Search results for: learning outcomes assessment
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14231

Search results for: learning outcomes assessment

9131 Intrusion Detection in Cloud Computing Using Machine Learning

Authors: Faiza Babur Khan, Sohail Asghar

Abstract:

With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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9130 Reliability Assessment for Tie Line Capacity Assistance of Power Systems Based on Multi-Agent System

Authors: Nadheer A. Shalash, Abu Zaharin Bin Ahmad

Abstract:

Technological developments in industrial innovations have currently been related to interconnected system assistance and distribution networks. This important in order to enable an electrical load to continue receive power in the event of disconnection of load from the main power grid. This paper represents a method for reliability assessment of interconnected power systems based. The multi-agent system consists of four agents. The first agent was the generator agent to using as connected the generator to the grid depending on the state of the reserve margin and the load demand. The second was a load agent is that located at the load. Meanwhile, the third is so-called "the reverse margin agent" that to limit the reserve margin between 0-25% depend on the load and the unit size generator. In the end, calculation reliability Agent can be calculate expected energy not supplied (EENS), loss of load expectation (LOLE) and the effecting of tie line capacity to determine the risk levels Roy Billinton Test System (RBTS) can use to evaluated the reliability indices by using the developed JADE package. The results estimated of the reliability interconnection power systems presented in this paper. The overall reliability of power system can be improved. Thus, the market becomes more concentrated against demand increasing and the generation units were operating in relation to reliability indices.

Keywords: reliability indices, load expectation, reserve margin, daily load, probability, multi-agent system

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9129 A Qualitative Study of the Efficacy of Teaching for Conceptual Understanding to Enhance Confidence and Engagement in Early Mathematics

Authors: Nigel P. Coutts, Stellina Z. Sim

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Research suggests that the pedagogy we utilize when teaching mathematics contributes to a negative attitude towards the discipline. Worried by this, we have explored teaching mathematics for understanding, fluency, and confidence. We investigated strategies to engage students with the beauty of mathematics, moving them beyond mimicry and memorization. The result is an integrated pedagogy and curriculum arrangement which combines concept-based mathematics with Number Talks, Visible Thinking Routines, and Teaching for Understanding. Our qualitative research shows that students self-report greater self-confidence and heightened engagement with mathematical thinking. Teacher reflections on student learning echo this finding. As a result of this, we advocate for teacher training in the implementation of a concept-based curriculum supplemented with Number Talk strategies.

Keywords: mathematical thinking, teaching for understanding, student confidence, concept-based learning, engagement

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9128 Multivariate Data Analysis for Automatic Atrial Fibrillation Detection

Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

Abstract:

Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

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9127 When and How Do Individuals Transition from Regular Drug Use to Injection Drug Use in Uganda? Findings from a Rapid Assessment

Authors: Stanely Nsubuga

Abstract:

Background In Uganda, injection drug use is a growing but less studied problem. Preventing the transition to injection drug use may help prevent blood-borne viral transmission, but little is known about when and how people transition to injection drug use. A greater understanding of this transition process may aid in the country’s efforts to prevent the continued growth of injection drug use, HIV, and hepatitis C Virus (HCV) infection among people who inject drugs (PWID). Methods Using a rapid situation assessment framework, we conducted semi-structured interviews among 125 PWID (102 males and 23 females)—recruited through outreach and snow-ball sampling. Participants were interviewed about their experiences on when and how they transitioned into injection drug use and these issues were also discussed in 12 focus groups held with the participants. Results All the study participants started their drug use career with non-injecting forms including chewing, smoking, and sniffing before transitioning to injecting. Transitioning was generally described as a peer-driven and socially learnt behavior. The participants’ social networks and accessibility to injectable drugs on the market and among close friends influenced the time lag between first regular drug use and first injecting—which took an average of 4.5 years. By the age of 24, at least 81.6% (95.7% for females and 78.4% for males) had transitioned into injecting. Over 84.8% shared injecting equipment during their first injection, 47.2% started injecting because a close friend was already injecting, 26.4% desired to achieve a greater “high” (26.4%) which could reflect drug-tolerance, and 12% out of curiosity.

