Search results for: Computational load reduction

Authors: Pisit Boonsrimuang, Arjin Numsomran, Tawil Paungma, Hideo Kobayashi

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One of the disadvantages of using OFDM is the larger peak to averaged power ratio (PAPR) in its time domain signal. The larger PAPR signal would course the fatal degradation of bit error rate performance (BER) due to the inter-modulation noise in the nonlinear channel. This paper proposes an improved DSI (Dummy Sequence Insertion) method, which can achieve the better PAPR and BER performances. The feature of proposed method is to optimize the phase of each dummy sub-carrier so as to reduce the PAPR performance by changing all predetermined phase coefficients in the time domain signal, which is calculated for data sub-carriers and dummy sub-carriers separately. To achieve the better PAPR performance, this paper also proposes to employ the time-frequency domain swapping algorithm for fine adjustment of phase coefficient of the dummy subcarriers, which can achieve the less complexity of processing and achieves the better PAPR and BER performances than those for the conventional DSI method. This paper presents various computer simulation results to verify the effectiveness of proposed method as comparing with the conventional methods in the non-linear channel.

Keywords: OFDM, PAPR, dummy sub-carriers, non-linear

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Authors: Insiya Kapasi, Roshni Udyavar Yehuda

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Cluster Redevelopment is a new concept in the city of Mumbai. Its regulations were laid down by the government in 2009. The concept of cluster redevelopment encompasses a group of buildings defined by a boundary as specified by the municipal authority (in this case, Mumbai), which may be dilapidated or approved for redevelopment. The study analyses the effect of cluster redevelopment in the form of renewal of old group of buildings as compared to refurbishment or restoration - on energy consumption. The methodology includes methods of assessment to determine increase or decrease in energy consumption in cluster redevelopment based on different criteria such as carpet area of the units, building envelope and its architectural elements. Results show that as the area and number of units increase the Energy consumption increases and the EPI (energy performance index) decreases as compared to the base case. The energy consumption per unit area declines by 29% in the proposed cluster redevelopment as compared to the original settlement. It is recommended that although the development is spacious and provides more light and ventilation, aspects such as glass type, traditional architectural features and consumer behavior are critical in the reduction of energy consumption.

Keywords: Cluster redevelopment, energy consumption, energy efficiency, typologies.

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Authors: Manas Ranjan Kabat, Manoj Kumar Patel, Chita Ranjan Tripathy

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Many multimedia communication applications require a source to transmit messages to multiple destinations subject to quality of service (QoS) delay constraint. To support delay constrained multicast communications, computer networks need to guarantee an upper bound end-to-end delay from the source node to each of the destination nodes. This is known as multicast delay problem. On the other hand, if the same message fails to arrive at each destination node at the same time, there may arise inconsistency and unfairness problem among users. This is related to multicast delayvariation problem. The problem to find a minimum cost multicast tree with delay and delay-variation constraints has been proven to be NP-Complete. In this paper, we propose an efficient heuristic algorithm, namely, Economic Delay and Delay-Variation Bounded Multicast (EDVBM) algorithm, based on a novel heuristic function, to construct an economic delay and delay-variation bounded multicast tree. A noteworthy feature of this algorithm is that it has very high probability of finding the optimal solution in polynomial time with low computational complexity.

Keywords: EDVBM, Heuristic algorithm, Multicast tree, QoS routing, Shortest path.

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Authors: Juhi Kaushik, Abhishek Agarwal, Manoj Sarda, Vatsal Sanjay, Arup Kumar Das

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Fire accidents in trains bring huge disaster to human life and property. Evacuation becomes a major challenge in such incidents owing to confined spaces, large passenger density and trains moving at high speeds. The pantry car in Indian Railways trains carry inflammable materials like cooking fuel and LPG and electrical fittings. The pantry car is therefore highly susceptible to fire accidents. Numerical simulations have been done in a pantry car of Indian locomotive train using computational fluid dynamics based software. Different scenarios of a fire outbreak have been explored by varying Heat Release Rate per Unit Area (HRRPUA) of the fire source, introduction of exhaust in the cooking area, and taking a case of an air conditioned pantry car. Temporal statures of flame and soot have been obtained for each scenario and differences have been studied and reported. Inputs from this study can be used to assess casualties in fire accidents in locomotive trains and development of smoke control/detection systems in Indian trains.

Keywords: Fire propagation, flame contour, pantry fire, soot flow.

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

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Real time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Thus, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Edge detection is one of the basic building blocks of video and image processing applications. It is a common block in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: High Level Synthesis, Canny edge detection, Hardware accelerators, and Computer Vision.

