Search results for: learning strategies

Authors: Fabrizio Logiurato

Abstract:

Light Polarization has many technological applications, and its discovery was crucial to reveal the transverse nature of the electromagnetic waves. However, despite its fundamental and practical importance, in high school, this property of light is often neglected. This is a pity not only for its conceptual relevance, but also because polarization gives the possibility to perform many brilliant experiments with low cost materials. Moreover, the treatment of this matter lends very well to an interdisciplinary approach between art, biology and technology, which usually makes things more interesting to students. For these reasons, we have developed, and in this work, we introduce a laboratory on light polarization for high school and undergraduate students. They can see beautiful pictures when birefringent materials are set between two crossed polarizing filters. Pupils are very fascinated and drawn into by what they observe. The colourful images remind them of those ones of abstract painting or alien landscapes. With this multidisciplinary teaching method, students are more engaged and participative, and also, the learning process of the respective physics concepts is more effective.

Keywords: Light polarization, optical activity, multidisciplinary education, science and art.

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Authors: D. Hassell, D. De Focatiis

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This paper presents work on the application of wiki based coursework for a fourth-year engineering module delivered as part of both a MEng and MSc programme in Chemical Engineering. The module was taught with an equivalent structure simultaneously on two separate campuses, one in the United Kingdom (UK) and one in Malaysia, and the subsequent results were compared. Student feedback was sought via questionnaires, with 45 respondents from the UK and 49 from Malaysia. Results include discussion on; perceived difficulty; student enjoyment and experiences; differences between MEng and MSc students; differences between cohorts on different campuses. The response of students to the use of wiki-based coursework was found to vary based on their experiences and background, with UK students being generally more positive on its application than those in Malaysia.

Keywords: Engineering education, student differences, student learning, web-based coursework.

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Authors: Rhoann Kerh, Chen-Fu Chien, Kuo-Yi Lin

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In the era of rapidly increasing notebook market, consumer electronics manufacturers are facing a highly dynamic and competitive environment. In particular, the product appearance is the first part for user to distinguish the product from the product of other brands. Notebook product should differ in its appearance to engage users and contribute to the user experience (UX). The UX evaluates various product concepts to find the design for user needs; in addition, help the designer to further understand the product appearance preference of different market segment. However, few studies have been done for exploring the relationship between consumer background and the reaction of product appearance. This study aims to propose a data mining framework to capture the user’s information and the important relation between product appearance factors. The proposed framework consists of problem definition and structuring, data preparation, rules generation, and results evaluation and interpretation. An empirical study has been done in Taiwan that recruited 168 subjects from different background to experience the appearance performance of 11 different portable computers. The results assist the designers to develop product strategies based on the characteristics of consumers and the product concept that related to the UX, which help to launch the products to the right customers and increase the market shares. The results have shown the practical feasibility of the proposed framework.

Keywords: Consumers Decision Making, Product Design, Rough Set Theory, User Experience.

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Authors: Amin Zabihinejad, Philippe Viarouge

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In this paper, a direct power control (DPC) strategies have been investigated in order to control a high power AC/DC converter with time variable load. This converter is composed of a three level three phase neutral point clamped (NPC) converter as rectifier and an H-bridge four quadrant current control converter. In the high power application, controller not only must adjust the desire outputs but also decrease the level of distortions which are injected to the network from the converter. Regarding to this reason and nonlinearity of the power electronic converter, the conventional controllers cannot achieve appropriate responses. In this research, the precise mathematical analysis has been employed to design the appropriate controller in order to control the time variable load. A DPC controller has been proposed and simulated using Matlab/ Simulink. In order to verify the simulation result, a real time simulator- OPAL-RT- has been employed. In this paper, the dynamic response and stability of the high power NPC with variable load has been investigated and compared with conventional types using a real time simulator. The results proved that the DPC controller is more stable and has more precise outputs in comparison with conventional controller.

Keywords: Direct Power Control, Three Level Rectifier, Real Time Simulator, High Power Application.

