occur periodically as natural hazard. Standardized Precipitation Index (SPI), Surface Water Supply Index (SWSI), and Palmer Drought Severity Index (PDSI) are three well-known indices which describe drought severity; each has its own advantages and disadvantages and can be used for specific types of drought. These indices take into account some factors such as precipitation, reservoir storage and discharge, temperature, and potential evapotranspiration in determining drought severity. In this paper, first all three indices are calculated in Aharchay river watershed located in northwestern part of Iran in East Azarbaijan province. Next, based on two other important parameters which are groundwater level and solar radiation, two new indices are defined. Finally, considering all five aforementioned indices, a combined drought index (CDI) is presented and calculated for the region. This combined index is based on all the meteorological, hydrological, and agricultural features of the region. The results show that the most severe drought condition in Aharchay watershed happened in Jun, 2004. The result of this study can be used for monitoring drought and prepare for the drought mitigation planning.

Keywords: Drought, index variation, regional assessment, monitoring.

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Authors: Lina Galinskaitė, Gytautas Ignatavičius

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Animal vehicle collisions (AVCs) affect human safety, cause property damage and wildlife welfare. The number of AVCs are increasing and creating serious implications for the animal conservation and management. Roe deer (Capreolus capreolus) and other large ungulates (moose, wild boar, red deer) are the most frequently collided ungulate with vehicles in Europe. Therefore, we analyzed temporal patterns of roe deer vehicle collisions (RDVC) occurring in Lithuania. Using a comprehensive dataset, consisting of 15,891 data points, we examined the influence of different time units (i.e. time of the day, day of week, month, and season) on RDVC. We identified accident periods within the analyzed time units. Highest frequencies of RDVC occurred on Fridays. Highest frequencies of roe deer-vehicle accidents occurred in May, November and December. Regarding diurnal patterns, most of RDVC occur after sunset and before sunset (during dark hours). Since vehicle collisions with animals showed temporal variation, these should be taken into consideration in developing statistical models of spatial AVC patterns, and also in planning strategies to reduce accident risk.

Keywords: Animal vehicle collision, diurnal patterns, road safety, roe deer, statistical analysis.

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Authors: Gaoyuan Wang, Tian Chen, Junnan Liu

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Facing a period of major change that is rarely seen in a century, China formulates the 14th Five-Year Plan and places emphasis on promoting high-quality development. In this context, the overall urban design has become a crucial and systematic tool for high-quality urban development. However, there are bottlenecks in the cognition of nature, content scope and transmission mechanisms of the current overall urban design in China. The paper interprets the emerging demands of the 14th Five-Year Plan on urban design in terms of new value-quality priority, new dynamic-space performance, new target-region coordination and new path-refined governance. Based on the new trend and appeal, the multi-dimensional thinking integrated with the major tasks of urban design are proposed accordingly, which is the biomass thinking in ecological, production and living element, the strategic thinking in spatial structure, the systematic thinking in the cityscape, the low-carbon thinking in urban form, the governance thinking in public space, the user thinking in design implementation. The paper explores the possibility of transforming the value thinking and technical system of urban design in China and provides a breakthrough path for the urban planning and design industry to better respond to the propositions of the country’s 14th Five-Year Plan.

Keywords: China’s 14th five-year plan, overall urban design, urban design thinking, transformation of urban design.

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Authors: Hadi Veisi, Mansour Jamzad

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In this paper we present an adaptive method for image compression that is based on complexity level of the image. The basic compressor/de-compressor structure of this method is a multilayer perceptron artificial neural network. In adaptive approach different Back-Propagation artificial neural networks are used as compressor and de-compressor and this is done by dividing the image into blocks, computing the complexity of each block and then selecting one network for each block according to its complexity value. Three complexity measure methods, called Entropy, Activity and Pattern-based are used to determine the level of complexity in image blocks and their ability in complexity estimation are evaluated and compared. In training and evaluation, each image block is assigned to a network based on its complexity value. Best-SNR is another alternative in selecting compressor network for image blocks in evolution phase which chooses one of the trained networks such that results best SNR in compressing the input image block. In our evaluations, best results are obtained when overlapping the blocks is allowed and choosing the networks in compressor is based on the Best-SNR. In this case, the results demonstrate superiority of this method comparing with previous similar works and JPEG standard coding.

