Search results for: Structural Learning.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3207

Search results for: Structural Learning.

2337 Machine Learning Methods for Environmental Monitoring and Flood Protection

Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer

Abstract:

More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.

Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.

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2336 Improving Similarity Search Using Clustered Data

Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

Abstract:

This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: Visual search, deep learning, convolutional neural network, machine learning.

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2335 Learning Programming for Hearing Impaired Students via an Avatar

Authors: Nihal Esam Abuzinadah, Areej Abbas Malibari, Arwa Abdulaziz Allinjawi, Paul Krause

Abstract:

Deaf and hearing-impaired students face many obstacles throughout their education, especially with learning applied sciences such as computer programming. In addition, there is no clear signs in the Arabic Sign Language that can be used to identify programming logic terminologies such as while, for, case, switch etc. However, hearing disabilities should not be a barrier for studying purpose nowadays, especially with the rapid growth in educational technology. In this paper, we develop an Avatar based system to teach computer programming to deaf and hearing-impaired students using Arabic Signed language with new signs vocabulary that is been developed for computer programming education. The system is tested on a number of high school students and results showed the importance of visualization in increasing the comprehension or understanding of concepts for deaf students through the avatar.

Keywords: Hearing-impaired students, isolation, self-esteem, learning difficulties.

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2334 Robust Integrated Design for a Mechatronic Feed Drive System of Machine Tools

Authors: Chin-Yin Chen, Chi-Cheng Cheng

Abstract:

This paper aims at to develop a robust optimization methodology for the mechatronic modules of machine tools by considering all important characteristics from all structural and control domains in one single process. The relationship between these two domains is strongly coupled. In order to reduce the disturbance caused by parameters in either one, the mechanical and controller design domains need to be integrated. Therefore, the concurrent integrated design method Design For Control (DFC), will be employed in this paper. In this connect, it is not only applied to achieve minimal power consumption but also enhance structural performance and system response at same time. To investigate the method for integrated optimization, a mechatronic feed drive system of the machine tools is used as a design platform. Pro/Engineer and AnSys are first used to build the 3D model to analyze and design structure parameters such as elastic deformation, nature frequency and component size, based on their effects and sensitivities to the structure. In addition, the robust controller,based on Quantitative Feedback Theory (QFT), will be applied to determine proper control parameters for the controller. Therefore, overall physical properties of the machine tool will be obtained in the initial stage. Finally, the technology of design for control will be carried out to modify the structural and control parameters to achieve overall system performance. Hence, the corresponding productivity is expected to be greatly improved.

Keywords: Machine tools, integrated structure and control design, design for control, multilevel decomposition, quantitative feedback theory.

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2333 Iron Doped Biomaterial Calcium Borate: Synthesis and Characterization

Authors: G. Çelik Gül, F. Kurtuluş

Abstract:

Colemanite is the most common borate mineral, and the main source of the boron required by plants, human, and earth. Transition metals exhibit optical and physical properties such as; non-linear optical character, structural diversity, thermal stability, long cycle life and luminescent radiation. The doping of colemanite with a transition metal, bring it very interesting and attractive properties which make them applicable in industry. Iron doped calcium borate was synthesized by conventional solid state method at 1200 °C for 12 h with a systematic pathway. X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy/energy dispersive analyze (SEM/EDS) were used to characterize structural and morphological properties. Also, thermal properties were recorded by thermogravimetric-differential thermal analysis (TG/DTA). 

Keywords: Colemanite, conventional synthesis, powder x-ray diffraction, borates.

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2332 Model Canvas and Process for Educational Game Design in Outcome-Based Education

Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

Abstract:

This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: Constructive alignment, constructivist theory, educational game, outcome-based education.

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2331 Flexural Strength of Alkali Resistant Glass Textile Reinforced Concrete Beam with Prestressing

Authors: Jongho Park, Taekyun Kim, Jungbhin You, Sungnam Hong, Sun-Kyu Park

Abstract:

Due to the aging of bridges, increasing of maintenance costs and decreasing of structural safety is occurred. The steel corrosion of reinforced concrete bridge is the most common problem and this phenomenon is accelerating due to abnormal weather and increasing CO2 concentration due to climate change. To solve these problems, composite members using textile have been studied. A textile reinforced concrete can reduce carbon emissions by reduced concrete and without steel bars, so a lot of structural behavior studies are needed. Therefore, in this study, textile reinforced concrete beam was made and flexural test was performed. Also, the change of flexural strength according to the prestressing was conducted. As a result, flexural strength of TRC with prestressing was increased compared and flexural behavior was shown as reinforced concrete.

