Search results for: computer games for learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3281

Search results for: computer games for learning

1331 Pattern Recognition of Biological Signals

Authors: Paulo S. Caparelli, Eduardo Costa, Alexsandro S. Soares, Hipolito Barbosa

Abstract:

This paper presents an evolutionary method for designing electronic circuits and numerical methods associated with monitoring systems. The instruments described here have been used in studies of weather and climate changes due to global warming, and also in medical patient supervision. Genetic Programming systems have been used both for designing circuits and sensors, and also for determining sensor parameters. The authors advance the thesis that the software side of such a system should be written in computer languages with a strong mathematical and logic background in order to prevent software obsolescence, and achieve program correctness.

Keywords: Pattern recognition, evolutionary computation, biological signal, functional programming.

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1330 Integrating Blogging into Peer Assessment on College Students’ English Writing

Authors: Su-Lien Liao

Abstract:

Most of college students in Taiwan do not have sufficient English proficiency to express themselves in written English. Teachers spent a lot of time correcting the errors in students’ English writing, but the results are not satisfactory. This study aims to use blogs as a teaching and learning tool in written English. Before applying peer assessment, students should be trained to be good reviewers.  The teacher starts the course by posting the error analysis of students’ first English composition on blogs as the comment models for students. Then the students will go through the process of drafting, composing, peer response and last revision on blogs. Evaluation questionnaires and interviews will be conducted at the end of the course to see the impact and also students’ perception for the course.

Keywords: Blog, Peer assessment, English writing, Error analysis.

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1329 A Classification Scheme for Game Input and Output

Authors: P. Prema, B. Ramadoss

Abstract:

Computer game industry has experienced exponential growth in recent years. A game is a recreational activity involving one or more players. Game input is information such as data, commands, etc., which is passed to the game system at run time from an external source. Conversely, game outputs are information which are generated by the game system and passed to an external target, but which is not used internally by the game. This paper identifies a new classification scheme for game input and output, which is based on player-s input and output. Using this, relationship table for game input classifier and output classifier is developed.

Keywords: Game Classification, Game Input, Game Output, Game Testing.

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1328 A Review on Image Segmentation Techniques and Performance Measures

Authors: David Libouga Li Gwet, Marius Otesteanu, Ideal Oscar Libouga, Laurent Bitjoka, Gheorghe D. Popa

Abstract:

Image segmentation is a method to extract regions of interest from an image. It remains a fundamental problem in computer vision. The increasing diversity and the complexity of segmentation algorithms have led us firstly, to make a review and classify segmentation techniques, secondly to identify the most used measures of segmentation performance and thirdly, discuss deeply on segmentation philosophy in order to help the choice of adequate segmentation techniques for some applications. To justify the relevance of our analysis, recent algorithms of segmentation are presented through the proposed classification.

Keywords: Classification, image segmentation, measures of performance.

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1327 Categorical Missing Data Imputation Using Fuzzy Neural Networks with Numerical and Categorical Inputs

Authors: Pilar Rey-del-Castillo, Jesús Cardeñosa

Abstract:

There are many situations where input feature vectors are incomplete and methods to tackle the problem have been studied for a long time. A commonly used procedure is to replace each missing value with an imputation. This paper presents a method to perform categorical missing data imputation from numerical and categorical variables. The imputations are based on Simpson-s fuzzy min-max neural networks where the input variables for learning and classification are just numerical. The proposed method extends the input to categorical variables by introducing new fuzzy sets, a new operation and a new architecture. The procedure is tested and compared with others using opinion poll data.

Keywords: Classifier, imputation techniques, fuzzy systems, fuzzy min-max neural networks.

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1326 Promoting Innovation Pedagogy in a Capacity Building Project in Indonesia

Authors: Juha Kettunen

Abstract:

This study presents a project that tests and adjusts active European learning and teaching methods in Indonesian universities to increase their external impact on enterprises and other organizations; it also assesses the implementation of the Erasmus+ projects funded by the European Union. The project is based on the approach of innovation pedagogy that responds to regional development needs and integrates applied research and development projects into education to create capabilities for students to participate in development work after graduation. The assessment of the Erasmus+ project resulted in many improvements that can be made to achieve higher quality and innovativeness. The results of this study are useful for those who want to improve the applied research and development projects of higher education institutions.