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Authors: Su-Ling Li, Qun-Yu Gao

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Mung bean starches were subjected to heat-moisture treatment (HMT) by different moisture contents (15%, 20%, 25%, 30% and 35%) at 120Ôäâ for 12h. The impact on the yields of resistant starch (RS), microstructure, physicochemical and functional properties was investigated. Compared to native starch, the RS content of heat-moisture treated starches increased significantly. The RS level of HMT-20 was the highest of all the starches. Birefringence was displayed clear at the center of native starch. For HMT starches, pronounced birefringence was exhibited on the periphery of starch granules; however, birefringence disappeared at the centre of some starch granules. The shape of HMT starches hadn-t been changed and the integrity of starch granules was preserved for all the conditions. Concavity could be observed on HMT starches under scanning electronic microscopy. After HMT, apparent amylose contents were increased and starch macromolecule was degraded in comparison with those of native starch. There was a reduction in swelling power on HMT starches, but the solubility of HMT starches was higher than that of native starch. Both of native and HMT starches showed A-type X-ray diffraction pattern. Furthermore, there is a higher intensity at the peak of 15.0 and 22.9 Å than those of native starch.

Keywords: Resistant starch, mung bean (Phaseolus radiatus) starch, heat-moisture treatment, physicochemical properties.

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Authors: Inwon Lee, Victor M. Kulik, Andrey V. Boiko, Ho Hwan Chun

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A specially designed flat plate was mounted vertically over the axial line in the wind tunnel of the Aerospace Department of the Pusan National University. The plate is 2 m long, 0.8 m high and 8 cm thick. The measurements were performed in velocity range from 15 to 60 m/s. A sand paper turbulizer was placed close to the plate nose to provide fully developed turbulent boundary layer over the most part of the plate. Strain balances were mounted in the trailing part of the plate to measure the skin friction drag over removable insertions of 0.55×0.25m2 size. A set of the insertions was designed and manufactured: 3mm thick polished metal surface and three compliant surfaces. The compliant surfaces were manufactured of a silicone rubber Silastic® S2 (Dow Corning company). To modify the viscoelastic properties of the rubber, its composition was varied: 90% of the rubber + 10% catalyst (standard), 92.5% + 7.5% (weak), 85% + 15% (strong). Modulus of elasticity and the loss tangent were measured accurately for these materials in the frequency range from 40 Hz to 3 KHz using the unique proposed technique.

Keywords: boundary layer, compliant coating, drag reduction, hot wire, wind tunnel.

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Authors: M. M. Qasaymeh, M. A. Khodeir

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Subspace channel estimation methods have been studied widely, where the subspace of the covariance matrix is decomposed to separate the signal subspace from noise subspace. The decomposition is normally done by using either the eigenvalue decomposition (EVD) or the singular value decomposition (SVD) of the auto-correlation matrix (ACM). However, the subspace decomposition process is computationally expensive. This paper considers the estimation of the multipath slow frequency hopping (FH) channel using noise space based method. In particular, an efficient method is proposed to estimate the multipath time delays by applying multiple signal classification (MUSIC) algorithm which is based on the null space extracted by the rank revealing LU (RRLU) factorization. As a result, precise information is provided by the RRLU about the numerical null space and the rank, (i.e., important tool in linear algebra). The simulation results demonstrate the effectiveness of the proposed novel method by approximately decreasing the computational complexity to the half as compared with RRQR methods keeping the same performance.

Keywords: Time Delay Estimation, RRLU, RRQR, MUSIC, LS-ESPRIT, LS-ESPRIT, Frequency Hopping.

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an ‘optimal’ value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: Cross Validation, Parameter Averaging, Parameter Selection, Regularization Parameter Search.

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Authors: Mahmood Reza Shakarami, Reza Sedaghati

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Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Power system operation is affected by stability related problems, leading to unpredictable system behavior. Voltage stability refers to the ability of a power system to sustain appropriate voltage levels through large and small disturbances. Steady-state voltage stability is concerned with limits on the existence of steady-state operating points for the network. FACTS devices can be utilized to increase the transmission capacity, the stability margin and dynamic behavior or serve to ensure improved power quality. Their main capabilities are reactive power compensation, voltage control and power flow control. Among the FACTS controllers, Static Var Compensator (SVC) provides fast acting dynamic reactive compensation for voltage support during contingency events. In this paper, voltage stability assessment with appropriate representations of tap-changer transformers and SVC is investigated. Integrating both of these devices is the main topic of this paper. Effect of the presence of tap-changing transformers on static VAR compensator controller parameters and ratings necessary to stabilize load voltages at certain values are highlighted. The interrelation between transformer off nominal tap ratios and the SVC controller gains and droop slopes and the SVC rating are found. P-V curves are constructed to calculate loadability margins.