Keywords: AR-glass, flexural strength, prestressing, textile reinforced concrete.

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2330 Applications of Prediction and Identification Using Adaptive DCMAC Neural Networks

Authors: Yu-Lin Liao, Ya-Fu Peng

Abstract:

An adaptive dynamic cerebellar model articulation controller (DCMAC) neural network used for solving the prediction and identification problem is proposed in this paper. The proposed DCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) neural network in efficient learning mechanism, guaranteed system stability and dynamic response. The recurrent network is embedded in the DCMAC by adding feedback connections in the association memory space so that the DCMAC captures the dynamic response, where the feedback units act as memory elements. The dynamic gradient descent method is adopted to adjust DCMAC parameters on-line. Moreover, the analytical method based on a Lyapunov function is proposed to determine the learning-rates of DCMAC so that the variable optimal learning-rates are derived to achieve most rapid convergence of identifying error. Finally, the adaptive DCMAC is applied in two computer simulations. Simulation results show that accurate identifying response and superior dynamic performance can be obtained because of the powerful on-line learning capability of the proposed DCMAC.

Keywords: adaptive, cerebellar model articulation controller, CMAC, prediction, identification

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2329 Machine Learning for Aiding Meningitis Diagnosis in Pediatric Patients

Authors: Karina Zaccari, Ernesto Cordeiro Marujo

Abstract:

This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.

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2328 Influence of Thermal Annealing on The Structural Properties of Vanadyl Phthalocyanine Thin Films: A Comparative Study

Authors: Fakhra Aziz, K. Sulaiman, M. R. Muhammad, M. Hassan Sayyad, Kh. Karimov

Abstract:

This paper presents a comparative study on Vanadyl Phthalocyanine (VOPc) thin films deposited by thermal evaporation and spin coating techniques. The samples were prepared on cleaned glass substrates and annealed at various temperatures ranging form 95oC to 155oC. To obtain the morphological and structural properties of VOPc thin films, X-ray diffraction (XRD) technique and atomic force microscopy (AFM) have been implied. The AFM topographic images show a very slight difference in the thermally grown films, before and after annealing, however best results are achieved for the spin-cast film annealed at 125oC. The XRD spectra show no existence of the sharp peaks, suggesting the material to be amorphous. The humps in the XRD patterns indicate the presence of some crystallites.

Keywords: Annealing, optical properties, thin films, Vanadylphthalocyanine.

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2327 Integration of Big Data to Predict Transportation for Smart Cities

Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: Big data, bus headway prediction, machine learning, public transportation.

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2326 Architectural and Structural Analysis of Selected Tall Buildings in Warsaw, Poland

Authors: J. Szolomicki, H. Golasz-Szolomicka

Abstract:

This paper presents elements of architectural and structural analysis of selected high-rise buildings in the Polish capital city of Warsaw. When analyzing the architecture of Warsaw, it can be concluded that it is currently a rapidly growing city with technologically advanced skyscrapers that belong to the category of intelligent buildings. The constructional boom over the last dozen years has seen the erection of postmodern skyscrapers for office and residential use. This article focuses on how Warsaw has recently joined the most architecturally interesting cities in Europe. Warsaw is currently in fifth place in Europe in terms of the number of skyscrapers and is considered the second most preferred city in Europe (after London) for investment related to them. However, the architectural development of the city could not take place without the participation of eminent Polish and foreign architects such as Stefan Kuryłowicz, Lary Oltmans, Helmut Jahn or Daniel Libeskind.

Keywords: Core structure, raft foundation, tall buildings.

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2325 The Importance of Bridge Health Monitoring

Authors: Punya Chupanit, Chayatan Phromsorn

Abstract:

In the past, there were many bridge-s collapses due to lack of bridge structural capacity information. Most of concrete bridge health was relied on information from visual inspection, which sometime was inadequate. This study was conducted in order to investigate relationship between bridge structural condition and bridge visual condition. This study was a part of a big project conducted at Department of Highways of Thailand. In this study, 31 bridges including slab-type bridges, plank-girder bridges, prestressed box-beam bridges, prestressed I-girder bridges and prestressed multibeam bridges were selected for visual inspection and load test. It was found a positive correlation between bridge appearance and bridge-s load carrying capacity. However, statistical characteristic revealed low correlation between them.

