Search results for: supervised learning algorithms
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8392

Search results for: supervised learning algorithms

1042 Using Wearable Device with Neuron Network to Classify Severity of Sleep Disorder

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

Abstract:

Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

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1041 Gender Differences in Biology Academic Performances among Foundation Students of PERMATApintar® National Gifted Center

Authors: N. Nor Azman, M. F. Kamarudin, S. I. Ong, N. Maaulot

Abstract:

PERMATApintar® National Gifted Center is, to the author’s best of knowledge, the first center in Malaysia that provides a platform for Malaysian talented students with high ability in thinking. This center has built a teaching and learning biology curriculum that suits the ability of these gifted students. The level of PERMATApintar® biology curriculum is basically higher than the national biology curriculum. Here, the foundation students are exposed to the PERMATApintar® biology curriculum at the age of as early as 11 years old. This center practices a 4-time-a-year examination system to monitor the academic performances of the students. Generally, most of the time, male students show no or low interest towards biology subject compared to female students. This study is to investigate the association of students’ gender and their academic performances in biology examination. A total of 39 students’ scores in twelve sets of biology examinations in 3 years have been collected and analyzed by using the statistical analysis. Based on the analysis, there are no significant differences between male and female students against the biology academic performances with a significant level of p = 0.05. This indicates that gender is not associated with the scores of biology examinations among the students. Another result showed that the average score for male studenta was higher than the female students. Future research can be done by comparing the biology academic achievement in Malaysian National Examination (Sijil Pelajaran Malaysia, SPM) between the Foundation 3 students (Grade 9) and Level 2 students (Grade 11) with similar PERMATApintar® biology curriculum.

Keywords: academic performances, biology, gender differences, gifted students,

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1040 Algerian EFL Students' Perceptions towards the Development of Writing through Weblog Storytelling

Authors: Nawel Mansouri

Abstract:

Weblog as a form of internet-based resources has become popular as an authentic and constructive learning tool, especially in the language classroom. This research explores the use of weblog storytelling as a pedagogical tool to develop Algerian EFL students’ creative writing. This study aims to investigate the effectiveness of weblog- writing and the attitudes of both Algerian EFL students and teachers towards weblog storytelling. It also seeks to explore the potential benefits and problems that may affect the use of weblog and investigate the possible solutions to overcome the problems encountered. The research work relies on a mixed-method approach which combines both qualitative and quantitative methods. A questionnaire will be applied to both EFL teachers and students as a means to obtain preliminary data. Interviews will be integrated in accordance with the primary data that will be gathered from the questionnaire with the aim of validating its accuracy or as a strategy to follow up any unexpected results. An intervention will take place on the integration of weblog- writing among 15 Algerian EFL students for a period of two months where students are required to write five narrative essays about their personal experiences, give feedback through the use of a rubric to two or three of their peers, and edit their work based on the feedback. After completion, questionnaires and interviews will also take place as a medium to obtain both the students’ perspectives towards the use of weblog as an innovative teaching approach. This study is interesting because weblog storytelling has recently been emerged as a new form of digital communication and it is a new concept within Algerian context. Furthermore, the students will not just develop their writing skill through weblog storytelling but it can also serve as a tool to develop students’ critical thinking, creativity, and autonomy.

Keywords: Weblog writing, EFL writing, EFL learners' attitudes, EFL teachers' views

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1039 Film Therapy on Adolescent Body Image: A Pilot Study

Authors: Sonia David, Uma Warrier

Abstract:

Background: Film therapy is the use of commercial or non-commercial films to enhance healing for therapeutic purposes. Objectives: The mixed-method study aims to evaluate the effect of film-based counseling on body image dissatisfaction among adolescents to precisely ascertain the cause of the alteration in body image dissatisfaction due to the said intervention. Method: The one group pre-test post-test research design study using inferential statistics and thematic analysis is based on a pre-test post-test design conducted on 44 school-going adolescents between 13 and 17. The Body Shape Questionnaire (BSQ- 34) was used as a pre-test and post-test measure. The film-based counseling intervention model was used through individual counseling sessions. The analysis involved paired sample t-test used to examine the data quantitatively, and thematic analysis was used to evaluate qualitative data. Findings: The results indicated that there is a significant difference between the pre-test and post-test means. Since t(44)= 9.042 is significant at a 99% confidence level, it is ascertained that film-based counseling intervention reduces body image dissatisfaction. The five distinct themes from the thematic analysis are “acceptance, awareness, empowered to change, empathy, and reflective.” Novelty: The paper originally contributes to the repertoire of research on film therapy as a successful counseling intervention for addressing the challenges of body image dissatisfaction. This study also opens avenues for considering alteration of teaching pedagogy to include video-based learning in various subjects.

