Search results for: physical learning environment
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19482

Search results for: physical learning environment

16332 Use of Machine Learning in Data Quality Assessment

Authors: Bruno Pinto Vieira, Marco Antonio Calijorne Soares, Armando Sérgio de Aguiar Filho

Abstract:

Nowadays, a massive amount of information has been produced by different data sources, including mobile devices and transactional systems. In this scenario, concerns arise on how to maintain or establish data quality, which is now treated as a product to be defined, measured, analyzed, and improved to meet consumers' needs, which is the one who uses these data in decision making and companies strategies. Information that reaches low levels of quality can lead to issues that can consume time and money, such as missed business opportunities, inadequate decisions, and bad risk management actions. The step of selecting, identifying, evaluating, and selecting data sources with significant quality according to the need has become a costly task for users since the sources do not provide information about their quality. Traditional data quality control methods are based on user experience or business rules limiting performance and slowing down the process with less than desirable accuracy. Using advanced machine learning algorithms, it is possible to take advantage of computational resources to overcome challenges and add value to companies and users. In this study, machine learning is applied to data quality analysis on different datasets, seeking to compare the performance of the techniques according to the dimensions of quality assessment. As a result, we could create a ranking of approaches used, besides a system that is able to carry out automatically, data quality assessment.

Keywords: machine learning, data quality, quality dimension, quality assessment

Procedia PDF Downloads 143
16331 Higher Education Institution Students’ Perception on Educational Technology

Authors: Kuek Teik Sheng, Leaw Zee Guan, Lim Wah Kien, Ting Tin Tin

Abstract:

Educational technology such as YouTube and Kahoot have arisen as an alternative to effective learning among higher education institutions. There are many researches done in carrying out experiments to test different educational technologies and received positive feedback from students. Yet, similar study is hardly found in Malaysia especially study that includes the latest educational technologies. As a developing country, it is crucial to ensure that these emerging technologies are assisting students in learning process before it is widely adopted in institutions. This paper conducted a study to explore the perception of higher education institution students on the current educational technologies in Malaysia which include online educational games, online videos/course, social media, presentation tools and resource management tool. Some of these technologies have not been looked into its potential in effective learning process. An online survey using questionnaire is conducted among a target of 300 university/college. In the survey, the result shows that majority of the target students in Malaysia agree that the current educational technologies help them in learning, understanding and manage their studies. It is necessary to discover students’ perceptions on the educational technologies in order to provide guidelines for the educators/institutions in selecting appropriate technology to conduct the lecture/tutorial efficiently and effectively.

Keywords: education, educational technology, Facebook, PowerPoint, YouTube

Procedia PDF Downloads 236
16330 A Physical Treatment Method as a Prevention Method for Barium Sulfate Scaling

Authors: M. A. Salman, G. Al-Nuwaibit, M. Safar, M. Rughaibi, A. Al-Mesri

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Barium sulfate (BaSO₄) is a hard scaling usually precipitates on the surface of equipment in many industrial systems, as oil and gas production, desalination and cooling and boiler operation. It is a scale that extremely resistance to both chemical and mechanical cleaning. So, BaSO₄ is a problematic and expensive scaling. Although barium ions are present in most natural waters at a very low concentration as low as 0.008 mg/l, it could result of scaling problems in the presence of high concentration of sulfate ion or when mixing with incompatible waters as in oil produced water. The scaling potential of BaSO₄ using seawater at the intake of seven desalination plants in Kuwait, brine water and Kuwait oil produced water was calculated and compared then the best location in regards of barium sulfate scaling was reported. Finally, a physical treatment method (magnetic treatment method) and chemical treatment method were used to control BaSO₄ scaling using saturated solutions at different operating temperatures, flow velocities, feed pHs and different magnetic strengths. The results of the two methods were discussed, and the more economical one with the reasonable performance was recommended, which is the physical treatment method.

