Search results for: service learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10452

Search results for: service learning

9102 A Hybrid System of Hidden Markov Models and Recurrent Neural Networks for Learning Deterministic Finite State Automata

Authors: Pavan K. Rallabandi, Kailash C. Patidar

Abstract:

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

Procedia PDF Downloads 388
9101 Exploring Perspectives and Complexities of E-tutoring: Insights from Students Opting out of Online Tutor Service

Authors: Prince Chukwuneme Enwereji, Annelien Van Rooyen

Abstract:

In recent years, technology integration in education has transformed the learning landscape, particularly in online institutions. One technological advancement that has gained popularity is e-tutoring, which offers personalised academic support to students through online platforms. While e-tutoring has become well-known and has been adopted to promote collaborative learning, there are still students who do not use these services for various reasons. However, little attention has been given to understanding the perspectives of students who have not utilized these services. The research objectives include identifying the perceived benefits that non-e-tutoring students believe e-tutoring could offer, such as enhanced academic support, personalized learning experiences, and improved performance. Additionally, the study explored the potential drawbacks or concerns that non-e-tutoring students associate with e-tutoring, such as concerns about efficacy, a lack of face-to-face interaction, and platform accessibility. The study adopted a quantitative research approach with a descriptive design to gather and analyze data on non-e-tutoring students' perspectives. Online questionnaires were employed as the primary data collection method, allowing for the efficient collection of data from many participants. The collected data was analyzed using the Statistical Package for the Social Sciences (SPSS). Ethical concepts such as informed consent, anonymity of responses and protection of respondents against harm were maintained. Findings indicate that non-e-tutoring students perceive a sense of control over their own pace of learning, suggesting a preference for self-directed learning and the ability to tailor their educational experience to their individual needs and learning styles. They also exhibit high levels of motivation, believe in their ability to effectively participate in their studies and organize their academic work, and feel comfortable studying on their own without the help of e-tutors. However, non-e-tutoring students feel that e-tutors do not sufficiently address their academic needs and lack engagement. They also perceive a lack of clarity in the roles of e-tutors, leading to uncertainty about their responsibilities. In terms of communication, students feel overwhelmed by the volume of announcements and find repetitive information frustrating. Additionally, some students face challenges with their internet connection and associated cost, which can hinder their participation in online activities. Furthermore, non-e-tutoring students express a desire for interactions with their peers and a sense of belonging to a group or team. They value opportunities for collaboration, teamwork in their learning experience, the importance of fostering social interactions and creating a sense of community in online learning environments. This study recommended that students seek alternate support systems by reaching out to professors or academic advisors for guidance and clarification. Developing self-directed learning skills is essential, empowering students to take charge of their own learning through setting objectives, creating own study plans, and utilising resources. For HEIs, it was recommended that they should ensure that a variety of support services are available to cater to the needs of all students, including non-e-tutoring students. HEIs should also ensure easy access to online resources, promote a supportive community, and regularly evaluate and adapt their support techniques to meet students' changing requirements.

Keywords: online-tutor;, student support;, online education, educational practices, distance education

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9100 Constructivist Grounded Theory of Intercultural Learning

Authors: Vaida Jurgile

Abstract:

Intercultural learning is one of the approaches taken to understand the cultural diversity of the modern world and to accept changes in cultural identity and otherness and the expression of tolerance. During intercultural learning, students develop their abilities to interact and communicate with their group members. These abilities help to understand social and cultural differences, to form one’s identity, and to give meaning to intercultural learning. Intercultural education recognizes that a true understanding of differences and similarities of another culture is necessary in order to lay the foundations for working together with others, which contributes to the promotion of intercultural dialogue, appreciation of diversity, and cultural exchange. Therefore, it is important to examine the concept of intercultural learning, revealed through students’ learning experiences and understanding of how this learning takes place and what significance this phenomenon has in higher education. At a scientific level, intercultural learning should be explored in order to uncover the influence of cultural identity, i.e., intercultural learning should be seen in a local context. This experience would provide an opportunity to learn from various everyday intercultural learning situations. Intercultural learning can be not only a form of learning but also a tool for building understanding between people of different cultures. The research object of the study is the process of intercultural learning. The aim of the dissertation is to develop a grounded theory of the process of learning in an intercultural study environment, revealing students’ learning experiences. The research strategy chosen in this study is a constructivist grounded theory (GT). GT is an inductive method that seeks to form a theory by applying the systematic collection, synthesis, analysis, and conceptualization of data. The targeted data collection was based on the analysis of data provided by previous research participants, which revealed the need for further research participants. During the research, only students with at least half a year of study experience, i.e., who have completed at least one semester of intercultural studies, were purposefully selected for the research. To select students, snowballing sampling was used. 18 interviews were conducted with students representing 3 different fields of sciences (social sciences, humanities, and technology sciences). In the process of intercultural learning, language expresses and embodies cultural reality and a person’s cultural identity. It is through language that individual experiences are expressed, and the world in which Others exist is perceived. The increased emphasis is placed on the fact that language conveys certain “signs’ of communication and perception with cultural value, enabling the students to identify the Self and the Other. Language becomes an important tool in the process of intercultural communication because it is only through language that learners can communicate, exchange information, and understand each other. Thus, in the process of intercultural learning, language either promotes interpersonal relationships with foreign students or leads to mutual rejection.

Keywords: intercultural learning, grounded theory, students, other

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9099 The Positive Impact of Wheelchair Service Provision on the Health and Overall Satisfaction of Wheelchair Users with the Devices

Authors: Archil Undilashvili, Ketevan Stvilia, Dustin Gilbreath, Giorgi Dzneladze, Gordon Charchward

Abstract:

Introduction: In recent years, diverse types of wheelchairs, both local production and imported, have been made available on the Georgian market for wheelchair users. Some types of wheelchairs are sold together with a service package, while the others, including the State Program, Supported locally-produced ones, don’t provide adjustment and maintenance service packages to users. Within the USAID Physical Rehabilitation Project in Georgia, a study was conducted to assess the impact of the wheelchair service provision in line with the WHO guidelines on the health and overall satisfaction of wheelchair users in Georgia. Methodology: A cross-sectional survey was conducted in May 2021. A structured questionnaire was used for telephone interviews that, along with socio-demographic characteristics, included questions for assessment of accessibility, availability, timeliness, cost and quality of wheelchair services received. Out of 1060 individuals listed in the census of wheelchair users, 752 were available for interview, with an actual response rate of 73.4%. 552 wheelchair users (31%) or their caregivers (69%) agreed to participate in the survey. In addition to using descriptive statistics, the study used multivariate matching of wheelchair users who received wheelchair services and who did not (control group). In addition, to evaluate satisfaction with service provision, respondents were asked to assess services. Findings: The majority (67%) of wheelchair users included in the survey were male. The average age of participants was 43. The three most frequently named reasons for using a wheelchair were cerebral palsy (29%), followed by stroke (18%), and amputation (12%). Users have had their current chair for four years on average. Overall, 60% of respondents reported that they were assessed before providing a wheelchair, but only half of them reported that their preferences and needs were considered. Only 13% of respondents had services in line with WHO guidelines and only 22% of wheelchair users had training when they received their current chair. 16% of participants said they had follow-up services, and 41% received adjustment services after receiving the chair. A slight majority (56%) of participants were satisfied with the quality of service provision and the service provision overall. Similarly, 55% were satisfied with the accessibility of service provision. A slightly larger majority (61%) were satisfied with the timeliness of service provision. The matching analysis suggests that users that received services in line with WHO guidelines were more satisfied with their chairs (the difference 17 point/0-100 scale) and they were four percentage points less likely to have health problems attributed to the chair. The regression analysis provides a similar finding of a 21 point increase in satisfaction attributable to services. Conclusion: The provision of wheelchair services in line with WHO guidelines and with follow-up services is likely to have a positive impact on the daily lives of wheelchair users in Georgia. Wheelchair services should be institutionalized as a standard component of wheelchair provision in Georgia.

Keywords: physical rehabilitation, wheelchair users, persons with disabilities, wheelchair production

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9098 Are Some Languages Harder to Learn and Teach Than Others?