Keywords: Higher education, innovations, project management, networks.

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1325 Using Data Mining Techniques for Estimating Minimum, Maximum and Average Daily Temperature Values

Authors: S. Kotsiantis, A. Kostoulas, S. Lykoudis, A. Argiriou, K. Menagias

Abstract:

Estimates of temperature values at a specific time of day, from daytime and daily profiles, are needed for a number of environmental, ecological, agricultural and technical applications, ranging from natural hazards assessments, crop growth forecasting to design of solar energy systems. The scope of this research is to investigate the efficiency of data mining techniques in estimating minimum, maximum and mean temperature values. For this reason, a number of experiments have been conducted with well-known regression algorithms using temperature data from the city of Patras in Greece. The performance of these algorithms has been evaluated using standard statistical indicators, such as Correlation Coefficient, Root Mean Squared Error, etc.

Keywords: regression algorithms, supervised machine learning.

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1324 Swarm Navigation in a Complex Environment

Authors: Jai Raj, Jito Vanualailai, Bibhya Sharma, Shonal Singh

Abstract:

This paper proposes a solution to the motion planning and control problem of car-like mobile robots which is required to move safely to a designated target in a priori known workspace cluttered with swarm of boids exhibiting collective emergent behaviors. A generalized algorithm for target convergence and swarm avoidance is proposed that will work for any number of swarms. The control laws proposed in this paper also ensures practical stability of the system. The effectiveness of the proposed control laws are demonstrated via computer simulations of an emergent behavior.

Keywords: Swarm, practical stability, motion planning, emergent.

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1323 A Multi Cordic Architecture on FPGA Platform

Authors: Ahmed Madian, Muaz Aljarhi

Abstract:

Coordinate Rotation Digital Computer (CORDIC) is a unique digital computing unit intended for the computation of mathematical operations and functions. This paper presents A multi CORDIC processor that integrates different CORDIC architectures on a single FPGA chip and allows the user to select the CORDIC architecture to proceed with based on what he wants to calculate and his needs. Synthesis show that radix 2 CORDIC has the lowest clock delay, radix 8 CORDIC has the highest LUT usage and lowest register usage while Hybrid Radix 4 CORDIC had the highest clock delay.

Keywords: Multi, CORDIC, FPGA, Processor.

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1322 Designing AI-Enabled Smart Maintenance Scheduler: Enhancing Object Reliability through Automated Management

Authors: Arun Prasad Jaganathan

Abstract:

In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling.

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1321 Educational Values of Virtual Reality: The Case of Spatial Ability

Authors: Elinda Ai-Lim Lee, Kok Wai Wong, Chun Che Fung

Abstract:

The use of Virtual Reality (VR) in schools and higher education is proliferating. Due to its interactive and animated features, it is regarded as a promising technology to increase students- spatial ability. Spatial ability is assumed to have a prominent role in science and engineering domains. However, research concerning individual differences such as spatial ability in the context of VR is still at its infancy. Moreover, empirical studies that focus on the features of VR to improve spatial ability are to date rare. Thus, this paper explores the possible educational values of VR in relation to spatial ability to call for more research concerning spatial ability in the context of VR based on studies in computerbased learning. It is believed that the incorporation of state-of-the-art VR technology for educational purposes should be justified by the enhanced benefits for the target learners.

Keywords: Ability-as-compensator, ability-as-enhancer, spatialability, virtual reality.

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1320 Sequential Partitioning Brainbow Image Segmentation Using Bayesian

Authors: Yayun Hsu, Henry Horng-Shing Lu

Abstract:

This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate crosstalk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds, since biological information is inherently included inside the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: Brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning.

