Search results for: community learning and development

Authors: Orathai Srithongtham, Ploypailin Mekathepakorn, Tossaphong Buraman, Pontida Moonpradap, Rungrueng Kitpati, Chulapon Kratet, Worayuth Nak-ai, Suwaree Charoenmukkayanan, Peeranuch Keawkanya

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The COVID-19 pandemic was effect to the health security of the Thai people. The PHEM principle was essential to the surveillance, prevention, and control of COVID-19. This study aimed to present the process of prevention and control of COVID-19 from February 29, 2021- April 30, 2022, and the factors and conditions influent the successful outcome. The study areas were three provinces. The target group was 37 people, composed of public health personnel. The data was collected in-depth, and group interviews followed the non-structure interview guide and were analyzed by content analysis. The components of COVID-19 prevention and control were found in the process of PHEM as follows; 1) Emergency Operation Center (EOC) with an incidence command system (ICS) from the district to provincial level and to propose the provincial measure, 2) Provincial Communicable Disease Committee (PCDC) to decide the provincial measure 3) The measure for surveillance, prevention, control, and treatment of COVID-19, and 4) outcomes and best practices for surveillance and control of COVID-19. The success factors of 4S and EC were as follows; Space: prepare the quarantine (HQ, LQ), Cohort Ward (CW), field hospital, and community isolation and home isolation to face with the patient and risky group, Staff network from various organization and group cover the community leader and Health Volunteer (HV), Stuff the management and sharing of the medical and non-medical equipment, System of Covid-19 respond were EOC, ICS, Joint Investigation Team (JIT) and Communicable Disease Control Unit (CDCU) for monitoring the real-time of surveillance and control of COVID-19 output, Environment management in hospital and the community with Infections Control (IC) principle, and Culture in term of social capital on “the relationship of Isan people” supported the patient provide the good care and support. The structure of PHEM, Isan’s Culture, and good preparation was a significant factor in the three provinces.

Keywords: public health, emergency management, covid-19, pandemic

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Authors: Ugiri Ejikeme

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In an executive summary, UNESCO describes Framework for Cultural Statistics as a tool for organizing cultural statistics both nationally and internationally. This is based on conceptual foundation and a common understanding of culture that will enable the measurement of a wide range of cultural expressions. This means therefore that cultural expression in whatever guise has the potentiality of contributing reasonably to the development of a given society. The paper looked into the various tangible and intangible cultures in Imo State of Nigeria. Due to government’s insensitivity, there is need to remind ourselves of the need to pay adequate attention to the cultural heritage bequeathed to us by our forefathers for the sake of posterity. Documenting this information in written form therefore becomes imperative. The study concludes that culture if developed, could reasonably contribute to economic and social growth of the society.

Keywords: detonating culture, statistics and development, Imo State, Nigeria

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Christiane H. Kellner, Sarah Reker