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Authors: Aji P. Wibawa, Andrew Nafalski, Neil Murray, Wayan F. Mahmudy

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Parallel text alignment is proposed as a way of aligning bahasa Indonesia to words in Javanese. Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).

Keywords: Parallel text alignment, phrase pair combination, edit distance coefficient, Javanese-Indonesian language.

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Authors: Ugwu Elias Ikechukwu

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Discussions on bilingualism have always dwelt on how the mother tongue interferes with the target language. This interference is considered a serious problem in second language learning. Usually, the interference has been phonological. But the objective of this research is to explore how the target language interferes with the mother tongue. In the case of the Igbo language, it interferes with English mostly at the phonological level while English interferes with Igbo at the realm of vocabulary. The result is a new language \"Engligbo\" which is a hybrid of English and Igbo. The Igbo language spoken by about 25 million people is one of the three most prominent languages in Nigeria. This paper discusses the phenomenal Engligbo, and other implications for Igbo learners of English. The method of analysis is descriptive. A number of recommendations were made that would help teachers handle problems arising from such mutual interferences.

Keywords: Bilingualism, Implications, Language Pedagogy, Reciprocal Interferences.

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Authors: Matthew J. Zagumny

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The current study reports an examination of the QUEST-25 (Q-Assessment of Undergraduate Epistemology and Scientific Thinking) online version for assessing the dispositional attitudes toward scientific thinking and intellectual curiosity among undergraduate students. The QUEST-25 consists of scientific thinking (SIQ-25) and intellectual curiosity (ICIQ-25), which were correlated in hypothesized directions with the Religious Commitment Inventory, Curiosity and Exploration Inventory, Belief in Science scale, and measures of academic self-efficacy. Additionally, concurrent validity was established by the resulting significant differences between those identifying the centrality of religious belief in their lives and those who do not self-identify as being guided daily by religious beliefs. This study demonstrates the utility of the QUEST-25 for research, evaluation, and theory development.

Keywords: Guided-inquiry learning, intellectual curiosity, psychometric assessment, scientific thinking.

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Authors: Somsri Binraman, Boonliang Kaewnapan, Krittika Tanprasert

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In the package design industry, there are a lot of tacit knowledge resided within each designer. The objectives are to capture them and compile it to be used as a teaching resource and to create a video clip of package design process as well as to evaluate its quality and learning effectiveness. Interview were used as a technique for capturing knowledge in brand design concept, differentiation, recognition, rank of recognition factor, consumer survey, knowledge about marketing, research, graphic design, the effect of color, and law and regulation. Video clip about package design were created. The clip consisted of both the speech and clip of actual process. The quality of the video in term of media was ranked as good while the content was ranked as excellent. The students- score on post-test was significantly greater than that of pretest (p>0.001).

Keywords: Tacit knowledge, interview, video, packaging, design.

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Authors: Maria J. Garcia-Garcia, Concepcion Gonzalez-Garcia, Gabriel A. Dorado, Luis J. Fernandez

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The results obtained after incorporating the competence “creativity" to the subject Technical Drawing of the first course of the Degree in Forestry, Technical University of Madrid, are presented in this study.At first, learning activities which could serve two functions at the same time -developing students- creativity and developing other specific competences of the subject- were considered. Besides, changes in the assessment procedure were made and a method which analyzes two aspects of the assessment of the competence creativity was established. On the one hand, the products are evaluated by analyzing the outcomes obtained by students in the essays suggested and by establishing a parameter to assess the creativity expressed in those essays. On the other, an assessment of the student is directly carried out through a psychometric test which has been previously chosen by the team.Moreover, these results can be applied to similar or could be of general application.

Keywords: assessment competence, assessment creativity, creativity, generic competences

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Authors: Chee Peng Lim, Wei Yee Goh

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In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.

Keywords: AdaBoost, Elman network, neural network ensemble, time series regression.