Keywords: magnetic field strength, flow velocity, retention time, barium sulfate

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16329 Numerical Analysis of 3D Electromagnetic Fields in Annular Induction Plasma

Authors: Abderazak Guettaf

Abstract:

The mathematical models of the physical phenomena interacting in inductive plasma were described by the physics equations of the continuous mediums. A 3D model based on magnetic potential vector and electric scalar potential (A, V) formulation is used. The finished volume method is applied to electromagnetic equation, to obtain the field distribution inside the plasma. The numerical results of the method developed on a basic model designed starting from a real three-dimensional model were exposed. From the mathematical model 3D spreading assumptions and boundary conditions, we evaluated the electric field in the load and we have developed a numerical code made under the MATLAB environment, all verifying the effectiveness and validity of this code.

Keywords: electric field, 3D magnetic potential vector and electric scalar potential (A, V) formulation, finished volumes, annular plasma

Procedia PDF Downloads 487
16328 The Revealed Preference Methods in Economic Valuation of Environmental Goods: A Review

Authors: Sara Sousa

Abstract:

The environmental goods and services have often been neglected in crucial decisions affecting the environment mainly because the difficulty in estimating their economic value, since we are dealing with non-market goods and, thus, without a price associated. Nevertheless, the inexistence of prices does not necessarily mean these goods have no value. The environment is a key element in today's society that seeks to be as sustainable as possible, where the environmental assets have both use and non-use values. To estimate the use value, researchers may apply the revealed preference methods. This paper provides a theoretical review of the main concepts and methodologies on the economic valuation of the environment, with particular emphasis on the revealed preference techniques. Based on a detailed literature review, this study concludes that, despite some inherent limitations, the revealed preference methodologies – travel cost, hedonic price, and averting behaviour – represent essential tools for the researchers who accept the challenge to estimate the use value of environmental goods and services based on the actual individuals` behaviour. The main purpose of this study is to contribute to an increased theoretical information on the economic valuation of environmental assets, allowing researchers and policymakers to improve future decisions regarding the environment.

Keywords: economic valuation, environmental goods, revealed preference methods, total economic value

Procedia PDF Downloads 126
16327 Effect of Semantic Relational Cues in Action Memory Performance over School Ages

Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharazi

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Research into long-term memory has demonstrated that the richness of the knowledge base cues in memory tasks improves retrieval process, which in turn influences learning and memory performance. The present research investigated the idea that adding cues connected to knowledge can affect memory performance in the context of action memory in children. In action memory studies, participants are instructed to learn a series of verb–object phrases as verbal learning and experience-based learning (learning by doing and learning by observation). It is well established that executing action phrases is a more memorable way to learn than verbally repeating the phrases, a finding called enactment effect. In the present study, a total of 410 students from four grade groups—2nd, 4th, 6th, and 8th—participated in this study. During the study, participants listened to verbal action phrases (VTs), performed the phrases (SPTs: subject-performed tasks), and observed the experimenter perform the phrases (EPTs: experimenter-performed tasks). During the test phase, cued recall test was administered. Semantic relational cues (i.e., well-integrated vs. poorly integrated items) were manipulated in the present study. In that, the participants were presented two lists of action phrases with high semantic integration between verb and noun, e.g., “write with the pen” and with low semantic integration between verb and noun, e.g., “pick up the glass”. Results revealed that experience-based learning had a better results than verbal learning for both well-integrated and poorly integrated items, though manipulations of semantic relational cues can moderate the enactment effect. In addition, children of different grade groups outperformed for well- than poorly integrated items, in flavour of older children. The results were discussed in relation to the effect of knowledge-based information in facilitating retrieval process in children.

Keywords: action memory, enactment effect, knowledge-based cues, school-aged children, semantic relational cues

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16326 The Interleaving Effect of Subject Matter and Perceptual Modality on Students’ Attention and Learning: A Portable EEG Study

Authors: Wen Chen

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To investigate the interleaving effect of subject matter (mathematics vs. history) and perceptual modality (visual vs. auditory materials) on student’s attention and learning outcomes, the present study collected self-reported data on subjective cognitive load (SCL) and attention level, EEG data, and learning outcomes from micro-lectures. Eighty-one 7th grade students were randomly assigned to four learning conditions: blocked (by subject matter) micro-lectures with auditory textual information (B-A condition), blocked (by subject matter) micro-lectures with visual textual information (B-V condition), interleaved (by subject matter) micro-lectures with auditory textual information (I-A condition), and interleaved micro-lectures by both perceptual modality and subject matter (I-all condition). The results showed that although interleaved conditions may show advantages in certain indices, the I-all condition showed the best overall outcomes (best performance, low SCL, and high attention). This study suggests that interleaving by both subject matter and perceptual modality should be preferred in scheduling and planning classes.