Keywords: body image dissatisfaction, adolescents, film-based counselling, film therapy, acceptance and commitment therapy

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1038 Acute Severe Hyponatremia in Patient with Psychogenic Polydipsia, Learning Disability and Epilepsy

Authors: Anisa Suraya Ab Razak, Izza Hayat

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Introduction: The diagnosis and management of severe hyponatremia in neuropsychiatric patients present a significant challenge to physicians. Several factors contribute, including diagnostic shadowing and attributing abnormal behavior to intellectual disability or psychiatric conditions. Hyponatraemia is the commonest electrolyte abnormality in the inpatient population, ranging from mild/asymptomatic, moderate to severe levels with life-threatening symptoms such as seizures, coma and death. There are several documented fatal case reports in the literature of severe hyponatremia secondary to psychogenic polydipsia, often diagnosed only in autopsy. This paper presents a case study of acute severe hyponatremia in a neuropsychiatric patient with early diagnosis and admission to intensive care. Case study: A 21-year old Caucasian male with known epilepsy and learning disability was admitted from residential living with generalized tonic-clonic self-terminating seizures after refusing medications for several weeks. Evidence of superficial head injury was detected on physical examination. His laboratory data demonstrated mild hyponatremia (125 mmol/L). Computed tomography imaging of his brain demonstrated no acute bleed or space-occupying lesion. He exhibited abnormal behavior - restlessness, drinking water from bathroom taps, inability to engage, paranoia, and hypersexuality. No collateral history was available to establish his baseline behavior. He was loaded with intravenous sodium valproate and leveritircaetam. Three hours later, he developed vomiting and a generalized tonic-clonic seizure lasting forty seconds. He remained drowsy for several hours and regained minimal recovery of consciousness. A repeat set of blood tests demonstrated profound hyponatremia (117 mmol/L). Outcomes: He was referred to intensive care for peripheral intravenous infusion of 2.7% sodium chloride solution with two-hourly laboratory monitoring of sodium concentration. Laboratory monitoring identified dangerously rapid correction of serum sodium concentration, and hypertonic saline was switched to a 5% dextrose solution to reduce the risk of acute large-volume fluid shifts from the cerebral intracellular compartment to the extracellular compartment. He underwent urethral catheterization and produced 8 liters of urine over 24 hours. Serum sodium concentration remained stable after 24 hours of correction fluids. His GCS recovered to baseline after 48 hours with improvement in behavior -he engaged with healthcare professionals, understood the importance of taking medications, admitted to illicit drug use and drinking massive amounts of water. He was transferred from high-dependency care to ward level and was initiated on multiple trials of anti-epileptics before achieving seizure-free days two weeks after resolution of acute hyponatremia. Conclusion: Psychogenic polydipsia is often found in young patients with intellectual disability or psychiatric disorders. Patients drink large volumes of water daily ranging from ten to forty liters, resulting in acute severe hyponatremia with mortality rates as high as 20%. Poor outcomes are due to challenges faced by physicians in making an early diagnosis and treating acute hyponatremia safely. A low index of suspicion of water intoxication is required in this population, including patients with known epilepsy. Monitoring urine output proved to be clinically effective in aiding diagnosis. Early referral and admission to intensive care should be considered for safe correction of sodium concentration while minimizing risk of fatal complications e.g. central pontine myelinolysis.

Keywords: epilepsy, psychogenic polydipsia, seizure, severe hyponatremia

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1037 Improving Medication Understanding, Use and Self-Efficacy among Stroke Patients: A Randomised Controlled Trial; Study Protocol

Authors: Jamunarani Appalasamy, Tha Kyi Kyi, Quek Kia Fatt, Joyce Pauline Joseph, Anuar Zaini M. Zain

Abstract:

Background: The Health Belief Theory had always been associated with chronic disease management. Various health behaviour concepts and perception branching from this Health Belief Theory had involved with medication understanding, use, and self-efficacy which directly link to medication adherence. In a previous quantitative and qualitative study, stroke patients in Malaysia were found to be strongly believing information obtained by various sources such as the internet and social communication. This action leads to lower perception of their stroke preventative medication benefit which in long-term creates non-adherence. Hence, this study intends to pilot an intervention which uses audio-visual concept incorporated with mHealth service to enhance learning and self-reflection among stroke patients to manage their disease. Methods/Design: Twenty patients will be allocated to a proposed intervention whereas another twenty patients are allocated to the usual treatment. The intervention involves a series of developed audio-visual videos sent via mobile phone which later await for responses and feedback from the receiver (patient) via SMS or recorded calls. The primary outcome would be the medication understanding, use and self-efficacy measured over two months pre and post intervention. Secondary outcome is measured from changes of blood parameters and other self-reported questionnaires. Discussion: This study shall also assess uptake/attrition, feasibility, and acceptability of this intervention. Trial Registration: NMRR-15-851-24737 (IIR)