Keywords: Adaptive image compression, Image complexity, Multi-layer perceptron neural network, JPEG Standard, PSNR.

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Authors: Z. Qi, T. J. Moir

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A combined three-microphone voice activity detector (VAD) and noise-canceling system is studied to enhance speech recognition in an automobile environment. A previous experiment clearly shows the ability of the composite system to cancel a single noise source outside of a defined zone. This paper investigates the performance of the composite system when there are frequently moving noise sources (noise sources are coming from different locations but are not always presented at the same time) e.g. there is other passenger speech or speech from a radio when a desired speech is presented. To work in a frequently moving noise sources environment, whilst a three-microphone voice activity detector (VAD) detects voice from a “VAD valid zone", the 3-microphone noise canceller uses a “noise canceller valid zone" defined in freespace around the users head. Therefore, a desired voice should be in the intersection of the noise canceller valid zone and VAD valid zone. Thus all noise is suppressed outside this intersection of area. Experiments are shown for a real environment e.g. all results were recorded in a car by omni-directional electret condenser microphones.

Keywords: Signal processing, voice activity detection, noise canceller, microphone array beam forming.

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Authors: S. Areerachakul

Abstract:

Nowadays, several techniques such as; Fuzzy Inference System (FIS) and Neural Network (NN) are employed for developing of the predictive models to estimate parameters of water quality. The main objective of this study is to compare between the predictive ability of the Adaptive Neuro-Fuzzy Inference System (ANFIS) model and Artificial Neural Network (ANN) model to estimate the Biochemical Oxygen Demand (BOD) on data from 11 sampling sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2004-2011. The five parameters of water quality namely Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Ammonia Nitrogen (NH3N), Nitrate Nitrogen (NO3N), and Total Coliform bacteria (T-coliform) are used as the input of the models. These water quality indices affect the biochemical oxygen demand. The experimental results indicate that the ANN model provides a higher correlation coefficient (R=0.73) and a lower root mean square error (RMSE=4.53) than the corresponding ANFIS model.

Keywords: adaptive neuro-fuzzy inference system, artificial neural network, biochemical oxygen demand, surface water.

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Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

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With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: Artificial neural network, ANN, chromatic dispersion, delay-tap sampling, optical signal-to-noise ratio, OSNR.

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Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria namely, the Mean Absolute Error and Root Mean Square Error. The National Renewable Energy Laboratory (NREL) residential energy consumption data are used to train the models. The results of this study show that SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts we can improve the robustness of the models for 24 hour ahead electricity load forecasting.

Keywords: Bagging, Fbprophet, Holt-Winters, LSTM, Load Forecast, SARIMA, tensorflow probability, time series.

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Authors: Benmoussa Rachid, Deguio Roland, Dubois Sebastien, Rasovska Ivana

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Implementation of LARG (Lean, Agile, Resilient, Green) practices in the supply chain management is a complex task mainly because ecological, economical and operational goals are usually in conflict. To implement these LARG practices successfully, companies’ need relevant decision making tools allowing processes performance control and improvement strategies visibility. To contribute to this issue, this work tries to answer the following research question: How to master performance and anticipate problems in supply chain LARG practices implementation? To answer this question, a risk management approach (RMA) is adopted. Indeed, the proposed RMA aims basically to assess the ability of a supply chain, guided by “Lean, Green and Achievement” performance goals, to face “agility and resilience risk” factors. To proof its relevance, a logistics academic case study based on simulation is used to illustrate all its stages. It shows particularly how to build the “LARG risk map” which is the main output of this approach.

Keywords: Risk approach, lean supply chain, agile supply chain, green supply chain, resilient supply chain.