Authors: David S. Rosenstein

Abstract:

The author believes that modern spoken languages should be equally difficult (or easy) to learn, since all normal children learning their native languages do so at approximately the same rate and with the same competence, progressing from easy to more complex grammar and syntax in the same way. Why then, do some languages seem more difficult than others? Perhaps people are referring to the written language, where it may be true that mastering Chinese requires more time than French, which in turn requires more time than Spanish. But this may be marginal, since Chinese and French children quickly catch up to their Spanish peers in reading comprehension. Rather, the real differences in difficulty derive from two sources: hardened L1 language habits trying to cope with contrasting L2 habits; and unfamiliarity with unique L2 characteristics causing faulty expectations. It would seem that effective L2 teaching and learning must take these two sources of difficulty into consideration. The author feels that the latter (faulty expectations) causes the greatest difficulty, making effective teaching and learning somewhat different for each given foreign language. Examples from Chinese and other languages are presented.

Keywords: learning different languages, language learning difficulties, faulty language expectations

Procedia PDF Downloads 533
9097 Literature Review: Adversarial Machine Learning Defense in Malware Detection

Authors: Leidy M. Aldana, Jorge E. Camargo

Abstract:

Adversarial Machine Learning has gained importance in recent years as Cybersecurity has gained too, especially malware, it has affected different entities and people in recent years. This paper shows a literature review about defense methods created to prevent adversarial machine learning attacks, firstable it shows an introduction about the context and the description of some terms, in the results section some of the attacks are described, focusing on detecting adversarial examples before coming to the machine learning algorithm and showing other categories that exist in defense. A method with five steps is proposed in the method section in order to define a way to make the literature review; in addition, this paper summarizes the contributions in this research field in the last seven years to identify research directions in this area. About the findings, the category with least quantity of challenges in defense is the Detection of adversarial examples being this one a viable research route with the adaptive approach in attack and defense.

Keywords: Malware, adversarial, machine learning, defense, attack

Procedia PDF Downloads 63
9096 E-Learning Platform for School Kids

Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.

Abstract:

E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.

Keywords: math, education games, e-learning platform, artificial intelligence

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9095 The Effects of Self-Graphing on the Reading Fluency of an Elementary Student with Learning Disabilities

Authors: Matthias Grünke

Abstract:

In this single-case study, we evaluated the effects of a self-graphing intervention to help students improve their reading fluency. Our participant was a 10-year-old girl with a suspected learning disability in reading. We applied an ABAB reversal design to test the efficacy of our approach. The dependent measure was the number of correctly read words from a children’s book within five minutes. Our participant recorded her daily performance using a simple line diagram. Results indicate that her reading rate improved simultaneously with the intervention and dropped as soon as the treatment was suspended. The findings give reasons for optimism that our simple strategy can be a very effective tool in supporting students with learning disabilities to boost their reading fluency.

Keywords: single-case study, learning disabilities, elementary education, reading problems, reading fluency

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9094 Emotional Labour and Employee Performance Appraisal: The Missing Link in Some Hotels in South East Nigeria

Authors: Polycarp Igbojekwe

Abstract:

The main objective of this study was to determine if emotional labour has become a criterion in performance appraisal, job description, selection, and training schemes in the hotel industry in Nigeria. Our main assumption was that majority of hotel organizations have not built emotional labour into their human resources management schemes. Data were gathered by the use of structured questionnaires designed in Likert format, and interviews. The focus group was managers of the selected hotels. Analyses revealed that majority of the hotels have not built emotional labour into their human resources schemes particularly in the 1, 2, and 3-star hotels. It was observed that service employees of 1, 2, and 3-star hotels have not been adequately trained to perform emotional labour; a critical factor in quality service delivery. Managers of 1, 2, and 3-star hotels have not given serious thought to emotional labour as a critical factor in quality service delivery. The study revealed that suitability of an individual’s characteristics is not being considered as a criterion for selection and performance appraisal for service employees. The implication of this is that, person-job-fit is not seriously considered. It was observed that there has been a disconnect between required emotional competency, its recognition, evaluation, and training. Based on the findings of this study, it is concluded that selection, training, job description and performance appraisal instruments in use in hotels in Nigeria are inadequate. Human resource implications of the findings in this study are presented. It is recommended that hotel organizations should re-design and plan the emotional content and context of their human resources practices to reflect the emotional demands of front line jobs in the hotel industry and the crucial role emotional labour plays during service encounters.