Keywords: health belief, medication understanding, medication use, self-efficacy

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1036 Recognition and Counting Algorithm for Sub-Regional Objects in a Handwritten Image through Image Sets

Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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1035 EECS: Reimagining the Future of Technology Education through Electrical Engineering and Computer Science Integration

Authors: Yousef Sharrab, Dimah Al-Fraihat, Monther Tarawneh, Aysh Alhroob, Ala’ Khalifeh, Nabil Sarhan

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This paper explores the evolution of Electrical Engineering (EE) and Computer Science (CS) education in higher learning, examining the feasibility of unifying them into Electrical Engineering and Computer Science (EECS) for the technology industry. It delves into the historical reasons for their separation and underscores the need for integration. Emerging technologies such as AI, Virtual Reality, IoT, Cloud Computing, and Cybersecurity demand an integrated EE and CS program to enhance students' understanding. The study evaluates curriculum integration models, drawing from prior research and case studies, demonstrating how integration can provide students with a comprehensive knowledge base for industry demands. Successful integration necessitates addressing administrative and pedagogical challenges. For academic institutions considering merging EE and CS programs, the paper offers guidance, advocating for a flexible curriculum encompassing foundational courses and specialized tracks in computer engineering, software engineering, bioinformatics, information systems, data science, AI, robotics, IoT, virtual reality, cybersecurity, and cloud computing. Elective courses are emphasized to keep pace with technological advancements. Implementing this integrated approach can prepare students for success in the technology industry, addressing the challenges of a technologically advanced society reliant on both EE and CS principles. Integrating EE and CS curricula is crucial for preparing students for the future.

Keywords: electrical engineering, computer science, EECS, curriculum integration of EE and CS

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1034 INRAM-3DCNN: Multi-Scale Convolutional Neural Network Based on Residual and Attention Module Combined with Multilayer Perceptron for Hyperspectral Image Classification

Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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1033 A Communication Signal Recognition Algorithm Based on Holder Coefficient Characteristics

Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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1032 English Test Success among Syrian Refugee Girls Attending Language Courses in Lebanon

Authors: Nina Leila Mussa

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Background: The devastating effects of the war on Syria’s educational infrastructure has been widely reported, with millions of children denied access. However, among those who resettled in Lebanon, the impact of receiving educational assistance on their abilities to pass the English entrance exam is not well described. The aim of this study was to identify predictors of success among Syrian refugees receiving English language courses in a Lebanese university. Methods: The database of Syrian refugee girls matriculated in English courses at the American University of Beirut (AUB) was reviewed. The study period was 7/2018-09/2020. Variables compared included: family size and income, welfare status, parents’ education, English proficiency, access to the internet, and need for external help with homework. Results: For the study period, there were 28 girls enrolled. The average family size was 6 (range 4-9), with eight having completed primary, 14 secondary education, and 6 graduated high school. Eighteen were single-income families. After 12 weeks of English courses, 16 passed the Test of English as Foreign Language (TOEFL) from the first attempt, and 12 failed. Out of the 12, 8 received external help, and 6 passed on the second attempt, which brings the total number of successful passing to 22. Conclusion: Despite the tragedy of war, girls receiving assistance in learning English in Lebanon are able to pass the basic language test. Investment in enhancing those educational experiences will be determinantal in achieving widespread progress among those at-risk children.

Keywords: refugee girls, TOEFL, education, success

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1031 Education in Schools and Public Policy in India

Authors: Sujeet Kumar

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Education has greater importance particularly in terms of increasing human capital and economic competitiveness. It plays a crucial role in terms of cognitive and skill development. Its plays a vital role in process of socialization, fostering social justice, and enhancing social cohesion. Policy related to education has been always a priority for developed countries, which is later adopted by developing countries also. The government of India has also brought change in education polices in line with recognizing change at national and supranational level. However, quality education is still not become an open door for every child in India and several reports are produced year to year about level of school education in India. This paper is concerned with schooling in India. Particularly, it focuses on two government and two private schools in Bihar, but reference has made to schools in Delhi especially around slum communities. The paper presents brief historical context and an overview of current school systems in India. Later, it focuses on analysis of current development in policy in reference with field observation, which is anchored around choice, diversity, market – orientation and gap between different groups of pupils. There is greater degree of difference observed at private and government school levels in terms of quality of teachers, method of teaching and overall environment of learning. The paper concludes that the recent policy development in education particularly Sarva Siksha Abhiyaan (SAA) and Right to Education Act (2009) has required renovating new approach to bridge the gap through broader consultation at grassroots and participatory approach with different stakeholders.