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Authors: Mi Ok Kang

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This study examined the influences of including LGBTQ-related content in a multicultural teacher education course on the development of prospective teachers’ social justice identities. Appling a content analysis to 53 reflection texts written by participating prospective teachers in response to the relevant course content, this study deduced the stages of social justice identity development (naïve, acceptance, resistance, redefinition, and internalization) that participants reached during the course. The analysis demonstrated that the participants reached various stages in the social identity development model and none of the participants remained at the naïve stage during/after class. The majority (53%) of the participants reached the internalization stage during the coursework and became conscious about the heterosexual privileges they have had and aware of possible impacts of such privilege on their future LGBTQ students. Also the participants had begun to develop pedagogic action plans and devised applicable teaching strategies for their future students based on the new understanding of heteronormativity. We expect this study will benefit teacher educators and educational administrators who want to address LGBTQ-related issues in their multicultural education programs and/or revisit the goals, directions, and implications of their approach.

Keywords: LGBTQ, heteronormativity, social justice identity, teacher education, multicultural education, content analysis.

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: Academic environment model, decision trees, FSASEC, K-nearest neighbor, machine learning, popularity index, support vector machine.

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Authors: Umar Ubandawaki

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Political participation involves voluntary and deliberate efforts by the members of a political system to determine the kinds of political institution and individuals that will govern them and equally influence the mobilization and allocation of the available societal resources. Over the years, youths in Nigeria participate actively in political party rallies and voting to elect their leaders and representatives in governance. This paper examines categories and nature of participation in politics as well as factors that drive youths into politics in Sokoto State. A survey conducted, through focus group discussions, interviews and questionnaire, in the six sampled Local Government of Sokoto State identifies three category of political participation; namely, active, moderate and apathetic participation. The findings reveal that 63.57% of respondents are apathetic to politics in the State and unemployed youth constitutes 34.74% of the entire responses. The paper establishes that lack of attainment of need (63.22%) is one of the reasons that make youths engage into participatory activities that encourage political thuggery and manipulation of electoral outcomes. The paper recommends that youths should be engaged into positive rational participatory activities that ensure inclusiveness and promotion of good governance in Nigeria. It is hoped that this will enlighten youths and policy implementers on the constructive strategies in controlling youths’ negative participation in politics in Nigeria.

Keywords: Democracy, Governance, Inclusiveness, Participation and Politics.

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Authors: Stephen Kirkup

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This paper discusses the implementation of the boundary element method (BEM) on an Excel spreadsheet and how it can be used in teaching vector calculus and simulation. There are two separate spreadheets, within which Laplace equation is solved by the BEM in two dimensions (LIBEM2) and axisymmetric three dimensions (LBEMA). The main algorithms are implemented in the associated programming language within Excel, Visual Basic for Applications (VBA). The BEM only requires a boundary mesh and hence it is a relatively accessible method. The BEM in the open spreadsheet environment is demonstrated as being useful as an aid to teaching and learning. The application of the BEM implemented on a spreadsheet for educational purposes in introductory vector calculus and simulation is explored. The development of assignment work is discussed, and sample results from student work are given. The spreadsheets were found to be useful tools in developing the students’ understanding of vector calculus and in simulating heat conduction.

Keywords: Boundary element method, laplace equation, vector calculus, simulation, education.

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Authors: Natanya Meyer, Johann Landsberg

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Globally, many women are still disadvantaged when it comes to business opportunities. Entrepreneurship development programs, specifically designed to assist women entrepreneurs, are assisting in solving this problem to a certain extent. The purpose of this study is to identify the factors that motivate females to start their own business. Females, from three different groups (2013, 2014 and 2015), who were all enrolled in a short learning program specifically designed for women in early start-up stage or intending to start a business, were asked what motivated them to start a business. The results indicated that, from all three groups, the majority of the women wanted to start a business to be independent and have freedom and to add towards a social goal. The results further indicated that in general, women would enter into entrepreneurship activity due to pull factors rather than push factors.

Keywords: Entrepreneurship programs, South Africa, female entrepreneurship, motivational factors.

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: River stage-discharge process, LSSVM, discrete wavelet transform (DWT), ensemble empirical decomposition mode (EEMD), multi-station modeling.