Keywords: emotional labour, employee selection, job description, performance appraisal, person-job-fit, employee compensation

Procedia PDF Downloads 191
9093 Developing Commitment to Change in Egyptian Modern Bureaucracies

Authors: Nada Basset

Abstract:

Purpose: To examine the nature of the civil service sector as an employer through identifying the likely ways to develop employees’ commitment towards change in the civil service sector. Design/Methodology/Approach: a qualitative research approach was followed. Data was collected via a triangulation of interviews, non-participant observation and archival documents analysis. Non-probability sampling took place with a case-study method applied on a sample of 33 civil servants working in the Egyptian Ministry of State for Administrative Development (MSAD) which is the civil service entity acting as the change agent responsible for managing the government administrative reforms plan in the civil service sector. All study participants were actually working in one of the change projects/programmes and had a minimum of 12 months of service in the civil service. Interviews were digitally recorded and transcribed in the form of MS-Word documents, and data transcripts were analyzed manually using MS-Excel worksheets and main research themes were developed and statistics drawn using those Excel worksheets. Findings: The results demonstrate that developing the civil servant’s commitment towards change may require a number of suggested solutions like (1) employee involvement and participation in the planning and implementation processes, (2) linking the employee support to change to some tangible rewards and incentives, (3) appointing some inspirational change leaders that should act as role models, and (4) as a last resort, enforcing employee’s commitment towards change by coercion and authoritarianism. Practical Implications: it is clear that civil servants’ lack of organizational commitment is not directly related to their level of commitment towards change. The research findings showed that civil servants’ commitment towards change can be raised and promoted by getting them involved in the planning and implementation processes, as this develops some sense of belongingness and ownership, thus there is a fair chance that low organizationally committed civil servants can develop high commitment towards change; given they are provided a favorable environment where they are invited to participate and get involved into the move of change. Originality/Value: the research addresses a relatively new area of ‘developing organizational commitment in modern bureaucracies’ by virtue of investigating the levels of civil servants’ commitment towards their jobs and/or organizations -on one hand- and suggesting different ways of developing their commitment towards administrative reform and change initiatives in the Egyptian civil service sector.

Keywords: change, commitment, Egypt, bureaucracy

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9092 Investigation of Delivery of Triple Play Service in GE-PON Fiber to the Home Network

Authors: Anurag Sharma, Dinesh Kumar, Rahul Malhotra, Manoj Kumar

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 733
9091 Extension Services' Needs of Small Farmers in Biliran Province, Philippines

Authors: Mario C. Nierras

Abstract:

This study aimed to determine the extension services’ needs of small farmers in Biliran province, Philippines. It also sought to find out other issues/concerns of the small farmers. Extension services’ needs of small farmers were gathered through personal interviewing and observational analysis of randomly-selected small farmers in Biliran, Philippines. Biliran small farmers extension services’ needs include: raising fruits, raising legumes, raising vegetables, raising swine, raising cattle, and raising chicken (as priority broad skills). For the specific skills, diagnosing symptoms on fertilizer deficiencies, controlling plant pests and diseases, diagnosing signs on specific pest and disease damage, controlling animal pests and diseases, and doing artificial insemination were the priority skills. They considered an on-farm trial of new technology as most needed to be coupled with industry and quality-orientedness, as positive behaviors needed in farming success. The farmers still adhere to the so-called wait-and-see attitude, thus they are more convinced to follow a particular technology if they see a concrete result of the introduced changes. Technical needs prioritization of Biliran small farmers showed that they have a real need for crop and animal production skills to include the other issues/concerns. Extension service program planning for small farmers should be patterned after their technical needs giving due attention to some issues/concerns so that extension work could deliver the right skills for the right needs of the farmers.