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The UN-Convention on the Rights of Persons with Disabilities, which Germany also ratified, postulates the necessity of user-centred design, especially when it comes to evaluating the individual needs and wishes of all citizens. Therefore, a multidimensional approach is required. Based on this insight, the structure of the town-like centre in Schönbrunn - a large residential complex and service provider for persons with disabilities in the outskirts of Munich - will be remodelled to open up the community to all people as well as transform social space. This strategy should lead to more equal opportunities and open the way for a much more diverse community. The research project “Index for participation development and quality of life for persons with disabilities” (TeLe-Index, 2014-2016), which is anchored at the Technische Universität München in Munich and at the Franziskuswerk Schönbrunn supports this transformation process called “Vision 2030”. In this context, we have provided academic supervision and support for three projects (the construction of a new school, inclusive housing for children and teenagers with disabilities and the professionalization of employees using person-centred planning). Since we cannot present all the issues of the umbrella-project within the conference framework, we will be focusing on one sub-project more in-depth, namely “The Person-Centred Think Tank” [Arbeitskreis Personenzentriertes Denken; PZD]. In the context of person-centred thinking (PCT), persons with disabilities are encouraged to (re)gain or retain control of their lives through the development of new choice options and the validation of individual lifestyles. PCT should thus foster and support both participation and quality of life. The project aims to establish PCT as a fundamental approach for both employees and persons with disabilities in the institution through in-house training for the staff and, subsequently, training for users. Hence, for the academic support and supervision team, the questions arising from this venture can be summed up as follows: (1) has PCT already gained a foothold at the Franziskuswerk Schönbrunn? And (2) how does it affect the interaction with persons with disabilities and how does it influence the latter’s everyday life? According to the holistic approach described above, the target groups for this study are both the staff and the users of the institution. Initially, we planned to implement the group discussion method for both target-groups. However, in the course of a pretest with persons with intellectual disabilities, it became clear that this type of interview, with hardly any external structuring, provided only limited feedback. In contrast, when the discussions were moderated, there was more interaction and dialogue between the interlocutors. Therefore, for this target-group, we introduced structured group interviews. The insights we have obtained until now will enable us to present the intermediary results of our evaluation. We analysed and evaluated the group interviews and discussions with the help of qualitative content analysis according to Mayring in order to obtain information about users’ quality of life. We sorted out the statements relating to quality of life obtained during the group interviews into three dimensions: subjective wellbeing, self-determination and participation. Nevertheless, the majority of statements were related to subjective wellbeing and self-determination. Thus, especially the limited feedback on participation clearly demonstrates that the lives of most users do not take place beyond the confines of the institution. A number of statements highlighted the fact that PCT is anchored in the everyday interactions within the groups. However, the implementation and fostering of PCT on a broader level could not be detected and thus remain further aims of the project. The additional interviews we have planned should validate the results obtained until now and open up new perspectives.

Keywords: person-centered thinking, research with persons with disabilities, residential complex and service provider, participation, self-determination.

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Authors: T. A. Ajiboye

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This study examines the effects of health education programme on knowledge and prevention of cerebrovascular disease among hypertensive patients in University College Hospital, Ibadan. A quasi-experimental design was adopted for the study. 100 hypertensive patients were conveniently selected from general outpatient department in UCH. Data generated were analyzed using ANOVA at 0.05 alpha levels. The findings of the study revealed that health education programme significantly influenced both the knowledge of hypertensive patients (F=22.70; DF=1/99; p < .05) and their attitude (F=10.377; DF=1/99; p < .05) on cerebrovascular disease. Findings also discovered that health education programme significantly reduce the complication of hypertension to cerebrovascular disease (F= 16.41; DF=7/286; p < 0.05) among the hypertensive patients at UCH. Based on the findings, it is recommended that hypertensive patients should relieve themselves from stress, engage themselves on regular exercises, compliance with drug and diet regimes coupled with keeping up of regular appointment. Government should design health information that will center on hypertension and cerebrovascular disease so as to keep health and community development problems to the barest minimum. Finally, there should be provision of social amenities and recreational centers, as this will prevents hypertension problems.

Keywords: cerebrovascular disease, effectiveness, health education, hypertension, knowledge, prevention

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Authors: Marla Wendy Spergel

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The purpose of this qualitative study is to showcase graduated high school students’ to voice on the impact past teachers had on their motivation to learn, and if this impact has affected their post-high-school lives. Through a focus group strategy, 21 graduated high school alumni participated in three separate focus groups. Participants discussed their former teacher’s emotional intelligence skills, which influenced their motivation to learn or not. A focused review of the literature revealed that teachers are a major factor in a student’s motivation to learn. This research was guided by Bandura’s Social Cognitive Theory of Motivation and constructs related to learning and motivation from Carl Rogers’ Humanistic Views of Personality, and from Brain-Based Learning perspectives with a major focus on the area of Emotional Intelligence. Findings revealed that the majority of participants identified teachers who most motivated them to learn and demonstrated skills associated with emotional intelligence. An important and disturbing finding relates to the saliency of negative experiences. Further work is recommended to expand this line of study in Higher Education, perform a long-term study to better gain insight into long-term benefits attributable to experiencing positive teachers, study the negative impact teachers have on students’ motivation to learn, specifically focusing on student anxiety and acquired helplessness.

