Search results for: adaptive educational digital learning environments
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13303

Search results for: adaptive educational digital learning environments

7123 Probabilistic Crash Prediction and Prevention of Vehicle Crash

Authors: Lavanya Annadi, Fahimeh Jafari

Abstract:

Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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7122 A Multilayer Perceptron Neural Network Model Optimized by Genetic Algorithm for Significant Wave Height Prediction

Authors: Luis C. Parra

Abstract:

The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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7121 The Role of Formal and Informal Social Support in Predicting the Involvement of Mothers and Fathers of Young Children with Autism Spectrum Disorder

Authors: Adi Sharabi, Dafna Marom-Golan

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Parents’ involvement in the care of their children with Autism Spectrum Disorder (ASD) and its beneficial effect on the children’s developmental and educational outcomes is well documented. At the same time, parents of children with ASD tend to experience greater psychological distress than parents of children with other developmental disabilities or with typical development. Positive social support is an important resource used by parents to reduce their psychological distress. The goal of the current research was to examine the contribution of formal and informal social support in explaining mothers’ and fathers’ involvement with their young children with ASD. The sample consisted of 107 parents who live in Israel (61 mothers and 46 fathers) of children aged between 2 and 7, all diagnosed with ASD and attending special kindergartens or special day care for children with ASD. Parental involvement and social support perception were assessed. Initial analysis focused on the relations between involvement, support, and demographic variables. In addition, analysis of variance (ANOVA) was conducted to test differences between mothers and fathers. Two hierarchical multiple regression analyses were performed to examine the predicted factors in the involvement model while controlling for group (mothers/fathers). Results indicate that mothers reported significantly higher levels of parenting involvement than fathers. Mothers reported higher levels of general involvement and all sub-types of involvement. For example, mothers reported that they were more interested in and have higher levels of attendance in their child’s educational program. They were also more collaborative in their child’s educational therapeutic program, and socialized with other parents of children from their child’s kindergarten than fathers. Mothers’ involvement was found to be related to their informal support (non-formal relatives). Findings also reveal significant differences between mothers and fathers on the formal support subscale measure of specializes services. Fathers, more than mothers, reported more specializes services support such as social workers or professional therapists. Separate hierarchical multiple regression analyses revealed a unique gender difference in the factors that explained parental involvement. Specifically, informal support only had a unique positive contribution in explaining mothers’, but not fathers’ involvement. This study highlights the central role of mothers in maintaining constant contact with the educational system and the professionals who help care for their child with ASD. At the same time, this research emphasizes the crucial role of both mothers and fathers in their child's development and well-being at every development stage, particularly in early development. Further, different kinds of social support seem to relate to the different kinds of parental involvement. It is in the best interest of educators and family therapists who work with families with children with ASD to support the cohesiveness of the family and the collaboration of the parents by understanding and respecting the way each member addresses the responsibilities of parenting a child with ASD, and her or his need for different types of social support.

Keywords: parental differences, parental involvement, social support, specialized support services

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7120 Housing Price Prediction Using Machine Learning Algorithms: The Case of Melbourne City, Australia

Authors: The Danh Phan

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House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

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7119 Portfolio Assessment and English as a Foreign Language Aboriginal Students’ English Learning Outcome in Taiwan

Authors: Li-Ching Hung

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The lack of empirical research on portfolio assessment in aboriginal EFL English classes of junior high schools in Taiwan may inhibit EFL teachers from appreciating the utility of this alternative assessment approach. This study addressed the following research questions: 1) understand how aboriginal EFL students and instructors of junior high schools in Taiwan perceive portfolio assessment, and 2) how portfolio assessment affects Taiwanese aboriginal EFL students’ learning outcomes. Ten classes of five junior high schools in Taiwan (from different regions of Taiwan) participated in this study. Two classes from each school joined the study, and each class was randomly assigned as a control group, and one was the experimental group. These five junior high schools consisted of at least 50% of aboriginal students. A mixed research design was utilized. The instructor of each class implemented a portfolio assessment for 15 weeks of the 2015 Fall Semester. At the beginning of the semester, all participants took a GEPT test (pretest), and in the 15th week, all participants took the same level of GEPT test (post-test). Scores of students’ GEPT tests were checked by the researcher as supplemental data in order to understand each student’s performance. In addition, each instructor was interviewed to provide qualitative data concerning students’ general learning performance and their perception of implementing portfolio assessments in their English classes. The results of this study were used to provide suggestions for EFL instructors while modifying their lesson plans regarding assessment. In addition, the empirical data were used as references for EFL instructors implementing portfolio assessments in their classes effectively.