Keywords: extension, extension service, extension service needs, extension service program, farmers, small farmers, marginal farmers

Procedia PDF Downloads 436
9090 Banking and Accounting Analysis Researches Effect on Environment and Income

Authors: Gerges Samaan Henin Abdalla

Abstract:

New methods of providing banking services to the customer have been introduced, such as online banking. Banks have begun to consider electronic banking (e-banking) as a way to replace some traditional branch functions by using the Internet as a new distribution channel. Some consumers have at least one account at multiple banks and access these accounts through online banking. To check their current net worth, clients need to log into each of their accounts, get detailed information, and work toward consolidation. Not only is it time consuming, but it is also a repeatable activity with a certain frequency. To solve this problem, the concept of account aggregation was added as a solution. Account consolidation in e-banking as a form of electronic banking appears to build a stronger relationship with customers. An account linking service is generally referred to as a service that allows customers to manage their bank accounts held at different institutions via a common online banking platform that places a high priority on security and data protection. The article provides an overview of the account aggregation approach in e-banking as a new service in the area of e-banking.

Keywords: compatibility, complexity, mobile banking, observation, risk banking technology, Internet banks, modernization of banks, banks, account aggregation, security, enterprise development

Procedia PDF Downloads 57
9089 Exploring Students’ Self-Evaluation on Their Learning Outcomes through an Integrated Cumulative Grade Point Average Reporting Mechanism

Authors: Suriyani Ariffin, Nor Aziah Alias, Khairil Iskandar Othman, Haslinda Yusoff

Abstract:

An Integrated Cumulative Grade Point Average (iCGPA) is a mechanism and strategy to ensure the curriculum of an academic programme is constructively aligned to the expected learning outcomes and student performance based on the attainment of those learning outcomes that is reported objectively in a spider web. Much effort and time has been spent to develop a viable mechanism and trains academics to utilize the platform for reporting. The question is: How well do learners conceive the idea of their achievement via iCGPA and whether quality learner attributes have been nurtured through the iCGPA mechanism? This paper presents the architecture of an integrated CGPA mechanism purported to address a holistic evaluation from the evaluation of courses learning outcomes to aligned programme learning outcomes attainment. The paper then discusses the students’ understanding of the mechanism and evaluation of their achievement from the generated spider web. A set of questionnaires were distributed to a group of students with iCGPA reporting and frequency analysis was used to compare the perspectives of students on their performance. In addition, the questionnaire also explored how they conceive the idea of an integrated, holistic reporting and how it generates their motivation to improve. The iCGPA group was found to be receptive to what they have achieved throughout their study period. They agreed that the achievement level generated from their spider web allows them to develop intervention and enhance the programme learning outcomes before they graduate.

Keywords: learning outcomes attainment, iCGPA, programme learning outcomes, spider web, iCGPA reporting skills

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9088 Unsupervised Images Generation Based on Sloan Digital Sky Survey with Deep Convolutional Generative Neural Networks

Authors: Guanghua Zhang, Fubao Wang, Weijun Duan

Abstract:

Convolution neural network (CNN) has attracted more and more attention on recent years. Especially in the field of computer vision and image classification. However, unsupervised learning with CNN has received less attention than supervised learning. In this work, we use a new powerful tool which is deep convolutional generative adversarial networks (DCGANs) to generate images from Sloan Digital Sky Survey. Training by various star and galaxy images, it shows that both the generator and the discriminator are good for unsupervised learning. In this paper, we also took several experiments to choose the best value for hyper-parameters and which could help to stabilize the training process and promise a good quality of the output.