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Authors: Benson Chizubem

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Because of the severe hazards that substantially impact workers' lives and assets lost, the oil and gas industry has established a goal of establishing zero occurrences or accidents in operations. Using leading indicators to measure and assess an organization's safety performance is a proactive approach to safety management. Also, it will provide early warning signals to solve inherent safety issues before they lead to an accident in the study industry. The analysis of these indicators' performance was based on a questionnaire-based methodology. A total number of 1000 questionnaires were disseminated to the workers, of which 327 were returned to the researcher team. The data collected were analysed to evaluate their safety perceptions on indicators performance. Data analysis identified safety training, safety system, safety supervision, safety rules and procedures, safety auditing, strategies and policies, management commitment, safety meeting and safety behaviour, as potential leading indicators that are capable of measuring organizational safety performance and as capable of providing early warning signals of weak safety area in an operational environment. The findings of this study have provided safety researchers and industrial safety practitioners with helpful information on the improvement of the existing safety monitoring process in the oil and gas industry, both locally and globally, as proactive actions.

Keywords: Early warning, safety, accident risks, oil and gas industry.

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled direct normal irradiance field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: Artificial Neural Networks, Resilient Propagation, Solar Radiation, Time Series Forecasting.

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: Edge network, embedded network, MMA, matrix multiplication accelerator and semantic segmentation network.

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feedforward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on selforganizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: Classification, SOFM, neural network, RGB images.

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Authors: Chingtham Tejbanta Singh, Shivashankar B. Nair

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This paper explores an application of an adaptive learning mechanism for robots based on the natural immune system. Most of the research carried out so far are based either on the innate or adaptive characteristics of the immune system, we present a combination of these to achieve behavior arbitration wherein a robot learns to detect vulnerable areas of a track and adapts to the required speed over such portions. The test bed comprises of two Lego robots deployed simultaneously on two predefined near concentric tracks with the outer robot capable of helping the inner one when it misaligns. The helper robot works in a damage-control mode by realigning itself to guide the other robot back onto its track. The panic-stricken robot records the conditions under which it was misaligned and learns to detect and adapt under similar conditions thereby making the overall system immune to such failures.

Keywords: Adaptive, AIS, Behavior Arbitration, ClonalSelection, Immune System, Innate, Robot, Self Healing.

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Authors: Klio Monokrousou, Maria Giannopoulou

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Urban areas, as they have been developed and operate today, are areas of accumulation of a significant amount of people and a large number of activities that generate desires and reasons for traveling. The territorial expansion of the cities as well as the need to preserve the importance of the central city areas lead to the continuous increase of transportation needs which in the limited urban space results in creating serious traffic and operational problems. The modern perception of urban planning is directed towards more holistic approaches and integrated policies that make it economically competitive, socially just and more environmentally friendly. Over the last 25 years, the goal of sustainable transport development has been central to the agenda of any plan or policy for the city. The modern planning of urban space takes into account the economic and social aspects of the city and the importance of the environment to sustainable urban development. In this context, the European Union promotes direct or indirect related interventions according to the cohesion and environmental policies; many countries even had the chance to actually test them. This paper explores the methods and processes that have been developed towards this direction and presents a review and systematic presentation of this work. The ultimate purpose of this research is to effectively use this review to create a decision making methodological framework which can be the basis of a useful operational tool for sustainable urban planning.

Keywords: Sustainable urban development, urban mobility, urban regeneration methods.