Keywords: Bridge, Visual Inspection, Load Test, Condition Rating, Rating Factor

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2324 Family Bonding and Self-Concept: An Indirect Effect Mediated by School Experiences among Students

Authors: Z. Ishak, F.P Chew

Abstract:

School experiences, family bonding and self-concept had always been a crucial factor in influencing all aspects of a student-s development. The purpose of this study is to develop and to validate a priori model of self-concept among students. The study was tested empirically using Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA) to validate the structural model. To address these concerns, 1167 students were randomly selected and utilized the Cognitive Psycho-Social University of Malaya instrument (2009).Resulted demonstrated there is indirect effect from family bonding to self-concept through school experiences among secondary school students as a mediator. Besides school experiences, there is a direct effect from family bonding to self-concept and family bonding to school experiences among students.

Keywords: Confirmatory Factor Analysis, self-concept, family bonding, and school experience

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2323 Accelerating Quantum Chemistry Calculations: Machine Learning for Efficient Evaluation of Electron-Repulsion Integrals

Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

Abstract:

A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient, but not the magnitude. A neural network with two hidden layers was then used to learn the coefficient magnitudes, along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: Quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction.

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2322 Students' Acceptance of Incorporating Emerging Communication Technologies in Higher Education in Kuwait

Authors: Bashaiar Alsanaa

Abstract:

Never has a revolution affected all aspects of humanity as the communication revolution during the past two decades. This revolution, with all its advances and utilities, swept the world thus becoming an integral part of our lives, hence giving way to emerging applications at the social, economic, political, and educational levels. More specifically, such applications have changed the delivery system through which learning is acquired by students. Interaction with educators, accessibility to content, and creative delivery options are but a few facets of the new learning experience now being offered through the use of technology in the educational field. With different success rates, third world countries have tried to pace themselves with use of educational technology in advanced parts of the world. One such country is the small rich-oil state of Kuwait which has tried to adopt the e-educational model, however, an evaluation of such trial is yet to be done. This study aimed to fill the void of research conducted around that topic. The study explored students' acceptance of incorporating communication technologies in higher education in Kuwait. Students' responses to survey questions presented an overview of the e-learning experience in this country, and drew a framework through which implications and suggestions for future research were discussed to better serve the advancement of e-education in developing countries.

Keywords: Communication technologies, E-learning, Kuwait, Social media

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2321 Identifying Unknown Dynamic Forces Applied on Two Dimensional Frames

Authors: H. Katkhuda

Abstract:

A time domain approach is used in this paper to identify unknown dynamic forces applied on two dimensional frames using the measured dynamic structural responses for a sub-structure in the two dimensional frame. In this paper a sub-structure finite element model with short length of measurement from only three or four accelerometers is required, and an iterative least-square algorithm is used to identify the unknown dynamic force applied on the structure. Validity of the method is demonstrated with numerical examples using noise-free and noise-contaminated structural responses. Both harmonic and impulsive forces are studied. The results show that the proposed approach can identify unknown dynamic forces within very limited iterations with high accuracy and shows its robustness even noise- polluted dynamic response measurements are utilized.

Keywords: Dynamic Force Identification, Dynamic Responses, Sub-structure and Time Domain.

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2320 Enhancing Critical Reflective Practice in Fieldwork Education: An Exploratory Study of the Role of Social Work Agencies in the Welfare Context of Hong Kong

Authors: Yee-May Chan

Abstract:

In recent decades, it is observed that social work agencies have participated actively, and thus, have gradually been more influential in social work education in Hong Kong. The neo-liberal welfare ideologies and changing funding mode have transformed the landscape in social work practice and have also had a major influence on the fieldwork environment in Hong Kong. The aim of this research is to explore the educational role of social work agencies and examine in particular whether they are able to enhance or hinder critical reflective learning in fieldwork. In-depth interviews with 15 frontline social workers and managers in different social work agencies were conducted to collect their views and experience in helping social work students in fieldwork. The overall findings revealed that under the current social welfare context most social workers consider that the most important role of social work agencies in fieldwork is to help students prepare to fit-in the practice requirements and work within agencies’ boundary. The fit-for-purpose and down-to-earth view of fieldwork practice is seen as prevalent among most social workers. This narrow perception of agency’s role seems to be more favourable to competence-based approaches. In contrast, though critical reflection has been seen as important in addressing the changing needs of service users, the role of enhancing critical reflective learning has not been clearly expected or understood by most agency workers. The notion of critical reflection, if considered, has been narrowly perceived in fieldwork learning. The findings suggest that the importance of critical reflection is found to be subordinate to that of practice competence. The lack of critical reflection in the field is somehow embedded in the competence-based social work practice. In general, social work students’ critical reflection has not been adequately supported or enhanced in fieldwork agencies, nor critical reflective practice has been encouraged in fieldwork process. To address this situation, the role of social work agencies in fieldwork should be re-examined. To maximise critical reflective learning in the field, critical reflection as an avowed objective in fieldwork learning should be clearly stated. Concrete suggestions are made to help fieldwork agencies become more prepared to critical reflective learning. It is expected that the research can help social work communities to reflect upon the current realities of fieldwork context and to identify ways to strengthen agencies’ capacities to enhance critical reflective learning and practice of social work students.

Keywords: Competence-based social work, fieldwork, neo-liberal welfare, critical reflective learning.

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2319 A Taguchi Approach to Investigate Impact of Factors for Reusability of Software Components

Authors: Parvinder S. Sandhu, Pavel Blecharz, Hardeep Singh

Abstract:

Quantitative Investigation of impact of the factors' contribution towards measuring the reusability of software components could be helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable component from existing legacy systems; that can save cost of developing the software from scratch. But the issue of the relative significance of contributing factors has remained relatively unexplored. In this paper, we have use the Taguchi's approach in analyzing the significance of different structural attributes or factors in deciding the reusability level of a particular component. The results obtained shows that the complexity is the most important factor in deciding the better Reusability of a function oriented Software. In case of Object Oriented Software, Coupling and Complexity collectively play significant role in high reusability.

Keywords: Taguchi Approach, Reusability, SoftwareComponents, Structural Attributes.

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2318 Determination of Recrystallization Temperature of Varying Degrees Formed Aluminium, by DMTA Technique

Authors: Zsolt Dugár, Péter Barkóczy, Gábor Béres, Dávid Kis, Attila Bata, Tamás Dugár, Zoltán Weltsch

Abstract:

This study is about the structural transformations of aluminium examining with the Dynamic Mechanical Thermal Analyzer (DMTA). It is a faster and simpler measuring method to make consequence about the metal’s structural transformations. The device measures the changing of the mechanical characteristics depending on the heating rate, and concludes certain transformations. This measuring method fast and shows clean-cut results comparing the conventional ways. Applying polymer measuring devices for metal investigations is not widespread method. One of the adaptable ways is shown in this study. The article compares the results of the small specimen test and the DMTA method, considering the temperature and the forming dependence of recrystallization temperature.

Keywords: DMTA, recrystallization, cold forming, rotation.

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2317 Optimization of CO2 Emissions and Cost for Composite Building Design with NSGA-II

Authors: Ji Hyeong Park, Ji Hye Jeon, Hyo Seon Park

Abstract:

Environmental pollution problems have been globally main concern in all fields including economy, society and culture into the 21st century. Beginning with the Kyoto Protocol, the reduction on the emissions of greenhouse gas such as CO2 and SOX has been a principal challenge of our day. As most buildings unlike durable goods in other industries have a characteristic and long life cycle, they consume energy in quantity and emit much CO2. Thus, for green building construction, more research is needed to reduce the CO2 emissions at each stage in the life cycle. However, recent studies are focused on the use and maintenance phase. Also, there is a lack of research on the initial design stage, especially the structure design. Therefore, in this study, we propose an optimal design plan considering CO2 emissions and cost in composite buildings simultaneously by applying to the structural design of actual building.

