Search results for: group processing

Authors: Edison Muzenda, Ayo S. Afolabi

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This paper is a continuation of our interest in the influence of temperature on specific retention volumes and the resulting infinite dilution activity coefficients. This has a direct effect in the design of absorption and stripping columns for the abatement of volatile organic compounds. The interaction of 13 volatile organic compounds (VOCs) with polydimethylsiloxane (PDMS) at varying temperatures was studied by gas liquid chromatography (GLC). Infinite dilution activity coefficients and specific retention volumes obtained in this study were found to be in agreement with those obtained from static headspace and group contribution methods by the authors as well as literature values for similar systems. Temperature variation also allows for transport calculations for different seasons. The results of this work confirm that PDMS is well suited for the scrubbing of VOCs from waste gas streams. Plots of specific retention volumes against temperature gave linear van-t Hoff plots.

Keywords: Specific retention volume, Waste gas streams, specific retention, infinite dilution, abatement, transport.

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Authors: Andra Blumberga, Armands Gravelsins, Haralds Vigants, Dagnija Blumberga

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The paper discovers biotechonomy development analysis by use of system dynamics modelling. The research is connected with investigations of biomass application for production of bioproducts with higher added value. The most popular bioresource is wood, and therefore, the main question today is about future development and eco-design of products. The paper emphasizes and evaluates energy sector which is open for use of wood logs, wood chips, wood pellets and so on. The main aim for this research study was to build a framework to analyse development perspectives for wood pellet production. To reach the goal, a system dynamics model of energy wood supplies, processing, and consumption is built. Production capacity, energy consumption, changes in energy and technology efficiency, required labour source, prices of wood, energy and labour are taken into account. Validation and verification tests with available data and information have been carried out and indicate that the model constitutes the dynamic hypothesis. It is found that the more is invested into pellets production, the higher the specific profit per production unit compared to wood logs and wood chips. As a result, wood chips production is decreasing dramatically and is replaced by wood pellets. The limiting factor for pellet industry growth is availability of wood sources. This is governed by felling limit set by the government based on sustainable forestry principles.

Keywords: Bioenergy, biotechonomy, system dynamics modelling, wood pellets.

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Authors: Mohamed Al Mahdi Eshtawie, Masuri Bin Othman

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Finite impulse response (FIR) filters have the advantage of linear phase, guaranteed stability, fewer finite precision errors, and efficient implementation. In contrast, they have a major disadvantage of high order need (more coefficients) than IIR counterpart with comparable performance. The high order demand imposes more hardware requirements, arithmetic operations, area usage, and power consumption when designing and fabricating the filter. Therefore, minimizing or reducing these parameters, is a major goal or target in digital filter design task. This paper presents an algorithm proposed for modifying values and the number of non-zero coefficients used to represent the FIR digital pulse shaping filter response. With this algorithm, the FIR filter frequency and phase response can be represented with a minimum number of non-zero coefficients. Therefore, reducing the arithmetic complexity needed to get the filter output. Consequently, the system characteristic i.e. power consumption, area usage, and processing time are also reduced. The proposed algorithm is more powerful when integrated with multiplierless algorithms such as distributed arithmetic (DA) in designing high order digital FIR filters. Here the DA usage eliminates the need for multipliers when implementing the multiply and accumulate unit (MAC) and the proposed algorithm will reduce the number of adders and addition operations needed through the minimization of the non-zero values coefficients to get the filter output.

Keywords: Pulse shaping Filter, Distributed Arithmetic, Optimization algorithm.

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Authors: Chih-Wei Lin, Duen-Ren Liu, Hui-Fang Chen

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Effective knowledge support relies on providing operation-relevant knowledge to workers promptly and accurately. A knowledge flow represents an individual-s or a group-s knowledge-needs and referencing behavior of codified knowledge during operation performance. The flow has been utilized to facilitate organizational knowledge support by illustrating workers- knowledge-needs systematically and precisely. However, conventional knowledge-flow models cannot work well in cooperative teams, which team members usually have diverse knowledge-needs in terms of roles. The reason is that those models only provide one single view to all participants and do not reflect individual knowledge-needs in flows. Hence, we propose a role-based knowledge-flow view model in this work. The model builds knowledge-flow views (or virtual knowledge flows) by creating appropriate virtual knowledge nodes and generalizing knowledge concepts to required concept levels. The customized views could represent individual role-s knowledge-needs in teamwork context. The novel model indicates knowledge-needs in condensed representation from a roles perspective and enhances the efficiency of cooperative knowledge support in organizations.