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Authors: Hui Fang Huang Su, Jia Borror

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This study compared two different interventions for math instruction among preschoolers with autism spectrum disorder (ASD). The first intervention, a combination of discrete trial teaching and Strategies for Teaching Based on Autism Research (STAR), was the regular math curriculum utilized at the preschool. The second activity-based, naturalistic intervention was Project Mind, also known as Math is Not Difficult. The curricular interventions were randomly assigned to four preschool classrooms with ASD students and implemented over three months for Project MIND. Measurements gained during the same three months for the STAR intervention were used. A quasi-experimental, pre-test/post-test design was selected to compare which intervention was the most effective in increasing mathematical knowledge and skills among preschoolers with ASD. Standardized pre and post-test instruments included the Bracken Basic Concept Scale-3 Receptive, the Applied Problems and Calculation subtests of the Woodcock-Johnson IV Tests of Achievement, and the TEMA 3: Test of Early Mathematics Ability – Third Edition. The STAR assessment is typically administered to all preschoolers at the study site three times per year, and those results were used in this study. We anticipated that the implementation of these two approaches would lead to improvement in the mathematical knowledge and skills of children with ASD. Still, it is essential to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: Autism, mathematics, preschool, special education.

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Authors: Y. Harold Robinson, M. Rajaram, Honey Raju

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Image segmentation and color identification is an important process used in various emerging fields like intelligent robotics. A method is proposed for the manipulator to grasp and place the color object into correct location. The existing methods such as PSO, has problems like accelerating the convergence speed and converging to a local minimum leading to sub optimal performance. To improve the performance, we are using watershed algorithm and for color identification, we are using EPSO. EPSO method is used to reduce the probability of being stuck in the local minimum. The proposed method offers the particles a more powerful global exploration capability. EPSO methods can determine the particles stuck in the local minimum and can also enhance learning speed as the particle movement will be faster.

Keywords: Color information, EPSO, hue, saturation, value (HSV), image segmentation, particle swarm optimization (PSO). Active Contour, GMM.

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Authors: Ahmed Amin Mousa, Gehan Azam

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The current study presents an electronic test to measure teaching skills. This test is a part of the admission system of the Faculty of Education for Early Childhood, Cairo University. The test has been prepared to evaluate university students who apply for admission the Faculty. It measures some social and physiological skills which are important for successful teachers, such as emotional adjustment and problem solving; moreover, the extent of their love for children and their capability to interact with them. The test has been approved by 13 experts. Finally, it has been introduced to 1,100 students during the admission system of the academic year 2016/2017. The results showed that most of the applicants have an auditory learning style. In addition, 97% of them have the minimum requirement skills for teaching children.

Keywords: Electronic test, early childhood, skills, teacher student.

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

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Authors: María Teresa García-Álvarez, Isabel Soares, Rosa María Mariz-Pérez

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Directive 2009/28/CE establishes, as obligatory objective, a share of renewable energies on energetic consumption of 20%, in European Union, in 2020 However, such European normative gives freedom to member states in the selection of the renewable promotion mechanism that allows them to obtain that objective. In this paper, we analyze the main characteristics of the promotion mechanisms of renewable energy used in the countries that shape the Electricity Iberian Market (Spain and Portugal) and the results in employment. The importance of these countries is given by the great increasing of the renewable energies which suppose a share higher than 30% of the overall generation in 2010. Therefore, this research paper can serve as the basis for the learning of other countries with regard to the main advantages that entail the use of a feed-in tariff system.

Keywords: Employment, Energy policy, Professional profiles, Renewable energies, Professional profiles.

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Authors: Sidhartha Panda, N. P. Padhy

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Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.

Keywords: Thyristor Controlled Series Compensator, geneticalgorithm; particle swarm optimization; Phillips-Heffron model;power system stability.

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Authors: Ali Nouri

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Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.

Keywords: Neuroeducation studies, neuroeducational theory, theory building, neuroeducation research.

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Authors: Shankar Kambhampaty, Harish Rohan Kambhampaty

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Data in IT systems in enterprises have been growing at phenomenal pace. This has provided opportunities to run analytics to gather intelligence on key business parameters that enable them to provide better products and services to customers. While there are several Artificial Intelligence/Machine Learning (AI/ML) and Business Intelligence (BI) tools and technologies available in marketplace to run analytics, there is a need for an integrated view when developing intelligent solutions in enterprises. This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information and intelligence components and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.

Keywords: Architecture, model, intelligence, artificial intelligence, business intelligence, AI, BI, ML, analytics, enterprise.

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