Keywords: cognitive load, interleaving effect, micro-lectures, sustained attention

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16325 Machine Learning Approach for Anomaly Detection in the Simulated Iec-60870-5-104 Traffic

Authors: Stepan Grebeniuk, Ersi Hodo, Henri Ruotsalainen, Paul Tavolato

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Substation security plays an important role in the power delivery system. During the past years, there has been an increase in number of attacks on automation networks of the substations. In spite of that, there hasn’t been enough focus dedicated to the protection of such networks. Aiming to design a specialized anomaly detection system based on machine learning, in this paper we will discuss the IEC 60870-5-104 protocol that is used for communication between substation and control station and focus on the simulation of the substation traffic. Firstly, we will simulate the communication between substation slave and server. Secondly, we will compare the system's normal behavior and its behavior under the attack, in order to extract the right features which will be needed for building an anomaly detection system. Lastly, based on the features we will suggest the anomaly detection system for the asynchronous protocol IEC 60870-5-104.

Keywords: Anomaly detection, IEC-60870-5-104, Machine learning, Man-in-the-Middle attacks, Substation security

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16324 Musical Instruments Classification Using Machine Learning Techniques

Authors: Bhalke D. G., Bormane D. S., Kharate G. K.

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This paper presents classification of musical instrument using machine learning techniques. The classification has been carried out using temporal, spectral, cepstral and wavelet features. Detail feature analysis is carried out using separate and combined features. Further, instrument model has been developed using K-Nearest Neighbor and Support Vector Machine (SVM). Benchmarked McGill university database has been used to test the performance of the system. Experimental result shows that SVM performs better as compared to KNN classifier.

Keywords: feature extraction, SVM, KNN, musical instruments

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16323 “Environmental-Friendly” and “People-Friendly” Project for a New North-East Italian Hospital

Authors: Emanuela Zilli, Antonella Ruffatto, Davide Bonaldo, Stefano Bevilacqua, Tommaso Caputo, Luisa Fontana, Carmelina Saraceno, Antonio Sturaroo, Teodoro Sava, Antonio Madia

Abstract:

The new Hospital in Cittadella - ULSS 6 Euganea Health Trust, in the North-East of Italy (400 beds, project completion date in 2026), will partially take the place of the existing building. Interesting features have been suggested in order to project a modern, “environmental-friendly” and “people-friendly” building. Specific multidisciplinary meetings (involving stakeholders and professionals with different backgrounds) have been organized on a periodic basis in order to guarantee the appropriate implementation of logistic and organizational solutions related to eco-sustainability, integration with the context, and the concept of “design for all” and “humanization of care.” The resulting building will be composed of organic shapes determined by the external environment (sun movement, climate, landscape, pre-existing buildings, roads) and the needs of the internal environment (areas of care and diagnostic-treatment paths reorganized with experience gained during the pandemic), with extensive use of renewable energy, solar panels, a 4th-generation heating system, sanitised and maintainable surfaces. There is particular attention to the quality of the staff areas, which include areas dedicated to psycho-physical well-being (relax points, yoga gym), study rooms, and a centralized conference room. Outdoor recreational spaces and gardens for music and watercolour therapy will be included; atai-chi gym is dedicated to oncology patients. Integration in the urban and social context is emphasized through window placement toward the gardens (maternal-infant, mental health, and rehabilitation wards). Service areas such as dialysis, radiology, and labs have views of the medieval walls, the symbol of the city’s history. The new building has been designed to pursue the maximum level of eco-sustainability, harmony with the environment, and integration with the historical, urban, and social context; the concept of humanization of care has been considered in all the phases of the project management.