Keywords: education, public policy, participatory approach

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1030 Is Materiality Determination the Key to Integrating Corporate Sustainability and Maximising Value?

Authors: Ruth Hegarty, Noel Connaughton

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Sustainability reporting has become a priority for many global multinational companies. This is associated with ever-increasing expectations from key stakeholders for companies to be transparent about their strategies, activities and management with regard to sustainability issues. The Global Reporting Initiative (GRI) encourages reporters to only provide information on the issues that are really critical in order to achieve the organisation’s goals for sustainability and manage its impact on environment and society. A key challenge for most reporting organisations is how to identify relevant issues for sustainability reporting and prioritise those material issues in accordance with company and stakeholder needs. A recent study indicates that most of the largest companies listed on the world’s stock exchanges are failing to provide data on key sustainability indicators such as employee turnover, energy, greenhouse gas emissions (GHGs), injury rate, pay equity, waste and water. This paper takes an indepth look at the approaches used by a select number of international sustainability leader corporates to identify key sustainability issues. The research methodology involves performing a detailed analysis of the sustainability report content of up to 50 companies listed on the 2014 Dow Jones Sustainability Indices (DJSI). The most recent sustainability report content found on the GRI Sustainability Disclosure Database is then compared with 91 GRI Specific Standard Disclosures and a small number of GRI Standard Disclosures. Preliminary research indicates significant gaps in the information disclosed in corporate sustainability reports versus the indicator content specified in the GRI Content Index. The following outlines some of the key findings to date: Most companies made a partial disclosure with regard to the Economic indicators of climate change risks and infrastructure investments, but did not focus on the associated negative impacts. The top Environmental indicators disclosed were energy consumption and reductions, GHG emissions, water withdrawals, waste and compliance. The lowest rates of indicator disclosure included biodiversity, water discharge, mitigation of environmental impacts of products and services, transport, environmental investments, screening of new suppliers and supply chain impacts. The top Social indicators disclosed were new employee hires, rates of injury, freedom of association in operations, child labour and forced labour. Lesser disclosure rates were reported for employee training, composition of governance bodies and employees, political contributions, corruption and fines for non-compliance. The reporting on most other Social indicators was found to be poor. In addition, most companies give only a brief explanation on how material issues are defined, identified and ranked. Data on the identification of key stakeholders and the degree and nature of engagement for determining issues and their weightings is also lacking. Generally, little to no data is provided on the algorithms used to score an issue. Research indicates that most companies lack a rigorous and thorough methodology to systematically determine the material issues of sustainability reporting in accordance with company and stakeholder needs.

Keywords: identification of key stakeholders, material issues, sustainability reporting, transparency

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1029 Studying the Impact of Farmers Field School on Vegetable Production in Peshawar District of Khyber Pakhtunkhwa Province of Pakistan

Authors: Muhammad Zafarullah Khan, Sumeera Abbasi

Abstract:

The Farmers Field School (FFS) learning approach aims to improve knowledge of the farmers through integrated crop management and provide leadership in their decision making process. The study was conducted to assess the impact of FFS on vegetables production before and after FFS intervention in four villages of district Peshawar in cropping season 2012, by interviewing 80 FFS respondents, twenty from each selected village. It was observed from the study results that all the respondents were satisfied from the impact of FFS and they informed an increased in production in vegetables. It was further observed that after the implementation of FFS the sowing seed rate of tomato and cucumber were decreased from 0.185kg/kanal to 0.100 kg/ kanal and 0.120kg/kanal to 0.010kg/kanal where as the production of tomato and cucumber were increased from 8158.75kgs/kanal to 10302. 5kgs/kanal and 3230kgs/kanal to 5340kgs/kanal, respectively. The cost of agriculture inputs per kanal including seed cost, crop management, Farm Yard Manure, and weedicides in case of tomato were reduced by Rs.28, Rs. 3170, Rs.658and Rs 205 whereas in cucumber reduced by Rs.35, Rs.570, Rs 80 and Rs.430 respectively. Only fertilizers cost was increased by Rs. 2200 in case of tomato and Rs 465 in case of cucumber. Overall the cost was reduced to Rs 545 in tomato and Rs 490 in cucumber production.FFS provided a healthy vegetables and also reduced input cost by adopting integrated crop management. Therefore the promotion of FFS is needed to be planned for farmers to reduce cost of production, so that the more farmers should be benefited.