Keywords: emotional intelligence, learning, motivation, pedagogy

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Authors: Duong Van Thanh

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Artificial Intelligence (AI) has been recently a new trend in Higher Education systems globally as well as in the Vietnamese Higher Education. This study explores the benefits and challenges in applications of AI in 02 selected universities, ie. Vietnam National Universities in Hanoi Capital and the University of Economics in Ho Chi Minh City. Particularly, this paper focuses on how the ethics of Artificial Intelligence have been addressed among faculty members at these two universities. The AI ethical issues include the access and inclusion, privacy and security, transparency and accountability. AI-powered educational technology has the potential to improve access and inclusion for students with disabilities or other learning needs. However, there is a risk that AI-based systems may not be accessible to all students and may even exacerbate existing inequalities. AI applications can be opaque and difficult to understand, making it challenging to hold them accountable for their decisions and actions. It is important to consider the benefits that adopting AI-systems bring to the institutions, teaching, and learning. And it is equally important to recognize the drawbacks of using AI in education and to take the necessary steps to mitigate any negative impact. The results of this study present a critical concern in higher education in Vietnam, where AI systems may be used to make important decisions about students’ learning and academic progress. The authors of this study attempt to make some recommendation that the AI-system in higher education system is frequently checked by a human in charge to verify that everything is working as it should or if the system needs some retraining or adjustments.

Keywords: artificial intelligence, ethics, challenges, vietnam

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Authors: Juanita, B. Kombaitan, Iwan Pratoyo Kusumantoro

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The traditional mode is a non-motorized vehicle powered by human or animal power. The objective of the study was to define the strategy of using traditional modes by the framework of sustainable urban transport in support of urban tourism activities. The study of the traditional mode does not include a modified mode using the engine power as motor tricycles are often called ‘bentor ‘in Indonesia. The use of non-motorized traditional mode in Indonesia has begun to shift, and its use began to be eliminated by the change of propulsion using the machine. In an effort to push back the use of traditional mode one of them with tourism activities. Strategies for the use of traditional modes within the framework of sustainable urban transport are seen from three dimensions: social, economic and environmental. The social dimension related to accessibility and livability, an economic dimension related to traditional modes can promote products and tourist attractions, while the environmental dimension related to the needs of the users/groups with respect to safety, comfort. The traditional mode is rarely noticed by the policy makers, and public opinion in its use needs attention. The involvement of policy-making between stakeholders and the community is needed in the development of sustainable traditional mode strategies in support of urban tourism activities.

Keywords: traditional mode, sustainable, urban, transportation

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Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

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Authors: Md. Wasiul Islam, Md. Jamius Shams Sowrov

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The Sundarbans is the largest single tract of mangrove forest in the world. This is located in the southwest corner of Bangladesh. This is a unique ecosystem which is a great breeding and nursing ground for a great biodiversity. It supports the livelihood of about 3.5 million coastal dwellers and also protects the coastal belt and inland areas from various natural calamities. Historically, the management of the Sundarbans was controlled by the Bangladesh Forest Department following top-down approach without the involvement of local communities. Such fence and fining-based blue-print approach was not effective to protect the forest which caused Sundarbans to degrade severely in the recent past. Fifty percent of the total tree cover has been lost in the last 30 years. Therefore, local multi-stakeholder based bottom-up co-management approach was introduced at some of the parts of the Sundarbans in 2006 to improve the biodiversity status by enhancing the protection level of the forest. Various co-management organizations were introduced under co-management approach where the local community people could actively involve in various activities related to the management and welfare of the Sundarbans including the decision-making process to achieve the goal. From this backdrop, the objective of the study was to assess the performance of co-management organizations to facilitate sustainable management of the Sundarbans mangrove forests. The qualitative study followed face-to-face interview to collect data using two sets of semi-structured questionnaires. A total of 40 respondents participated in the research that was from eight villagers under two forest ranges. 32 representatives from the local communities as well as 8 official representatives involved in co-management approach were interviewed using snowball sampling technique. The study shows that the co-management approach improved governance system of the Sundarbans through active participation of the local community people and their interactions with the officials via the platform of co-management organizations. It facilitated accountability and transparency system to some extent through following some formal and informal rules and regulations. It also improved the power structure of the management process by fostering local empowerment process particularly the women. Moreover, people were able to learn from their interactions with and within the co-management organizations as well as interventions improved environmental awareness and promoted social learning. The respondents considered good governance as the most important factor for achieving the goal of sustainable management and biodiversity conservation of the Sundarbans. The success of co-management planning process also depends on the active and functional participation of different stakeholders including the local communities where co-management organizations were considered as the most functional platform. However, the governance system was also facing various challenges which resulted in barriers to the sustainable management of the Sundarbans mangrove forest. But still there were some members involved in illegal forest operations and created obstacles against sustainable management of the Sundarbans. Respondents recommended greater patronization from the government, financial and logistic incentives for alternative income generation opportunities with effective participatory monitoring and evaluation system to improve sustainable management of the Sundarbans.