Keywords: cooperative knowledge support, knowledge flow, knowledge-flow view, role-based models

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Authors: Yoon-Hyuk Choi

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Studies on the distribution of traffic demands have been proceeding by providing traffic information for reducing greenhouse gases and reinforcing the road's competitiveness in the transport section, however, since it is preferentially required the extensive studies on the driver's behavior changing routes and its influence factors, this study has been developed a discriminant model for changing routes considering driving conditions including traffic conditions of roads and driver's preferences for information media. It is divided into three groups depending on driving conditions in group classification with the CART analysis, which is statistically meaningful. And the extent that driving conditions and preferred media affect a route change is examined through a discriminant analysis, and it is developed a discriminant model equation to predict a route change. As a result of building the discriminant model equation, it is shown that driving conditions affect a route change much more, the entire discriminant hit ratio is derived as 64.2%, and this discriminant equation shows high discriminant ability more than a certain degree.

Keywords: CART analysis, Diversion, Discriminant model, Driving conditions, and preferred media

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Authors: Hui Fang Huang Su, Leanne Lai, Pei-Fen Li, Mei-Hwei Ho, Yu-Wen Chiu

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This study aimed to provide a practical, systematic, and comprehensive intervention for children with Autism Spectrum Disorder (ASD). A pilot study of quasi-experimental pre-post intervention with control group design was conducted to evaluate if the mathematical intervention (Project MIND - Math Is Not Difficult) increases the math comprehension of children with ASD Children with ASD in the primary grades (K-1, 2) participated in math interventions to enhance their math comprehension and cognitive ability. The Bracken basic concept scale was used to evaluate subjects’ language skills, cognitive development, and school readiness. The study found that our systemic interventions of Project MIND significantly improved the mathematical and cognitive abilities in children with autism. The results of this study may lead to a major change in effective and adequate health care services for children with ASD and their families. All statistical analyses were performed with the IBM SPSS Statistics Version 25 for Windows. The significant level was set at 0.05 P-value.

Keywords: Young Children, Autism, Mathematics, Curriculum, teaching and learning, children with special needs, Project MIND.

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Authors: Sihana Ahmeti Lika, Merita Dauti, Ledjan Malaj

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The objective of this study is to analyze the prophylactic usage of low molecular weight heparin (LMWH) along pregnancy and the correlation between their usage and month/week of pregnancy, in the Department of Gynecology and Obstetrics, at Clinical Hospital in Tetovo. A retrospective study was undertaken during 01 January – 31 December 2012. Over of one year, the total number of patients was 4636. Among the 1447 (32.21%) pregnant women, 298 (20.59%) of them were prescribed LMWH. The majority of patients given LMWH, 119 (39.93%) were diagnosed hypercoagulable. The age group with the highest attendance was 25- 35, 141 patients (47.32%). For 195 (65.44%) patients, this was their first pregnancy. Earliest stage of using LMWH was the second month of pregnancy 4 (1.34%) cases. The most common patients were 70 women along the seventh month (23.49%), followed by 68 in the ninth month of pregnancy (22.81%). Women in the 28th gestational week, were found to be the most affected, a total of 55 (78.57%) were in that week. Clexane 2000 and Fraxiparine 0.3 were the most common for which low molecular weight heparin was prescribed. The number of patients which received Clexane 2000 was 84 (28.19%), followed by those with Fraxiparine 0.3 81 (27.18%). The administration of LMWH is associated with long hospitalization (median 14,6 days).

Keywords: Hypercoagulable state, low molecular weight heparin, month of pregnancy, pregnant women.