Keywords: People who Use Drugs, transition, injection drug use, Uganda

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9126 Short-Term Forecast of Wind Turbine Production with Machine Learning Methods: Direct Approach and Indirect Approach

Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

Abstract:

The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

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9125 The Leadership Criterion: Challenges in Pursuing Excellence in the Jordanian Public Sector

Authors: Shaker Aladwan, Paul Forrester

Abstract:

This paper explores the challenges that face leaders when implementing business excellence programmes in the Jordanian public sector. The study adopted a content analysis approach to analyse the excellence assessment reports that have been produced by the King Abdullah II Centre for Excellence (KACE). The sample comprises ten public organisations which have participated in the King Abdullah Award for Excellence (KAA) more than once and acknowledge in their reports that they have failed to achieve satisfactory results. The key challenges to the implementation of leadership criteria in the public sector in Jordan were found to be poor strategic planning, lack of employee empowerment, weaknesses in benchmarking performance, a lack of financial resources, poor integration and coordination, and poor measurement system: This study proposes a conceptual model for the as assessment of challenges that face managers when seeking to implement excellence in leadership in the Jordanian public sector. Theoretically, this paper fills context gaps in the excellence literature in general and organisational excellence in the public sector in particular. Leadership challenges in the public sector are generally widely studied, but it is important to gain a better understanding of how these challenges can be overcome. In comparison to many existing studies, this research has provided specific and detailed insights these organisational excellence challenges in the public sector and provides a conceptual model for use by other researchers into the future.

Keywords: leadership criterion, organisational excellence, challenges, quality awards, public sector, Jordan

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9124 Current Global Education Trends: Issues and Challenges of Physical and Health Education Teaching and Learning in Nigerian Schools

Authors: Bichi Muktar Sani

Abstract:

The philosophy of Physical and Health Education is to develop academic and professional competency which will enable individuals earn a living and render unique services to the society and also provide good basis of knowledge and experience that characterize an educated and fully developed person through physical activities. With the increase of sedentary activities such as watching television, playing videogames, increased computer technology, automation and reduction of high school Physical and Health Education schedules, young people are most likely to become overweight, and less fit. Physical Education is a systematic instruction in sports, training, practice, gymnastics, exercises, and hygiene given as part of a school or college program. Physical and Health Education is the study, practice, and appreciation of the art and science of human movement. Physical and Health Education is course in the curricula that utilizes the learning in the cognitive, affective, and psychomotor domains in a lay or movement exploration setting. The paper made some recommendations on the way forward.

Keywords: issues, challenges, physical education, school

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9123 Criticality Assessment Model for Water Pipelines Using Fuzzy Analytical Network Process

Authors: A. Assad, T. Zayed

Abstract:

Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

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9122 Using Wiki for Enhancing the Knowledge Transfer to Newcomers: An Experience Report

Authors: Hualter Oliveira Barbosa, Raquel Feitosa do Vale Cunha, Erika Muniz dos Santos, Fernanda Belmira Souza, Fabio Sousa, Luis Henrique Pascareli, Franciney de Oliveira Lima, Ana Cláudia Reis da Silva, Christiane Moreira de Almeida

Abstract:

Software development is intrinsic human-based knowledge-intensive. Due to globalization, software development has become a complex challenge and we usually face barriers related to knowledge management, team building, costly testing processes, especially in distributed settings. For this reason, several approaches have been proposed to minimize barriers caused by geographic distance. In this paper, we present as we use experimental studies to improve our knowledge management process using the Wiki system. According to the results, it was possible to identify learning preferences from our software projects leader team, organize and improve the learning experience of our Wiki and; facilitate collaboration by newcomers to improve Wiki with new contents available in the Wiki.

Keywords: mobile product, knowledge transfer, knowledge management process, wiki, GSD

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9121 Making Use of Content and Language Integrated Learning for Teaching Entrepreneurship and Neuromarketing to Master Students: Case Study

Authors: Svetlana Polskaya

Abstract:

The study deals with the issue of using the Content and Language Integrated Learning (CLIL) concept when teaching Master Program students majoring in neuromarketing and entrepreneurship. Present-day employers expect young graduates to conduct professional communication with their English-speaking peers and demonstrate proper knowledge of the industry’s terminology and jargon. The idea of applying CLIL was the result of the above-mentioned students possessing high proficiency in English, thus, not requiring any further knowledge of the English language in terms of traditional grammar or lexis. Due to this situation, a CLIL-type program was devised, allowing learners to acquire new knowledge of entrepreneurship and neuromarketing spheres combined with simultaneous honing their English language practical usage. The case study analyzes CLIL application within this particular program as well as the experience accumulated in the process.

