Search results for: Interval endurance training program

Authors: Erh-Wen Hu, Cyril S. Ku, Andrew T. Russo, Bogong Su, Jian Wang

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Unlike general-purpose processors, digital signal processors (DSP processors) are strongly application-dependent. To meet the needs for diverse applications, a wide variety of DSP processors based on different architectures ranging from the traditional to VLIW have been introduced to the market over the years. The functionality, performance, and cost of these processors vary over a wide range. In order to select a processor that meets the design criteria for an application, processor performance is usually the major concern for digital signal processing (DSP) application developers. Performance data are also essential for the designers of DSP processors to improve their design. Consequently, several DSP performance benchmarks have been proposed over the past decade or so. However, none of these benchmarks seem to have included recent new DSP applications. In this paper, we use a new benchmark that we recently developed to compare the performance of popular DSP processors from Texas Instruments and StarCore. The new benchmark is based on the Selectable Mode Vocoder (SMV), a speech-coding program from the recent third generation (3G) wireless voice applications. All benchmark kernels are compiled by the compilers of the respective DSP processors and run on their simulators. Weighted arithmetic mean of clock cycles and arithmetic mean of code size are used to compare the performance of five DSP processors. In addition, we studied how the performance of a processor is affected by code structure, features of processor architecture and optimization of compiler. The extensive experimental data gathered, analyzed, and presented in this paper should be helpful for DSP processor and compiler designers to meet their specific design goals.

Keywords: digital signal processors, DSP benchmark, instruction level parallelism, modified cyclomatic complexity, performance analysis.

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Authors: Seema Chopra, R. Mitra, Vijay Kumar

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A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.

Keywords: Fuzzy control, neuro-fuzzy techniques, fuzzy subtractive clustering, extraction of rules, and optimization of membership functions.

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Authors: K. Chethana, A. S. Guru Prasad, S. N. Omkar, B. Vadiraj, S. Asokan

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This paper describes an ab-initio design, development and calibration results of an Optical Sensor Ground Reaction Force Measurement Platform (OSGRFP) for gait and geriatric studies. The developed system employs an array of FBG sensors to measure the respective ground reaction forces from all three axes (X, Y and Z), which are perpendicular to each other. The novelty of this work is two folded. One is in its uniqueness to resolve the tri axial resultant forces during the stance in to the respective pure axis loads and the other is the applicability of inherently advantageous FBG sensors which are most suitable for biomechanical instrumentation. To validate the response of the FBG sensors installed in OSGRFP and to measure the cross sensitivity of the force applied in other directions, load sensors with indicators are used. Further in this work, relevant mathematical formulations are presented for extracting respective ground reaction forces from wavelength shifts/strain of FBG sensors on the OSGRFP. The result of this device has implications in understanding the foot function, identifying issues in gait cycle and measuring discrepancies between left and right foot. The device also provides a method to quantify and compare relative postural stability of different subjects under test, which has implications in post-surgical rehabilitation, geriatrics and optimizing training protocols for sports personnel.

Keywords: Balance, stability, Gait analysis, FBG applications, optical sensor ground reaction force platform.

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Authors: Nalinee Sophatsathit

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The objectives of memorabilia of Suan Sunandha are to develop a general knowledge presentation about the historical royal garden through interactive graphic simulation technique and to employ high-functionality context in enhancing interactive user navigation. The approach infers non-intrusive display of relevant history in response to situational context. User’s navigation runs through the virtual reality campus, consisting of new and restored buildings. A flash back presentation of information pertaining to the history in the form of photos, paintings, and textual descriptions are displayed along each passing-by building. To keep the presentation lively, graphical simulation is created in a serendipity game play so that the user can both learn and enjoy the educational tour. The benefits of this human-computer interaction development are two folds. First, lively presentation technique and situational context modeling are developed that entail a usable paradigm of knowledge and information presentation combinations. Second, cost effective training and promotion for both internal personnel and public visitors to learn and keep informed of this historical royal garden can be furnished without the need for a dedicated public relations service. Future improvement on graphic simulation and ability based display can extend this work to be more realistic, user-friendly, and informative for all.

Keywords: Interactive user navigation, high-functionality context, situational context, human-computer interaction.

