Search results for: human machine interface.

Authors: Soe Sandar Aung, Han Phyo Wai, Nyein Nyein Soe

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The induction hardening machines are utilized in the industries which modify machine parts and tools needed to achieve high ware resistance. This paper describes the model of induction heating process design of inverter circuit and the results of induction surface hardening of heating coil. In the design of heating coil, the shape and the turn numbers of the coil are very important design factors because they decide the overall operating performance of induction heater including resonant frequency, Q factor, efficiency and power factor. The performance will be tested by experiments in some cases high frequency induction hardening machine.

Keywords: Induction Heating, Resonant Circuit, InverterCircuit, Coil Design, Induction Hardening Machine.

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Authors: Chutchada Nusai, Yoshimi Suzuki, Haruaki Yamazaki

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Selecting the word translation from a set of target language words, one that conveys the correct sense of source word and makes more fluent target language output, is one of core problems in machine translation. In this paper we compare the 3 methods of estimating word translation probabilities for selecting the translation word in Thai – English Machine Translation. The 3 methods are (1) Method based on frequency of word translation, (2) Method based on collocation of word translation, and (3) Method based on Expectation Maximization (EM) algorithm. For evaluation we used Thai – English parallel sentences generated by NECTEC. The method based on EM algorithm is the best method in comparison to the other methods and gives the satisfying results.

Keywords: Machine translation, EM algorithm.

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Authors: Aminu J. A. Koguna, Aliyu M. Aliyu, Olawale T. Fajemidupe, Yahaya D. Baba

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Production fluids are transported from the platform to tankers or process facilities through transfer pipelines. Water being one of the heavier phases tends to settle at the bottom of pipelines especially at low flow velocities and this has adverse consequences for pipeline integrity. On restart after a shutdown, this could result in corrosion and issues for process equipment, thus the need to have the heavier liquid dispersed into the flowing lighter fluid. This study looked at the flow regime of low water cut and low flow velocity oil and water flow using conductive film thickness probes in a large diameter 4-inch pipe to obtain oil and water interface height and the interface structural velocity. A wide range of 0.1–1.0 m/s oil and water mixture velocities was investigated for 0.5–5% water cut. Two fluid model predictions were used to compare with the experimental results.

Keywords: Interface height, liquid-liquid flow, two-fluid model, water cut.

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Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: Agricultural object detection, Deep learning, machine vision, YOLO family.

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Authors: Babak Mohajeri, Sen Bao, Timo Nyberg

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Customer experience is increasingly the differentiator between successful companies and those who struggle. Currently, customer experiences become more dynamic; and they advance with each interaction between the company and a customer. Every customer conversation and any effort to evolve these conversations would be beneficial and should ultimately result in a positive customer experience. The aim of this paper is to analyze the evolving customer experience management landscape and the relevant challenges and opportunities. A case study on the “paper machine” companies is chosen. Hence, this paper analyzes the challenges and opportunities in customer experience management of paper machine companies for the case of “road to steel”. Road to steel shows the journey of steel from raw material to end product (i.e. paper machine in this paper). ALPHA (Steel company) and BETA (paper machine company), are chosen and their efforts to evolve the customer experiences are investigated. Semi-structured interviews are conducted with experts in those companies to identify the challenges and opportunities of the evolving customer experience management from their point of view. The findings of this paper contribute to the theory and business practices in the realm of the evolving customer experience management landscape.

Keywords: Customer experience management, paper machine risk analysis, value chain management.

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Authors: Jiewei Li, Hongyan Cui, Chunqi Chang, Yong Hu

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It was expected to benefit patient with hemiparesis after stroke by extensive arm rehabilitation, to partially regain forearm and hand function. This paper propose a robotic rehabilitation arm in assisting the hemiparetic patient to learn new ways of using and moving their weak arms. In this study, the robotic arm was driven by a somatosensory stimulated brain computer interface (BCI), which is a new modality BCI. The use of somatosensory stimulation is not only an input for BCI, but also a electrical stimulation for treatment of hemiparesis to strengthen the arm and improve its range of motion. A trial of this robotic rehabilitation arm was performed in a stroke patient with pure motor hemiparesis. The initial trial showed a promising result from the patient with great motivation and function improvement. It suggests that robotic rehabilitation arm driven by somatosensory BCI can enhance the rehabilitation performance and progress for hemiparetic patients after stroke.