Keywords: impact, farmer field schools, vegetable production, Peshawar Khyber Pakhtunkhwa

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1028 Academic Literacy: A Study of L2 Academic Reading Literacy among a Group of EFL/ESL Postgraduate Arab Learners in a British University

Authors: Hanadi Khadawardi

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The current study contributes to research on foreign/second language (L2) academic reading by presenting a significant case study, which seeks to investigate specific groups of international (Arab) postgraduate students’ L2 academic reading practices in the UK educational context. In particular, the study scrutinises postgraduate students’ L2 paper-based and digital-based academic reading strategies, and their use of digital aids while engaged in L2 academic reading. To this end, the study investigates Arab readers’ attitudes toward digital L2 academic reading. The study aims to compare between paper and digital L2 academic reading strategies that the students employ and which reading formats they prefer. This study tracks Masters-level students and examines the way in which their reading strategies and attitudes change throughout their Masters programme in the UK educational context. The academic reading strategies and attitudes of five students from four different disciplines (Health Science, Psychology, Management, and Education) are investigated at two points during their one-year Masters programmes. In addition, the study investigates the same phenomenon with 15 Saudi PhD students drawn from seven different disciplines (Computer Science, Engineering, Psychology, Management, Marketing, Health Science, and Applied Linguistics) at one period of their study in the same context. The study uses think-aloud protocol, field notes, stimulated recall, and semi-structured interviews to collect data. The data is analysed qualitatively. The results of the study will explain the process of learning in terms of reading L2 paper and digital academic texts in the L2 context.

Keywords: EFL: English as a foreign language, ESL: English as a second language, L: Language

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1027 Neural Network Supervisory Proportional-Integral-Derivative Control of the Pressurized Water Reactor Core Power Load Following Operation

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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1026 Insights Into Serotonin-Receptor Binding and Stability via Molecular Dynamics Simulations: Key Residues for Electrostatic Interactions and Signal Transduction

Authors: Arunima Verma, Padmabati Mondal

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Serotonin-receptor binding plays a key role in several neurological and biological processes, including mood, sleep, hunger, cognition, learning, and memory. In this article, we performed molecular dynamics simulation to examine the key residues that play an essential role in the binding of serotonin to the G-protein-coupled 5-HT₁ᴮ receptor (5-HT₁ᴮ R) via electrostatic interactions. An end-point free energy calculation method (MM-PBSA) determines the stability of the 5-HT1B R due to serotonin binding. The single-point mutation of the polar or charged amino acid residues (Asp129, Thr134) on the binding sites and the calculation of binding free energy validate the importance of these residues in the stability of the serotonin-receptor complex. Principal component analysis indicates the serotonin-bound 5-HT1BR is more stabilized than the apo-receptor in terms of dynamical changes. The difference dynamic cross-correlations map shows the correlation between the transmembrane and mini-Go, which indicates signal transduction happening between mini-Go and the receptor. Allosteric communication reveals the key nodes for signal transduction in 5-HT1BR. These results provide useful insights into the signal transduction pathways and mutagenesis study to regulate the functionality of the complex. The developed protocols can be applied to study local non-covalent interactions and long-range allosteric communications in any protein-ligand system for computer-aided drug design.

Keywords: allostery, CADD, MD simulations, MM-PBSA

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1025 A Prediction Model for Dynamic Responses of Building from Earthquake Based on Evolutionary Learning

Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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1024 Effect of Ausubel's Advance Organizer Model to Enhancing Meta-Cognition of Students at Secondary Level

Authors: Qaisara Parveen, M. Imran Yousuf

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The purpose of this study was to find the effectiveness of the use of advance organizer model for enhancing meta-cognition of students in the subject of science. It was hypothesized that the students of experimental group taught through advance organizer model would show the better cognition than the students of control group taught through traditional teaching. The population of the study consisted of all secondary school students studying in government high school located in Rawalpindi. The sample of the study consisted of 50 students of 9th class of humanities group. The sample was selected on the basis of their pretest scores through matching, and the groups were randomly assigned for the treatment. The experimental group was taught through advance organizer model while the control group was taught through traditional teaching. The self-developed achievement test was used for the purpose of pretest and posttest. After collecting the pre-test score and post-test score, the data was analyzed and interpreted by use of descriptive statistics as mean and standard deviation and inferential statistics t-test. The findings indicate that students taught using advance organizers had a higher level of meta-cognition as compared to control group. Further, meta cognition level of boys was found higher than that of girls students. This study also revealed the fact that though the students at different meta-cognition level approached learning situations in a different manner, Advance organizer model is far superior to Traditional method of teaching.