Keywords: assessment, portfolio assessment, qualitative design, aboriginal ESL students

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7118 'Get the DNR': Exploring the Impact of an Educational eModule on Internal Medicine Residents' Attitudes and Approaches to Goals of Care Conversations

Authors: Leora Branfield Day, Stephanie Saunders, Leah Steinberg, Shiphra Ginsburg, Christine Soong

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Introduction: Discordance between patients expressed and documented preferences at the end of life is common. Although junior trainees frequently lead goals of care (GOC) conversations, lack of training can result in poor communication. Based on a needs assessment, we developed an interactive electronic learning module (eModule) for conducting patient-centred GOC discussions. The purpose of this study was to evaluate the impact of the eModule on residents’ attitudes towards GOC conversations. Methods: First-year internal medicine residents (n=11) from the University of Toronto selected using purposive sampling underwent semi-structured interviews before and after completing a GOC eModule. Interviews were anonymized, transcribed and open-coded using NVivo. Using a constructivist grounded theory approach, we developed a framework to understand the attitudes of residents to GOC conversations before and after viewing the module. Results: Before the module, participants described limited training and negative emotions towards GOC conversations. Many focused on code status and procedure choices (e.g., ventilation) instead of eliciting patient-centered values. Pressure to “get the DNR" led to conflicting feelings and distress. After the module, participants’ approached conversations with a greater focus on patient values and process. They felt more prepared and comfortable, recognizing the complexity of conversations and the importance of patient-centeredness. Conclusions: A novel GOC eModule allowed residents to develop a patient-centered and standardized approach to GOC conversations while improving confidence and preparedness. This resource could be an effective strategy toward attaining a critical communication competency among learners with the potential to enhance accurate GOC documentation.

Keywords: goals of care conversations, communication skills, emodule, medical education

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7117 Implementing Effective Strategies to Improve Teaching and Learning in Higher Education: Balancing the Engagement Acts between Lecturers And Students

Authors: Jeffrey Siphiwe Mkhize

Abstract:

Twelve years of schooling for most South African children, particularly those children from disadvantaged past, are confronted with numerous and diverse challenges. These challenges range from infrastructural limitations, language of teaching, poor resources and varying family backgrounds. Likewise, schools are categorized to signify schools’ geographic location, poverty lines, societal class and type of students that the school are likely to enroll. Such categorization perpetuates particular lines of identities that are indirectly reinforced by the same system that seeks to redress. South African universities prefer point systems to determine students’ suitability to gain access to their programmes. Once students are admitted based on the qualifying points there is an assumed equity in the manner in which they receive tuition. They are assumed as equal; noting the widened access to South African universities as means to redress past inequalities. Given the challenges, inequalities, it is necessary to view higher education as a site for knowledge construction that is accessible to all students. Epistemological access is key to all students irrespective of their socio-economic status. This paper seeks to contribute to the discourse of student engagement using lecturer-student relationship as a lens to understand this phenomenon. Data were generated using South African Survey of Student Engagement, focus group interviews, semi-structured one-on-one-interviews as well as document analysis. The focus was on students registered for the first year of a Bachelor of Education degree as well as lecturers that teach high risk modules in this qualification at the same level. The findings suggest that lecturers are challenged by overcrowded classrooms and over-enrolled modules; this challenge hampers their good intentions to become more efficient and innovative in their teaching. Students lack confidence in approaching lecturers for assistance. Collaborative learning has stronger results and students believe in self-support to deal with their challenges based on their individual strengths. Collaborative learning is key to student academic performance.

Keywords: collaborative learning, consultations, student engagement, student performance

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7116 A Dimensional Approach to Family Involvement in Forensic Mental Health Settings - Prevention of the Systemic Replication of Abuse, Need for Accepted Falsehoods and Family Guilt and Shame

Authors: Katie E. Jennings

Abstract:

The interactions between family dynamics and environmental factors with mental health vulnerability in individuals are well known and are a theme for on-going research and debate. The impact upon mental health issues and forensic issues on family dynamics, experience, and emotional wellbeing cannot be over-Emphasised. For forensic patients with diagnosed mental disorders, these relationships and environments may have also been functionally linked to the development and maintenance of those disorders; with significant adverse childhood experiences being a common feature of many Patient’s histories. Mental health hospitals remove the patient from their home environments and provide treatment outside of these relationships and often outside of the home area. There is, therefore, a major focus on Services ensuring that patients are able to build and maintain relationships with family and friends, requiring services to involve families in Patients' care and treatment wherever possible. There are standards set by Government and clinical bodies that require absolute demonstration of the inclusion of family and friends in all aspects of the care and treatment of forensic patients. For some patients and family members, this push to take on a “role” in care can be unhelpful, extremely stressful, and has constant implications for the potential delicate reparation of relationships. Based on work undertaken for over 20 years in forensic mental health settings, this paper explores the positive psychology approach to a dimensional model to family inclusion in mental health care that learns from family court work and allows for the maintenance of relationships to be at both proximal and Distil levels; to prevent the replication of abuse, decrease the need for falsehoods and assist the recovery of all. The model is based on allowing families to choose to not be involved or be involved in different ways if this is seen to be more helpful. It also allows patients to choose the level of potential involvement that they would find helpful, and for this to be reviewed at a timeframe agreed by all parties, rather than when the next survey is due or the patient has a significant care meeting. This paper is significant as there is a lack of research to support services to use a positive psychology approach to work in this area, the assumption that being asked to be involved must be positive for all seems naïve at best for this patient group. Work relating to the psychology of family can significantly contribute to the development of knowledge in this area. The development of a dimensional model will support choice within families and assist in the development of more honest and open relationships.