Keywords: Robotic rehabilitation arm, brain computer interface (BCI), hemiparesis, stroke, somatosensory stimulation.

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Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

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There is a dramatic surge in the adoption of Machine Learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. Artificial Intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and two defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt ML techniques without rigorous testing, since they may be vulnerable to adversarial attacks, especially in security-critical areas such as the nuclear industry. We observed that while the adopted defence methods can effectively defend against different attacks, none of them could protect against all five adversarial attacks entirely.

Keywords: Resilient Machine Learning, attacks, defences, nuclear industry, crack detection.

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Authors: Kamarul Hawari Ghazali, Mohd. Marzuki Mustafa, Aini Hussain

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Machine vision is an application of computer vision to automate conventional work in industry, manufacturing or any other field. Nowadays, people in agriculture industry have embarked into research on implementation of engineering technology in their farming activities. One of the precision farming activities that involve machine vision system is automatic weeding strategy. Automatic weeding strategy in oil palm plantation could minimize the volume of herbicides that is sprayed to the fields. This paper discusses an automatic weeding strategy in oil palm plantation using machine vision system for the detection and differential spraying of weeds. The implementation of vision system involved the used of image processing technique to analyze weed images in order to recognized and distinguished its types. Image filtering technique has been used to process the images as well as a feature extraction method to classify the type of weed images. As a result, the image processing technique contributes a promising result of classification to be implemented in machine vision system for automated weeding strategy.

Keywords: Machine vision, Automatic Weeding Strategy, filter, feature extraction

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Authors: Helen P. Greatrex

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Many states are now committed to implementing international human rights standards domestically. In terms of practical governance, how might effectiveness be measured? A facevalue answer can be found in domestic laws and institutions relating to human rights. However, this article provides two further tools to help states assess their status on the spectrum of robust to fragile human rights governance. The first recognises that each state has its own 'human rights history' and the ideal end stage is robust human rights governance, and the second is developing criteria to assess robustness. Although a New Zealand case study is used to illustrate these tools, the widespread adoption of human rights standards by many states inevitably means that the issues are relevant to other countries. This is even though there will always be varying degrees of similarity-difference in constitutional background and developed or emerging human rights systems.

Keywords: robust human rights governance, fragile states.

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Authors: M. Bagheri, P. Mottaghizadeh

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Reliable information about tool temperature distribution is of central importance in metal cutting. In this study, tool-chip interface temperature was determined in cutting of ST37 steel workpiece by applying HSS as the cutting tool in dry turning. Two different approaches were implemented for temperature measuring: an embedded thermocouple (RTD) in to the cutting tool and infrared (IR) camera. Comparisons are made between experimental data and results of MSC.SuperForm and FLUENT software. An investigation of heat generation in cutting tool was performed by varying cutting parameters at the stable cutting tool geometry and results were saved in a computer; then the diagrams of tool temperature vs. various cutting parameters were obtained. The experimental results reveal that the main factors of the increasing cutting temperature are cutting speed (V ), feed rate ( S ) and depth of cut ( h ), respectively. It was also determined that simultaneously change in cutting speed and feed rate has the maximum effect on increasing cutting temperature.

Keywords: Cutting parameters, Finite element modeling, Temperature measurement, Tool-chip interface temperature.

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Authors: H. M. El-Zomor, M. Hany

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Recycling of aluminum beverage cans is an important issue due to its economic and environmental effect. One of the significant factors in aluminum cans recycling process is the transportation cost from the landfill space. An automatic compression baler (ACB) machine has been designed and built to densify the aluminum beverage cans. It has been constructed using numerous fabricated components. Two types of control methodology have been introduced in this ACB machine to achieve its goal. The first is a semi-automatic system, and the second is a mechatronic system by using a Programmable Logic Control (PLC). The effect of single and double pre-compression for the beverage cans have been evaluated by using the PLC control. Comparisons have been performed between the two types of control methodologies by operating this ACB machine in different working conditions. The double pre-compression in PLC control proves that there is an enhancement in the ACB performance by 133% greater than the direct compression in the semi-automatic control. In addition, the percentage of the reduction ratio in volume reaches 77%, and the compaction ratio reaches about four times of the initial volume.