Keywords: environmental-friendly, humanization, eco-sustainability, new hospital

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16322 Managing Data from One Hundred Thousand Internet of Things Devices Globally for Mining Insights

Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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16321 A Qualitative Study on Metacognitive Patterns among High and Low Performance Problem Based on Learning Groups

Authors: Zuhairah Abdul Hadi, Mohd Nazir bin Md. Zabit, Zuriadah Ismail

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Metacognitive has been empirically evidenced to be one important element influencing learning outcomes. Expert learners engage in metacognition by monitoring and controlling their thinking, and listing, considering and selecting the best strategies to achieve desired goals. Studies also found that good critical thinkers engage in more metacognition and people tend to activate more metacognition when solving complex problems. This study extends past studies by performing a qualitative analysis to understand metacognitive patterns among two high and two low performing groups by carefully examining video and audio records taken during Problem-based learning activities. High performing groups are groups with majority members scored well in Watson Glaser II Critical Thinking Appraisal (WGCTA II) and academic achievement tests. Low performing groups are groups with majority members fail to perform in the two tests. Audio records are transcribed and analyzed using schemas adopted from past studies. Metacognitive statements are analyzed using three stages model and patterns of metacognitive are described by contexts, components, and levels for each high and low performing groups.

Keywords: academic achievement, critical thinking, metacognitive, problem-based learning

Procedia PDF Downloads 281
16320 The Development of Online Lessons in Integration Model

Authors: Chalermpol Tapsai

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The objectives of this research were to develop and find the efficiency of integrated online lessons by investigating the usage of online lessons, the relationship between learners’ background knowledge, and the achievement after learning with online lessons. The sample group in this study consisted of 97 students randomly selected from 121 students registering in 1/2012 at Trimitwittayaram Learning Center. The sample technique employed stratified sample technique of 4 groups according to their proficiency, i.e. high, moderate, low, and non-knowledge. The research instrument included online lessons in integration model on the topic of Java Programming, test after each lesson, the achievement test at the end of the course, and the questionnaires to find learners’ satisfaction. The results showed that the efficiency of online lessons was 90.20/89.18 with the achievement of after learning with the lessons higher than that before the lessons at the statistically significant level of 0.05. Moreover, the background knowledge of the learners on the programming showed the positive relationship with the achievement learning at the statistically significant level at 0.05. Learners with high background knowledge employed less exercises and samples than those with lower background knowledge. While learners with different background in the group of moderate and low did not show the significant difference in employing samples and exercises.

Keywords: integration model, online lessons, learners’ background knowledge, efficiency

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16319 Lived Experiences of Primary Caregiver of Schizophrenia Patients at Acute Crisis Intervention Service

Authors: Mykah W. Sumoldao, Maria Erissa C. Susa, Triny Cate M. Telan, Christian Arvin M. Torres, Jasmine I. Udasco, Franceis Jeramil M. Walis, Shellyn S. Wandagan, Janine May M. Warding, Queenie Diana Rose P. Zalun Hope Lulet A. Lomioan

Abstract:

This descriptive phenomenological study explored the lived experiences of the primary caregiver of schizophrenia patients at the Acute Crisis Intervention Service in Cagayan Valley Medical Center. The research aimed to understand the emotional, physical, and financial challenges these primary caregivers face. Data was gathered through interviews with nine (9) primary caregivers and analyzed using Colaizzi’s seven-step method. Two main themes emerged: Experience/ Challenges (Emotional, Physical, and Financial Challenges) and Managing Mechanisms (Support Systems and Resilience and Commitment). The study found that primary caregivers deal with a complex mix of difficulties, often with limited resources. They rely heavily on personal strength, faith, family, friends and community support to manage their roles. The findings highlighted the need for better support systems to ease primary caregivers' burdens. Financial aid, respite care, and mental health support are crucial for improving primary caregivers' quality of life and the care they provide. Additionally, raising awareness about primary caregivers' challenges can foster a supportive community, with more help from local organizations and government entities. Thus, this study provided insights into the caregiving experiences of those supporting schizophrenia patients. It emphasized the importance of practical support and emotional resilience. By addressing these needs, a more supportive environment can be created, benefiting both primary caregivers and their patients.