Keywords: family dynamics, forensic, mental disorder, positive psychology

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7115 Antimicrobial Properties of SEBS Compounds with Copper Microparticles

Authors: Vanda Ferreira Ribeiro, Daiane Tomacheski, Douglas Naue Simões, Michele Pitto, Ruth Marlene Campomanes Santana

Abstract:

Indoor environments, such as car cabins and public transportation vehicles are places where users are subject to air quality. Microorganisms (bacteria, fungi, yeasts) enter these environments through windows, ventilation systems and may use the organic particles present as a growth substrate. In addition, atmospheric pollutants can act as potential carbon and nitrogen sources for some microorganisms. Compounds base SEBS copolymers, poly(styrene-b-(ethylene-co-butylene)-b-styrene, are a class of thermoplastic elastomers (TPEs), fully recyclable and largely used in automotive parts. Metals, such as cooper and silver, have biocidal activities and the production of the SEBS compounds by melting blending with these agents can be a good option for producing compounds for use in plastic parts of ventilation systems and automotive air-conditioning, in order to minimize the problems caused by growth of pathogenic microorganisms. In this sense, the aim of this work was to evaluate the effect of copper microparticles as antimicrobial agent in compositions based on SEBS/PP/oil/calcite. Copper microparticles were used in weight proportion of 0%, 1%, 2% and 4%. The compounds were prepared using a co-rotating double screw extruder (L/D ratio of 40/1 and 16 mm screw diameter). The processing parameters were 300 rpm of screw rotation rate, with a temperature profile between 150 to 190°C. SEBS based TPE compounds were injection molded. The compounds emission were characterized by gravimetric fogging test. Compounds were characterized by physical (density and staining by contact), mechanical (hardness and tension properties) and rheological properties (melt volume rate – MVR). Antibacterial properties were evaluated against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) strains. To avaluate the abilities toward the fungi have been chosen Aspergillus niger (A. niger), Candida albicans (C. albicans), Cladosporium cladosporioides (C. cladosporioides) and Penicillium chrysogenum (P. chrysogenum). The results of biological tests showed a reduction on bacteria in up to 88% in E.coli and up to 93% in S. aureus. The tests with fungi showed no conclusive results because the sample without copper also demonstrated inhibition of the development of these microorganisms. The copper addition did not cause significant variations in mechanical properties, in the MVR and the emission behavior of the compounds. The density increases with the increment of copper in compounds.

Keywords: air conditioner, antimicrobial, cooper, SEBS

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7114 Socio-Economic Impact of Covid-19 in Ethiopia

Authors: Kebron Abich Asnake

Abstract:

The outbreak of COVID-19 has had far-reaching socio-economic consequences globally, and Ethiopia is no exception. This abstract provides a summary of a research study on the socio-economic impact of COVID-19 in Ethiopia. The study analyzes the health impact, economic repercussions, social consequences, government response measures, and opportunities for post-crisis recovery. In terms of health impact, the research explores the spread and transmission of the virus, the capacity and response of the healthcare system, and the mortality rate, with a focus on vulnerable populations. The economic impact analysis entails investigating the contraction of the GDP, employment and income loss, disruption in key sectors such as agriculture, tourism, and manufacturing, and the specific implications for small and medium-sized enterprises (SMEs), foreign direct investment, and remittances. The social impact section looks at the disruptions in education and the digital divide, food security and nutrition challenges, increased poverty and inequality, gender-based violence, and mental health issues. The research also examines the measures taken by the Ethiopian government, including health and safety regulations, economic stimulus packages, social protection programs, and support for vulnerable populations. Furthermore, the study outlines long-term recovery prospects, social cohesion, and community resilience challenges. It highlights the need to strengthen the healthcare system and finds a balance between health and economic priorities. The research concludes by presenting recommendations for policy-makers and stakeholders, emphasizing opportunities for post-crisis recovery such as diversification of the economy, enhanced healthcare infrastructure, investment in digital infrastructure and technology, and support for domestic tourism and local industries. This research provides valuable insights into the socio-economic impact of COVID-19 in Ethiopia, offering a comprehensive analysis of the challenges faced and potential pathways towards recovery.