Keywords: SVC, voltage stability, P-V curve, reactive power, tap changing transformer.

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Authors: Ping He

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This paper addresses the problem of the partial state feedback stabilization of a class of nonlinear systems. In order to stabilization this class systems, the especial place of this paper is to reverse designing the state feedback control law from the method of judging system stability with the center manifold theory. First of all, the center manifold theory is applied to discuss the stabilization sufficient condition and design the stabilizing state control laws for a class of nonlinear. Secondly, the problem of partial stabilization for a class of plane nonlinear system is discuss using the lyapunov second method and the center manifold theory. Thirdly, we investigate specially the problem of the stabilization for a class of homogenous plane nonlinear systems, a class of nonlinear with dual-zero eigenvalues and a class of nonlinear with zero-center using the method of lyapunov function with homogenous derivative, specifically. At the end of this paper, some examples and simulation results are given show that the approach of this paper to this class of nonlinear system is effective and convenient.

Keywords: Partial stabilization, Nonlinear critical systems, Centermanifold theory, Lyapunov function, System reduction.

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Authors: Tong Liu, Xuan Xu, Xiaodi Wang

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Computational techniques derived from digital image processing are playing a significant role in the security and digital copyrights of multimedia and visual arts. This technology has the effect within the domain of computers. This research presents discrete M-band wavelet transform (MWT) and cosine transform (DCT) based watermarking algorithm by incorporating the principal component analysis (PCA). The proposed algorithm is expected to achieve higher perceptual transparency. Specifically, the developed watermarking scheme can successfully resist common signal processing, such as geometric distortions, and Gaussian noise. In addition, the proposed algorithm can be parameterized, thus resulting in more security. To meet these requirements, the image is transformed by a combination of MWT & DCT. In order to improve the security further, we randomize the watermark image to create three code books. During the watermark embedding, PCA is applied to the coefficients in approximation sub-band. Finally, first few component bands represent an excellent domain for inserting the watermark.

Keywords: discrete M-band wavelet transform , discrete M-band wavelet transform, randomized watermark, principal component analysis

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Authors: Azin Shakibabarough, Mojtaba Valinejadshoubi, Ashutosh Bagchi

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Structural vibration means repetitive motion that causes fatigue and reduction of the performance of a structure. An earthquake may release high amount of energy that can have adverse effect on all components of a structure. Therefore, decreasing of vibration or maintaining performance of structures such as bridges, dams, roads and buildings is important for life safety and reducing economic loss. When earthquake or any vibration happens, investigation on parts of a structure which sustain the seismic loads is mandatory to provide a safe condition for the occupants. One of the solutions for reducing the earthquake vibration in a structure is using of vibration control devices such as dampers and base isolators. The objective of this study is to investigate the optimal positions of friction dampers and base isolators for better seismic response of 2D frame. For this purpose, a two bay and six story frame with different distribution formats was modeled and some of their responses to earthquake such as inter-story drift, max joint displacement, max axial force and max bending moment were determined and compared using non-linear dynamic analysis.

Keywords: Fast nonlinear analysis, friction damper, base isolator, seismic vibration control, seismic response.

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Authors: P. Pasomboon, P. Chumnanpuen, T. E-kobon

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Hyaluronic acid (HA) consists of linear heteropolysaccharides repeat of D-glucuronic acid and N-acetyl-D-glucosamine. HA has various useful properties to maintain skin elasticity and moisture, reduce inflammation, and lubricate the movement of various body parts without causing immunogenic allergy. HA can be found in several animal tissues as well as in the capsule component of some bacteria including Pasteurella multocida. This study aimed to modify a genome-scale metabolic model of Escherichia coli using computational simulation and flux analysis methods to predict HA productivity under different carbon sources and nitrogen supplement by the addition of two enzymes (GLMU2 and HYAD) from P. multocida to improve the HA production under the specified amount of carbon sources and nitrogen supplements. Result revealed that threonine and aspartate supplement raised the HA production by 12.186%. Our analyses proposed the genome-scale metabolic model is useful for improving the HA production and narrows the number of conditions to be tested further.

Keywords: Pasteurella multocida, Escherichia coli, hyaluronic acid, genome-scale metabolic model, bioinformatics.