Keywords: Bangladesh, co-management approach, co-management organizations, governance, Sundarbans, sustainable management

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Authors: Papazafeiropoulou Olga

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The first Greek expatriates created centers of culture in Australia from the beginning of the 19th century, in the large urban centers of the cities (Sydney, Melbourne, Brisbane, Adelaide, Perth). They created community theater according to their cultural standards, their socio-spiritual progress and development and their relationship with theatrical creation. At the same time, the Greek immigrants of the small towns and, especially of NSW, created their own temples of art, rebuilding theater buildings (theatres and cinemas), many of which are preserved to this day. Hellenism in Australia operated in the field of entertainment, reflecting the currents of the time and the global spread of mechanical developments. The Australian-born young people of the parish, as well as pioneering expatriates joined the theater and cinematographic events of Australia. They mobilized beyond the narrow confines of the parish, gaining recognition and projecting Hellenism to the Australian establishment. G. Paizis (A. Haggard), Dimitrios Ioannidis, Stelios Saligaros, Angela Parselli, Sofia Pergamali, Raoul Kardamatis, Adam Tavlaridis, John Lemonne, Rudy Ricco, Artemis Linou, distinguished themselves by writing their names in the history of Australian theater, as they served consequently the theatrical process, elevating the sentiment of the expatriate during the early years of its settlement in the Australian Commonwealth until 1950.

Keywords: greeks, commubity, australia, theatre

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Authors: Ahcene Habbi, Yassine Boudouaoui

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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: automatic design, learning, fuzzy rules, hybrid, swarm optimization

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Authors: Edward Shizha, Edward Makwarimba

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This literature review explores current research on the educational strengths and barriers of newcomer and refugee youth in Canada. Canada’s shift in immigration policy in the past three decades, from Europe to Asian and African countries as source continents of recent immigrants to Canada, has tremendously increased the ethnic, linguistic, cultural and religious diversity of the population, including that of students in its education system. Over 18% of the country’s population was born in another country, of which 70% are visible minorities. There has been an increase in admitted immigrants and refugees, with a total of 226,203 between July 2020 and June 2021. Newcomer parents and their children in all major destination countries, including Canada, face tremendous challenges, including racism and discrimination, lack of English language skills, poverty, income inequality, unemployment, and underemployment. They face additional challenges, including discrimination against those who cannot speak the official languages, English or French. The severity of the challenges depends on several intersectional factors, including immigrant status (asylum seeker, refugee, or immigrant), age, gender, level of education and others. Through the lens of intersectionality as an explanatory perspective, this literature review examines the educational attainment and outcomes of newcomer and refugee youth in Canada in order to understand their educational needs, educational barriers and strengths. Newcomer youths’ experiences are shaped by numerous intersectional and interconnected sociocultural, sociopolitical, and socioeconomic factors—including gender, migration status, racialized status, ethnicity, socioeconomic class, sexual minority status, age, race—that produce and perpetuate their disadvantage. According to research, immigrants and refugees from visible minority ethnic backgrounds experience exclusions more than newcomers from other backgrounds and groups from the mainstream population. For many immigrant parents, migration provides financial and educational opportunities for their children. Yet, when attending school, newcomer and refugee youth face unique challenges related to racism and discrimination, negative attitudes and stereotypes from teachers and other school authorities, language learning and proficiency, differing levels of acculturation, and different cultural views of the role of parents in relation to teachers and school, and unfamiliarity with the social or school context in Canada. Recognizing discrepancies in educational attainment of newcomer and refugee youth based on their race and immigrant status, the paper develops insights into existing research and data gaps related to educational strengths and challenges for visible minority newcomer youth in Canada. The paper concludes that the educational successes or failures of the newcomer and refugee youth and their settlement and integration into the school system in Canada may depend on where their families settle, the attitudes of the host community and the school officials (teachers, guidance counsellors and school administrators) after-school support programs and their own set of coping mechanisms. Conceivably a unique approach to after-school programming should provide learning supports and opportunities that consider newcomer and refugee youth’s needs, experiences, backgrounds and circumstances. This support is likely to translate into significant academic and psychological well-being of newcomer students.