Keywords: impact, covid, ethiopia, health

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7113 Development of Intelligent Smart Multi Tracking Agent System to Support of Logistics Safety

Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

Abstract:

Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

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7112 Optimizing Microgrid Operations: A Framework of Adaptive Model Predictive Control

Authors: Ruben Lopez-Rodriguez

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In a microgrid, diverse energy sources (both renewable and non-renewable) are combined with energy storage units to form a localized power system. Microgrids function as independent entities, capable of meeting the energy needs of specific areas or communities. This paper introduces a Model Predictive Control (MPC) approach tailored for grid-connected microgrids, aiming to optimize their operation. The formulation employs Mixed-Integer Programming (MIP) to find optimal trajectories. This entails the fulfillment of continuous and binary constraints, all while accounting for commutations between various operating conditions such as storage unit charge/discharge, import/export from/towards the main grid, as well as asset connection/disconnection. To validate the proposed approach, a microgrid case study is conducted, and the simulation results are compared with those obtained using a rule-based strategy.

Keywords: microgrids, mixed logical dynamical systems, mixed-integer optimization, model predictive control

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7111 Analysis the Impacts of WeChat Mobile Payment in China Teens' Online Purchasing Behaviors

Authors: Lok Yi Joyce Poon

Abstract:

China's mobile payment market has boomed in the past few years. WeChat (Chinese name as Weixin) owned by Tencent is known as the fastest growing all-in-one social messaging platforms. The company has launched the WeChat Pay in 2013, in which users can link their credit card to their user account and make payments within the app’s built in digital wallet. WeChat Payment is a one-stop payment tool that can provide a seamless online experience for the shoppers to transfer money between WeChat users (peer-to-peer) and make payments online by scanning a QR code, a prominent facilitator for transactions in WeChat, to complete the payment with the app without directing the users to the external websites. The aims of this study are to examine the effectiveness of WeChat mobile payment in China as well as the impacts of the China teen’s online purchasing behavior since the establishment of WeChat Payment. The research method of this study is conducted by both online survey on Sojump, a popular online survey platform in China. A total of 120 respondents among 18 to 25 teens in China completed the survey. Data sources included participants’ response to an end-of-session questionnaire, encompassing with the types of multiple choice, open-ended questions. To have an in-depth analysis, a face-to-face interview with a Chinese teen who is a frequent user of the WeChat Pay. The main finding of the study shows that the majority of the teenagers frequently use the WeChat payment tool because of its convenience, user-friendliness and the scenarios offered within the WeChat Wallet. The respondents claimed that they will settle the bills in their daily lives via WeChat Pay. However, the respondents in the age group of 40 or above will not use the WeChat Pay due to the security concern and they do not see the app as a platform for commercial activities like online shopping. Throughout the study, it is recommended WeChat should put more efforts on the security issue and improve the payment technology by adopting the near-field communication terminals instead of requiring users to scan QR codes before they complete the transaction.

Keywords: digital wallet, mobile payment, online purchasing behavior, WeChat Pay

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7110 Intelligent Software Architecture and Automatic Re-Architecting Based on Machine Learning

Authors: Gebremeskel Hagos Gebremedhin, Feng Chong, Heyan Huang

Abstract:

Software system is the combination of architecture and organized components to accomplish a specific function or set of functions. A good software architecture facilitates application system development, promotes achievement of functional requirements, and supports system reconfiguration. We describe three studies demonstrating the utility of our architecture in the subdomain of mobile office robots and identify software engineering principles embodied in the architecture. The main aim of this paper is to analyze prove architecture design and automatic re-architecting using machine learning. Intelligence software architecture and automatic re-architecting process is reorganizing in to more suitable one of the software organizational structure system using the user access dataset for creating relationship among the components of the system. The 3-step approach of data mining was used to analyze effective recovery, transformation and implantation with the use of clustering algorithm. Therefore, automatic re-architecting without changing the source code is possible to solve the software complexity problem and system software reuse.

Keywords: intelligence, software architecture, re-architecting, software reuse, High level design

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7109 The Association between Psychosocial Characteristics, Training Variables and Well-Being: An Exploratory Study among Organizational Workers

Authors: Norshaffika I. Zaiedy Nor, Andrew P. Smith

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Background: Training is essential to develop individuals’ expertise to meet current and future job demands and to improve work performance. At the same time, individuals’ well-being is crucial to ensure that they can fully and positively carry out their daily duties. In addition to the studies that have examined what constitutes well-being and the factors behind it, many researchers have investigated the predictors of training effectiveness and transfer of training. However, there has been very little integration between them. This study was an attempt to bridge the gap between training effectiveness predictors and well-being. Purpose: This research paper aimed to investigate the association between well-being among employees and psychosocial characteristics, together with training variables. Training variables consist of motivation to learn; learning; implementation intention; and cognitive dissonance. Methodology: In total, 210 workers who had undergone various training programs completed an online survey measuring various psychosocial characteristics, four training variables, and level of well-being. Findings: The results showed that certain types of positive psychosocial characteristics (e.g., positive personality, positive work behaviors, positive work and resources) predict motivation to learn, learning and implementation intention. Meanwhile, negative psychosocial characteristics (e.g. negative work demands and resources, negative coping) predict cognitive dissonance. Also, all the training variables had a moderate to high correlation with well-being. However, after controlling other variables (age, gender, education and psychosocial characteristics), none of the training variables predicted well-being. Self-determination theory, cognitive dissonance theory, and the DRIVE model were used to explain these findings. Conclusion: As there is limited research on the integration of training variables with well-being, this study gives a new perspective in the field of both training and well-being. Further investigations are needed to examine the relationships between them.