Keywords: CLIL, entrepreneurship, neuromarketing, foreign language acquisition, proficiency level

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9120 Managing Student Internationalization during the COVID-19 Pandemic: Three Approaches That Should Endure beyond the Present

Authors: David Cobham

Abstract:

In higher education, a great degree of importance is placed on the internationalization of the student experience. This is seen as a valuable contributor to elements such as building confidence, broadening knowledge, creating networks and connections, and enhancing employability for current students who will become the next generation of managers in technology and business. The COVID-19 pandemic has affected all areas of people’s lives. The limitations of travel coupled with the fears and concerns generated by the health risks have dramatically reduced the opportunity for students to engage with this agenda. Institutions of higher education have been required to rethink fundamental aspects of their business model from recruitment and enrolment through learning approaches, assessment methods, and the pathway to employment. This paper presents a case study which focuses on student mobility and how the physical experience of being in another country, either to study, to work, to volunteer or to gain cultural and social enhancement, has of necessity been replaced by alternative approaches. It considers trans-national education as an alternative to physical study overseas, virtual mobility and internships as an alternative to international work experience, and adopting collaborative online projects as an alternative to in-person encounters. The paper concludes that although these elements have been adopted to address the current situation, the lessons learned and the feedback gained suggests that they have contributed successfully in new and sometimes unexpected ways and that they will persist beyond the present to become part of the 'new normal' for the future. That being the case, senior leaders of institutions of higher education will be required to revisit their international plans and to rewrite their international strategies to take account of and build upon these changes.

Keywords: higher education management, internationalization, transnational education, virtual mobility

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9119 1-D Convolutional Neural Network Approach for Wheel Flat Detection for Freight Wagons

Authors: Dachuan Shi, M. Hecht, Y. Ye

Abstract:

With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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9118 Promoting Diversity and Equity through Interdisciplinary Leadership Training

Authors: Sharon Milberger, Jane Turner, Denise White-Perkins

Abstract:

Michigan shares the overall U.S. national need for more highly qualified professionals who have knowledge and experience in the use of evidence-based practices to meet the special health care needs of children, adolescents, and adults with neurodevelopmental disabilities including autism spectrum disorder (DD/ASD). The Michigan Leadership Education in Neurodevelopmental Disabilities (MI-LEND) program is a consortium of six universities that spans the state of Michigan and serves more than 181,800 undergraduate, graduate, and professional students. The purpose of the MI LEND program is to improve the health of infants, children and adolescents with disabilities in Michigan by training individuals from different disciplines to assume leadership roles in their respective fields and work across disciplines. The MI-LEND program integrates “L.I.F.E.” perspectives into all training components. L.I.F.E. is an acronym for Leadership, Interdisciplinary, Family-Centered and Equity perspectives. This paper will describe how L.I.F.E. perspectives are embedded into all aspects of the MI-LEND training program including the application process, didactic training, community and clinical experiences, discussions, journaling and projects. Specific curriculum components will be described including content from a training module dedicated to Equity. Upon completion of the Equity module, trainees are expected to be able to: 1) Use a population health framework to identify key social determinants impacting families and children; 2) Explain how addressing bias and providing culturally appropriate linguistic care/services can influence patient/client health and wellbeing; and 3) Describe the impact of policy and structural/institutional factors influencing care and services for children with DD/ASD and their families. Each trainee completes two self-assessments: the Cultural and Linguistic Competence Health Practitioner Assessment and the other assessing social attitudes/implicit bias. Trainees also conduct interviews with a family with a child with DD/ASD. In addition, interdisciplinary Equity-related group activities are incorporated into face-to-face training sessions. Each MI-LEND trainee has multiple ongoing opportunities for self-reflection through discussion and journaling and completion of a L.I.F.E. project as a culminating component of the program. The poster will also discuss the challenges related to teaching and measuring successful outcomes related to diversity/equity perspectives.