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Authors: Nazedah Ain Ibrahim, Mohamed Mansor Manan

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Information regarding early onset neonatal sepsis (EONS) pathogens may vary between regions. Global perspectives showed Group B Streptococcal (GBS) as the most common causative pathogens, but the widespread use of intrapartum antibiotics has changed the pathogens pattern towards gram negative microorganisms, especially E. coli. Objective of this study is to describe the pathogens isolated, to assess current treatment and risk of EONS. Records of 899 neonates born in three General Hospitals between 2009 until 2012 were retrospectively reviewed. Proven was found in 22 (3%) neonates. The majority was isolated with gram positive organisms, 17 (2.3%). All grams positive and most gram negative organisms showed sensitivity to the tested antibiotics. Only two rare gram negative organisms showed total resistant. Male was possible risk of proven EONS. Although proven EONS remains uncommon in Malaysia, nonetheless, the effect of intrapartum antibiotics still required continuous surveillance.

Keywords: Early onset neonatal sepsis, neonates, pathogens, gram positive, gram negative.

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Authors: Arun Kumar Datta, M. A. Ansari, N. R. Mondal, B. V. Raghavaiah, Manisha Dubey, Shailendra Jain

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This study is carried out to understand the effects of Static frequency converter (SFC) on large machine. SFC has a feature of four quadrant operations. By virtue of this it can be implemented to run a synchronous machine either as a motor or alternator. This dual mode operation helps a single machine to start & run as a motor and then it can be converted as an alternator whenever required. One such dual purpose machine is taken here for study. This machine is installed at a laboratory carrying out short circuit test on high power electrical equipment. SFC connected with this machine is broadly described in this paper. The same SFC has been modeled with the MATLAB/Simulink software. The data applied on this virtual model are the actual parameters from SFC and synchronous machine. After running the model, simulated machine voltage and current waveforms are validated with the real measurements. Processing of these waveforms is done through Fast Fourier Transformation (FFT) which reveals that the waveforms are not sinusoidal rather they contain number of harmonics. These harmonics are the major cause of generating shaft voltage. It is known that bearings of electrical machine are vulnerable to current flow through it due to shaft voltage. A general discussion on causes of shaft voltage in perspective with this machine is presented in this paper.

Keywords: Alternators, AC-DC power conversion, capacitive coupling, electric discharge machining, frequency converter, Fourier transforms, inductive coupling, simulation, Shaft voltage, synchronous machines, static excitation, thyristor.

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Authors: Addion Nizori, Lan T.T. Bui, Darryl M. Small

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Ascorbic acid (AA), commonly known as vitamin C, is essential for normal functioning of the body and maintenance of metabolic integrity. Among its various roles are as an antioxidant, a cofactor in collagen formation and other reactions, as well as reducing physical stress and maintenance of the immune system. Recent collaborative research between the Australian Defence Science and Technology Organisation (DSTO) in Scottsdale, Tasmania and RMIT University has sought to overcome the problems arising from the inherent instability of ascorbic acid during processing and storage of foods. The recent work has demonstrated the potential of microencapsulation by spray drying as a means to enhance retention. The purpose of this current study has been focused upon the influence of spray drying conditions on the properties of encapsulated ascorbic acid. The process was carried out according to a central composite design. Independent variables were: inlet temperature (80-120° C) and feed flow rate (7-14 mL/minute). Process yield, ascorbic acid loss, moisture content, water activity and particle size distribution were analysed as responses. The results have demonstrated the potential of microencapsulation by spray drying as a means to enhance retention. Vitamin retention, moisture content, water activity and process yield were influenced positively by inlet air temperature and negatively by feed flow rate.

Keywords: Microencapsulation, spray drying, ascorbic acid.

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Authors: Ashok Kumar, Narottam Chand, Vinod Kumar

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Due to the limited energy resources, energy efficient operation of sensor node is a key issue in wireless sensor networks. Clustering is an effective method to prolong the lifetime of energy constrained wireless sensor network. However, clustering in wireless sensor network faces several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we propose a protocol supporting an energy efficient clustering, cluster head selection/rotation and data routing method to prolong the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection/rotation and data routing.

Keywords: Wireless sensor networks, clustering, energy efficient, localization.

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Authors: Anupama Pande, Vishik Goel

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A complex valued neural network is a neural network, which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in image and vision processing. In Neural networks, radial basis functions are often used for interpolation in multidimensional space. A Radial Basis function is a function, which has built into it a distance criterion with respect to a centre. Radial basis functions have often been applied in the area of neural networks where they may be used as a replacement for the sigmoid hidden layer transfer characteristic in multi-layer perceptron. This paper aims to present exhaustive results of using RBF units in a complex-valued neural network model that uses the back-propagation algorithm (called 'Complex-BP') for learning. Our experiments results demonstrate the effectiveness of a Radial basis function in a complex valued neural network in image recognition over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error on a neural network model with RBF units. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Radial BasisFunction, Image recognition.