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Authors: Hamed Afrasiab, Saeed Khodaygan

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Prediction of machining process capability in the design stage plays a key role to reach the precision design and manufacturing of mechanical products. Inaccuracies in machining process lead to errors in position and orientation of machined features on the part, and strongly affect the process capability in the final quality of the product. In this paper, an efficient systematic approach is given to investigate the machining errors to predict the manufacturing errors of the parts and capability prediction of corresponding machining processes. A mathematical formulation of fixture locators modeling is presented to establish the relationship between the part errors and the related sources. Based on this method, the final machining errors of the part can be accurately estimated by relating them to the combined dimensional and geometric tolerances of the workpiece – fixture system. This method is developed for uncertainty analysis based on the Worst Case and statistical approaches. The application of the presented method is illustrated through presenting an example and the computational results are compared with the Monte Carlo simulation results.

Keywords: Process capability, machining error, dimensional and geometrical tolerances, uncertainty analysis.

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Authors: Manjie Li, Xiangju Cheng, Yongcan Chen

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With rapid development of industrialization and urbanization, water environmental deterioration is widespread in majority of urban rivers, which seriously affects city image and life satisfaction of residents. As an emergency measure to improve water quality, clean water diversion is introduced for water environmental management. Lubao River and Southwest River, two urban rivers in typical plain tidal river network, are identified as technically and economically feasible for the application of clean water diversion. One-dimensional hydrodynamic-water quality model is developed to simulate temporal and spatial variations of water level and water quality, with satisfactory accuracy. The mathematical model after calibration is applied to investigate hydrodynamic and water quality variations in rivers as well as determine the optimum operation scheme of water diversion. Assessment system is developed for evaluation of positive and negative effects of water diversion, demonstrating the effectiveness of clean water diversion and the necessity of pollution reduction.

Keywords: Assessment system, clean water diversion, hydrodynamic-water quality model, tidal river network, urban rivers, water environment improvement.

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Authors: M. Tehranizadeh, E. Shoushtari Rezvani

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Seismic performance of steel moment-resisting frame structures is investigated considering nonlinear soil-structure interaction (SSI) effects. 10-, 15-, and 20-story planar building frames with aspect ratio of 3 are designed in accordance with current building codes. Inelastic seismic demands of the superstructure are considered using concentrated plasticity model. The raft foundation system is designed for different soil types. Beam-on-nonlinear Winkler foundation (BNWF) is used to represent dynamic impedance of the underlying soil. Two sets of pulse-like as well as no-pulse near-fault earthquakes are used as input ground motions. The results show that the reduction in drift demands due to nonlinear SSI is characterized by a more uniform distribution pattern along the height when compared to the fixed-base and linear SSI condition. It is also concluded that beneficial effects of nonlinear SSI on displacement demands is more significant in case of pulse-like ground motions and performance level of the steel moment-resisting frames can be enhanced.

Keywords: Soil-structure interaction, uplifting, soil plasticity, near-fault earthquake, tall building.

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision-making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a fuzzy linguistic term. The finding suggests that fuzzy linguistic evaluation is practical and meaningful in knowledge-based system development purpose. 

Keywords: Case-based reasoning, decision-support system, fuzzy linguistic term, rule-based reasoning, system evaluation.

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Authors: Pawit Tangviroon, Apichit Svang-Ariyaskul

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As the limited availability of petroleum-based fuel has been a major concern, biodiesel is one of the most attractive alternative fuels because it is renewable and it also has advantages over the conventional petroleum-base diesel. At Present, productions of biodiesel generally perform by transesterification of vegetable oils with low molecular weight alcohol, mainly methanol, using chemical catalysts. Methanol is petrochemical product that makes biodiesel producing from methanol to be not pure renewable energy source. Therefore, ethanol as a product produced by fermentation processes. It appears as a potential feed stock that makes biodiesel to be pure renewable alternative fuel. The research is conducted based on two biodiesel production processes by reacting soybean oils with methanol and ethanol. Life cycle assessment was carried out in order to evaluate the environmental impacts and to identify the process alternative. Nine mid-point impact categories are investigated. The results indicate that better performance on abiotic depletion potential (ADP) and acidification potential (AP) are observed in biodiesel production from methanol when compared with biodiesel production from ethanol due to less energy consumption during the production processes. Except for ADP and AP, using methanol as feed stock does not show any advantages over biodiesel from ethanol. The single score method is also included in this study in order to identify the best option between two processes of biodiesel production. The global normalization and weighting factor based on ecotaxes are used and it shows that producing biodiesel form ethanol has less environmental load compare to biodiesel from methanol.