Keywords: disability, diversity, equity, training

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9117 Impact of Hepatitis C Virus Chronic Infection on Quality of Life in Egypt

Authors: Ammal M. Metwally, Ghada A. Abdel-Latif, Walaa A. Fouad, Thanaa M. Rabah, Amira Mohsen, Fatma A. Shaaban, Iman I. Salama

Abstract:

The study aimed at determining the impact of chronic hepatitis C virus (HCV) infection on patients’ Quality of Life (QoL) , its relation to geographical characteristics of patients, awareness of the disease, treatment regimen, co-morbid psychiatric or other diseases. 457 patients were randomly selected from ten National Treatment Reference Centers of Ministry of Health hospitals from four community locations representing Egypt. Health related QoL assessment questionnaire with the 36-item Short Form used for assessment of the enrolled patients. The study showed no significant difference between HCV patients in different governorates as regards total QoL. Females, illiterate patients and those had bilharziasis, diabetes mellitus, hypertension or were depressed had significantly the lowest QoL score. HCV patients who knew the danger of the disease had significant lower mean score of physical and mental health components. Optimal care of overall well-being of HCV patients requires adequate knowledge of their neurological and psychological status. It is important to know that any patient will need to take the time to know that his new physical limitations do not limit him as a person, as soul, no matter what other people are thinking as a positive hopeful attitude is essential for combating HCV.

Keywords: hepatitis C virus chronic infection - physical health component and mental health component of QoL– total quality of life

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9116 Assessment of Analytical Equations for the Derivation of Young’s Modulus of Bonded Rubber Materials

Authors: Z. N. Haji, S. O. Oyadiji, H. Samami, O. Farrell

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The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Keywords: bonded rubber, quasi-static test, shape factor, apparent Young’s modulus

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9115 The Development of Digital Commerce in Community Enterprise Products to Promote the Distribution of Samut Songkhram Province

Authors: Natcha Wattanaprapa, Alongkorn Taengtong, Phachaya Chaiwchan

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This study investigates and promotes the distribution of community enterprise products of Samut Songkhram province by using e-commerce web technology to help distribute the products. This study also aims to develop the information system to be able to operate on multiple platforms and promote the easy usability on smartphones to increase the efficiency and promote the distribution of community enterprise products of Samut Songkhram province in three areas including Baan Saraphi learning center, the learning center of Bang Noi Floating market as well as Bang Nang Li learning center. The main structure consists of spreading the knowledge regarding the tourist attraction in the area of community enterprise, e-commerce system of community enterprise products, and Chatbot. The researcher developed the system into an application form using the software package to create and manage the content on the internet. Connect management system (CMS) word press was used for managing web pages. Add-on CMS word press was used for creating the system of Chatbot, and the database of PHP My Admin was used as the database management system. The evaluation by the experts and users in 5 aspects, including the system efficiency, the accuracy in the operation of the system, the convenience and ease of use of the system, the design, and the promotion of product distribution in Samut Songkhram province by using questionnaires revealed that the result of evaluation in the promotion of product distribution in Samut Songkhram province was the highest with the mean of 4.20. When evaluating the efficiency of the developed system, it was found that the result of system efficiency was the highest level with a mean of 4.10.

Keywords: community enterprise, digital commerce, promotion of product distribution, Samut Songkhram province

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9114 [Keynote Talk] The Practices and Issues of Career Education: Focusing on Career Development Course on Various Problems of Society