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Authors: Abubakar Uba Ibrahim, Ibrahim Haruna Shanono

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Smart metering and demand response are gaining ground in industrial and residential applications. Smart Appliances have been given concern towards achieving Smart home. The success of Smart grid development relies on the successful implementation of Information and Communication Technology (ICT) in power sector. Smart Appliances have been the technology under development and many new contributions to its realization have been reported in the last few years. The role of ICT here is to capture data in real time, thereby allowing bi-directional flow of information/data between producing and utilization point; that lead a way for the attainment of Smart appliances where home appliances can communicate between themselves and provide a self-control (switch on and off) using the signal (information) obtained from the grid. This paper depicts the background on ICT for smart appliances paying a particular attention to the current technology and identifying the future ICT trends for load monitoring through which smart appliances can be achieved to facilitate an efficient smart home system which promote demand response program. This paper grouped and reviewed the recent contributions, in order to establish the current state of the art and trends of the technology, so that the reader can be provided with a comprehensive and insightful review of where ICT for smart appliances stands and is heading to. The paper also presents a brief overview of communication types, and then narrowed the discussion to the load monitoring (Non-intrusive Appliances Load Monitoring ‘NALM’). Finally, some future trends and challenges in the further development of the ICT framework are discussed to motivate future contributions that address open problems and explore new possibilities.

Keywords: Communication technology between appliances, demand response, load monitoring, smart appliances and smart grid.

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Authors: Qasim Hamakhurshid Hamamurad, Normal Mat Jusoh, Uznir Ujang

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The concept of the city with an infrastructure of Information and Communication Technology (ICT) embraces several definitions depending on the meanings of the word "smart" which include: intelligent city, smart city, knowledge city, ubiquitous city, sustainable city, and digital city. Many definitions of the city exist, but this study explores which one has been universally acknowledged. From the literature analysis, it emerges that the term smart city is the most used in the articles to show the smartness of a city. This paper shares exploration of the research from the seven main website digital databases and journals focusing on the smart city from January 2015 to February 2020 to: (a) Time research, to examine the causes of the smart city phenomenon and other concept literature in the last five years; (b) Review of words, to see how and where the smart city specification and relation of different definitions are implemented; (c) Geographical research to consider where smart cities' greatest concentrations are in the world and determine if Malaysians are interacting with the smart city; and (d) How many papers are published in all of Malaysia from 2015 to 2020 about smart cities. Three steps are followed to accomplish the aim of this study: (1) The analysis which covered a systematic literature review search strategy to gather a representative sub-set of papers on the smart city and other definitions utilizing GoogleScholar, Elsevier, Scopus, ScienceDirect, IEEEXplore, WebofScience, and Springer between January 2015-February 2020; (2) The formation of a bibliometric map based on the bibliometric evaluation using the mapping technique VOSviewer to visualize differences; (3) VOSviewer application program to build initial clusters. The bibliometric analytical findings targeted the word harmony.

Keywords: Bibliometric research, smart city, ICT, VOSviewer, urban modernization.

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor, when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics, and using the weighted sum-squared prediction error as the residual. The Recursive Orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. Several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature, and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control.

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Authors: Fatemeh Behjati Ardakani, Fatemeh Khademian, Abbas Nowzari Dalini, Reza Ebrahimpour

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Human activity is a major concern in a wide variety of applications, such as video surveillance, human computer interface and face image database management. Detecting and recognizing faces is a crucial step in these applications. Furthermore, major advancements and initiatives in security applications in the past years have propelled face recognition technology into the spotlight. The performance of existing face recognition systems declines significantly if the resolution of the face image falls below a certain level. This is especially critical in surveillance imagery where often, due to many reasons, only low-resolution video of faces is available. If these low-resolution images are passed to a face recognition system, the performance is usually unacceptable. Hence, resolution plays a key role in face recognition systems. In this paper we introduce a new low resolution face recognition system based on mixture of expert neural networks. In order to produce the low resolution input images we down-sampled the 48 × 48 ORL images to 12 × 12 ones using the nearest neighbor interpolation method and after that applying the bicubic interpolation method yields enhanced images which is given to the Principal Component Analysis feature extractor system. Comparison with some of the most related methods indicates that the proposed novel model yields excellent recognition rate in low resolution face recognition that is the recognition rate of 100% for the training set and 96.5% for the test set.