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Authors: Rizwan Nasir, Hilmi Mukhtar, Zakaria Man, Dzeti Farhah Mohshim

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Carbon dioxide has been well associated with greenhouse effect, and due to its corrosive nature it is an undesirable compound. A variety of physical-chemical processes are available for the removal of carbon dioxide. Previous attempts in this field have established alkanolamine group has the capability to remove carbon dioxide. So, this study combined the polymeric membrane and alkanolamine solutions to fabricate the amine polymeric membrane (APM) to remove carbon dioxide (CO₂). This study entails the effect of three types of amines, monoethanolamine (MEA), diethanolamine (DEA), and methyldiethanolamine (MDEA). The effect of each alkanolamine group on the morphology and performance of polyether sulfone (PES) polymeric membranes was studied. Flat sheet membranes were fabricated by solvent evaporation method by adding polymer and different alkanolamine solutions in the N-Methyl-2-pyrrolidone (NMP) solvent. The final membranes were characterized by using Field Emission Electron Microscope (FESEM), Fourier Transform Infrared (FTIR), and Thermo-Gravimetric Analysis (TGA). The membrane separation performance was studied. The PES-DEA and PES-MDEA membrane has good ability to remove carbon dioxide. 

Keywords: Amine Polymeric membrane, Alkanolamine solution, CO2 Removal, Characterization.

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Authors: Tarun Kumar Naiya, Biswajit Singha, Ashim Kumar Bhattacharya, Sudip Kumar Das

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Fuller’s earth is a fine-grained, naturally occurring substance that has a substantial ability to adsorb impurities. In the present study Fuller’s earth has been characterized and used for the removal of Pb(II) from aqueous solution. The effect of various physicochemical parameters such as pH, adsorbent dosage and shaking time on adsorption were studied. The result of the equilibrium studies showed that the solution pH was the key factor affecting the adsorption. The optimum pH for adsorption was 5. Kinetics data for the adsorption of Pb(II) was best described by pseudo-second order model. The effective diffusion co-efficient for Pb(II) adsorption was of the order of 10-8 m2/s. The adsorption data for metal adsorption can be well described by Langmuir adsorption isotherm. The maximum uptake of metal was 103.3 mg/g of adsorbent. Mass transfer analysis was also carried out for the adsorption process. The values of mass transfer coefficients obtained from the study indicate that the velocity of the adsorbate transport from bulk to the solid phase was quite fast. The mean sorption energy calculated from Dubinin-Radushkevich isotherm indicated that the metal adsorption process was chemical in nature. 

Keywords: Fuller's earth, Pseudo second order, Mass Transfer co-efficient, Langmuir

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Authors: Rosziati Ibrahim, Siow Yen Yen

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System development life cycle (SDLC) is a process uses during the development of any system. SDLC consists of four main phases: analysis, design, implement and testing. During analysis phase, context diagram and data flow diagrams are used to produce the process model of a system. A consistency of the context diagram to lower-level data flow diagrams is very important in smoothing up developing process of a system. However, manual consistency check from context diagram to lower-level data flow diagrams by using a checklist is time-consuming process. At the same time, the limitation of human ability to validate the errors is one of the factors that influence the correctness and balancing of the diagrams. This paper presents a tool that automates the consistency check between Data Flow Diagrams (DFDs) based on the rules of DFDs. The tool serves two purposes: as an editor to draw the diagrams and as a checker to check the correctness of the diagrams drawn. The consistency check from context diagram to lower-level data flow diagrams is embedded inside the tool to overcome the manual checking problem.

Keywords: Data Flow Diagram, Context Diagram, ConsistencyCheck, Syntax and Semantic Rules

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Authors: Martin Doran, Roy Sterritt, George Wilkie

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The majority of today’s mobile robots are very dependent on battery power. Mobile robots can operate untethered for a number of hours but eventually they will need to recharge their batteries in-order to continue to function. While computer processing and sensors have become cheaper and more powerful each year, battery development has progress very little. They are slow to re-charge, inefficient and lagging behind in the general progression of robotic development we see today. However, batteries are relatively cheap and when fully charged, can supply high power output necessary for operating heavy mobile robots. As there are no cheap alternatives to batteries, we need to find efficient ways to manage the power that batteries provide during their operational lifetime. This paper proposes the use of autonomic principles of self-adaption to address the behavioral changes a battery experiences as it gets older. In life, as we get older, we cannot perform tasks in the same way as we did in our youth; these tasks generally take longer to perform and require more of our energy to complete. Batteries also suffer from a form of degradation. As a battery gets older, it loses the ability to retain the same charge capacity it would have when brand new. This paper investigates how we can adapt the current state of a battery charge and cycle count, to the requirements of a mobile robot to perform its tasks.