Keywords: Aluminum can recycling, Fully automatic machine, Hydraulic system control, Multi-compression.

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Authors: Aldan A. Sapargaliyev, Yerbol A. Sapargaliyev

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Since the invention, the electric machine (EM) can be defined as oEM – one-vector electric machine, as it works due to one-vector inductive coupling with use of one-vector electromagnet. The disadvantages of oEM are large size and limited efficiency at low and medium power applications. This paper describes multi-vector electric machine (mEM) based on multi-vector inductive coupling, which is characterized by the increased surface area of ​​the inductive coupling per EM volume, with a reduced share of inefficient and energy-consuming part of the winding, in comparison with oEM’s. Particularly, it is considered, calculated and compared the performance of three different electrical motors and their power at the same volumes and rotor frequencies. It is also presented the result of calculation of correlation between power density and volume for oEM and mEM. The method of multi-vector inductive coupling enables mEM to possess 1.5-4.0 greater density of power per volume and significantly higher efficiency, in comparison with today’s oEM, especially in low and medium power applications. mEM has distinct advantages, when used in transport vehicles such as electric cars and aircrafts.

Keywords: Electric machine, electric motor, electromagnet, efficiency of electric motor.

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Authors: Jaakko Parviainen, Keijo Haataja, Antti Väänänen, Pekka Toivanen

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Tablet computers and Multifunctional Hardcopy Devices (MHDs) are common devices in daily life. Though, many scientific studies have not been published. The tablet computers are straightforward to use whereas the MHDs are comparatively difficult to use. Thus, to assist different levels of users, we propose combining these two devices to achieve straightforward intelligent user interface (UI) and versatile What You See Is What You Get (WYSIWYG) document management and production. Our approach to this issue is to design an intelligent user dependent UI for a MHD applying a tablet computer. Furthermore, we propose hardware interconnection and versatile intelligent software between these two devices. In this study, we first provide a state-of-the-art survey on MHDs and tablet computers, and their interconnections. Secondly we provide a comparative UI survey on two state-of-the-art MHDs with a proposal of a novel UI for the MHDs using Jakob Nielsen-s Ten Usability Heuristics Evaluation.

Keywords: Computational intelligence, hardcopy device, tablet computer, user interface.

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

Abstract:

Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: Machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation.

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Authors: Wai Phyo Aung

Abstract:

Wheeled Mobile Robots (WMRs) are built with their Wheels- drive machine, Motors. Depend on their desire design of WMR, Technicians made used of DC Motors for motion control. In this paper, the author would like to analyze how to choose DC motor to be balance with their applications of especially for WMR. Specification of DC Motor that can be used with desire WMR is to be determined by using MATLAB Simulink model. Therefore, this paper is mainly focus on software application of MATLAB and Control Technology. As the driving system of DC motor, a Peripheral Interface Controller (PIC) based control system is designed including the assembly software technology and H-bridge control circuit. This Driving system is used to drive two DC gear motors which are used to control the motion of WMR. In this analyzing process, the author mainly focus the drive system on driving two DC gear motors that will control with Differential Drive technique to the Wheeled Mobile Robot . For the design analysis of Motor Driving System, PIC16F84A is used and five inputs of sensors detected data are tested with five ON/OFF switches. The outputs of PIC are the commands to drive two DC gear motors, inputs of Hbridge circuit .In this paper, Control techniques of PIC microcontroller and H-bridge circuit, Mechanism assignments of WMR are combined and analyzed by mainly focusing with the “Modeling and Simulink of DC Motor using MATLAB".

Keywords: Control System Design, DC Motors, DifferentialDrive, H-bridge control circuit, MATLAB Simulink model, Peripheral Interface Controller (PIC), Wheeled Mobile Robots.

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Authors: Paul Y. Oh, Rares I. Stanciu

Abstract:

Cameras are often mounted on platforms that canmove like rovers, booms, gantries and aircraft. People operate suchplatforms to capture desired views of scene or target. To avoidcollisions with the environment and occlusions, such platforms oftenpossess redundant degrees-of-freedom. As a result, manipulatingsuch platforms demands much skill. Visual-servoing some degrees-of-freedom may reduce operator burden and improve tracking per-formance. This concept, which we call human-in-the-loop visual-servoing, is demonstrated in this paper and applies a Α-β-γ filter and feedforward controller to a broadcast camera boom.