Keywords: Low resolution face recognition, Multilayered neuralnetwork, Mixture of experts neural network, Principal componentanalysis, Bicubic interpolation, Nearest neighbor interpolation.

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Authors: N. Talisa, K. Rungsarid, P. Chakrit

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The objectives of the research are to study the existing agricultural patterns, and to evaluate the sustainability of agricultural on economic, social and environmental aspects. The samplings were the representatives of the agriculturist group from Ban Paew district, Samut Sakorn province by purposive sampling method of 30 households. The tools being used were interview forms together with the Rapid Rural Appraisal (RRA) and the Participation Rural Appraisal (PRA). The information collected was analyzed with the principle of Content Analysis andusing Descriptive Statistics. After that all the information gotten was analyze the sustainability on the household level and village level. The research result can be concluded as follows: The agricultural Patterns: For most of the cultivation main crop was fruit trees planted and the supplement crop was around the patch or added other plants in the trenches. There were trenches for the cultivating water. The product distribution was by selling (97.5%) and the selling to middle man was the highest number (62.5%). Evaluating the sustainability of the agricultural by the indicators which were appropriate to the area: For the agricultural sustainability on the household level it was found that only one household had sustainable, others household had conditioned sustainable. For on the village level it was found that the sustainability on the issue of agricultural knowledge training had the lowest level (Sustainability index = 31.67%). Secondary was the acknowledging about soil information (Sustainability index = 35.0), and the household labors on agriculture, net return over cash cost (Sustainability index = 55.0%) respectively. Performance percentage is 48.81 %. It was brought to the conclusion that this area did not have the agricultural sustainability.

Keywords: Sustainability of agricultural, sustainability indicators, sustainability index.

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Authors: K. Okubo, Y. Kurihara, T. Kaburagi, K. Watanabe

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Many of the ever-growing elderly population require exercise, such as running, for health management. One important element of a runner’s training is the choice of shoes for exercise; shoes are important because they provide the interface between the feet and road. When we purchase shoes, we may instinctively choose a pair after trying on many different pairs of shoes. Selecting the shoes instinctively may work, but it does not guarantee a suitable fit for running activities. Therefore, if we could select suitable shoes for each runner from the viewpoint of brain activities, it would be helpful for validating shoe selection. In this paper, we describe how brain activities show different characteristics during particular task, corresponding to different properties of shoes. Using five subjects, we performed a verification experiment, applying weight, softness, and flexibility as shoe properties. In order to affect the shoe property’s differences to the brain, subjects run for 10 min. Before and after running, subjects conducted a paced auditory serial addition task (PASAT) as the particular task; and the subjects’ brain activities during the PASAT are evaluated based on oxyhemoglobin and deoxyhemoglobin relative concentration changes, measured by near-infrared spectroscopy (NIRS). When the brain works actively, oxihemoglobin and deoxyhemoglobin concentration drastically changes; therefore, we calculate the maximum values of concentration changes. In order to normalize relative concentration changes after running, the maximum value are divided by before running maximum value as evaluation parameters. The classification of the groups of shoes is expressed on a self-organizing map (SOM). As a result, deoxyhemoglobin can make clusters for two of the three types of shoes.

Keywords: Brain activities, NIRS, PASAT, running shoes.

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Authors: Essam A. Al-Bahkali, Mahir H. Es-saheb, Jonny Herwan

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In this study the elastic-plastic stress distribution in weld-bonded joint, fabricated from austenitic stainless steel (AISI 304) sheet of 1.00 mm thickness and Epoxy adhesive Araldite 2011, subjected to axial loading is investigated. This is needed to improve design procedures and welding codes, and saving efforts in the cumbersome experiments and analysis. Therefore, a complete 3-D finite element modelling and analysis of spot welded, bonded and weld-bonded joints under axial loading conditions is carried out. A comprehensive systematic experimental program is conducted to determine many properties and quantities, of the base metals and the adhesive, needed for FE modelling, such like the elastic – plastic properties, modulus of elasticity, fracture limit, the nugget and heat affected zones (HAZ) properties, etc. Consequently, the finite element models developed, for each case, are used to evaluate stresses distributions across the entire joint, in both the elastic and plastic regions. The stress distribution curves are obtained, particularly in the elastic regions and found to be consistent and in excellent agreement with the published data. Furthermore, the stresses distributions are obtained in the weld-bonded joint and display the best results with almost uniform smooth distribution compared to spot and bonded cases. The stress concentration peaks at the edges of the weld-bonded region, are almost eliminated resulting in achieving the strongest joint of all processes.