Keywords: deficit discourse, discrimination, educational outcomes, newcomer and refugee youth, racism, strength-based approach, whiteness

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Authors: Adadu Yahaya, Abdullahi Erunke Canice

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The study sets out to examine the interface that tends to exist in the relationship between gender policy and Nigeria’s socio-economic development. Despite Nigeria’s ratification of virtually all international instruments on the protection and promotion of gender rights and equality, it appears that the practice is honored in the breach than in observance; hence, these policies have not been adequately domesticated and implemented. The implication of this is that the women folks have generally been isolated from mainstream politics and their political rights and privileges truncated in the scheme of things. The paper observes that gender inequality and marginalization in Nigeria has practically occasioned the unwholesome subjugation of Nigerian women to the background, hence poses more critical questions and challenges to the national question. The consequence of this, to this paper, is that Nigeria’s development process will be adversely affected if this trend is not checked. The paper sums up with appropriate policy options which are believed to have the potentials of giving women the right pride of place in the socio-economic and political dynamics in the 21st century Nigeria and beyond.

Keywords: development, equality, gender, policy

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Authors: Luís Rocha, Adam Gąska, Enrico Savio, Michael Marxer, Christoph Battaglia

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The changes observed in the last years in the field of manufacturing and production engineering, popularly known as "Fourth Industry Revolution", utilizes the achievements in the different areas of computer sciences, introducing new solutions at almost every stage of the production process, just to mention such concepts as mass customization, cloud computing, knowledge-based engineering, virtual reality, rapid prototyping, or virtual models of measuring systems. To effectively speed up the production process and make it more flexible, it is necessary to tighten the bonds connecting individual stages of the production process and to raise the awareness and knowledge of employees of individual sectors about the nature and specificity of work in other stages. It is important to discover and develop a suitable education method adapted to the specificities of each stage of the production process, becoming an extremely crucial issue to exploit the potential of the fourth industrial revolution properly. Because of it, the project “Train4Dim” (T4D) intends to develop complex training material for digital manufacturing, including content for design, manufacturing, and quality control, with a focus on coordinate metrology and portable measuring systems. In this paper, the authors present an approach to using an active learning methodology for digital manufacturing. T4D main objective is to develop a multi-degree (apprenticeship up to master’s degree studies) and educational approach that can be adapted to different teaching levels. It’s also described the process of creating the underneath methodology. The paper will share the steps to achieve the aims of the project (training model for digital manufacturing): 1) surveying the stakeholders, 2) Defining the learning aims, 3) producing all contents and curriculum, 4) training for tutors, and 5) Pilot courses test and improvements.

Keywords: learning, Industry 4.0, active learning, digital manufacturing

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Authors: Sobia Rana

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The study intends to explain the problems of English collocational use faced by college students in Rawalpindi, Pakistan and recommends some authentic ways that will help in removing the learning barriers in light of the concerning methodological issues. It will not only help the students to improve their knowledge of the phenomena but will also enlighten the target teachers about the significance of authentic collocational use and how it naturalizes both written and spoken expressions. Data from both the students and teachers have been collected with the help of open/close-ended questionnaires to unearth the genuine cause/s and supplement them with the required solutions rooted in the actual problems. The students fail to use authentic collocations owing to multiple reasons: lack of awareness about English collocational use, improper teaching methodologies, and inexpert teachers.