Keywords: Biodiesel, Ethanol, Life Cycle Assessment, Methanol, Soybean Oil.

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Authors: M. Veeresham

Abstract:

The microstructure, texture, phase stability, and tensile properties of annealed Ta_0.5Nb_0.5Hf_0.5ZrTi_1.5 alloy have been investigated in the present research. The alloy was severely hybrid-rolled up to 93.5% thickness reduction, subsequently rolled samples subjected to an annealing treatment at 800 °C and 1000 °C temperatures for 1 h. Consequently, the rolled condition and both annealed temperatures have a body-centered cubic (BCC) structure. Furthermore, quantitative texture measurements (orientation distribution function (ODF) analysis) and microstructural examinations (analytical electron backscatter diffraction (EBSD) maps) permitted to establish a good relationship between annealing texture and microstructure and universal testing machine (UTM) utilized for obtaining the mechanical properties. Impressive room temperature tensile properties combination with the tensile strength (1380 MPa) and (24.7%) elongation is achieved for the 800 °C heat-treated condition. The evolution of the coarse microstructure featured in the case of 1000 °C annealed temperature ascribed to the influence of high thermal energy.

Keywords: Refractory high entropy alloys, hybrid-rolling, recrystallization, microstructure, tensile properties.

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Authors: Ying Shang, Chencheng Wang

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The wind field is the main driving factor for the spread of forest fires. For the simulation results of forest fire spread to be more accurate, it is necessary to obtain more detailed wind field data. Therefore, this paper studied the mountainous fine wind field simulation method coupled with WRF (Weather Research and Forecasting Model) and CFD (Computational Fluid Dynamics) to realize the numerical simulation of the wind field in a mountainous area with a scale of 30 m and a small measurement error. Local topographical changes have an important impact on the wind field. Based on the Rothermel fire spread model, a forest fire in Idaho in the western United States was simulated. The historical data proved that the simulation results had a good accuracy. They showed that the fire spread rate will decrease rapidly with time and then reach a steady state. After reaching a steady state, the fire spread growth area will not only be affected by the slope, but will also show a significant quadratic linear positive correlation with the wind speed change.

Keywords: Wind field, numerical simulation, forest fire spread, fire behavior model, complex terrain.

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling. The research proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling. The paper concludes the challenges and improvement directions for Deep Reinforcement Learning-based resource scheduling algorithms.

Keywords: Resource scheduling, deep reinforcement learning, distributed system, artificial intelligence.

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Authors: P. Vijaya Laxmi, V. Goswami, V. Suchitra

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This paper presents a finite buffer renewal input single working vacation and vacation interruption queue with state dependent services and state dependent vacations, which has a wide range of applications in several areas including manufacturing, wireless communication systems. Service times during busy period, vacation period and vacation times are exponentially distributed and are state dependent. As a result of the finite waiting space, state dependent services and state dependent vacation policies, the analysis of these queueing models needs special attention. We provide a recursive method using the supplementary variable technique to compute the stationary queue length distributions at pre-arrival and arbitrary epochs. An efficient computational algorithm of the model is presented which is fast and accurate and easy to implement. Various performance measures have been discussed. Finally, some special cases and numerical results have been depicted in the form of tables and graphs. 

Keywords: State Dependent Service, Vacation Interruption, Supplementary Variable, Single Working Vacation, Blocking Probability.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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Authors: M. A. At-Tasneem, N. T. Rao, T. M. Y. S. Tuan Ya, M. S. Idris, M. Ammar

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River flow over micro hydro power (MHP) turbines of multiple arrays arrangement is simulated with computational fluid dynamics (CFD) software to obtain the flow characteristics. In this paper, CFD software is used to simulate the water flow over MHP turbines as they are placed in a river. Multiple arrays arrangement of MHP turbines lead to generate large amount of power. In this study, a river model is created and simulated in CFD software to obtain the water flow characteristic. The process then continued by simulating different types of arrays arrangement in the river model. A MHP turbine model consists of a turbine outer body and static propeller blade in it. Five types of arrangements are used which are parallel, series, triangular, square and rhombus with different spacing sizes. The velocity profiles on each MHP turbines are identified at the mouth of each turbine bodies. This study is required to obtain the arrangement with increasing spacing sizes that can produce highest power density through the water flow variation.

Keywords: Micro hydro power, CFD, arrays arrangement, spacing sizes, velocity profile, power.