Keywords: Spot Welded, Weld-Bonded, Load-Displacement curve, Stress distribution

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: Information Gain (IG), Intrusion Detection System (IDS), K-means Clustering, Weka.

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Authors: Aliakbar Golshani, Seyyed Mehdi Poorhashemi, Mahsa Gharizadeh

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The under passing tunnels are strongly influenced by the soils around. There are some complexities in the specification of real soil behavior, owing to the fact that lots of uncertainties exist in soil properties, and additionally, inappropriate soil constitutive models. Such mentioned factors may cause incompatible settlements in numerical analysis with the obtained values in actual construction. This paper aims to report a case study on a specific tunnel constructed by NATM. The tunnel has a depth of 11.4 m, height of 12.2 m, and width of 14.4 m with 2.5 lanes. The numerical modeling was based on a 2D finite element program. The soil material behavior was modeled by hardening soil model. According to the field observations, the numerical estimated settlement at the ground surface was approximately four times more than the measured one, after the entire installation of the initial lining, indicating that some unknown factors affect the values. Consequently, the geotechnical parameters are accurately revised by a numerical back-analysis using laboratory and field test data and based on the obtained monitoring data. The obtained result confirms that typically, the soil parameters are conservatively low-estimated. And additionally, the constitutive models cannot be applied properly for all soil conditions.

Keywords: NATM tunnel, initial lining, field test data, laboratory test data, monitoring data, numerical back-analysis.

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Authors: S. Pirrello

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Sydney’s booming real estate market has pushed property developers to invest in historically “no-go” areas, which were previously too expensive to develop. These areas are usually near rivers where the sites are underlain by deep alluvial and estuarine sediments. In these ground conditions, conventional bored pile techniques are often not competitive. Contiguous Flight Auger (CFA) and Drilled Displacement (DD) Piles techniques are on the other hand suitable for these ground conditions. This paper deals with the design and construction challenges encountered with these piling techniques for a series of high-rise towers in Sydney’s West. The advantages of DD over CFA piles such as reduced overall spoil with substantial cost savings and achievable rock sockets in medium strength bedrock are discussed. Design performances were assessed with PIGLET. Pile performances are validated in two stages, during constructions with the interpretation of real-time data from the piling rigs’ on-board computer data, and after construction with analyses of results from high strain pile dynamic testing (PDA). Results are then presented and discussed. High Strain testing data are presented as Case Pile Wave Analysis Program (CAPWAP) analyses.

Keywords: Contiguous flight auger, case pile wave analysis, high strain pile, drilled displacement, pile performance.

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Authors: Mukesh Singh Boori, Venerando Eustáquio Amaro

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The objective of this study was to improve our understanding of vulnerability and environmental change; it's causes basically show the intensity, its distribution and human-environment effect on the ecosystem in the Apodi Valley Region, This paper is identify, assess and classify vulnerability and environmental change in the Apodi valley region using a combined approach of landscape pattern and ecosystem sensitivity. Models were developed using the following five thematic layers: Geology, geomorphology, soil, vegetation and land use/cover, by means of a Geographical Information Systems (GIS)-based on hydro-geophysical parameters. In spite of the data problems and shortcomings, using ESRI-s ArcGIS 9.3 program, the vulnerability score, to classify, weight and combine a number of 15 separate land cover classes to create a single indicator provides a reliable measure of differences (6 classes) among regions and communities that are exposed to similar ranges of hazards. Indeed, the ongoing and active development of vulnerability concepts and methods have already produced some tools to help overcome common issues, such as acting in a context of high uncertainties, taking into account the dynamics and spatial scale of asocial-ecological system, or gathering viewpoints from different sciences to combine human and impact-based approaches. Based on this assessment, this paper proposes concrete perspectives and possibilities to benefit from existing commonalities in the construction and application of assessment tools.