Keywords: Autonomic, self-adaptive, self-optimizing, degradation.

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Authors: Eakarat Boonreang

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The past two decades, Thailand faced the natural disasters, for instance, Gay typhoon in 1989, tsunami in 2004, and huge flood in 2011. The disaster management in Thailand was improved both structure and mechanism for cope with the natural disaster since 2007. However, the natural disaster management in Thailand has various problems, for examples, cooperation between related an organizations have not unity, inadequate resources, the natural disaster management of public sectors not proactive, people has not awareness the risk of the natural disaster, and communities did not participate in the natural disaster management. Objective of this study is to find the methods for capacity building in the natural disaster management of Thailand. The concept and information about the capacity building and the natural disaster management of Thailand were reviewed and analyzed by classifying and organizing data. The result found that the methods for capacity building in the natural disaster management of Thailand should be consist of 1) link operation and information in the natural disaster management between nation, province, local and community levels, 2) enhance competency and resources of public sectors which relate to the natural disaster management, 3) establish proactive natural disaster management both planning and implementation, 4) decentralize the natural disaster management to local government organizations, 5) construct public awareness in the natural disaster management to community, 6) support Community Based Disaster Risk Management (CBDRM) seriously, and 7) emphasis on participation in the natural disaster management of all stakeholders.

Keywords: Capacity Building, Community Based Disaster Risk Management, Natural Disaster Management, Thailand.

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

Abstract:

Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: Cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma.

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Authors: Md. Ashikur Rahman Khan, M. M. Rahman, K. Kadirgama, M.A. Maleque, Rosli A. Bakar

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Conventionally the selection of parameters depends intensely on the operator-s experience or conservative technological data provided by the EDM equipment manufacturers that assign inconsistent machining performance. The parameter settings given by the manufacturers are only relevant with common steel grades. A single parameter change influences the process in a complex way. Hence, the present research proposes artificial neural network (ANN) models for the prediction of surface roughness on first commenced Ti-15-3 alloy in electrical discharge machining (EDM) process. The proposed models use peak current, pulse on time, pulse off time and servo voltage as input parameters. Multilayer perceptron (MLP) with three hidden layer feedforward networks are applied. An assessment is carried out with the models of distinct hidden layer. Training of the models is performed with data from an extensive series of experiments utilizing copper electrode as positive polarity. The predictions based on the above developed models have been verified with another set of experiments and are found to be in good agreement with the experimental results. Beside this they can be exercised as precious tools for the process planning for EDM.

Keywords: Ti-15l-3, surface roughness, copper, positive polarity, multi-layered perceptron.

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

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Gas lift is one of the most common forms of artificial lift, particularly for offshore wells because of its relative down hole simplicity, flexibility, reliability, and ability to operate over a large range of rates and occupy very little space at the well head. Presently, petroleum industry is investing in exploration and development fields in offshore locations where oil and gas wells are being drilled thousands of feet below the ocean in high pressure and temperature conditions. Therefore, gas-lifted oil wells are capable of failure through gas lift valves which are considered as the heart of the gas lift system for controlling the amount of the gas inside the tubing string. The gas injection rate through gas lift valve must be controlled to be sufficient to obtain and maintain critical flow, also, gas lift valves must be designed not only to allow gas passage through it and prevent oil passage, but also for gas injection into wells to be started and stopped when needed. In this paper, smart gas lift valve has been used to investigate the effect of the valve port size, depth of injection and vertical lift performance on well productivity; all these aspects have been investigated using PROSPER simulator program coupled with experimental data. The results show that by using smart gas lift valve, the gas injection rate can be controlled which leads to improved flow performance.