Keywords: Multi-objective optimization, CO2 emissions, structural cost, encased composite structure

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2316 Early-Age Structural and Thermal Performance of GGBS Concrete

Authors: Kangkang Tang

Abstract:

A large amount of blast furnace slag is generated in China. Most ground granulated blast furnace slag (GGBS) however ends up in low-grade applications. Blast furnace slag, ground to an appropriate fineness, can be used as a partial replacement of cementitious material in concrete. The potential for using GGBS in structural concrete, e.g. concrete beams and columns is investigated at Xi’an Jiaotong-Liverpool University (XJTLU). With 50% of CEM I cement replaced with GGBS, peak hydration temperatures determined in a suspended concrete slab reduced by 20%. This beneficiary effect has not been further improved with 70% of CEM I replaced with GGBS. Partial replacement of CEM I with GGBS has a retardation effect on the early-age strength of concrete. More GGBS concrete mixes will be conducted to identify an ‘optimum’ replacement level which will lead to a reduced thermal loading, without significantly compromising the early-age strength of concrete.

Keywords: GGBS, thermal effect, sustainable construction, CEM I.

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2315 Leveraging Reasoning through Discourse: A Case Study in Secondary Mathematics Classrooms

Authors: Cory A. Bennett

Abstract:

Teaching and learning through the use of discourse support students’ conceptual understanding by attending to key concepts and relationships. One discourse structure used in primary classrooms is number talks wherein students mentally calculate, discuss, and reason about the appropriateness and efficiency of their strategies. In the secondary mathematics classroom, the mathematics understudy does not often lend itself to mental calculations yet learning to reason, and articulate reasoning, is central to learning mathematics. This qualitative case study discusses how one secondary school in the Middle East adapted the number talk protocol for secondary mathematics classrooms. Several challenges in implementing ‘reasoning talks’ became apparent including shifting current discourse protocols and practices to a more student-centric model, accurately recording and probing student thinking, and specifically attending to reasoning rather than computations.

Keywords: Discourse, reasoning, secondary mathematics, teacher development.

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2314 Strategies for Developing e-LMS for Tanzania Secondary Schools

Authors: Ellen A. Kalinga, R. B. Bagile Burchard, Lena Trojer

Abstract:

Tanzania secondary schools in rural areas are geographically and socially isolated, hence face a number of problems in getting learning materials resulting in poor performance in National examinations. E-learning as defined to be the use of information and communication technology (ICT) for supporting the educational processes has motivated Tanzania to apply ICT in its education system. There has been effort to improve secondary school education using ICT through several projects. ICT for e-learning to Tanzania rural secondary school is one of the research projects conceived by the University of Dar-es-Salaam through its College of Engineering and Technology. The main objective of the project is to develop a tool to enable ICT support rural secondary school. The project is comprehensive with a number of components, one being development of e-learning management system (e-LMS) for Tanzania secondary schools. This paper presents strategies of developing e-LMS. It shows the importance of integrating action research methodology with the modeling methods as presented by model driven architecture (MDA) and the usefulness of Unified Modeling Language (UML) on the issue of modeling. The benefit of MDA will go along with the development based on software development life cycle (SDLC) process, from analysis and requirement phase through design and implementation stages as employed by object oriented system analysis and design approach. The paper also explains the employment of open source code reuse from open source learning platforms for the context sensitive development of the e-LMS for Tanzania secondary schools.

Keywords: Action Research Methodology, OOSA&D, MDA, UML, Open Source LMS.

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2313 A Protocol for Applied Consumer Behavior Research in Academia

Authors: A. Otjen, S. Keller

Abstract:

A Montana university has used applied consumer research in experiential learning with non-profit clients for over a decade. Through trial and error, a successful protocol has been established from problem statement through formative research to integrated marketing campaign execution. In this paper, we describe the protocol and its applications. Analysis was completed to determine the effectiveness of the campaigns and the results of how pre- and post-consumer research mark societal change because of media.

Keywords: Marketing, experiential learning, consumer behavior, community partner.

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2312 Reinforcement Learning-Based Coexistence Interference Management in Wireless Body Area Networks

Authors: Izaz Ahmad, Farhatullah, Shahbaz Ali, Farhad Ali, Faiza, Hazrat Junaid, Farhan Zaid

Abstract:

Current trends in remote health monitoring to monetize on the Internet of Things applications have been raised in efficient and interference free communications in Wireless Body Area Network (WBAN) scenario. Co-existence interference in WBANs have aggravates the over-congested radio bands, thereby requiring efficient Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) strategies and improve interference management. Existing solutions utilize simplistic heuristics to approach interference problems. The scope of this research article is to investigate reinforcement learning for efficient interference management under co-existing scenarios with an emphasis on homogenous interferences. The aim of this paper is to suggest a smart CSMA/CA mechanism based on reinforcement learning called QIM-MAC that effectively uses sense slots with minimal interference. Simulation results are analyzed based on scenarios which show that the proposed approach maximized Average Network Throughput and Packet Delivery Ratio and minimized Packet Loss Ratio, Energy Consumption and Average Delay.