Keywords: Vulnerability, Land use/cover, Ecosystem, Remotesensing, GIS.

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Authors: Ioannis P. Panagopoulos, Christos C. Pavlatos, George K. Papakonstantinou

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Conventional approaches in the implementation of logic programming applications on embedded systems are solely of software nature. As a consequence, a compiler is needed that transforms the initial declarative logic program to its equivalent procedural one, to be programmed to the microprocessor. This approach increases the complexity of the final implementation and reduces the overall system's performance. On the contrary, presenting hardware implementations which are only capable of supporting logic programs prevents their use in applications where logic programs need to be intertwined with traditional procedural ones, for a specific application. We exploit HW/SW codesign methods to present a microprocessor, capable of supporting hybrid applications using both programming approaches. We take advantage of the close relationship between attribute grammar (AG) evaluation and knowledge engineering methods to present a programmable hardware parser that performs logic derivations and combine it with an extension of a conventional RISC microprocessor that performs the unification process to report the success or failure of those derivations. The extended RISC microprocessor is still capable of executing conventional procedural programs, thus hybrid applications can be implemented. The presented implementation is programmable, supports the execution of hybrid applications, increases the performance of logic derivations (experimental analysis yields an approximate 1000% increase in performance) and reduces the complexity of the final implemented code. The proposed hardware design is supported by a proposed extended C-language called C-AG.

Keywords: Attribute Grammars, Logic Programming, RISC microprocessor.

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: Distribution network, machine learning, network topology, phase identification, smart grid.

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Authors: Mohd Hasmadi Ismail, Kamaruzaman Jusoff

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In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Keywords: Image Classification, Reference Data, Accuracy Assessment, Kappa Statistic, Forest Land Cover

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars, and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: Remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction.

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Authors: A. S. Adesuyi, Z. Munch

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This study investigates the use of a time-series of MODIS NDVI data to identify agricultural land cover change on an annual time step (2007 - 2012) and characterize the trend. Following an ISODATA classification of the MODIS imagery to selectively mask areas not agriculture or semi-natural, NDVI signatures were created to identify areas cereals and vineyards with the aid of ancillary, pictometry and field sample data for 2010. The NDVI signature curve and training samples were used to create a decision tree model in WEKA 3.6.9 using decision tree classifier (J48) algorithm; Model 1 including ISODATA classification and Model 2 not. These two models were then used to classify all data for the study area for 2010, producing land cover maps with classification accuracies of 77% and 80% for Model 1 and 2 respectively. Model 2 was subsequently used to create land cover classification and change detection maps for all other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices. Over the years as predicted by the land cover classification. Forty one percent of the catchment comprised of cereals with 35% possibly following a crop rotation system. Vineyards largely remained constant with only one percent conversion to vineyard from other land cover classes.

Keywords: Change detection, Land cover, NDVI, time-series.

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Authors: Wardoyo, Humairoh

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In global competition nowadays, the world economy heavily depends upon high technology and capital intensive industries that are mainly owned by well-established economic and developed countries, such as United States of America, United Kingdom, Japan, and South Korea. Indonesia as a developing country is building its economic activities towards industrial country as well, although a slightly different approach was implemented. For example, similar to the concept of one village one product (OVOP) implemented in Japan, Indonesia also adopted this concept by promoting local traditional products to improve incomes of village people and to enhance local economic activities. Analysis on how OVOP program increase local people’s income and influence customer satisfaction were the objective of this paper. Behavioral intention to purchase and re-purchase, customer satisfaction and promotion are key factors for local products to play significant roles in improving local income and economy of the region. The concepts of OVOP and key factors that influence economic activities of local people and the region will be described and explained in the paper. Results of research, in a case study based on 300 respondents, customers of a local restaurant at Tangerang City, Banten Province of Indonesia, indicated that local product, service quality and behavioral intention individually have significant influence to customer satisfaction; whereas simultaneous tests to the variables indicated positive and significant influence to the behavioral intention through customer satisfaction as the intervening variable.