Keywords: Effect of gas lift valve port size, effect water cut, and vertical flow performance.

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Authors: M. Tazky, R. Hela, P. Novosad, L. Osuska

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This paper deals with the possibility of safe incorporation fluidised bed combustion fly ash (waste material) into cement matrix together with next commonly used secondary raw material, which is high-temperature fly ash. Both of these materials have a very high pozzolanic ability, and the right combination could bring important improvements in both the physico-mechanical properties and the better durability of a cement composite. This paper tries to determine the correct methodology for designing green concrete by using modern methods measuring rheology of fresh concrete and following hydration processes. The use of fluidised bed combustion fly ash in cement composite production as an admixture is not currently common, but there are some real possibilities for its potential. The most striking negative aspect is its chemical composition which supports the development of new product formation, influencing the durability of the composite. Another disadvantage is the morphology of grains, which have a negative effect on consistency. This raises the question of how this waste can be used in concrete production to emphasize its positive properties and eliminate negatives. The focal point of the experiment carried out on cement pastes was particularly on the progress of hydration processes, aiming for the possible acceleration of pozzolanic reactions of both types of fly ash.

Keywords: High-temperature fly ash, fluidised bed combustion fly ash, pozzolanic, CaO (calcium oxide), rheology.

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Authors: Parvinder S. Sandhu, Urvashi Malhotra, E. Ardil

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There is lot of work done in prediction of the fault proneness of the software systems. But, it is the severity of the faults that is more important than number of faults existing in the developed system as the major faults matters most for a developer and those major faults needs immediate attention. In this paper, we tried to predict the level of impact of the existing faults in software systems. Neuro-Fuzzy based predictor models is applied NASA-s public domain defect dataset coded in C programming language. As Correlation-based Feature Selection (CFS) evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them. So, CFS is used for the selecting the best metrics that have highly correlated with level of severity of faults. The results are compared with the prediction results of Logistic Models (LMT) that was earlier quoted as the best technique in [17]. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provide a relatively better prediction accuracy as compared to other models and hence, can be used for the modeling of the level of impact of faults in function based systems.

Keywords: Software Metrics, Fuzzy, Neuro-Fuzzy, Software Faults, Accuracy, MAE, RMSE.

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Authors: Somenath Mukherjee, Rajdeep Ray, Raj Kumar Samanta, Mofazzal H. Khondekar, Gautam Sanyal

Abstract:

In next generation wireless networks (i.e., 4G and beyond), one of the main objectives is to ensure highest level of customer satisfaction in terms of data transfer speed, decrease in cost and delay, non-rejection and no drop of calls, availability of ‘always-on’ connectivity and services, continuity of connected services, hastle-free roaming in addition to the convenience of use of network services from anywhere and anytime. To take care of these requirements effectively, internet service providers (ISPs) and network planners have to go for major capacity enhancement of network resources and at the same time these resources are to be used effectively and efficiently to reduce cost and to increase revenue. In this work, the effective bandwidth available in a Mobile Switching Center (MSC) of a wireless network providing multi-class multimedia services is analyzed. Bandwidth requirement of the users for a customized Quality of Service (QoS) is estimated. The findings of the QoS estimation are applied for the capacity planning and admission control of the multi-class traffic flows coming into the MSC.

Keywords: Next generation wireless network, mobile switching center, multi-class traffic, quality of service, admission control, effective bandwidth.

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Authors: A. Hortacsu, A. Tektas

Abstract:

This paper aims to develop a model that assists the international retailer in selecting the country that maximizes the degree of fit between the retailer-s goals and the country characteristics in his initial internationalization move. A two-stage multi criteria decision model is designed integrating the Analytic Hierarchy Process (AHP) and Goal Programming. Ethical, cultural, geographic and economic proximity are identified as the relevant constructs of the internationalization decision. The constructs are further structured into sub-factors within analytic hierarchy. The model helps the retailer to integrate, rank and weigh a number of hard and soft factors and prioritize the countries accordingly. The model has been implemented on a Turkish luxury goods retailer who was planning to internationalize. Actual entry of the specific retailer in the selected country is a support for the model. Implementation on a single retailer limits the generalizability of the results; however, the emphasis of the paper is on construct identification and model development. The paper enriches the existing literature by proposing a hybrid multi objective decision model which introduces new soft dimensions i.e. perceived distance, ethical proximity, humane orientation to the decision process and facilitates effective decision making.