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Authors: Tru C. Le, France Cheong

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Although the Vietnamese catfish farming has grown at very high rates in recent years, the industry has also faced many problems affecting its sustainability. This paper studies the perceptions of catfish farmers regarding risk and risk management strategies in their production activities. Specifically, the study aims to measure the consequences, likelihoods, and levels of risks as well as the efficacy of risk management in Vietnamese catfish farming. Data for the study were collected through a sample of 261 catfish farmers in the Mekong Delta, Vietnam using a questionnaire survey in 2008. Results show that, in general, price and production risks were perceived as the most important risks. Farm management and technical measures were perceived more effective than other kinds of risk management strategies in risk reduction. Although price risks were rated as important risks, price risk management strategies were not perceived as important measures for risk mitigation. The results of the study are discussed to provide implications for various industry stakeholders, including policy makers, processors, advisors, and developers of new risk management strategies.

Keywords: Aquaculture, catfish farming, sources of risk, riskmanagement, risk strategies, risk mitigation.

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Authors: Amit Kumar, Peeyush Sharma, Anil Bhandari

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The aim of present work was to optimize the effect of Ethyl Cellulose (EC) and Polyvinyl Pyrrolidone (PVP) concentration in extended release solid dispersion of Glibenclamide using combination of hydrophilic and hydrophobic polymers such as Polyvinyl Pyrrolidone and Ethyl cellulose. The advantage of solid dispersion technique provides a unique approach to particle size reduction and increased rates of dissolution. The compatibility studies of the drug and polymers were studied by TLC and results suggested no interaction between drug and polymers. Solid dispersions of Glibenclamide were prepared by common solvent evaporation method using Polyvinyl Pyrrolidone and Ethyl cellulose. The results indicated that homogeneous or heterogeneous conditions during the preparation methods employed governed the internal structures of the polymer matrices while retaining the drug in an amorphous form. F2 formulation prepared by solid dispersion method, displayed extended drug release followed by Higuchi matrix model indicating diffusion release of GLB from polymer matrices.

Keywords: Ethyl Cellulose, Glibenclamide, Polyvinyl Pyrrolidone, Solid Dispersion.

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Authors: Fei Long Wei, Hua Yang, Hai Tao Zhang, Zhou Ping Yin

Abstract:

In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.

Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment.

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Authors: Mohammad Shafigh, Nasser Fatouraee, Amirsaied Seddighi

Abstract:

Mechanical properties of cerebral arteries are, due to their relationship with cerebrovascular diseases, of clinical worth. To acquire these properties, eight samples were obtained from middle cerebral arteries of human cadavers, whose death were not due to injuries or diseases of cerebral vessels, and tested within twelve hours after resection, by a precise biaxial tensile test device specially developed for the present study considering the dimensions, sensitivity and anisotropic nature of samples. The resulting stress-stretch curve was plotted and subsequently fitted to a hyperelastic three-parameter Fung model. It was found that the arteries were noticeably stiffer in circumferential than in axial direction. It was also demonstrated that the use of multi-parameter hyperelastic constitutive models is useful for mathematical description of behavior of cerebral vessel tissue. The reported material properties are a proper reference for numerical modeling of cerebral arteries and computational analysis of healthy or diseased intracranial arteries.

Keywords: Anisotropic Tissue, Cerebral Blood Vessels, Fung Model, Nonlinear Material, Plain Stress.

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Authors: Nuanpan Nangsue

Abstract:

Ratio and regression type estimators have been used by previous authors to estimate a population mean for the principal variable from samples in which both auxiliary x and principal y variable data are available. However, missing data are a common problem in statistical analyses with real data. Ratio and regression type estimators have also been used for imputing values of missing y data. In this paper, six new ratio and regression type estimators are proposed for imputing values for any missing y data and estimating a population mean for y from samples with missing x and/or y data. A simulation study has been conducted to compare the six ratio and regression type estimators with a previous estimator of Rueda. Two population sizes N = 1,000 and 5,000 have been considered with sample sizes of 10% and 30% and with correlation coefficients between population variables X and Y of 0.5 and 0.8. In the simulations, 10 and 40 percent of sample y values and 10 and 40 percent of sample x values were randomly designated as missing. The new ratio and regression type estimators give similar mean absolute percentage errors that are smaller than the Rueda estimator for all cases. The new estimators give a large reduction in errors for the case of 40% missing y values and sampling fraction of 30%.

Keywords: Auxiliary variable, missing data, ratio and regression type estimators.

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