Authors: Azusa Katsumata

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Several universities in Japan have introduced activities aimed at the mutual enlightenment of a diversity of people in career education. However, several programs emphasize on delivering results, and on practicing the prepared materials as planned. Few programs focus on unexpected failures and setbacks. This way of learning is important in career education so that classmates can help each other, overcome difficulties, draw out each other’s strengths, and learn from them. Seijo University in Tokyo offered excursion focusing Various Problems of Society, as second year career education course, Students will learn about contraception, infertility, homeless people, LGBT, and they will discuss based on the excursion. This paper aims to study the ‘learning platform’ created by a series of processes such as the excursion, the discussion, and the presentation. In this course, students looked back on their lives and imagined the future in concrete terms, performing tasks in groups. The students came across a range of values through lectures and conversations, thereby developing feelings of self-efficacy. We conducted a questionnaire to measure the development of career in class. From the results of the questionnaire, we can see, in the example of this class, that students respected diversity and understood the importance of uncertainty and discontinuity. Whereas the students developed career awareness, they actually did not come across that scene and would do so only in the future when it became necessary. In this class, students consciously considered social problems, but did not develop the practical skills necessary to deal with these. This is appropriate for one of project, but we need to consider how this can be incorporated into future courses. University constitutes only a single period in life-long career formation. Thus, further research may be indicated to determine whether the positive effects of career education at university continue to contribute to individual careers going forward.

Keywords: career education of university, excursion, learning platform, problems of society

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9113 Project-Based Learning and Evidence Based Nursing as Tools for Developing Students' Integrative Critical Thinking Skills: Content Analysis of Final Students' Projects

Authors: E. Maoz

Abstract:

Background: As a teaching method, project-based learning is strongly linked to developing students’ critical thinking skills. It combines creative independent thinking, team work, and disciplinary subject-field integration. In the 'Introduction to Nursing Research Methods' course (year 3, Generic Track), project based learning is used to teach the topic of 'Evidence-Based Nursing'. This topic examines a clinical care issue encountered by students in the field. At the end of their project, students present proposals for managing the said issue. Proposals are the product of independent integrative thinking integrating a wide range of factors influencing the issue’s management. Method: Papers by 27 groups of students (165 students) were content analyzed to identify which themes emerged from the students' recommendations for managing the clinical issue. Findings: Five main themes emerged—current management approach; adapting procedures in line with current recent research recommendations; training for change (veteran nursing staff, beginner students, patients, significant others); analysis of 'economic benefit vs. patient benefit'; multidisciplinary team engagement in implementing change in practice. Two surprising themes also emerged: advertising and marketing using new technologies, which reflects how the new generation thinks. Summary and Recommendations: Among the main challenges in nursing education is training nursing graduates to think independently, integratively, and critically. Combining PBL with classical teaching methods stimulates students cognitively while opening new vistas with implications on all levels of the profession: management, research, education, and practice. Advanced students can successfully grasp and interpret the current state of clinical practice. They are competent and open to leading change and able to consider the diverse factors and interconnections that characterize the nurse's work.

Keywords: evidence based nursing, critical thinking skills, project based learning, students education

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9112 Students’ Perceptions on Educational Game for Learning Programming Subject: A Case Study

Authors: Roslina Ibrahim, Azizah Jaafar, Khalili Khalil

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Educational games (EG) are regarded as a promising teaching and learning tool for the new generation. Growing number of studies and literatures can be found in EG studies. Both academic researchers and commercial developers come out with various educational games prototypes and titles. Despite that, acceptance of educational games still lacks among the students. It is important to understanding students’ perceptions of EG, since they are the main stakeholder of the technology. Thus, this study seeks to understand perceptions of undergraduates’ students using a framework originated from user acceptance theory. The framework consists of six constructs with twenty-eight items. Data collection was done on 180 undergraduate students of Universiti Teknologi Malaysia, Kuala Lumpur using self-developed online EG called ROBO-C. Data analysis was done using descriptive, factor analysis and correlations. Performance expectancy, effort expectancy, attitude, and enjoyment factors were found significantly correlated with the intention to use EG. This study provides more understanding towards the use of educational games among students.

Keywords: educational games, perceptions, acceptance, UTAUT

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9111 An Efficient Machine Learning Model to Detect Metastatic Cancer in Pathology Scans Using Principal Component Analysis Algorithm, Genetic Algorithm, and Classification Algorithms

Authors: Bliss Singhal

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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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9110 Differences Between Mother and Father Perpetrators on Child Maltreatment Foster Care Outcomes: An Emphasis on Hispanic and Native American Families