Keywords: Computer vision, visual-servoing, man-machine sys-tems, human-in-the-loop control

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Authors: V. Musalimov, I. Stepanov, Y. Monahov, A. Safonov

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This report examines the current state of human gait simulator development based on the human hip joint model. This unit will create a database of human gait types, useful for setting up and calibrating Mechano devices, as well as the creation of new systems of rehabilitation, exoskeletons and walking robots. The system has many opportunities to configure the dimensions and stiffness, while maintaining relative simplicity.

Keywords: Hip joint, human gait, physiotherapy, simulation.

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: Bioassay, machine learning, preprocessing, virtual screen.

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Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

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The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the supportvectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: Discrete Wavelet Transform, Electroencephalogram, Pattern Recognition, Principal Component Analysis, Support Vector Machine.

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Authors: Philippe Fauquet-Alekhine

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For professions of high risk industries, simulation training has always been thought in terms of high degree of fidelity regarding the real operational situation. Due to the recent progress, this way of training is changing, modifying the human-computer and software interactions: the interactions between trainees during simulation training session tend to become virtual, transforming the social-based embodiness (the way subjects integrate social skills for interpersonal relationship with co-workers). On the basis of the analysis of eight different profession trainings, a categorization of interactions has help to produce an analytical tool, the social interactions table. This tool may be very valuable to point out the changes of social interactions when the training sessions are skipping from a high fidelity simulator to a virtual simulator. In this case, it helps the designers of professional training to analyze and to assess the consequences of the potential lack the social-based embodiness.

Keywords: Interface, interaction, simulator, virtual training.

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Authors: Venkatesh Bagaria, Nagesh AS, Varun AV

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In the domain of machine vision, the measurement of length is done using cameras where the accuracy is directly proportional to the resolution of the camera and inversely to the size of the object. Since most of the pixels are wasted imaging the entire body as opposed to just imaging the edges in a conventional system, a double aperture system is constructed to focus on the edges to measure at higher resolution. The paper discusses the complexities and how they are mitigated to realize a practical machine vision system.

Keywords: Machine Vision, double aperture camera, accurate length measurement

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Authors: M. Giannopoulou, I. Roukounis, A. Roukouni.

Abstract:

Geographical Information Systems are an integral part of planning in modern technical systems. Nowadays referred to as Spatial Decision Support Systems, as they allow synergy database management systems and models within a single user interface machine and they are important tools in spatial design for evaluating policies and programs at all levels of administration. This work refers to the creation of a Geographical Information System in the context of a broader research in the area of influence of an under construction station of the new metro in the Greek city of Thessaloniki, which included statistical and multivariate data analysis and diagrammatic representation, mapping and interpretation of the results.

Keywords: Databases, Geographical information systems (GIS), Land-use planning, Metro stations

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Authors: Ghada A. Alfattni

Abstract:

Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: Imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour.

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Authors: Shewit Tsegaye, Kinde A. Fante

Abstract:

This paper presents the comparison and performance evaluation of synchronous machine excitation models. The two models, DC1A and AC4A, are among the IEEE standardized model structures for representing the wide variety of synchronous machine excitation systems. The performance evaluation of these models is done using SIMULINK simulation software. The simulation results obtained using transient analysis show that the DC1A excitation system is more reliable and stable than AC4A excitation system.

Keywords: Excitation system, synchronous machines, AC and DC regulators.

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Authors: Zenaide Carvalho da Silva, Leandro Rodrigues Ferreira, Andrey Ricardo Pimentel

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Learning styles (LS) refer to the ways and forms that the student prefers to learn in the teaching and learning process. Each student has their own way of receiving and processing information throughout the learning process. Therefore, knowing their LS is important to better understand their individual learning preferences, and also, understand why the use of some teaching methods and techniques give better results with some students, while others it does not. We believe that knowledge of these styles enables the possibility of making propositions for teaching; thus, reorganizing teaching methods and techniques in order to allow learning that is adapted to the individual needs of the student. Adapting learning would be possible through the creation of online educational resources adapted to the style of the student. In this context, this article presents the structure of a learning object interface adaptation based on the LS. The structure created should enable the creation of the adapted learning object according to the student's LS and contributes to the increase of student’s motivation in the use of a learning object as an educational resource.