Keywords: descriptive, experimental, humanities, meta-cognition, statistics, science

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1023 The Analysis of Emergency Shutdown Valves Torque Data in Terms of Its Use as a Health Indicator for System Prognostics

Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

Procedia PDF Downloads 74
1022 The Meaning of Adolescent Mothers' Experience with Childrearing and Studying Simultaneously

Authors: Benyapa Thitimapong

Abstract:

Teenage pregnancy and adolescent mothers have become a matter of increasing concern in Thailand. Since adolescent mothers have been a big problem for two main consequences; health outcomes and socio-economic impacts. Adolescent mothers often endure poor living conditions; limited financial resources while also experience high stress, family instability, and limited educational opportunities. These disadvantages are negative and have long-term effects on adolescent mothers, their families, and the community. The majority of pregnant students and adolescent mothers dropped out of school after becoming pregnant, and some of them return to study again after they gave birth. This research aimed to explain the meaning of adolescent mothers who had undergone with childrearing and studying simultaneously after childbirth. A phenomenological qualitative approach was undertaken to investigate this study. The participants were 20 adolescent mothers each of whom became a mother and a student concurrently within less than 2 years after giving birth to a healthy baby and had also undergone the experience of childrearing and studying in non-formal education. In-depth interview was carried out for data collection, and the data were analyzed using content analysis method. ‘Learning to move forward’ was the meaning of adolescent mothers who experienced with childrearing and studying simultaneously. Their expressions were classified into two categories 1) having more responsibility, and 2) conceding and going on. The result of this study can be used as evidence for health care providers, especially nurses to facilitate and support pregnant adolescents and adolescent mothers to continue their education. Also, it can be used to guide policy to promote in all educational system to enable these groups to remain in school for their life-long success in the future.

Keywords: adolescent mothers, childrearing, studying, teenage pregnancy

Procedia PDF Downloads 117
1021 A Model for Academic Coaching for Success and Inclusive Excellence in Science, Technology, Engineering, and Mathematics Education

Authors: Sylvanus N. Wosu

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Research shows that factors, such as low motivation, preparation, resources, emotional and social integration, and fears of risk-taking, are the most common barriers to access, matriculation, and retention into science, technology, engineering, and mathematics (STEM) disciplines for underrepresented (URM) students. These factors have been shown to impact students’ attraction and success in STEM fields. Standardized tests such as the SAT and ACT often used as predictor of success, are not always true predictors of success for African and Hispanic American students. Without an adequate academic support environment, even a high SAT score does not guarantee academic success in science and engineering. This paper proposes a model for Academic Coaching for building success and inclusive excellence in STEM education. Academic coaching is framed as a process of motivating students to be independent learners through relational mentorship, facilitating learning supports inside and outside of the classroom or school environment, and developing problem-solving skills and success attitudes that lead to higher performance in the specific subjects. The model is formulated based on best strategies and practices for enriching Academic Performance Impact skills and motivating students’ interests in STEM. A scaled model for measuring the Academic Performance Impact (API) index and STEM is discussed. The study correlates API with state standardized test and shows that the average impact of those skills can be predicted by the Academic Performance Impact (API) index or Academic Preparedness Index.

Keywords: diversity, equity, graduate education, inclusion, inclusive excellence, model

Procedia PDF Downloads 173
1020 Optimizing Data Transfer and Processing in Multi-Cloud Environments for Big Data Workloads

Authors: Gaurav Kumar Sinha

Abstract:

In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

Procedia PDF Downloads 47
1019 Health Professions Students' Knowledge of and Attitude toward Complementary and Alternative Medicine

Authors: Peter R. Reuter

Abstract:

Health professionals play important roles in helping patients use Complementary and Alternative Medicine (CAM) practices safely and accurately. Consequently, it is important for future health professionals to learn about CAM practices during their time in undergraduate and graduate programs. To satisfy this need for education, teaching CAM in nursing and medical schools and other health professions programs is becoming more prevalent. Our study was the first to look specifically at the knowledge of, and attitude toward CAM of undergraduate health professions students at a university in the U.S. Students were invited to participate in one of two anonymous online surveys depending on whether they were pre-health professions students or graduating health professions seniors. Of the 763 responses analyzed, 71.7% were from pre-health professions students, and 28.3% came from graduating seniors. The overall attitude of participants toward and interest in learning about CAM practices was generally fairly positive with graduating seniors being more positive than pre-health professions students. Yoga, meditation, massage therapy, aromatherapy, and chiropractic care were the practices most respondents had personal experience with. Massage therapy, yoga, chiropractic care, meditation, music therapy, and diet-based therapy received the highest ratings from respondents. Three-quarters of respondents planned on including aspects of holistic medicine in their future career as a health professional. The top five practices named were yoga, meditation, massage therapy, diet-based therapy, and music therapy. The study confirms the need to educate health professions students about CAM practices to give them the background information they need to select or recommend the best practices for their patients' needs.