Keywords: Behavioral intention, customer satisfaction, local products, one village one product.

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Authors: Cleto J. Sauer Jr

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Introduction: Brazil’s new national curriculum guidelines (NCG) for medical education were published in 2014, presenting active learning methodologies as a cornerstone. Simulation was initially applied for aviation pilots’ training and is currently applied in health sciences. The high-fidelity simulator replicates human body anatomy in detail, also reproducing physiological functions and its use is increasing in medical schools. Realistic Simulation (RS) has pedagogical aspects that are aligned with Brazil’s NCG teaching concepts. The main objective of this study is to carry on a narrative review on RS’s aspects that are aligned with Brazil’s new NCG teaching concepts. Methodology: A narrative review was conducted, with search in three databases (PubMed, Embase and BVS) of studies published between 2010 and 2020. Results: After systematized search, 49 studies were selected and divided into four thematic groups. RS is aligned with new Brazilian medical curriculum as it is an active learning methodology, providing greater patient safety, uniform teaching, and student's emotional skills enhancement. RS is based on reflective learning, a teaching concept developed for adult’s education. Conclusion: RS is a methodology aligned with NCG teaching concepts and has potential to assist in the implementation of new Brazilian medical school’s curriculum. It is an immersive and interactive methodology, which provides reflective learning in a safe environment for students and patients.

Keywords: Curriculum, high-fidelity simulator, medical education, realistic simulation.

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Authors: Ahmad Fahim Nasiry, Shigeo Honma

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We examine two-dimensional oil displacement by water in a petroleum reservoir. The pore fluid is immiscible, and the porous media is homogenous and isotropic in the horizontal direction. Buckley-Leverett theory and a combination of Laplacian and Darcy’s law are used to study the fluid flow through porous media, and the Laplacian that defines the dispersion and diffusion of fluid in the sand using heavy oil is discussed. The reservoir is homogenous in the horizontal direction, as expressed by the partial differential equation. Two main factors which are observed are the water saturation and pressure distribution in the reservoir, and they are evaluated for predicting oil recovery in two dimensions by a physical and mathematical simulation model. We review the numerical simulation that solves difficult partial differential reservoir equations. Based on the numerical simulations, the saturation and pressure equations are calculated by the iterative alternating direction implicit method and the iterative alternating direction explicit method, respectively, according to the finite difference assumption. However, to understand the displacement of oil by water and the amount of water dispersion in the reservoir better, an interpolated contour line of the water distribution of the five-spot pattern, that provides an approximate solution which agrees well with the experimental results, is also presented. Finally, a computer program is developed to calculate the equation for pressure and water saturation and to draw the pressure contour line and water distribution contour line for the reservoir.

Keywords: Numerical simulation, immiscible, finite difference, IADI, IADE, waterflooding.

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Authors: Eftah Bte. Moh Hj Abdullah, Abd Aziz Bin Abd Shukor, Norazilawati Binti Abdullah, Rahimah Adam, Othman Bin Lebar

Abstract:

The competency and integrity required for better understanding and practice of School-based Assessment (PBS) comes not only from the process, but also in providing the support or ‘scaffolding’ for teachers to recognize the student as a learner, improve their self-assessment skills, understanding of the daily teaching plan and its constructive alignment of the curriculum, pedagogy and assessment. The cultivation of integrity in PBS among the teachers is geared towards encouraging them to become committed and dedicated in implementing assessments in a serious, efficient manner, thus moving away from the usual teacher-focused approach to the student-focused approach. The teachers show their integrity via their professional commitment, responsibility and actions. The module based on the cultivation of integrity in PBS among Malaysian teachers aims to broaden the guidance support for teachers (embedded in the training), which consists of various domains to enable better evaluation of complex assessment tasks and the construction of suitable instrument for measuring the relevant cognitive, affective and psychomotor domains to describe the students’ achievement. The instrument for integrity cultivation in PBS has been developed and validated for measuring the effectiveness of the module constructed. This module is targeted towards assisting the staff in the Education Ministry, especially the principal trainers, teachers, headmasters and education officers to acquire effective intervention for improving the PBS assessors’ integrity and competency.

Keywords: School-based assessment, Assessment competency Integrity cultivation, Professional commitment, Module.