Authors: Yadira Tejeda, Wynette Whitegoat, Dylan Jones, Brett Drake

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Background and Purpose: Hispanic and American Indian/Alaska Native (AI/AN) families impacted by child protective services (CPS) continue to be a population in literature where little is known. There is less known about the fathers of these children and the safety or risk factors attributed to child maltreatment and case outcomes. However, it is known that involving fathers in children’s lives is needed for healthy development, academic achievement, and cognitive development. The few articles that have studied the impacts of engaging fathers in the CPS have found that children in general experience shorter times in foster care, are likely to reunify with their biological family, and overall have better case outcomes. The purpose of this study is to determine whether perpetrators identified as the mother, father, or both impact foster care placement in Hispanic and AI/AN families in CPS. Methods: Using NCANDS Child File data, the selected reports submitted in FY2017 with at least one substantiated allegation, i.e. those with perpetrator information. Reports were categorized into one of three categories: mom-perpetrator-only, father-perpetrator-only, and both. Reports that did not fall into any one of these three categorizations were omitted (<18%). Lastly, only reports where the mother and father self-identified as Hispanic or AI/AN were kept. Foster care placement was measured if any child in the report was placed within three months of the report date. Multilevel Logistic Regression models (random intercepts at the state and county) were used to model the relationship between report-parent type and foster care placement. Controls included Maltreatment types, number of children, any prior reports, and age of the youngest child. Results: For AI/AN reports, 64% were mom-perpetrator-only, 20% were father-perpetrator-only, and 16% both. Father-perpetrator-only reports had 60% lower odds of placement than mom-perpetrator-only, and both had 35% greater odds than mom-only. For Hispanics, 51% were mom-perpetrator-only, 30% father-perpetrator-only, and 19% both. Father-perpetrator-only reports had 74% lower odds than mom-perpetrator-only, and both had 55% greater odds than mom-perpetrator-only. Conclusion and Implications: Fatherhood research focused on prevention and intervention services should include Hispanic and AI/AN fathers to create culturally relevant and tailored services for both groups. By identifying differences in children’s CPS trajectories conditional on fathers’ involvement as a perpetrator, this analysis helps to inform where and how prevention efforts should be focused when considering variation in parental involvement for both populations. The findings indicate that the father’s involvement predicts substantial differences in the probability of future placement, with the direction depending on the mother’s joint involvement. Future research should investigate mediating pathways of these relationships while accounting for the unique experiences of AI/AN and Hispanic families. Each of these racial groups faces unique and differing challenges related to CPS, yet both groups have a shared understanding of the importance of fatherhood in the lives of children. Developing a better understanding of what is happening with Hispanic and AI/AN fathers as it relates to children's CPS experiences may result in new tools to reduce child maltreatment rates in these communities.

Keywords: child Abuse, child maltreatment, NDACAN, latino, native American

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9109 Implementation of Enhanced Recovery after Surgery (ERAS) Protocols in Laparoscopic Sleeve Gastrectomy (LSG); A Systematic Review and Meta-analysis

Authors: Misbah Nizamani, Saira Malik

Abstract:

Introduction: Bariatric surgery is the most effective treatment for patients suffering from morbid obesity. Laparoscopic sleeve gastrectomy (LSG) accounts for over 50% of total bariatric procedures. The aim of our meta-analysis is to investigate the effectiveness and safety of Enhanced Recovery After Surgery (ERAS) protocols for patients undergoing laparoscopic sleeve gastrectomy. Method: To gather data, we searched PubMed, Google Scholar, ScienceDirect, and Cochrane Central. Eligible studies were randomized controlled trials and cohort studies involving adult patients (≥18 years) undergoing bariatric surgeries, i.e., Laparoscopic sleeve gastrectomy. Outcome measures included LOS, postoperative narcotic usage, postoperative pain score, postoperative nausea and vomiting, postoperative complications and mortality, emergency department visits and readmission rates. RevMan version 5.4 was used to analyze outcomes. Results: Three RCTs and three cohorts with 1522 patients were included in this study. ERAS group and control group were compared for eight outcomes. LOS was reduced significantly in the intervention group (p=0.00001), readmission rates had borderline differences (p=0.35) and higher postoperative complications in the control group, but the result was non-significant (p=0.68), whereas postoperative pain score was significantly reduced (p=0.005). Total MME requirements became significant after performing sensitivity analysis (p= 0.0004). Postoperative mortality could not be analyzed on account of invalid data showing 0% mortality in two cohort studies. Conclusion: This systemic review indicated the effectiveness of the application of ERAS protocols in LSG in reducing the length of stay, post-operative pain and total MME requirements postoperatively, indicating the feasibility and assurance of its application.