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Authors: Zohreh Bang Tavakoli, Shuktika Chatterjee

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This study is investigating the impact of ideological structures in terms of conservative and liberal on shaping immigration acceptance attitudes under the contribution of socio-economic status. According to motivated reasoning theory, political ideology is identified as a recurrent impact on the formation of attitude, while conservatives tend to express more hostility toward immigrants in comparison to liberals which are proposed to be more tolerant towards immigrants. Our finding suggests that political ideology will structure individual attitudes when citizens socio-economic vulnerability and level of education are low enough to consider immigrants as a threat. Therefore, economic vulnerability is proposed to weaken the ideological predispositions’ resistance. There has been some threats and factors such as level of education and economic condition proposed by group competition theory and labor market competition theory as fundamental factors which can strengthen or weaken the effects of political ideology on individuals’ attitudes towards immigration; those mechanisms for liberals and conservatives will be operated differently.

Keywords: Conservative, immigration, liberal, political ideology.

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Authors: M. Mokhtarzadeh, M. Taheri Qomi, M. Nikafrooz, A. Atashafrooz

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The purpose of the present study was to investigate the effectiveness of using motion graphics as a learning medium on training hearing aids maintenance skills to hearing-impaired children. The statistical population of this study consisted of all children with hearing loss in Ahvaz city, at age 4 to 7 years old. As the sample, 60, whom were selected by multistage random sampling, were randomly assigned to two groups; experimental (30 children) and control (30 children) groups. The research method was experimental and the design was pretest-posttest with the control group. The intervention consisted of a 2-minute motion graphics clip to train hearing aids maintenance skills. Data were collected using a 9-question researcher-made questionnaire. The data were analyzed by using one-way analysis of covariance. Results showed that the training of hearing aids maintenance skills with motion graphics was significantly effective for those children. The results of this study can be used by educators, teachers, professionals, and parents to train children with disabilities or normal students.

Keywords: Hearing-impaired children, hearing aids, hearing aids maintenance skill, and motion graphics.

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Authors: Jianwei Ma, Diriba Gemechu

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In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: Anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, Split Bregman Algorithm.

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Authors: Raziah Bi Mohamed Sadique, Jamal Roudaki, Murray B. Clark, Norhayati Alias

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Economic crime (i.e. corporate fraud) has a significant impact on business. This study analyzes the fraud cases reported by the Malaysian Securities Commission. Frauds involving market manipulation and/or illegal share trading are the most common types of fraud reported over the 6 years analyzed. The highest number of frauds reported involved investment and fund holding companies. Alarmingly the results indicate quite a high number of frauds cases are committed by management. The higher number of Chinese perpetrators may be due to fact that they are the dominant group in Malaysian business. The result also shows that more than half of companies involved with fraud are privately held companies in the investment/fund/finance sector. The results of this study highlight general characteristic of perpetrators (person and company) that commit fraud which could help the regulators in their monitoring and enforcement activities. To investors, this would help in analyzing their business investment or portfolio risk.

Keywords: Corporate fraud, economic crime, fraudcharacteristic, perpetrators

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Authors: Kawtar Benghazi Akhlaki, Manuel I. Capel-Tuñón

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UML is a collection of notations for capturing a software system specification. These notations have a specific syntax defined by the Object Management Group (OMG), but many of their constructs only present informal semantics. They are primarily graphical, with textual annotation. The inadequacies of standard UML as a vehicle for complete specification and implementation of real-time embedded systems has led to a variety of competing and complementary proposals. The Real-time UML profile (UML-RT), developed and standardized by OMG, defines a unified framework to express the time, scheduling and performance aspects of a system. We present in this paper a framework approach aimed at deriving a complete specification of a real-time system. Therefore, we combine two methods, a semiformal one, UML-RT, which allows the visual modeling of a realtime system and a formal one, CSP+T, which is a design language including the specification of real-time requirements. As to show the applicability of the approach, a correct design of a real-time system with hard real time constraints by applying a set of mapping rules is obtained.