Keywords: cognitive dissonance, implementation intention, learning, motivation to learn, psychosocial characteristics, well-being

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7108 The University-Industry Relationships in Sweden and Iran: A Critical Comparative Study

Authors: Sepideh Nikounejad, Mostafa Ghaderi, Nematollah Azizi, Per-Olof Thang, Mohamad Reza Neyestani

Abstract:

From an educational perspective, an effective and efficient relationship between university and industry can be considered as an important means by which not only both sides are improved but also it brings many advantages and benefits for both parties. It means more specifically, mutual collaboration between universities and industry can not only reduce youth unemployment, but it can improve the quality of teaching and learning in higher education settings while providing more qualified people to industrial enterprises. Indeed the lack of effective interaction between Iranian universities and industry has confronted the country and created many challenges include in increasing number of unskillful and unemployed graduates. However, in order to suggest appropriate practical strategies, it is very important to see how this issue has been tackled by Swedish universities, which have had a good background in this collaboration and how they are connected to the industry in particular and labour market in general. The research aims to study and compare the mechanisms, processes, and policies of the current model in the relationships between university and industry in Iran and Sweden. As a qualitative study, grounded theory was applied. Data were collected via semi-structured interviews. Participants were selected purposefully and by the snowball sampling method. The findings indicate that despite reported needs from both sides for close collaborations between universities and industries in Iran, current policies and practices, including internship, laboratory, and financial support, need to be revised critically. However, in light of our findings on the Swedish policies and practices for linking universities and industries, some practical strategies will be suggested for the Iranian higher education context. In conclusion, cooperation models between universities and industries in Iran and Sweden will be described.

Keywords: cooperation, higher education, industry, comparative

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7107 Perceived Physical Exercise Benefits among Staff of Tertiary Institutions in Adamawa State

Authors: Salihu Mohammed Umar

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Perceived physical exercise benefits among staff of tertiary institutions in Adamawa State was investigated as a basis for formulating proper exercise intervention strategies. The study utilized descriptive survey design. The purpose of the study was to determine perceived exercise benefits among staff of tertiary institutions in Adamawa state, Nigeria. The instrument used for data collection was a questionnaire adapted from Exercise Benefit/Barrier Scale (EBBS) developed by Sechrist, Walker and Pender (1985) which was validated by five experts. Three hundred and thirty (330) copies of the questionnaire were distributed among study participants in six institutions of higher learning in Adamawa state. The scale comprised two components; Benefits and Barriers dimensions. To achieve this purpose, three research questions were posed. The instrument had a four response forced-choice Likert-type format with responses ranging from 4 = strongly agree (SA), 3 = Agree (A), 2 = Disagree (D) and 1 = Strongly Disagree (SD). The findings of the study revealed that both male and female staff in institutions of higher learning in Adamawa state perceived exercise as highly beneficial. However, male staff had higher perceived benefits score than their female counterparts. (Male: x̄ = 95.02. SD = 3.08) > female: x̄ = 94.04, SD = 4.35. There was also no significant difference in perceived exercise barriers between staff and students of tertiary institutions in Adamawa state. Based on the finding of the study, it was concluded that staff of tertiary institutions perceived exercise as highly beneficial. It was recommended that since staff of institutions of higher learning in Adamawa State irrespective of gender and religious affiliations have basic knowledge of perceived benefits of exercise, there is the need to explore programmes that will enable staff across the sub-groups to overcome barriers that could discourage physical exercise participation.

Keywords: perception, physical exercise, staff, benefits

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7106 The Relevance of Shared Cultural Leadership in the Survival of the Language and of the Francophone Culture in a Minority Language Environment

Authors: Lyne Chantal Boudreau, Claudine Auger, Arline Laforest

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As an English-speaking country, Canada faces challenges in French-language education. During both editions of a provincial congress on education planned and conducted under shared cultural leadership, three organizers created a Francophone space where, for the first time in the province of New Brunswick (the only officially bilingual province in Canada), a group of stakeholders from the school, post-secondary and community sectors have succeeded in contributing to reflections on specific topics by sharing winning practices to meet the challenges of learning in a minority Francophone environment. Shared cultural leadership is a hybrid between theories of leadership styles in minority communities and theories of shared leadership. Through shared cultural leadership, the goal is simply to guide leadership and to set up all minority leaderships in minority context through shared leadership. This leadership style requires leaders to transition from a hierarchical to a horizontal approach, that is, to an approach where each individual is at the same level. In this exploratory research, it has been demonstrated that shared leadership exercised under the T-learning model best fosters the mobilization of all partners in advancing in-depth knowledge in a particular field while simultaneously allowing learning of the elements related to the domain in question. This session will present how it is possible to mobilize the whole community through leaders who continually develop their knowledge and skills in their specific field but also in related fields. Leaders in this style of management associated to shared cultural leadership acquire the ability to consider solutions to problems from a holistic perspective and to develop a collective power derived from the leadership of each and everyone in a space where all are rallied to promote the ultimate advancement of society.