Keywords: Analytic hierarchy process, culture, ethics, goal programming, retail foreign market selection.

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Authors: Gaddafi S. Shehu, T. Yalcinoz, Abdullahi B. Kunya

Abstract:

Multilevel inverters such as flying capacitor, diodeclamped, and cascaded H-bridge inverters are very popular particularly in medium and high power applications. This paper focuses on a cascaded H-bridge module using a single direct current (DC) source in order to generate an 11-level output voltage. The noble approach reduces the number of switches and gate drivers, in comparison with a conventional method. The anticipated topology produces more accurate result with an isolation transformer at high switching frequency. Different modulation techniques can be used for the multilevel inverter, but this work features modulation techniques known as selective harmonic elimination (SHE).This modulation approach reduces the number of carriers with reduction in Switching Losses, Total Harmonic Distortion (THD), and thereby increasing Power Quality (PQ). Based on the simulation result obtained, it appears SHE has the ability to eliminate selected harmonics by chopping off the fundamental output component. The performance evaluation of the proposed cascaded multilevel inverter is performed using PSIM simulation package and THD of 0.94% is obtained.

Keywords: Cascaded H-bridge Multilevel Inverter, Power Quality, Selective Harmonic Elimination.

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Authors: A. Ahmadi Nadooshan, S. Daneshmand, C. Aghanajafi

Abstract:

Traditionally, wind tunnel models are made of metal and are very expensive. In these years, everyone is looking for ways to do more with less. Under the right test conditions, a rapid prototype part could be tested in a wind tunnel. Using rapid prototype manufacturing techniques and materials in this way significantly reduces time and cost of production of wind tunnel models. This study was done of fused deposition modeling (FDM) and their ability to make components for wind tunnel models in a timely and cost effective manner. This paper discusses the application of wind tunnel model configuration constructed using FDM for transonic wind tunnel testing. A study was undertaken comparing a rapid prototyping model constructed of FDM Technologies using polycarbonate to that of a standard machined steel model. Testing covered the Mach range of Mach 0.3 to Mach 0.75 at an angle-ofattack range of - 2° to +12°. Results from this study show relatively good agreement between the two models and rapid prototyping Method reduces time and cost of production of wind tunnel models. It can be concluded from this study that wind tunnel models constructed using rapid prototyping method and materials can be used in wind tunnel testing for initial baseline aerodynamic database development.

Keywords: Polycarbonate, Fabrication, FDM, Model, RapidPrototyping, Wind Tunnel.

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Authors: Wannakarn Likitrattanaporn

Abstract:

The ultimate purpose of this investigation was to determine the teachers’ opinions as well as students’ opinions towards the Adapted English Lessons. The subjects of the study were 5 Thai teachers, who teach English, and 85 Grade 10 mixed-ability students at Triamudom Suksa Pattanakarn Ratchada School, Bangkok, Thailand. The research instruments included questionnaires and the informal interview. The data from the research instruments was collected and analyzed concerning linguistic principles of minimal pair and articulatory phonetics as well as teaching techniques of mimicry-memorization; vocabulary substitution drills, language pattern drills, reading comprehension exercise, practicing listening, speaking and writing skill and communicative activities; informal talk and free writing. The data was statistically compiled according to an arithmetic percentage. The results showed that the teachers and students have very highly positive opinions towards adapting linguistic principles for teaching and learning phonological accuracy. Teaching techniques provided in the Adapted English Lessons can be used efficiently in the classroom. The teachers and students have positive opinions towards them too.

Keywords: Applying linguistic principles and teaching techniques, teachers’ and students’ opinions, teaching English, the Adapted English Lessons.

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