Keywords: convolution neural network, discriminator, generator, unsupervised learning

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9087 Combining Shallow and Deep Unsupervised Machine Learning Techniques to Detect Bad Actors in Complex Datasets

Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

Abstract:

Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

Procedia PDF Downloads 94
9086 Performance Comparison of Situation-Aware Models for Activating Robot Vacuum Cleaner in a Smart Home

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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9085 Effectiveness of Active Learning in Social Science Courses at Japanese Universities

Authors: Kumiko Inagaki

Abstract:

In recent, years, Japanese universities have begun to face a dilemma: more than half of all high school graduates go on to attend an institution of higher learning, overwhelming Japanese universities accustomed to small student bodies. These universities have been forced to embrace qualitative changes to accommodate the increased number and diversity of students who enter their establishments, students who differ in their motivations for learning, their levels of eagerness to learn, and their perspectives on the future. One of these changes is an increase in awareness among Japanese educators of the importance of active learning, which deepens students’ understanding of course material through a range of activities, including writing, speaking, thinking, and presenting, in addition to conventional “passive learning” methods such as listening to a one-way lecture.  The purpose of this study is to examine the effectiveness of the teaching method adapted to improve active learning. A teaching method designed to promote active learning was implemented in a social science course at one of the most popular universities in Japan. A questionnaire using a five-point response format was given to students in 2,305 courses throughout the university to evaluate the effectiveness of the method based on the following measures: ① the ratio of students who were motivated to attend the classes, ② the rate at which students learned new information, and ③ the teaching method adopted in the classes. The results of this study show that the percentage of students who attended the active learning course eagerly, and the rate of new knowledge acquired through the course, both exceeded the average for the university, the department, and the subject area of social science. In addition, there are strong correlations between teaching method and student motivation and between teaching method and knowledge acquisition rate. These results indicate that the active learning teaching method was effectively implemented and that it may improve student eagerness to attend class and motivation to learn.

Keywords: active learning, Japanese university, teaching method, university education

Procedia PDF Downloads 195
9084 Artificial Intelligent-Based Approaches for Task ‎Offloading, ‎Resource ‎Allocation and Service ‎Placement of ‎Internet of Things ‎Applications: State of the Art

Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib‎

Abstract:

In order to support the continued growth, critical latency of ‎IoT ‎applications, and ‎various obstacles of traditional data centers, ‎mobile edge ‎computing (MEC) has ‎emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. ‎By adopting a MEC structure, IoT applications could be executed ‎locally, on ‎an edge server, different fog nodes, or distant cloud ‎data centers. However, we are ‎often ‎faced with wanting to optimize conflicting criteria such as ‎minimizing energy ‎consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge ‎devices and trying to ‎keep ‎high performance (reducing ‎response time, increasing throughput and service availability) ‎at the same ‎time‎. Achieving one goal may affect the other, making task offloading (TO), ‎resource allocation (RA), and service placement (SP) complex ‎processes. ‎It is a nontrivial multi-objective optimization ‎problem ‎to study the trade-off between conflicting criteria. ‎The paper provides a survey on different TO, SP, and RA recent multi-‎objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications‎.

Keywords: mobile edge computing, multi-objective optimization, artificial ‎intelligence ‎approaches, task offloading, resource allocation, ‎ service placement

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9083 Mentor and Mentee Based Learning

Authors: Erhan Eroğlu

Abstract:

This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

Procedia PDF Downloads 228
9082 A Case Study of Deep Learning for Disease Detection in Crops

Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

Abstract:

In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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9081 Hacking the Spatial Limitations in Bridging Virtual and Traditional Teaching Methodologies in Sri Lanka

Authors: Manuela Nayantara Jeyaraj

Abstract:

Having moved into the 21st century, it is way past being arguable that innovative technology needs to be incorporated into conventional classroom teaching. Though the Western world has found presumable success in achieving this, it is still a concept under battle in developing countries such as Sri Lanka. Reaching the acme of implementing interactive virtual learning within classrooms is a struggling idealistic fascination within the island. In order to overcome this problem, this study is set to reveal facts that limit the implementation of virtual, interactive learning within the school classrooms and provide hacks that could prove the augmented use of the Virtual World to enhance teaching and learning experiences. As each classroom moves along with the usage of technology to fulfill its functionalities, a few intense hacks provided will build the administrative onuses on a virtual system. These hacks may divulge barriers based on social conventions, financial boundaries, digital literacy, intellectual capacity of the staff, and highlight the impediments in introducing students to an interactive virtual learning environment and thereby provide the necessary actions or changes to be made to succeed and march along in creating an intellectual society built on virtual learning and lifestyle. This digital learning environment will be composed of multimedia presentations, trivia and pop quizzes conducted on a GUI, assessments conducted via a virtual system, records maintained on a database, etc. The ultimate objective of this study could enhance every child's basic learning environment; hence, diminishing the digital divide that exists in certain communities.