Keywords: CAM education, health professions, health professions students, pre-health professions students

Procedia PDF Downloads 127
1018 An Empirical Study of the Effect of Robot Programming Education on the Computational Thinking of Young Children: The Role of Flowcharts

Authors: Wei Sun, Yan Dong

Abstract:

There is an increasing interest in introducing computational thinking at an early age. Computational thinking, like mathematical thinking, engineering thinking, and scientific thinking, is a kind of analytical thinking. Learning computational thinking skills is not only to improve technological literacy, but also allows learners to equip with practicable skills such as problem-solving skills. As people realize the importance of computational thinking, the field of educational technology faces a problem: how to choose appropriate tools and activities to help students develop computational thinking skills. Robots are gradually becoming a popular teaching tool, as robots provide a tangible way for young children to access to technology, and controlling a robot through programming offers them opportunities to engage in developing computational thinking. This study explores whether the introduction of flowcharts into the robotics programming courses can help children convert natural language into a programming language more easily, and then to better cultivate their computational thinking skills. An experimental study was adopted with a sample of children ages six to seven (N = 16) participated, and a one-meter-tall humanoid robot was used as the teaching tool. Results show that children can master basic programming concepts through robotic courses. Children's computational thinking has been significantly improved. Besides, results suggest that flowcharts do have an impact on young children’s computational thinking skills development, but it only has a significant effect on the "sequencing" and "correspondence" skills. Overall, the study demonstrates that the humanoid robot and flowcharts have qualities that foster young children to learn programming and develop computational thinking skills.

Keywords: robotics, computational thinking, programming, young children, flow chart

Procedia PDF Downloads 129
1017 Multiscale Entropy Analysis of Electroencephalogram (EEG) of Alcoholic and Control Subjects

Authors: Lal Hussain, Wajid Aziz, Imtiaz Ahmed Awan, Sharjeel Saeed

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Multiscale entropy analysis (MSE) is a useful technique recently developed to quantify the dynamics of physiological signals at different time scales. This study is aimed at investigating the electroencephalogram (EEG) signals to analyze the background activity of alcoholic and control subjects by inspecting various coarse-grained sequences formed at different time scales. EEG recordings of alcoholic and control subjects were taken from the publically available machine learning repository of University of California (UCI) acquired using 64 electrodes. The MSE analysis was performed on the EEG data acquired from all the electrodes of alcoholic and control subjects. Mann-Whitney rank test was used to find significant differences between the groups and result were considered statistically significant for p-values<0.05. The area under receiver operator curve was computed to find the degree separation between the groups. The mean ranks of MSE values at all the times scales for all electrodes were higher control subject as compared to alcoholic subjects. Higher mean ranks represent higher complexity and vice versa. The finding indicated that EEG signals acquired through electrodes C3, C4, F3, F7, F8, O1, O2, P3, T7 showed significant differences between alcoholic and control subjects at time scales 1 to 5. Moreover, all electrodes exhibit significance level at different time scales. Likewise, the highest accuracy and separation was obtained at the central region (C3 and C4), front polar regions (P3, O1, F3, F7, F8 and T8) while other electrodes such asFp1, Fp2, P4 and F4 shows no significant results.

Keywords: electroencephalogram (EEG), multiscale sample entropy (MSE), Mann-Whitney test (MMT), Receiver Operator Curve (ROC), complexity analysis

Procedia PDF Downloads 361
1016 Investigate the Effect and the Main Influencing Factors of the Accelerated Reader Programme on Chinese Primary School Students’ Reading Achievement

Authors: Fujia Yang

Abstract:

Alongside technological innovation, the current “double reduction” policy and English Curriculum Standards for Compulsory Education in China both emphasise and encourage appropriately integrating educational technologies into the classroom. Therefore, schools are increasingly using digital means to engage students in English reading, but the impact of such technologies on Chinese pupils’ reading achievement remains unclear. To serve as a reference for reforming English reading education in primary schools under the double reduction policy, this study investigates the effects and primary influencing factors of a specific reading programme, Accelerated Reader (AR), on Chinese primary school students’ reading achievement. A quantitative online survey was used to collect 37 valid questionnaires from teachers, and the results demonstrate that, from teachers’ perspectives, the AR program seemed to positively affect students’ reading achievement by recommending material at the appropriate reading levels and developing students’ reading habits. Although the reading enjoyment derived from the AR program does not directly influence students’ reading achievement, these factors are strongly correlated. This can be explained by the self-paced, independent learning AR format, its high accuracy in predicting reading level, the quiz format and external motivation, and the importance of examinations and resource limitations in China. The results of this study may support reforming English reading education in Chinese primary schools.