Keywords: eras protocol, sleeve gastrectomy, bariatric surgery, enhanced recovery after surgery

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9108 The Impact of Neuroscience Knowledge on the Field of Education

Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena

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Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.

Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors

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9107 Design of Fuzzy Logic Based Global Power System Stabilizer for Dynamic Stability Enhancement in Multi-Machine Power System

Authors: N. P. Patidar, J. Earnest, Laxmikant Nagar, Akshay Sharma

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This paper describes the diligence of a new input signal based fuzzy power system stabilizer in multi-machine power system. Instead of conventional input pairs like speed deviation (∆ω) and derivative of speed deviation i.e. acceleration (∆ω ̇) or speed deviation and accelerating power deviation of each machine, in this paper, deviation of active power through the tie line colligating two areas is used as one of the inputs to the fuzzy logic controller in concurrence with the speed deviation. Fuzzy Logic has the features of simple concept, easy effectuation, and computationally efficient. The advantage of this input is that, the same signal can be fed to each of the fuzzy logic controller connected with each machine. The simulated system comprises of two fully symmetrical areas coupled together by two 230 kV lines. Each area is equipped with two superposable generators rated 20 kV/900MVA and area-1 is exporting 413 MW to area-2. The effectiveness of the proposed control scheme has been assessed by performing small signal stability assessment and transient stability assessment. The proposed control scheme has been compared with a conventional PSS. Digital simulation is used to demonstrate the performance of fuzzy logic controller.

Keywords: Power System Stabilizer (PSS), small signal stability, inter-area oscillation, fuzzy logic controller, membership function, rule base

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9106 Design of Dry Chemical Fire Extinguisher Inspection Equipment in Order to Reduce Ergonomic Risks for Fire Extinguisher Inspectors

Authors: Sitrapee Changmuenwai, Sudaratana Wongweragiat

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It is important that a dry chemical fire extinguisher must be inspected for its readiness. For each inspection, the inspectors need to turn the fire extinguisher tank upside down to let the chemical inside the tank move and prevent solidification, which would make the tank not ready for usage when needed. Each tank weighs approximately 16 kg. The inspectors have to turn each tank upside down twice (2 minutes/round). They need to put the tanks over their shoulder close to their ear in order to hear the chemical flow inside the tank or use their hands to feel it. The survey and questionnaire 'The Questionnaire Know Body', which includes neck, left shoulder, upper and lower right arms suggest that all 12 security staffs have the same fatigues. The current dry chemical fire extinguisher inspection affects various ergonomic health problems. Rapid Entire Body Assessment (REBA) is used for evaluation of posture risks so that the working postures may be redesigned or corrected. The dry chemical fire extinguisher inspection equipment has been developed to reduce ergonomic health risks for the inspectors. A REBA analysis has been performed again, and the risk score has been decreased from 13 to 3. In addition, feedbacks from the first trial of the developed equipment show that there are demands to increase the installation in order to reduce the ergonomic health risks.

Keywords: dry chemical fire extinguisher inspection equipment, ergonomic, REBA, rapid entire body assessment

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9105 Multi-Objective Evolutionary Computation Based Feature Selection Applied to Behaviour Assessment of Children

Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

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9104 On Deterministic Chaos: Disclosing the Missing Mathematics from the Lorenz-Haken Equations

Authors: Meziane Belkacem

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We aim at converting the original 3D Lorenz-Haken equations, which describe laser dynamics –in terms of self-pulsing and chaos- into 2-second-order differential equations, out of which we extract the so far missing mathematics and corroborations with respect to nonlinear interactions. Leaning on basic trigonometry, we pull out important outcomes; a fundamental result attributes chaos to forbidden periodic solutions inside some precisely delimited region of the control parameter space that governs the bewildering dynamics.