Keywords: English collocational use, teaching methodologies, English learning barriers, vocabulary acquisition, college students of Rawalpindi

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Ehsan Yadegari

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While there are several metaheuristics and exact approaches to solving the Supply Chain Network Design (SCND) problem, there still remains an unfilled gap in using the Teaching-Learning-Based Optimization (TLBO) algorithm. The algorithm has demonstrated desirable results with problems with complicated combinational optimization. The present study introduces a Discrete Self-Study TLBO (DSS-TLBO) with priority-based solution representation that can solve a supply chain network configuration model to lower the total expenses of establishing facilities and the flow of materials. The network features four layers, namely suppliers, plants, distribution centers (DCs), and customer zones. It is designed to meet the customer’s demand through transporting the material between layers of network and providing facilities in the best economic Potential locations. To have a higher quality of the solution and increase the speed of TLBO, a distinct operator was introduced that ensures self-adaptation (self-study) in the algorithm based on the four types of local search. In addition, while TLBO is used in continuous solution representation and priority-based solution representation is discrete, a few modifications were added to the algorithm to remove the solutions that are infeasible. As shown by the results of experiments, the superiority of DSS-TLBO compared to pure TLBO, genetic algorithm (GA) and firefly Algorithm (FA) was established.

Keywords: supply chain network design, teaching–learning-based optimization, improved metaheuristics, discrete solution representation

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Authors: Tzan-Chain Lee

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Seeds are non-leaves green tissues. Photosynthesis begins with light absorption by chlorophyll and then the energy transfer between two pigment-protein complexes (PPC). Most studies of photosynthesis and PPC expression were focused on leaves; however, during seeds’ development were rare. Developed seeds from beginning pod (stage R3) to dried seed (stage R8), and the dried seed after sowing for 1-4 day, were analyzed for their chlorophyll contents. Thornber and MARS gel systems analysis compositions of PPC. Chlorophyll fluorescence was used to detect maximal photosynthetic efficiency (Fv/Fm). During soybean and black soybean seeds development (stages R3-R6), Fv/Fm up to 0.8, and then down-regulated after full seed (stage R7). In dried seed (stage R8), the two plant seeds lost photosynthetic activity (Fv/Fm=0), but chlorophyll degradation only occurred in soybean after full seed. After seeds sowing for 4 days, chlorophyll drastically increased in soybean seeds, and Fv/Fm recovered to 0.8 in the two seeds. In PPC, the two soybean seeds contained all PPC during seeds development (stages R3-R6), including CPI, CPII, A1, AB1, AB2, and AB3. However, many proteins A1, AB1, AB2, and CPI were totally missing in the two dried seeds (stage R8). The deficiency of these proteins in dried seeds might be caused by the incomplete photosynthetic activity. After seeds germination and seedling exposed to light for 4 days, all PPC were recovered, suggesting that completed PPC took place in the two soybean seeds. This study showed the reversibility of photosynthetic activity and pigment-protein complexes during soybean and black soybean seeds development.

Keywords: light-harvesting complex, pigment–protein complexes, soybean cotyledon, grana development

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Authors: M. Tomaschko

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The integration of technology in educational settings has gained a lot of interest. Especially the use of mobile devices and accompanying mobile applications can offer great potentials to complement traditional education with new technologies and enrich students’ learning in various ways. Nevertheless, the usability of the deployed mathematics application is an indicative factor to exploit the full potential of technology enhanced learning because directing cognitive load toward using an application will likely inhibit effective learning. For this reason, the purpose of this research study is the identification of possible usability issues of the mobile GeoGebra Graphing Calculator application. Therefore, eye tracking in combination with task scenarios, think aloud method, and a SUS questionnaire were used. Based on the revealed usability issues, the mobile application was iteratively redesigned and assessed in order to verify the success of the usability improvements. In this paper, the identified usability issues are presented, and recommendations on how to overcome these concerns are provided. The main findings relate to the conception of a mathematics keyboard and the interaction design in relation to an equation editor, as well as the representation of geometrical construction tools. In total, 12 recommendations were formed to improve the usability of a mobile graphing calculator application. The benefit to be gained from this research study is not only the improvement of the usability of the existing GeoGebra Graphing Calculator application but also to provide helpful hints that could be considered from designers and developers of mobile math applications.