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Authors: Nikhil Kewal Krishna Mehta

Abstract:

In the past researchers have questioned the effectiveness of ethics training in higher education. Also, there are observations that support the view that ethical behaviour (range of actions)/ethical decision making models used in the past make use of vignettes to explain ethical behaviour. The understanding remains in the perspective that these vignettes play a limited role in determining individual intentions and not actions. Some authors have also agreed that there are possibilities of differences in one’s intentions and actions. This paper makes an attempt to fill those gaps by evaluating real actions rather than intentions. In a way this study suggests the use of an experiential methodology to explore Berlo’s model of communication as an action along with orchestration of various principles. To this endeavor, an attempt was made to use conversational analysis in the pursuance of evaluating ethical decision making behaviour among students and middle level managers. The process was repeated six times with the set of an average of 15 participants. Similarities have been observed in the behaviour of students and middle level managers that calls for understanding that both the groups of individuals have no cognizance of their actual actions. The deliberations derived out of conversation were taken a step forward for meta-ethical evaluations to portray a clear picture of ethical behaviour among participants. This study provides insights for understanding demonstrated unconscious human behaviour which may fortuitously be termed both ethical and unethical.

Keywords: Berlo’s action model of communication, Conversational Analysis, Ethical behaviour, Ethical decision making, experiential learning, Intentions and Actions.

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Authors: Shih-Wen Hsiao, Rong-Qi Chen

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In the field of fashion design, 3D Mannequin is a kind of assisting tool which could rapidly realize the design concepts. While the concept of 3D Mannequin is applied to the computer added fashion design, it will connect with the development and the application of design platform and system. Thus, the situation mentioned above revealed a truth that it is very critical to develop a module of 3D Mannequin which would correspond with the necessity of fashion design. This research proposes a concrete plan that developing and constructing a system of 3D Mannequin with Kinect. In the content, ergonomic measurements of objective human features could be attained real-time through the implement with depth camera of Kinect, and then the mesh morphing can be implemented through transformed the locations of the control-points on the model by inputting those ergonomic data to get an exclusive 3D mannequin model. In the proposed methodology, after the scanned points from the Kinect are revised for accuracy and smoothening, a complete human feature would be reconstructed by the ICP algorithm with the method of image processing. Also, the objective human feature could be recognized to analyze and get real measurements. Furthermore, the data of ergonomic measurements could be applied to shape morphing for the division of 3D Mannequin reconstructed by feature curves. Due to a standardized and customer-oriented 3D Mannequin would be generated by the implement of subdivision, the research could be applied to the fashion design or the presentation and display of 3D virtual clothes. In order to examine the practicality of research structure, a system of 3D Mannequin would be constructed with JAVA program in this study. Through the revision of experiments the practicability-contained research result would come out.

Keywords: 3D Mannequin, kinect scanner, interactive closest point, shape morphing, subdivision.

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Authors: Kalsoom Sumra

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The increasing concern of public sector reforms brings new challenges to public service ethics in developing countries not only at central level but also at local level. This paper aims to identify perceptions on public service ethics of public officials and examines more generally the understanding of public servants in Pakistan towards public service ethics in local public organizations. The study uses an independently administered structured questionnaire to collect data to know the extent of the recognition of public service ethics in local organizations. A total of 150 completed questionnaires are analyzed received from public servants working at the local level in Pakistan. The analysis explores how traditional, social patterns and cultural ethics can provide us with a rounded picture of the main antecedents, moderators of public service ethics in Pakistan. Moreover, the findings of this study contribute in association of public service ethics which are crucial in ongoing political and administrative culture of Pakistan, the most crucial core for public organizational ethical climate. This study also has numerous implications for local public administration and it highlights the importance of expanding research agenda on public service ethics in developing settings with challenging institutional contexts with imperfect training and operating environments. This study may well be particularly important for practice of public service ethics in developing countries in public administration. To the best of author’s knowledge, this study is the first of its kind to provide an initial step in practical implications to emphasize relevant public service ethics in public administration in developing transparent and accountable organization.

Keywords: Public service ethics, accountability and transparency, public service reforms, public administration, organizational ethical climate.