Keywords: Adaptation, interface, learning object, learning style.

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Authors: Chalakorn Chitsaart, Suchada Rianmora, Mann Rattana-Areeyagon, Wutichai Namjaiprasert

Abstract:

G-code is the main factor in computer numerical control (CNC) machine for controlling the toolpaths and generating the profile of the object’s features. For obtaining high surface accuracy of the surface finish, non-stop operation is required for CNC machine. Recently, to design a new product, the strategy that concerns about a change that has low impact on business and does not consume lot of resources has been introduced. Cost and time for designing minor changes can be reduced since the traditional geometric details of the existing models are applied. In order to support this strategy as the alternative channel for machining operation, this research proposes the automatic generating codes for CNC milling operation. Using this technique can assist the manufacturer to easily change the size and the geometric shape of the product during the operation where the time spent for setting up or processing the machine are reduced. The algorithm implemented on MATLAB platform is developed by analyzing and evaluating the geometric information of the part. Codes are created rapidly to control the operations of the machine. Comparing to the codes obtained from CAM, this developed algorithm can shortly generate and simulate the cutting profile of the part.

Keywords: Geometric shapes, Milling operation, Minor changes, CNC Machine, G-code, and Cutting parameters.

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Authors: K. M. Doraiswamy, Lakshminarayana Merugu, B. C. Jinaga

Abstract:

This paper explains the cause of nonlinearity in floor attenuation hither to left unexplained. The performance degradation occurring in air interface for GSM signals is quantitatively analysed using the concept of Radiating Columns of buildings. The signal levels were measured using Wireless Network Optimising Drive Test Tool (E6474A of Agilent Technologies). The measurements were taken in reflected signal environment under usual fading conditions on actual GSM signals radiated from base stations. A mathematical model is derived from the measurements to predict the GSM signal levels in different floors. It was applied on three buildings and found that the predicted signal levels deviated from the measured levels with in +/- 2 dB for all floors. It is more accurate than the prediction models based on Floor Attenuation Factor. It can be used for planning proper indoor coverage in multi storey buildings.

Keywords: GSM air interface, nonlinear attenuation, multistory building, radiating columns, ground conduction and floor attenuation factor.

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Authors: A. Hassannia, S. Ramezani

Abstract:

The technology of superconductivity has developed in many power system devices such as transmission cable, transformer, current limiter, motor and generator. Superconducting wires can carry high density current without loss, which is the capability that is used to design the compact, lightweight and more efficient electrical machines. Superconducting motors have found applications in marine and air propulsion systems as well as superconducting generators are considered in low power hydraulic and wind generators. This paper presents a rim-driven superconducting synchronous generator for hydraulic power plant. The rim-driven concept improves the performance of hydro turbine. Furthermore, high magnetic field that is produced by superconducting windings allows replacing the rotor core. As a consequent, the volume and weight of the machine is decreased significantly. In this paper, a 1 MW coreless rim-driven superconducting synchronous generator is designed. Main performance characteristics of the proposed machine are then evaluated using finite elements method and compared to an ordinary similar size synchronous generator.

Keywords: Coreless machine, electrical machine design, hydraulic generator, rim-driven machine, superconducting generator.

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Authors: D. Karimi, M.J. Nategh

Abstract:

One of the main concerns about parallel mechanisms is the presence of singular points within their workspaces. In singular positions the mechanism gains or loses one or several degrees of freedom. It is impossible to control the mechanism in singular positions. Therefore, these positions have to be avoided. This is a vital need especially in computer controlled machine tools designed and manufactured on the basis of parallel mechanisms. This need has to be taken into consideration when selecting design parameters. A prerequisite to this is a thorough knowledge about the effect of design parameters and constraints on singularity. In this paper, quality condition index was introduced as a criterion for evaluating singularities of different configurations of a hexapod mechanism obtainable by different design parameters. It was illustrated that this method can effectively be employed to obtain the optimum configuration of hexapod mechanism with the aim of avoiding singularity within the workspace. This method was then employed to design the hexapod table of a CNC milling machine.

Keywords: Hexapod, Machine Tool, Singularity, Workspace.

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: Deregulated energy market, forecasting, machine learning, system marginal price, energy efficiency and quality.

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