Keywords: education, minority context, shared leadership, t-leaning

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7105 Municipal-Level Gender Norms: Measurement and Effects on Women in Politics

Authors: Luisa Carrer, Lorenzo De Masi

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In this paper, we exploit the massive amount of information from Facebook to build a measure of gender attitudes in Italy at a previously impossible resolution—the municipal level. We construct our index via a machine learning method to replicate a benchmark region-level measure. Interestingly, we find that most of the variation in our Gender Norms Index (GNI) is across towns within narrowly defined geographical areas rather than across regions or provinces. In a second step, we show how this local variation in norms can be leveraged for identification purposes. In particular, we use our index to investigate whether these differences in norms carry over to the policy activity of politicians elected in the Italian Parliament. We document that females are more likely to sit in parliamentary committees focused on gender-sensitive matters, labor, and social issues, but not if they come from a relatively conservative town. These effects are robust to conditioning the legislative term and electoral district, suggesting the importance of social norms in shaping legislators’ policy activity.

Keywords: gender equality, gender norms index, Facebook, machine learning, politics

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7104 Implementation of a Distant Learning Physician Assistant Program in Northern Michigan to Address Health Care Provider Shortage: Importance of Evaluation

Authors: Theresa Bacon-Baguley, Martina Reinhold

Abstract:

Introduction: The purpose of this paper is to discuss the importance of both formative and summative evaluation of a Physician Assistant (PA) program with a distant campus delivered through Interactive Television (ITV) to assure equity of educational experiences. Methodology: A needs assessment utilizing a case-control design determined the need and interest in expanding the existing PA program to northern Michigan. A federal grant was written and funded, which supported the hiring of two full-time faculty members and support staff at the distant site. The strengths and weaknesses of delivering a program through ITV were evaluated using weekly formative evaluation, and bi-semester summative evaluation. Formative evaluation involved discussion of lecture content to be delivered, special ITV needs, orientation of new lecturers to the system, student concerns, support staff updates, and scheduling of student/faculty traveling between the two campuses. The summative evaluation, designed from a literature review of barriers to ITV, included 19 statements designed to evaluate the following items: quality of technology (audio, video, etc.), confidence in the ITV system, quality of instruction and instructor interaction between the two locations, and availability of resources at each location. In addition, students were given the opportunity to write qualitative remarks for each course delivered between the two locations. This summative evaluation was given to all students at mid-semester and at the end of the semester. The goal of the summative evaluation was to have 80% or greater of the students respond favorably (‘Very Good’ or ‘Good’) to each of the 19 statements. Results: Prior to the start of the first cohort at the distant campus, the technology was tested. During this time period, the formative evaluations identified key components needing modification, which were rapidly addressed: ability to record lectures, lighting, sound, and content delivery. When the mid-semester summative survey was given to the first cohort of students, 18 of the 19 statements in the summative evaluation met the goal of 80% or greater in the favorable category. When the summative evaluation statements were stratified by the two cohorts, the summative evaluation identified that students at the home location responded that they did not have adequate access to printers, and students at the expansion location responded that they did not have adequate access to library resources. These results allowed the program to address the deficiencies through contacting informational technology for additional printers, and to provide students with knowledge on how to access library resources. Conclusion: Successful expansion of programs to a distant site utilizing ITV technology requires extensive monitoring using both formative and summative evaluation. The formative evaluation allowed for quick identification of issues that could immediately be addressed, both at the planning and developing stage, as well as during implementation. Through use of the summative evaluation the program is able to monitor the success/ effectiveness of the expansion and identify specific needs of students at each location.

Keywords: assessment, distance learning, formative feedback, interactive television (ITV), student experience, summative feedback, support

Procedia PDF Downloads 241
7103 Automatic Classification of the Stand-to-Sit Phase in the TUG Test Using Machine Learning

Authors: Yasmine Abu Adla, Racha Soubra, Milana Kasab, Mohamad O. Diab, Aly Chkeir

Abstract:

Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals, out of which 11 were chosen based on their intraclass correlation coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, 5 features were introduced to the linear discriminant analysis classifier, and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90%, respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

Procedia PDF Downloads 156
7102 Digitalization: The Uneven Geography of Information and Communication Technology (ICTS) CTSoss Four Major States in India

Authors: Sanchari Mukhopadhyay

Abstract:

Today, almost the entire realm of human activities are becoming increasingly dependent on the power of information, where through ICTs it is now possible to cater distances and avail various services at a few clicks. In principle, ICTs are thus expected to blur location-specific differences and affiliations of development and bring in an inclusive society at the wake of globalization. However, eventually researchers and policy analysts realized that ICTs are also generating inequality in spite of the hope for an integrated world and widespread social well-being. Regarding this unevenness, location plays a major role as often ICT development is seen to be concentrated into pockets, leaving behind large tracks as underprivileged. Thus, understanding the spatial pattern of ICT development and distribution is significant in relation to exploring the extent to which ICTs are fulfilling the promises or reassuring the existing divisions. In addition, it is also profoundly crucial to investigate how regions are connecting and competing both locally and globally. The focus of the research paper is to evaluate the spatial structure of ICT led development in India. Thereby, it attempts to understand the state level (four selected states) pattern of ICT penetration, the pattern of diffusion across districts with respect to large urban centres and the rural-urban disparity of technology adoption. It also tries to assess the changes in access dynamisms of ICTs as one move away from a large metropolitan city towards the periphery. In brief, the analysis investigates into the tendency towards the uneven growth of development through the identification of the core areas of ICT advancement within the country and its diffusion from the core to the periphery. In order to assess the level of ICT development and rural-urban disparity across the districts of selected states, two indices named ICT Development Index and Rural-Urban Digital Divide Index have been constructed. The study mostly encompasses the latest Census (2011) of the country and TRAI (Telecom Regulatory Authority of India) in some cases.

Keywords: ICT development, diffusion, core-periphery, digital divide

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7101 Noise Removal Techniques in Medical Images

Authors: Amhimmid Mohammed Saffour, Abdelkader Salama

Abstract:

Filtering is a part of image enhancement techniques, it is used to enhance certain details such as edges in the image that are relevant to the application. Additionally, filtering can even be used to eliminate unwanted components of noise. Medical images typically contain salt and pepper noise and Poisson noise. This noise appears to the presence of minute grey scale variations within the image. In this paper, different filters techniques namely (Median, Wiener, Rank order3, Rank order5, and Average) were applied on CT medical images (Brain and chest). We using all these filters to remove salt and pepper noise from these images. This type of noise consists of random pixels being set to black or white. Peak Signal to Noise Ratio (PSNR), Mean Square Error r(MSE) and Histogram were used to evaluated the quality of filtered images. The results, which we have achieved shows that, these filters, are more useful and they prove to be helpful for general medical practitioners to analyze the symptoms of the patients with no difficulty.

Keywords: CT imaging, median filter, adaptive filter and average filter, MATLAB

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7100 Predictive Factors of Exercise Behaviors of Junior High School Students in Chonburi Province

Authors: Tanida Julvanichpong

Abstract:

Exercise has been regarded as a necessary and important aspect to enhance physical performance and psychology health. Body weight statistics of students in junior high school students in Chonburi Province beyond a standard risk of obesity. Promoting exercise among Junior high school students in Chonburi Province, essential knowledge concerning factors influencing exercise is needed. Therefore, this study aims to (1) determine the levels of perceived exercise behavior, exercise behavior in the past, perceived barriers to exercise, perceived benefits of exercise, perceived self-efficacy to exercise, feelings associated with exercise behavior, influence of the family to exercise, influence of friends to exercise, and the perceived influence of the environment on exercise. (2) examine the predicting ability of each of the above factors while including personal factors (sex, educational level) for exercise behavior. Pender’s Health Promotion Model was used as a guide for the study. Sample included 652 students in junior high schools, Chonburi Provience. The samples were selected by Multi-Stage Random Sampling. Data Collection has been done by using self-administered questionnaires. Data were analyzed using descriptive statistics, Pearson’s product moment correlation coefficient, Eta, and stepwise multiple regression analysis. The research results showed that: 1. Perceived benefits of exercise, influence of teacher, influence of environmental, feelings associated with exercise behavior were at a high level. Influence of the family to exercise, exercise behavior, exercise behavior in the past, perceived self-efficacy to exercise and influence of friends were at a moderate level. Perceived barriers to exercise were at a low level. 2. Exercise behavior was positively significant related to perceived benefits of exercise, influence of the family to exercise, exercise behavior in the past, perceived self-efficacy to exercise, influence of friends, influence of teacher, influence of environmental and feelings associated with exercise behavior (p < .01, respectively) and was negatively significant related to educational level and perceived barriers to exercise (p < .01, respectively). Exercise behavior was significant related to sex (Eta = 0.243, p=.000). 3. Exercise behavior in the past, influence of the family to exercise significantly contributed 60.10 percent of the variance to the prediction of exercise behavior in male students (p < .01). Exercise behavior in the past, perceived self-efficacy to exercise, perceived barriers to exercise, and educational level significantly contributed 52.60 percent of the variance to the prediction of exercise behavior in female students (p < .01).