Keywords: CSP+T, formal software specification, process algebras, real-time systems, unified modeling language.

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Authors: B. Sabayan, A. Alidadi, S. Ebrahimi, N. M. Bakhshani

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Neuropsychological problems are more common in hemodialysis (HD) patients than in healthy individuals. The aim of this study was to investigate the effect of long term HD on memory types of HD patients. To assess the different type of memory, we used memory parts of the Persian Papers and Pencil Cognitive assessment package (PCAP) and Addenbrooke's Cognitive Examination (ACE-R). Our study included 80 HD patients of whom 39 had less than six months of HD and 41 patients and another group which had a history of HD more than six months. The population had a mean age of 51.60 years old and 27.5% of them were female. The scores of patients who have been hemodialyzed for a long time (median time of HD was up to 4 years) had lower score in anterograde, explicit, visual, recall and recognition memory (5.44±1.07, 9.49±3.472, 22.805±6.6913, 5.59±10.435, 11.02±3.190 score) than the HD patients who underwent HD for a shorter term, where the median time was 3 to 5 months (P<0.01). The regression result shows that, by increasing the HD duration, all memory types are reduced (R2=0.600, P<0.01). The present study demonstrated that HD patients who were under HD for a long time had significantly lower scores in the different types of memory. However, additional researches are needed in this area.

Keywords: Hemodialysis patients, duration of hemodialysis, memory types, Zahedan.

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Authors: Byounghyun Kim, Youngjoon Han, Hernsoo Hahn

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The purpose of this study is to find natural gait of biped robot such as human being by analyzing the COG (Center Of Gravity) trajectory of human being's gait. It is discovered that human beings gait naturally maintain the stability and use the minimum energy. This paper intends to find the natural gait pattern of biped robot using the minimum energy as well as maintaining the stability by analyzing the human's gait pattern that is measured from gait image on the sagittal plane and COG trajectory on the frontal plane. It is not possible to apply the torques of human's articulation to those of biped robot's because they have different degrees of freedom. Nonetheless, human and 5-link biped robots are similar in kinematics. For this, we generate gait pattern of the 5-link biped robot by using the GA algorithm of adaptation gait pattern which utilize the human's ZMP (Zero Moment Point) and torque of all articulation that are measured from human's gait pattern. The algorithm proposed creates biped robot's fluent gait pattern as that of human being's and to minimize energy consumption because the gait pattern of the 5-link biped robot model is modeled after consideration about the torque of human's each articulation on the sagittal plane and ZMP trajectory on the frontal plane. This paper demonstrate that the algorithm proposed is superior by evaluating 2 kinds of the 5-link biped robot applied to each gait patterns generated both in the general way using inverse kinematics and in the special way in which by considering visuality and efficiency.

Keywords: 5-link biped robot, gait pattern, COG (Center OfGravity), ZMP (Zero Moment Point).

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Authors: Faisal Amin, Abdul Mueed, Xu Jiadong

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This paper describes the development of a fully automated measurement software for antenna radiation pattern measurements in a Compact Antenna Test Range (CATR). The CATR has a frequency range from 2-40 GHz and the measurement hardware includes a Network Analyzer for transmitting and Receiving the microwave signal and a Positioner controller to control the motion of the Styrofoam column. The measurement process includes Calibration of CATR with a Standard Gain Horn (SGH) antenna followed by Gain versus angle measurement of the Antenna under test (AUT). The software is designed to control a variety of microwave transmitter / receiver and two axis Positioner controllers through the standard General Purpose interface bus (GPIB) interface. Addition of new Network Analyzers is supported through a slight modification of hardware control module. Time-domain gating is implemented to remove the unwanted signals and get the isolated response of AUT. The gated response of the AUT is compared with the calibration data in the frequency domain to obtain the desired results. The data acquisition and processing is implemented in Agilent VEE and Matlab. A variety of experimental measurements with SGH antennas were performed to validate the accuracy of software. A comparison of results with existing commercial softwares is presented and the measured results are found to be within .2 dBm.