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Authors: Raphael de Oliveira Garcia, Samuel Rocha de Oliveira

Abstract:

We have developed a new computer program in Fortran 90, in order to obtain numerical solutions of a system of Relativistic Magnetohydrodynamics partial differential equations with predetermined gravitation (GRMHD), capable of simulating the formation of relativistic jets from the accretion disk of matter up to his ejection. Initially we carried out a study on numerical methods of unidimensional Finite Volume, namely Lax-Friedrichs, Lax-Wendroff, Nessyahu-Tadmor method and Godunov methods dependent on Riemann problems, applied to equations Euler in order to verify their main features and make comparisons among those methods. It was then implemented the method of Finite Volume Centered of Nessyahu-Tadmor, a numerical schemes that has a formulation free and without dimensional separation of Riemann problem solvers, even in two or more spatial dimensions, at this point, already applied in equations GRMHD. Finally, the Nessyahu-Tadmor method was possible to obtain stable numerical solutions - without spurious oscillations or excessive dissipation - from the magnetized accretion disk process in rotation with respect to a central black hole (BH) Schwarzschild and immersed in a magnetosphere, for the ejection of matter in the form of jet over a distance of fourteen times the radius of the BH, a record in terms of astrophysical simulation of this kind. Also in our simulations, we managed to get substructures jets. A great advantage obtained was that, with the our code, we got simulate GRMHD equations in a simple personal computer.

Keywords: Finite Volume Methods, Central Schemes, Fortran 90, Relativistic Astrophysics, Jet.

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Authors: Osama Elgadi, Martin Birkett, Wai Ming Cheung

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This paper investigates the barriers behind the underutilisation of six sigma in Libyan manufacturing companies (LMCs). A mixed-method methodology is proposed, starting by conducting interviews to collect qualitative data followed by the development of a questionnaire to obtain quantitative data. The focus of this paper is on discussing the findings of the interview stage and how these can be used to further develop the questionnaire stage. The interview results showed that only four key barriers were highlighted as being encountered by LMCs. With a difference in terms of their significance, these factors were identified, and placed in descending order according to their importance, namely: “Lack of top management commitment”, “Lack of training”, “Lack of knowledge about six sigma”, and “Culture effect”. The findings also showed that some barriers which, were found in previous studies of six sigma implementation were not considered as barriers to LMCs but can, in fact, be considered as success factors or enablers for six sigma adoption. These factors were identified as: “sufficiency of time and financial resources”; “customers unsatisfied”; “good communication between all departments in the company”; “we are certain about its results and benefits to our company and unhappy with the current quality system”. These results suggest that LMCs face fewer barriers to adopting six sigma than many well-established global companies operating in other countries and could take advantage of these successful factors by developing and implementing a six sigma framework to improve their product quality and competitiveness.

Keywords: Six sigma, barriers, Libyan manufacturing companies, interview.

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Authors: Roberto Iglesias, Theocharis Kyriacou, Ulrich Nehmzow, Steve Billings

Abstract:

Fundamental sensor-motor couplings form the backbone of most mobile robot control tasks, and often need to be implemented fast, efficiently and nevertheless reliably. Machine learning techniques are therefore often used to obtain the desired sensor-motor competences. In this paper we present an alternative to established machine learning methods such as artificial neural networks, that is very fast, easy to implement, and has the distinct advantage that it generates transparent, analysable sensor-motor couplings: system identification through nonlinear polynomial mapping. This work, which is part of the RobotMODIC project at the universities of Essex and Sheffield, aims to develop a theoretical understanding of the interaction between the robot and its environment. One of the purposes of this research is to enable the principled design of robot control programs. As a first step towards this aim we model the behaviour of the robot, as this emerges from its interaction with the environment, with the NARMAX modelling method (Nonlinear, Auto-Regressive, Moving Average models with eXogenous inputs). This method produces explicit polynomial functions that can be subsequently analysed using established mathematical methods. In this paper we demonstrate the fidelity of the obtained NARMAX models in the challenging task of robot route learning; we present a set of experiments in which a Magellan Pro mobile robot was taught to follow four different routes, always using the same mechanism to obtain the required control law.

Keywords: Mobile robotics, system identification, non-linear modelling, NARMAX.

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