Keywords: predictive factors, exercise behaviors, Junior high school, Chonburi Province

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7099 Deep Reinforcement Learning-Based Computation Offloading for 5G Vehicle-Aware Multi-Access Edge Computing Network

Authors: Ziying Wu, Danfeng Yan

Abstract:

Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

Procedia PDF Downloads 111
7098 Sliding Mode MRAS Observer for Optimized Backstepping Control of Induction Motor

Authors: Chaouch Souad, Abdou Latifa, Larbi Chrifi Alaoui

Abstract:

This paper deals with sensorless backstepping control of induction motor using MRAS technique associated to sliding mode approach. A high order genetic algorithm structure is used to approximate a control law designed by the Backstepping technique, and to find the best parameters globally optimized. However, the Backstepping control approach is unsuitable for high performance applications because the need of a speed sensor for increased accuracy and the absence of any error decay mechanism. In this paper a nonlinear observer, obtained by combining sliding mode structure and model reference adaptive system (MRAS), is designed for the rotor flux and rotor speed estimations. To validate the proposed method, the results are presented for showing the improved drive characteristics and performances.

Keywords: Backstepping Control, Induction Motor, Genetic Algorithm, Sliding Mode observer

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7097 CFD Simulations to Study the Cooling Effects of Different Greening Modifications

Authors: An-Shik Yang, Chih-Yung Wen, Chiang-Ho Cheng, Yu-Hsuan Juan

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The objective of this study is to conduct computational fluid dynamic (CFD) simulations for evaluating the cooling efficacy from vegetation implanted in a public park in the Taipei, Taiwan. To probe the impacts of park renewal by means of adding three pavilions and supplementary green areas on urban microclimates, the simulated results have revealed that the park having a higher percentage of green coverage ratio (GCR) tended to experience a better cooling effect. These findings can be used to explore the effects of different greening modifications on urban environments for achieving an effective thermal comfort in urban public spaces.

Keywords: CFD simulations, Green Coverage Ratio, Urban heat island, Urban Public Park

Procedia PDF Downloads 483
7096 Design and Implementation of a Software Platform Based on Artificial Intelligence for Product Recommendation

Authors: Giuseppina Settanni, Antonio Panarese, Raffaele Vaira, Maurizio Galiano

Abstract:

Nowdays, artificial intelligence is used successfully in academia and industry for its ability to learn from a large amount of data. In particular, in recent years the use of machine learning algorithms in the field of e-commerce has spread worldwide. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a chatbot and a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. The recommendation systems perform the important function of automatically filtering and personalizing information, thus allowing to manage with the IT overload to which the user is exposed on a daily basis. Recently, international research has experimented with the use of machine learning technologies with the aim to increase the potential of traditional recommendation systems. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Artificial intelligence algorithms have been implemented and trained on historical data collected from user browsing. Finally, the testing phase allowed to validate the implemented model, which will be further tested by letting customers use it.

Keywords: machine learning, recommender system, software platform, support vector machine

Procedia PDF Downloads 131
7095 Small Entrepreneurs as Creators of Chaos: Increasing Returns Requires Scaling

Authors: M. B. Neace, Xin GAo

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Small entrepreneurs are ubiquitous. Regardless of location their success depends on several behavioral characteristics and several market conditions. In this concept paper, we extend this paradigm to include elements from the science of chaos. Our observations, research findings, literature search and intuition lead us to the proposition that all entrepreneurs seek increasing returns, as did the many small entrepreneurs we have interviewed over the years. There will be a few whose initial perturbations may create tsunami-like waves of increasing returns over time resulting in very large market consequences–the butterfly impact. When small entrepreneurs perturb the market-place and their initial efforts take root a series of phase-space transitions begin to occur. They sustain the stream of increasing returns by scaling up. Chaos theory contributes to our understanding of this phenomenon. Sustaining and nourishing increasing returns of small entrepreneurs as complex adaptive systems requires scaling. In this paper we focus on the most critical element of the small entrepreneur scaling process–the mindset of the owner-operator.

Keywords: entrepreneur, increasing returns, scaling, chaos

Procedia PDF Downloads 454
7094 Socio-Economic Impact of Education on Urban Women in Pakistan

Authors: Muhammad Ali Khan

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Education is a word has been derived from Latin word "Educare", means to train. Therefore, the harmonious growth of the potentialities for achieving the qualities desirable and useful in the human society is called education. It is claimed that by educating women we can develop our economy, family health and decrease population growth. To explore the socio-economic impact of education on urban women. A prospective study design was used. Over a period of six months 50 respondents were randomly selected from Hayat Abad, an urban city in the North West of Pakistan. A questionnaire was used to explore marital, educational, occupational, social, economical and political status of urban women. Of the total, 50% (25) were employed, where 56% were married and 44% unmarried. Of the employed participants, 56% were teachers fallowed by social worker 16%. Monthly income was significantly high (p=001) of women with master degree. Understanding between wife and husband was also very significant in women with masters. . 78% of employed women replied that Parda (Hija) should be on choice not imposed. 52% of educated women replied participation in social activates, such as parties, shopping etc. Education has a high impact on urban women because it is directly related to employment, decision of power, economy and social life. Urban women with high education have significant political awareness and empowerment. Improving women educational level in rural areas of Pakistan is the key for economic growth and political empowerment

Keywords: women, urban, Pakistan, socio economic

Procedia PDF Downloads 94