Keywords: Antenna measurement, calibration, time-domain gating, VNA, Positioner controller

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Authors: B. Kędra, R. Małkowski

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This paper presents information on Power System Component Simulator – a device designed for LINTE^2 laboratory owned by Gdansk University of Technology in Poland. In this paper, we first provide an introductory information on the Power System Component Simulator and its capabilities. Then, the concept of the unit is presented. Requirements for the unit are described as well as proposed and introduced functions are listed. Implementation details are given. Hardware structure is presented and described. Information about used communication interface, data maintenance and storage solution, as well as used Simulink real-time features are presented. List and description of all measurements is provided. Potential of laboratory setup modifications is evaluated. Lastly, the results of experiments performed using Power System Component Simulator are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area.

Keywords: Power converter, Simulink real-time, MATLAB, load, tap controller.

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Authors: Christopher C. Anyadubalu

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This study investigated students- perception of self efficacy and anxiety in acquiring English language, and consequently examined the relationship existing among the independent variables, confounding variables and students- performances in the English language. The researcher tested the research hypotheses using a sample group of 318 respondents out of the population size of 400 students. The results obtained revealed that there was a significant moderate negative relationship between English language anxiety and performance in English language, but no significant relationship between self-efficacy and English language performance, among the middle-school students. There was a significant moderate negative relationship between English language anxiety and self-efficacy. It was discovered that general self-efficacy and English language anxiety represented a significantly more powerful set of predictors than the set of confounding variables. Thus, the study concluded that English language anxiety and general self-efficacy were significant predictors of English language performance among middle-school students in Satri Si Suriyothai School.

Keywords: Anxiety, English Language Anxiety, Performance inEnglish Language, Self Efficacy.

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Authors: C. Ardil

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Uncertainty set theory is a generalization of fuzzy set theory and intuitionistic fuzzy set theory. It serves as an effective tool for dealing with inconsistent, imprecise, and vague information. The technique for order preference by similarity to ideal solution (TOPSIS) method is a multiple-attribute method used to identify solutions from a finite set of alternatives. It simultaneously minimizes the distance from an ideal point and maximizes the distance from a nadir point. In this paper, an extension of the TOPSIS method for multiple attribute group decision-making (MAGDM) based on uncertainty sets is presented. In uncertainty decision analysis, decision-makers express information about attribute values and weights using uncertainty numbers to select the best stealth combat aircraft.

Keywords: Uncertainty set, stealth combat aircraft selection multiple criteria decision-making analysis, MCDM, uncertainty decision analysis, TOPSIS

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Authors: Bolanle F. Oladejo, Victor T. Odumuyiwa, Amos A. David

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Knowledge is attributed to human whose problemsolving behavior is subjective and complex. In today-s knowledge economy, the need to manage knowledge produced by a community of actors cannot be overemphasized. This is due to the fact that actors possess some level of tacit knowledge which is generally difficult to articulate. Problem-solving requires searching and sharing of knowledge among a group of actors in a particular context. Knowledge expressed within the context of a problem resolution must be capitalized for future reuse. In this paper, an approach that permits dynamic capitalization of relevant and reliable actors- knowledge in solving decision problem following Economic Intelligence process is proposed. Knowledge annotation method and temporal attributes are used for handling the complexity in the communication among actors and in contextualizing expressed knowledge. A prototype is built to demonstrate the functionalities of a collaborative Knowledge Management system based on this approach. It is tested with sample cases and the result showed that dynamic capitalization leads to knowledge validation hence increasing reliability of captured knowledge for reuse. The system can be adapted to various domains.

Keywords: Actors' communication, knowledge annotation, recursive knowledge capitalization, visualization.

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Authors: Yi-Chung Hu, Yu-Lin Liao

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Due to the fast development of technology, the competition of technological products is turbulent; therefore, it is important to understand the market trend, consumers- demand and preferences. As the smartphones are prevalent, the main purpose of this paper is to utilize Analytic Hierarchy Process (AHP) to analyze consumer-s purchase evaluation factors of smartphones. Through the AHP expert questionnaire, the smartphones- main functions are classified as “user interface", “mobile commerce functions", “hardware and software specifications", “entertainment functions" and “appearance and design", five aspects to analyze the weights. Then four evaluation criteria are evaluated under each aspect to rank the weights. Based on an analysis of data shows that consumers consider when purchase factors are “hardware and software specifications", “user interface", “appearance and design", “mobile commerce functions" and “entertainment functions" in sequence. The “hardware and software specifications" aspect obtains the weight of 33.18%; it is the most important factor that consumers are taken into account. In addition, the most important evaluation criteria are central processing unit, operating system, touch screen, and battery function in sequence. The results of the study can be adopted as reference data for mobile phone manufacturers in the future on the design and marketing strategy to satisfy the voice of customer.