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1319 Learning and Teaching in the Panopticon:Ethical and Social Issues in Creating a Virtual Educational Environment

Authors: K. Sheehy, R. Ferguson, G. Clough

Abstract:

This paper examines ethical and social issues which have proved important when initiating and creating educational spaces within a virtual environment. It focuses on one project, identifying the key decisions made, the barriers to new practice encountered and the impact these had on the project. It demonstrates the importance of the 'backstage' ethical and social issues involved in the creation of a virtual education community and offers conclusions, and questions, which will inform future research and practice in this area. These ethical issues are considered using Knobel-s framework of front-end, in-process and back-end concerns, and include establishing social practices for the islands, allocating access rights, considering personal safety and supporting researchers appropriately within this context.

Keywords: distance education, ethics, virtual environments.

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1318 Simulating a Single-Server Queue using the Q – Simulator

Authors: Irene K. Amponsah, Bennony K. Gordor, Francis Dogbey

Abstract:

This paper introduces a technique for simulating a single-server exponential queuing system. The technique called the Q-Simulator is a computer program which can simulate the effect of traffic intensity on all system average quantities given the arrival and/or service rates. The Q-Simulator has three phases namely: the formula based method, the uncontrolled simulation, and the controlled simulation. The Q-Simulator generates graphs (crystal solutions) for all results of the simulation or calculation and can be used to estimate desirable average quantities such as waiting times, queue lengths, etc.

Keywords: Automation system-Simulator, Simulation, Singleserver exponential system

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1317 On Bounds For The Zeros of Univariate Polynomial

Authors: Matthias Dehmer1 Jürgen Kilian

Abstract:

Problems on algebraical polynomials appear in many fields of mathematics and computer science. Especially the task of determining the roots of polynomials has been frequently investigated.Nonetheless, the task of locating the zeros of complex polynomials is still challenging. In this paper we deal with the location of zeros of univariate complex polynomials. We prove some novel upper bounds for the moduli of the zeros of complex polynomials. That means, we provide disks in the complex plane where all zeros of a complex polynomial are situated. Such bounds are extremely useful for obtaining a priori assertations regarding the location of zeros of polynomials. Based on the proven bounds and a test set of polynomials, we present an experimental study to examine which bound is optimal.

Keywords: complex polynomials, zeros, inequalities

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1316 E-Appointment Scheduling (EAS)

Authors: Noraziah Ahmad, Roslina Mohd Sidek, Mohd Affendy Omardin

Abstract:

E-Appointment Scheduling (EAS) has been developed to handle appointment for UMP students, lecturers in Faculty of Computer Systems & Software Engineering (FCSSE) and Student Medical Center. The schedules are based on the timetable and university activities. Constraints Logic Programming (CLP) has been implemented to solve the scheduling problems by giving recommendation to the users in part of determining any available slots from the lecturers and doctors- timetable. By using this system, we can avoid wasting time and cost because this application will set an appointment by auto-generated. In addition, this system can be an alternative to the lecturers and doctors to make decisions whether to approve or reject the appointments.

Keywords: EAS, Constraint Logic Programming, PHP, Apache.

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1315 Gender Differences of Elementary Prospective Teachers in Mathematical Beliefs and Mathematics Teaching Anxiety

Authors: Ersen Yazıcı, Erhan Ertekin

Abstract:

In this study, any possible differences between mathematics beliefs and anxiety of prospective elementary mathematics teachers have been investigated according to their gender. In this purpose, 1st, 2nd, 3rd and 4th grade students from a Government University in Turkey were selected as a sample. Mathematics Teaching Anxiety Scale (MATAS) and Beliefs About Mathematics Survey (BAMS) has been used as data collection tools. As a result of the study, it has been observed that prospective male teachers have more instrumentalist approach in learning mathematics than females according to their mathematical beliefs. On the other hand, females have more mathematics teaching anxiety than males especially, for subject knowledge in mathematics and selfconfidence.