Keywords: educational technology, reading programme, primary students, accelerated reader, reading effects

Procedia PDF Downloads 65
1015 A Qualitative Study Examining the Process of EFL Course Design from the Perspectives of Teachers

Authors: Iman Al Khalidi

Abstract:

Recently, English has become the language of globalization and technology. In turn, this has resulted in a seemingly bewildering array of influences and trends in the domain of TESOL curriculum. In light of these changes, higher education has to provide a new and more powerful kind of education. It should prepare students to be more engaged citizens, more capable to solve complex problems at work, and well prepared to lead meaningful life. In response to this, universities, colleges, schools, and departments have to work out in light of the requirements and challenges of the global and technological era. Consequently they have to focus on the adoption of contemporary curriculum which goes in line with the pedagogical shifts from teaching –centered approach to learning centered approach. Ideally, there has been noticeable emphasis on the crucial importance of developing and professionalizing teachers in order to engage them in the process of curriculum development and action research. This is a qualitative study that aims at understanding and exploring the process of designing EFL courses by teachers at the tertiary level from the perspectives of the participants in a professional context in TESOL, Department of English, a private college in Oman. It is a case study that stands on the philosophy of the qualitative approach. It employs multi methods for collecting qualitative data: semi-structured interviews with teachers, focus group discussions with students, and document analysis. The collected data have been analyzed qualitatively by adopting Miles and Huberman's Approach using procedures of reduction, coding, displaying and conclusion drawing and verification.

Keywords: course design, components of course design, case study, data analysis

Procedia PDF Downloads 525
1014 A Qualitative Study Examining the Process of Course Design from the Perspectives of Teachers

Authors: Iman Al Khalidi

Abstract:

Recently, English has become the language of globalization and technology. In turn, this has resulted in a seemingly bewildering array of influences and trends in the domain of TESOL curriculum. In light of these changes, higher education has to provide a new and more powerful kind of education. It should prepare students to be more engaged citizens, more capable to solve complex problems at work, and well prepared to lead a meaningful life. In response to this, universities, colleges, schools, and departments have to work out in light of the requirements and challenges of the global and technological era. Consequently, they have to focus on the adoption of contemporary curriculum which goes in line with the pedagogical shifts from teaching –centered approach to learning centered approach. Ideally, there has been noticeable emphasis on the crucial importance of developing and professionalizing teachers in order to engage them in the process of curriculum development and action research. This is a qualitative study that aims at understanding and exploring the process of designing EFL courses by teachers at the tertiary level from the perspectives of the participants in a professional context in TESOL, Department of English, a private college in Oman. It is a case study that stands on the philosophy of the qualitative approach. It employs multi-methods for collecting qualitative data: semi-structured interviews with teachers, focus group discussions with students, and document analysis. The collected data have been analyzed qualitatively by adopting Miles and Huberman's Approach using procedures of reduction, coding, displaying, and conclusion drawing and verification.

Keywords: course design, components of course design, case study, data analysis

Procedia PDF Downloads 430
1013 Organization Culture: Mediator of Information Technology Competence and IT Governance Effectiveness

Authors: Sonny Nyeko, Moses Niwe

Abstract:

Purpose: This research paper examined the mediation effect of organization culture in the relationship between information technology (IT) competence and IT governance effectiveness in Ugandan public universities. The purpose of the research paper is to examine the role of organizational culture in the relationship between IT competence and IT governance effectiveness. Design/methodology/approach: The paper adopted the MedGraph program, Sobel tests and Kenny and Baron Approach for testing the mediation effects. Findings: It is impeccable that IT competence and organization culture are true drivers of IT governance effectiveness in Ugandan public universities. However, organizational culture reveals partial mediation in the IT competence and IT governance effectiveness relationship. Research limitations/implications: The empirical investigation in this research depends profoundly on public universities. Future research in Ugandan private universities could be undertaken to compare results. Practical implications: To effectively achieve IT governance effectiveness, it means senior management requires IT knowledge which is a vital ingredient of IT competence. Moreover, organizations today ought to adopt cultures that are intended to have them competitive in their businesses, with IT operations not in isolation. Originality/value: Spending thousands of dollars on IT resources in advanced institutes of learning necessitates IT control. Preliminary studies in Ugandan public universities have revealed the ineffective utilization of IT resources. Besides, IT governance issues with IT competence and organization culture remain outstanding. Thus, it’s a new study testing the mediating outcome of organization culture in the association between IT competence and IT governance effectiveness in the Ugandan universities.

Keywords: organization culture, IT competence, IT governance, effectiveness, mediating effect, universities, Uganda

Procedia PDF Downloads 113