Keywords: GeoGebra, graphing calculator, math education, smartphone, usability

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Authors: Salam M. H. Kareem

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Instructional or teaching procedures and their proper sequence are essential for high-quality learning outcomes. These actions are the path that the teacher takes during the learning process after setting the learning objectives. Teachers and specialists in the education field should include teaching procedures with putting in place an effective mechanism for the procedure’s implementation to achieve a logical sequence with the desired output of overall education process. Determining the sequence of these actions may be a strategic process outlined by a strategic educational plan or drawn by teachers with a high level of experience, enabling them to determine those logical procedures. While specific actions may be necessary for a specific form, many Physical Education (PE) teachers can work out on various sports disciplines. This study was conducted to investigate the impact of using the teaching sequence of the teaching pyramid in raising the level of enjoyment in swimming classes. Four months later of teaching swimming skills to the control and experimental groups of the study, we figured that using the tools shown in the teaching pyramid with the experimental group led to statistically significant differences in the positive tendencies of students to participate in the swimming classes by using the traditional procedures of teaching and using of successive procedures in the teaching pyramid, and in favor of the teaching pyramid, The students are influenced by enhancing their tendency to participate in swimming classes when the teaching procedures followed are sensitive to individual differences and are based on the element of pleasure in learning, and less positive levels of the tendency of students when using traditional teaching procedures, by getting the level of skills' requirements higher and more difficult to perform. The level of positive tendencies of students when using successive procedures in the teaching pyramid was increased, by getting the level of skills' requirements higher and more difficult to perform, because of the high level of motivation and the desire to challenge the self-provided by the teaching pyramid.

Keywords: physical education, swimming classes, teaching process, teaching pyramid

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Authors: Esperanza C. Santos

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Japanese Language was traditionally considered as a means of imparting culture and training aesthetic experience in students and therefore as something beyond the practical aims of language teaching and learning. Due to the complexity of foreign languages, lots of language learners and teachers shared deep reservations about the potentials of foreign language in enhancing the communication skills of the students. In spite of the arguments against the use of Foreign Language (Nihon-go) in the classroom, the researcher strongly support the use of Nihon-go in teaching communication skills as the researcher believes that Nihon-go is a valuable resource to be exploited in the classroom in order to help the students explore the language in an interesting and challenging way. The focus of this research is to find out the relationship between the preferences, opinions, and perceptions with the communication skills. This study also identifies the significance of the relationship between preferences, opinions and perceptions and communications skills in the activities employed in Foreign language (Nihon-go) among the junior and senior students in Foreign Language 2 at the Imus Institute, Imus Cavite during the academic year 2013-2014. The results of the study are expected to encourage further studies that particularly focused on the communication skills as brought about by the identified factors namely: preferences, opinions, and perceptions on the benefits factor namely the language acquisition; access to Japanese culture and students' interpretative ability. Therefore, this research is in its quest for the issues and concerns on how to effectively teach different learning activities in a Nihon-go class.

Keywords: preferences, opinions, perceptions, language acquisition

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Authors: Shogo Nagano, Yusuke Tanigaki, Hirokazu Fukuda

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Vegetables harvested early in the morning or late in the afternoon are valued in plant production, and so the time of harvest is important. The biological functions known as circadian clocks have a significant effect on this harvest timing. The purpose of this study was to non-destructively estimate the circadian clock and so construct a method for determining a suitable harvest time. We took eight samples of green busil (Perilla frutescens var. crispa) every 4 hours, six times for 1 day and analyzed all samples at the same time. A hyperspectral camera was used to collect spectrum intensities at 141 different wavelengths (350–1050 nm). Calculation of correlations between spectrum intensity of each wavelength and harvest time suggested the suitability of the hyperspectral camera for non-destructive estimation. However, even the highest correlated wavelength had a weak correlation, so we used machine learning to raise the accuracy of estimation and constructed a machine learning model to estimate the internal time of the circadian clock. Artificial neural networks (ANN) were used for machine learning because this is an effective analysis method for large amounts of data. Using the estimation model resulted in an error between estimated and real times of 3 min. The estimations were made in less than 2 hours. Thus, we successfully demonstrated this method of non-destructively estimating internal time.