Keywords: Mathematical beliefs, mathematics teaching anxiety, gender, prospective elementary mathematics teachers.

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1314 Development of a Simulator for Explaining Organic Chemical Reactions Based on Qualitative Process Theory

Authors: Alicia Y. C. Tang, Rukaini Hj. Abdullah, Sharifuddin M. Zain

Abstract:

This paper discusses the development of a qualitative simulator (abbreviated QRiOM) for predicting the behaviour of organic chemical reactions. The simulation technique is based on the qualitative process theory (QPT) ontology. The modelling constructs of QPT embody notions of causality which can be used to explain the behaviour of a chemical system. The major theme of this work is that, in a qualitative simulation environment, students are able to articulate his/her knowledge through the inspection of explanations generated by software. The implementation languages are Java and Prolog. The software produces explanation in various forms that stresses on the causal theories in the chemical system which can be effectively used to support learning.

Keywords: Chemical reactions, explanation, qualitative processtheory, simulation

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1313 Practical Problems as Tools for the Development of Secondary School Students’ Motivation to Learn Mathematics

Authors: M. Rodionov, Z. Dedovets

Abstract:

This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: Mathematics, motivation, secondary school, student, practical problem.

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1312 Some Separations in Covering Approximation Spaces

Authors: Xun Ge, Jinjin Li, Ying Ge

Abstract:

Adopting Zakowski-s upper approximation operator C and lower approximation operator C, this paper investigates granularity-wise separations in covering approximation spaces. Some characterizations of granularity-wise separations are obtained by means of Pawlak rough sets and some relations among granularitywise separations are established, which makes it possible to research covering approximation spaces by logical methods and mathematical methods in computer science. Results of this paper give further applications of Pawlak rough set theory in pattern recognition and artificial intelligence.

Keywords: Rough set, covering approximation space, granularitywise separation.

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1311 On Constructing Approximate Convex Hull

Authors: M. Zahid Hossain, M. Ashraful Amin

Abstract:

The algorithms of convex hull have been extensively studied in literature, principally because of their wide range of applications in different areas. This article presents an efficient algorithm to construct approximate convex hull from a set of n points in the plane in O(n + k) time, where k is the approximation error control parameter. The proposed algorithm is suitable for applications preferred to reduce the computation time in exchange of accuracy level such as animation and interaction in computer graphics where rapid and real-time graphics rendering is indispensable.

Keywords: Convex hull, Approximation algorithm, Computational geometry, Linear time.

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1310 Alive Cemeteries with Augmented Reality and Semantic Web Technologies

Authors: TamásMatuszka, Attila Kiss

Abstract:

Due the proliferation of smartphones in everyday use, several different outdoor navigation systems have become available. Since these smartphones are able to connect to the Internet, the users can obtain location-based information during the navigation as well. The users could interactively get to know the specifics of a particular area (for instance, ancient cultural area, Statue Park, cemetery) with the help of thus obtained information. In this paper, we present an Augmented Reality system which uses Semantic Web technologies and is based on the interaction between the user and the smartphone. The system allows navigating through a specific area and provides information and details about the sight an interactive manner.

Keywords: Augmented Reality, Semantic Web, Human Computer Interaction, Mobile Application.

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1309 Finding Sparse Features in Face Detection Using Genetic Algorithms

Authors: H. Sagha, S. Kasaei, E. Enayati, M. Dehghani

Abstract:

Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and its recent analogous is Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and gets more effective features in learning process for face detection that causes more accuracy.

Keywords: Face Detection, Genetic Algorithms, Sparse Feature.

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1308 Identification of MIMO Systems Using Neuro-Fuzzy Models with a Shuffled Frog Leaping Algorithm

Authors: Sana Bouzaida, Anis Sakly, Faouzi M'Sahli

Abstract:

In this paper, a TSK-type Neuro-fuzzy Inference System that combines the features of fuzzy sets and neural networks has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA).

Keywords: Identification, Shuffled frog Leaping Algorithm (SFLA), TSK-type neuro-fuzzy model.