Keywords: digital divide, digital learning, digitization, Sri Lanka, teaching methodologies

Procedia PDF Downloads 353
9080 Multi-Classification Deep Learning Model for Diagnosing Different Chest Diseases

Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

Abstract:

Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

Procedia PDF Downloads 92
9079 Spontaneous and Posed Smile Detection: Deep Learning, Traditional Machine Learning, and Human Performance

Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

Abstract:

A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

Procedia PDF Downloads 125
9078 Relationship between Learning Methods and Learning Outcomes: Focusing on Discussions in Learning

Authors: Jaeseo Lim, Jooyong Park

Abstract:

Although there is ample evidence that student involvement enhances learning, college education is still mainly centered on lectures. However, in recent years, the effectiveness of discussions and the use of collective intelligence have attracted considerable attention. This study intends to examine the empirical effects of discussions on learning outcomes in various conditions. Eighty eight college students participated in the study and were randomly assigned to three groups. Group 1 was told to review material after a lecture, as in a traditional lecture-centered class. Students were given time to review the material for themselves after watching the lecture in a video clip. Group 2 participated in a discussion in groups of three or four after watching the lecture. Group 3 participated in a discussion after studying on their own. Unlike the previous two groups, students in Group 3 did not watch the lecture. The participants in the three groups were tested after studying. The test questions consisted of memorization problems, comprehension problems, and application problems. The results showed that the groups where students participated in discussions had significantly higher test scores. Moreover, the group where students studied on their own did better than that where students watched a lecture. Thus discussions are shown to be effective for enhancing learning. In particular, discussions seem to play a role in preparing students to solve application problems. This is a preliminary study and other age groups and various academic subjects need to be examined in order to generalize these findings. We also plan to investigate what kind of support is needed to facilitate discussions.

Keywords: discussions, education, learning, lecture, test

Procedia PDF Downloads 176
9077 Deep Reinforcement Learning Model for Autonomous Driving

Authors: Boumaraf Malak

Abstract:

The development of intelligent transportation systems (ITS) and artificial intelligence (AI) are spurring us to pave the way for the widespread adoption of autonomous vehicles (AVs). This is open again opportunities for smart roads, smart traffic safety, and mobility comfort. A highly intelligent decision-making system is essential for autonomous driving around dense, dynamic objects. It must be able to handle complex road geometry and topology, as well as complex multiagent interactions, and closely follow higher-level commands such as routing information. Autonomous vehicles have become a very hot research topic in recent years due to their significant ability to reduce traffic accidents and personal injuries. Using new artificial intelligence-based technologies handles important functions in scene understanding, motion planning, decision making, vehicle control, social behavior, and communication for AV. This paper focuses only on deep reinforcement learning-based methods; it does not include traditional (flat) planar techniques, which have been the subject of extensive research in the past because reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. The DRL algorithm used so far found solutions to the four main problems of autonomous driving; in our paper, we highlight the challenges and point to possible future research directions.

Keywords: deep reinforcement learning, autonomous driving, deep deterministic policy gradient, deep Q-learning

Procedia PDF Downloads 85
9076 Machine Learning Approach for Mutation Testing

Authors: Michael Stewart

Abstract:

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

Procedia PDF Downloads 198
9075 The Risk of Deaths from Viral Hepatitis among the Female Workers in the Beauty Service Industry

Authors: Byeongju Choi, Sanggil Lee, Kyung-Eun Lee

Abstract:

Introduction: In the republic of Korea, the number of workers in the beauty industry has been increasing. Because the prevalence of hepatitis B carriers in Korea is higher than in other countries, the risk of blood-borne infection including viral hepatitis B and C, among the workers by using the sharp and contaminated instruments during procedure can be expected among beauty salon workers. However, the health care policies for the workers to prevent the blood-borne infection are not established due to the lack of evidences. Moreover, the workers in hair and nail salon were mostly employed at small businesses, where national mandatory systems or policies for workers’ health management are not applied. In this study, the risk of the viral hepatitis B and C from the job experiencing the hair and nail procedures in the mortality was assessed. Method: We conducted a retrospective review of the job histories and causes of death in the female deaths from 2006-2016. 132,744 of female deaths who had one more job experiences during their lifetime were included in this study. Job histories were assessed using the employment insurance database in Korea Employment Information Service (KEIS) and the causes of death were in death statistics produced by Statistics Korea. Case group (n= 666) who died from viral hepatitis was classified the death having record involved in ‘B15-B19’ as a cause of deaths based on Korean Standard Classification of Diseases(KCD) with the deaths from other causes, control group (n=132,078). The group of the workers in the beauty service industry were defined as the employees who had ever worked in the industry coded as ‘9611’ based on Korea Standard Industry Classification (KSIC) and others were others. Other than job histories, birth year, marital status, education level were investigated from the death statistics. Multiple logistic regression analysis were used to assess the risk of deaths from viral hepatitis in the case and control group. Result: The number of the deaths having ever job experiences at the hair and nail salon was 255. After adjusting confounders of age, marital status and education, the odds ratio(OR) for deaths from viral hepatitis was quite high in the group having experiences with working in the beauty service industry with 3.14(95% confidence interval(CI) 1.00-9.87). Other associated factors with increasing the risk of deaths from viral hepatitis were low education level(OR=1.34, 95% CI 1.04-1.73), married women (OR=1.42, 95% CI 1.02-1.97). Conclusion: The risk of deaths from viral hepatitis were high in the workers in the beauty service industry but not statistically significant, which might attributed from the small number of workers in beauty service industry. It was likely that the number of workers in beauty service industry could be underestimated due to their temporary job position. Further studies evaluating the status and the incidence of viral infection among the workers with consideration of the vertical transmission would be required.

Keywords: beauty service, viral hepatitis, blood-borne infection, viral infection

Procedia PDF Downloads 138
9074 Circular Economy in Social Practice in Response to Social Needs: Community Actions Versus Government Policy

Authors: Sai-Kit Choi

Abstract:

While traditional social services heavily depended on Government funding and support, there were always time lag, and resources mismatch with the fast growing and changing social needs. This study aims at investigating the effectiveness of implementing Circular Economy concept in a social service setting with comparison to Government Policy in response to social needs in 3 areas: response time, suitability, and community participation. To investigate the effectiveness of implementing Circular Economy concept in a social service setting, a real service model, a community resources sharing platform, was set up and statistics of the first 6 months’ operation data were used as comparison with traditional social services. Literature review was conducted as a reference basis of traditional social services under Government Policy. Case studies were conducted to provide the qualitative perspectives of the innovative approach. The results suggest that the Circular Economy model showed extraordinarily high level of community participation. In addition, it could utilize community resources in response precisely to the burning social needs. On the other hand, the available resources were unstable when comparing to those services supported by Government funding. The research team concluded that Circular Economy has high potential in applications in social service, especially in certain areas, such as resources sharing platform. Notwithstanding, it should be aware of the stability of resources when the services targeted to support some crucial needs.

Keywords: circular economy, social innovation, community participation, sharing economy, social response

Procedia PDF Downloads 113
9073 Use of Smartphone in Practical Classes to Facilitate Teaching and Learning of Microscopic Analysis and Interpretation of Tissues Sections

Authors: Lise P. Labéjof, Krisnayne S. Ribeiro, Nicolle P. dos Santos

Abstract:

An unrecorded experiment of use of the smartphone as a tool for practical classes of histology is presented in this article. Behavior, learning of the students of three science courses at the University were analyzed and compared as well as the mode of teaching of this discipline and the appreciation of the students, using either digital photographs taken by phone or drawings for record microscopic observations, analyze and interpret histological sections of human or animal tissues.

Keywords: cell phone, digital micrographies, learning of sciences, teaching practices

Procedia PDF Downloads 596