Keywords: Analytic Hierarchy Process (AHP), evaluation criteria, purchase evaluation factors, smartphone.

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Authors: Mohd Yussni Hashim, Mohd Nazrul Roslan, Azriszul Mohd Amin, Ahmad Mujahid Ahmad Zaidi, Saparudin Ariffin

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Environmental awareness and depletion of the petroleum resources are among vital factors that motivate a number of researchers to explore the potential of reusing natural fiber as an alternative composite material in industries such as packaging, automotive and building constructions. Natural fibers are available in abundance, low cost, lightweight polymer composite and most importance its biodegradability features, which often called “ecofriendly" materials. However, their applications are still limited due to several factors like moisture absorption, poor wettability and large scattering in mechanical properties. Among the main challenges on natural fibers reinforced matrices composite is their inclination to entangle and form fibers agglomerates during processing due to fiber-fiber interaction. This tends to prevent better dispersion of the fibers into the matrix, resulting in poor interfacial adhesion between the hydrophobic matrix and the hydrophilic reinforced natural fiber. Therefore, to overcome this challenge, fiber treatment process is one common alternative that can be use to modify the fiber surface topology by chemically, physically or mechanically technique. Nevertheless, this paper attempt to focus on the effect of mercerization treatment on mechanical properties enhancement of natural fiber reinforced composite or so-called bio composite. It specifically discussed on mercerization parameters, and natural fiber reinforced composite mechanical properties enhancement.

Keywords: Mercerization treatment, mechanical properties, natural fiber and bio composite

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Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

Abstract:

The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural Language Processing (NLP) in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis.

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Authors: Pei-Lin Yueh, Bor-Yann Chen, Chuan-Chung Hsueh

Abstract:

This first-attempt study revealed that decolorized intermediates of azo dyes could act as redox mediators to assist wastewater (WW) decolorization due to enhancement of electron-transport phenomena. Electrochemical impedance spectra indicated that hydroxyl and amino-substituent(s) were functional group(s) as redox-mediator(s). As azo dyes are usually multiple benzene-rings structured, their derived decolorized intermediates are likely to play roles of electron shuttles due to lower barrier of energy gap for electron shuttling. According to cyclic voltammetric profiles, redox mediating characteristics of decolorized intermediates of azo dyes (e.g., RBu171, RR198, RR141, RBk5) were clearly disclosed. With supplementation of biodecolorized metabolites of RR141 and 198, decolorization performance of could be evidently augmented. This study also suggested the optimal modes of microbial fuel cell (MFC)-assisted WW decolorization would be plug-flow or batch mode of operation with no mix. Single chamber-MFCs would be more favourable than double chamber MFCs due to non-mixing contacting reactor scheme for operation.

Keywords: Redox mediators, dye decolorization, bioelectricity generation, microbial fuel cells.

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

Abstract:

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, Speech Emotion Recognition, longitudinal biomarker, machine learning.

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Authors: Fatemeh Mosalman Yazdi

Abstract:

One of the most important requirements for the operation and planning activities of an electrical utility is the prediction of load for the next hour to several days out, known as short term load forecasting. This paper presents the development of an artificial neural network based short-term load forecasting model. The model can forecast daily load profiles with a load time of one day for next 24 hours. In this method can divide days of year with using average temperature. Groups make according linearity rate of curve. Ultimate forecast for each group obtain with considering weekday and weekend. This paper investigates effects of temperature and humidity on consuming curve. For forecasting load curve of holidays at first forecast pick and valley and then the neural network forecast is re-shaped with the new data. The ANN-based load models are trained using hourly historical. Load data and daily historical max/min temperature and humidity data. The results of testing the system on data from Yazd utility are reported.

Keywords: Artificial neural network, Holiday forecasting, pickand valley load forecasting, Short-term load-forecasting.

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