Keywords: artificial neural network (ANN), circadian clock, green busil, hyperspectral camera, non-destructive evaluation

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Authors: Bendjazia Radia, Samira Kilani-Morakchi, Nadia Aribi

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Azadirachtin is a biorational insecticide commonly reported as selective to a range of beneficial insects. It is one of the most biologically active natural inhibitors of insect growth and development and it is known to be an antagonist of the juvenile hormone and 20-hydroxyecdysone (20E). However, its mechanism of action remains still unknown. In the present study, the toxicity of a commercial formulation of Azadirachtin (Neem Azal, 1% azadirachtine) was evaluated by topical application at various doses (0.1, 0.25, 0.5, 1 and 2 µg/insect) on the third instars larvae of D. melanogaster. Lethal doses (LD25: 0.28µg and LD50: 0.67µg), were evaluated by cumulated mortality at the immature stages. The effects of azadirachtin (LD25 and LD50) were then evaluated on the development (duration of the larval and pupal instars, the weight of larvae, pupa and adults) of Drosophila melanogaster. Results showed that the insecticide increased significantly the larval and pupal instar duration. A reduction of larval and pupal weight is noted under azadirachtin treatment as compared to controls. In addition, the weight of surviving adults at the two tested dose was also reduced. In conclusion, azadirachtin seemed to interfere with the functions of the endocrine system resulting in development defects.

Keywords: azadirachtin, d.melanogaster, toxicity, development

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Authors: Md Rabiul Islam, Ben Wadham

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This paper describes how indigenous students face challenges with various school activities due to inadequate equity and diversity principles in mainstream primary schools in Bangladesh. This study focuses on indigenous students’ interactions with mainstream class teachers and students through teaching-learning activities at public primary schools. Ethnographic research methods guided data collection under a case study methodology in Chittagong Hill Tracts (CHTs) region where maximum indigenous peoples’ inhabitants. The participants (class teachers) shared information through in-depth interviews about their experiences in the four selecting schools. The authors also observed the effects of school activities by use of equity and diversity lens for indigenous students’ situations in those schools. The authors argue that the socio-economic situations of indigenous families are not supportive of the educational development of their children. Similarly, the Bangladesh government does not have enough initiative programs based on equity and diversity principles for fundamental education of indigenous children at rural schools level. Besides this, the conventional teaching system cannot improve the diversification among the students in classrooms. The principles of equity and diversity are not well embedded in professional development of teachers, and using teaching materials in classrooms. The findings suggest that implementing equitable education; there are needed to arrange teachers’ education with equitable knowledge and introducing diversified teaching materials, and implementing teaching through students centered activities that promote the diversification among the multicultural students.

Keywords: case study research, chittagong hill tracts, equity and diversity, Indigenous children

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Authors: Irfan Ali, Srikant Gupta, Aquil Ahmed

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Every country needs a sustainable development (SD) for its economic growth by forming suitable policies and initiative programs for the development of different sectors of the country. This paper is comprised of modeling and optimization of different sectors of India that form a multi-criterion model. In this paper, we developed a fractional goal programming (FGP) model that helps in providing the efficient allocation of resources simultaneously by achieving the sustainable goals in gross domestic product (GDP), electricity consumption (EC) and greenhouse gasses (GHG) emission by the year 2030. Also, a weighted model of FGP is presented to obtain varying solution according to the priorities set by the policy maker for achieving future goals of GDP growth, EC, and GHG emission. The presented models provide a useful insight to the decision makers for implementing strategies in a different sector.

Keywords: sustainable and economic development, multi-objective fractional programming, fuzzy goal programming, weighted fuzzy goal programming

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Authors: EMMANUEL DWAMENA SASU

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International climate policy actions require countries under Paris Agreement to design instruments, provide support (financial and technical), and strengthen institutional capacity with tendency to transcending policy formulation to implementation and sustainability. Changes associated with moisture depletion has been a growing phenomenon; especially in developing countries with projected global GDP drop from 7% to 2% between 2005 and 2050. These developments have potential to adversely affect food production in feeding the growing world population, with corresponding rise in global hunger. Incongruously, there is global absence of a harmonized policy direction; capable of providing the required indicators on climate policies for monitoring sustainability of international agricultural development projects. We conduct extensive review and synthesis on existing limitations on global climate policy governance, agricultural food security and sustainability of international agricultural development projects, and conjecture the role of non-state and sub-national climate stakeholder engagements, and monitoring and evaluation strategies for improved climate policy action for sustaining international agricultural development projects.

Keywords: climate policy, agriculture, development projects, sustainability

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Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

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Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

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Authors: Jazim Sohail, Filipe Teixeira-Dias

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Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

Procedia PDF Downloads 202