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1307 Exploring Performance-Based Music Attributes for Stylometric Analysis

Authors: Abdellghani Bellaachia, Edward Jimenez

Abstract:

Music Information Retrieval (MIR) and modern data mining techniques are applied to identify style markers in midi music for stylometric analysis and author attribution. Over 100 attributes are extracted from a library of 2830 songs then mined using supervised learning data mining techniques. Two attributes are identified that provide high informational gain. These attributes are then used as style markers to predict authorship. Using these style markers the authors are able to correctly distinguish songs written by the Beatles from those that were not with a precision and accuracy of over 98 per cent. The identification of these style markers as well as the architecture for this research provides a foundation for future research in musical stylometry.

Keywords: Music Information Retrieval, Music Data Mining, Stylometry.

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1306 Detecting Tomato Flowers in Greenhouses Using Computer Vision

Authors: Dor Oppenheim, Yael Edan, Guy Shani

Abstract:

This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: Agricultural engineering, computer vision, image processing, flower detection.

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1305 Evaluation of Ultrasonic C-Scan Images by Fractal Dimension

Authors: S. Samanta, D. Datta, S. S. Gautam

Abstract:

In this paper, quantitative evaluation of ultrasonic Cscan images through estimation of their Fractal Dimension (FD) is discussed. Necessary algorithm for evaluation of FD of any 2-D digitized image is implemented by developing a computer code. For the evaluation purpose several C-scan images of the Kevlar composite impacted by high speed bullet and glass fibre composite having flaw in the form of inclusion is used. This analysis automatically differentiates a C-scan image showing distinct damage zone, from an image that contains no such damage.

Keywords: C-scan, Impact, Fractal Dimension, Kevlar composite and Inclusion Flaw

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1304 Fuzzy Voting in Internal Elections of Educational and Party Organizations

Authors: R. Hosseingholizadeh

Abstract:

This article presents a method for elections between the members of a group that is founded by fuzzy logic. Linguistic variables are objects for decision on election cards and deduction is based on t-norms and s-norms. In this election-s method election cards are questionnaire. The questionnaires are comprised of some questions with some choices. The choices are words from natural language. Presented method is accompanied by center of gravity (COG) defuzzification added up to a computer program by MATLAB. Finally the method is illustrated by solving two examples; choose a head for a research group-s members and a representative for students.

Keywords: fuzzy election, fuzzy electoral card, fuzzy inference, questionnaire.

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1303 Reconfigurable Autonomous Mini Robot Design using CPLD's

Authors: Aditya K, Dinesh P, Ramesh Bhakthavatchalu

Abstract:

This paper explains a project based learning method where autonomous mini-robots are developed for research, education and entertainment purposes. In case of remote systems wireless sensors are developed in critical areas, which would collect data at specific time intervals, send the data to the central wireless node based on certain preferred information would make decisions to turn on or off a switch or control unit. Such information transfers hardly sums up to a few bytes and hence low data rates would suffice for such implementations. As a robot is a multidisciplinary platform, the interfacing issues involved are discussed in this paper. The paper is mainly focused on power supply, grounding and decoupling issues.

Keywords: CPLD, power supply, decoupling, grounding.

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1302 Emotional, Behavioural and Social Development: Modality of Hierarchy of Needs in Supporting Parents with Special Needs

Authors: Fadzilah Abdul Rahman

Abstract:

Emotional development is developed between the parents and their child. Behavioural development is also developed between the parents and their child. Social Development is how parents can help their special needs child to adapt to society and to face challenges. In promoting a lifelong learning mindset, enhancing skill sets and readiness to face challenges, parents would be able to counter balance these challenges during their care giving process and better manage their expectations through understanding the hierarchy of needs modality towards a positive attitude, and in turn, improve their quality of life and participation in society. This paper aims to demonstrate how the hierarchy of needs can be applied in various situations of caregiving for parents with a special needs child.

Keywords: Hierarchy of needs, parents, special needs, care-giving.

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