Keywords: Physics, optics, nonlinear dynamics, chaos

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9103 The Effect of Primary Treatment on Histopathological Patterns and Choice of Neck Dissection in Regional Failure of Nasopharyngeal Carcinoma Patients

Authors: Ralene Sim, Stefan Mueller, N. Gopalakrishna Iyer, Ngian Chye Tan, Khee Chee Soo, R. Shetty Mahalakshmi, Hiang Khoon Tan

Abstract:

Background: Regional failure in nasopharyngeal carcinoma (NPC) is managed by salvage treatment in the form of neck dissection. Radical neck dissection (RND) is preferred over modified radical neck dissection (MRND) since it is traditionally believed to offer better long-term disease control. However, with the advent of more advanced imaging modalities like high-resolution Magnetic Resonance Imaging, Computed Tomography, and Positron Emission Tomography-CT scans, earlier detection is achieved. Additionally, concurrent chemotherapy also contributes to reduced tumour burden. Hence, there may be a lesser need for an RND and a greater role for MRND. With this retrospective study, the primary aim is to ascertain whether MRND, as opposed to RND, has similar outcomes and hence, whether there would be more grounds to offer a less aggressive procedure to achieve lower patient morbidity. Methods: This is a retrospective study of 66 NPC patients treated at Singapore General Hospital between 1994 to 2016 for histologically proven regional recurrence, of which 41 patients underwent RND and 25 who underwent MRND, based on surgeon preference. The type of ND performed, primary treatment mode, adjuvant treatment, and pattern of recurrence were reviewed. Overall survival (OS) was calculated using Kaplan-Meier estimate and compared. Results: Overall, the disease parameters such as nodal involvement and extranodal extension were comparable between the two groups. Comparing MRND and RND, the median (IQR) OS is 1.76 (0.58 to 3.49) and 2.41 (0.78 to 4.11) respectively. However, the p-value found is 0.5301 and hence not statistically significant. Conclusion: RND is more aggressive and has been associated with greater morbidity. Hence, with similar outcomes, MRND could be an alternative salvage procedure for regional failure in selected NPC patients, allowing similar salvage rates with lesser mortality and morbidity.

Keywords: nasopharyngeal carcinoma, neck dissection, modified neck dissection, radical neck dissection

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9102 Unraveling the Complexities of Competitive Aggressiveness: A Qualitative Exploration in the Oil and Gas Industry

Authors: Salim Al Harthy, Alexandre A. Bachkirov

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This study delves into the complexities of competitive aggressiveness in the oil and gas industry, focusing on the characteristics of the identified competitive actions. The current quantitative research on competitive aggressiveness lacks agreement on the connection between antecedents and outcomes, prompting a qualitative investigation. To address this gap, the research utilizes qualitative interviews with CEOs from Oman's oil and gas service industry to explore the dynamics of competitive aggressiveness. Using Noklenain's typology, the study categorizes and analyzes identified actions, shedding light on the spectrum of competitive behaviors within the industry. Notably, actions predominantly fall under the "Bring about" and "Preserve" elements, with a notable absence in the "Forebear" and "Destroy" categories, possibly linked to the study's focus on service-oriented businesses. The study also explores the detectability of actions, revealing that "Bring about" actions are detectable, while those in "Preserve" and "Suppress" are not. This challenges conventional definitions of competitive aggressiveness, suggesting that not all actions are readily detectable despite being considered competitive. The presence of non-detectable actions introduces complexity to measurement methods reliant on visible empirical data. Moreover, the study contends that companies can adopt an aggressive competitive approach without directly challenging rivals. This challenges traditional views and emphasizes the innovative and entrepreneurial aspects of actions not explicitly aimed at competitors. By not revealing strategic intentions, such actions put rivals at a disadvantage, underscoring the need for a nuanced understanding of competitive aggressiveness. In summary, the lack of consensus in existing literature regarding the relationship between antecedents and outcomes in competitive aggressiveness is addressed. The study reveals a spectrum of detectable and undetectable actions, posing challenges in measurement and emphasizing the need for alternative methods to assess undetectable actions in competitive behavior. This research contributes to a more nuanced understanding of competitive aggressiveness, acknowledging the diverse actions shaping a company's strategic positioning in dynamic business environments.

Keywords: competitive aggressiveness, qualitative exploration, noklenain's typology, oil and gas industry

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