Keywords: WBAN, IEEE 802.15.4 Standard, CAP Super-frame, Q-Learning.

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2311 Teachers’ Continuance Intention Towards Using Madrasati Platform: A Conceptual Framework

Authors: Fiasal Assiri, Joanna Wincenciak, David Morrison-Love

Abstract:

With the rapid spread of the COVID-19 pandemic, the Saudi government suspended students from going to school to combat the outbreak. As e-learning was not applied at all in schools, online teaching and learning have been revived in Saudi Arabia by providing a new platform called ‘Madrasati’. The Decomposed Theory of Planned Behaviour (DTPB) is used to examine individuals’ intention behaviour in many fields. Nevertheless, the factors that affect teachers’ continuance intention of the Madrasati platform have not yet been investigated. The purpose of this paper is to present a conceptual model in light with DTPB. To enhance the predictability of the model, the study incorporates other variables including learning content quality and interactivity as sub-factors under the perceived usefulness, students and government influences under the subjective norms, and technical support and prior e-learning experience under the perceived behavioural control. The model will be further validated using a mixed methods approach. Such findings would help administrators and stakeholders to understand teachers’ needs and develop new methods that might encourage teachers to continue using Madrasati effectively in their teaching.

Keywords: Madrasati, Decomposed Theory of Planned Behaviour, continuance intention, attitude, subjective norms, perceived behavioural control.

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2310 Multi-Agent Systems for Intelligent Clustering

Authors: Jung-Eun Park, Kyung-Whan Oh

Abstract:

Intelligent systems are required in order to quickly and accurately analyze enormous quantities of data in the Internet environment. In intelligent systems, information extracting processes can be divided into supervised learning and unsupervised learning. This paper investigates intelligent clustering by unsupervised learning. Intelligent clustering is the clustering system which determines the clustering model for data analysis and evaluates results by itself. This system can make a clustering model more rapidly, objectively and accurately than an analyzer. The methodology for the automatic clustering intelligent system is a multi-agent system that comprises a clustering agent and a cluster performance evaluation agent. An agent exchanges information about clusters with another agent and the system determines the optimal cluster number through this information. Experiments using data sets in the UCI Machine Repository are performed in order to prove the validity of the system.

Keywords: Intelligent Clustering, Multi-Agent System, PCA, SOM, VC(Variance Criterion)

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2309 Hybrid Reliability-Similarity-Based Approach for Supervised Machine Learning

Authors: Walid Cherif

Abstract:

Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: Data mining, knowledge discovery, machine learning, similarity measurement, supervised classification.

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2308 The Low-Cost Design and 3D Printing of Structural Knee Orthotics for Athletic Knee Injury Patients

Authors: Alexander Hendricks, Sean Nevin, Clayton Wikoff, Melissa Dougherty, Jacob Orlita, Rafiqul Noorani

Abstract:

Knee orthotics play an important role in aiding in the recovery of those with knee injuries, especially athletes. However, structural knee orthotics is often very expensive, ranging between $300 and $800. The primary reason for this project was to answer the question: can 3D printed orthotics represent a viable and cost-effective alternative to present structural knee orthotics? The primary objective for this research project was to design a knee orthotic for athletes with knee injuries for a low-cost under $100 and evaluate its effectiveness. The initial design for the orthotic was done in SolidWorks, a computer-aided design (CAD) software available at Loyola Marymount University. After this design was completed, finite element analysis (FEA) was utilized to understand how normal stresses placed upon the knee affected the orthotic. The knee orthotic was then adjusted and redesigned to meet a specified factor-of-safety of 3.25 based on the data gathered during FEA and literature sources. Once the FEA was completed and the orthotic was redesigned based from the data gathered, the next step was to move on to 3D-printing the first design of the knee brace. Subsequently, physical therapy movement trials were used to evaluate physical performance. Using the data from these movement trials, the CAD design of the brace was refined to accommodate the design requirements. The final goal of this research means to explore the possibility of replacing high-cost, outsourced knee orthotics with a readily available low-cost alternative.

Keywords: Knee Orthotics, 3D printing, finite element analysis.

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