Keywords: primary caregiver burden, mental health, primary caregiver well-being, primary caregiver

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16318 A Flipped Learning Experience in an Introductory Course of Information and Communication Technology in Two Bachelor's Degrees: Combining the Best of Online and Face-to-Face Teaching

Authors: Begona del Pino, Beatriz Prieto, Alberto Prieto

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Two opposite approaches to teaching can be considered: in-class learning (teacher-oriented) versus virtual learning (student-oriented). The most known example of the latter is Massive Online Open Courses (MOOCs). Both methodologies have pros and cons. Nowadays there is an increasing trend towards combining both of them. Blending learning is considered a valuable tool for improving learning since it combines student-centred interactive e-learning and face to face instruction. The aim of this contribution is to exchange and share the experience and research results of a blended-learning project that took place in the University of Granada (Spain). The research objective was to prove how combining didactic resources of a MOOC with in-class teaching, interacting directly with students, can substantially improve academic results, as well as student acceptance. The proposed methodology is based on the use of flipped learning technics applied to the subject ‘Fundamentals of Computer Science’ of the first course of two degrees: Telecommunications Engineering, and Industrial Electronics. In this proposal, students acquire the theoretical knowledges at home through a MOOC platform, where they watch video-lectures, do self-evaluation tests, and use other academic multimedia online resources. Afterwards, they have to attend to in-class teaching where they do other activities in order to interact with teachers and the rest of students (discussing of the videos, solving of doubts and practical exercises, etc.), trying to overcome the disadvantages of self-regulated learning. The results are obtained through the grades of the students and their assessment of the blended experience, based on an opinion survey conducted at the end of the course. The major findings of the study are the following: The percentage of students passing the subject has grown from 53% (average from 2011 to 2014 using traditional learning methodology) to 76% (average from 2015 to 2018 using blended methodology). The average grade has improved from 5.20±1.99 to 6.38±1.66. The results of the opinion survey indicate that most students preferred blended methodology to traditional approaches, and positively valued both courses. In fact, 69% of students felt ‘quite’ or ‘very’ satisfied with the classroom activities; 65% of students preferred the flipped classroom methodology to traditional in-class lectures, and finally, 79% said they were ‘quite’ or ‘very’ satisfied with the course in general. The main conclusions of the experience are the improvement in academic results, as well as the highly satisfactory assessments obtained in the opinion surveys. The results confirm the huge potential of combining MOOCs in formal undergraduate studies with on-campus learning activities. Nevertheless, the results in terms of students’ participation and follow-up have a wide margin for improvement. The method is highly demanding for both students and teachers. As a recommendation, students must perform the assigned tasks with perseverance, every week, in order to take advantage of the face-to-face classes. This perseverance is precisely what needs to be promoted among students because it clearly brings about an improvement in learning.

Keywords: blended learning, educational paradigm, flipped classroom, flipped learning technologies, lessons learned, massive online open course, MOOC, teacher roles through technology

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16317 The Relevance of Community Involvement in Flood Risk Governance Towards Resilience to Groundwater Flooding. A Case Study of Project Groundwater Buckinghamshire, UK

Authors: Claude Nsobya, Alice Moncaster, Karen Potter, Jed Ramsay

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The shift in Flood Risk Governance (FRG) has moved away from traditional approaches that solely relied on centralized decision-making and structural flood defenses. Instead, there is now the adoption of integrated flood risk management measures that involve various actors and stakeholders. This new approach emphasizes people-centered approaches, including adaptation and learning. This shift to a diversity of FRG approaches has been identified as a significant factor in enhancing resilience. Resilience here refers to a community's ability to withstand, absorb, recover, adapt, and potentially transform in the face of flood events. It is argued that if the FRG merely focused on the conventional 'fighting the water' - flood defense - communities would not be resilient. The move to these people-centered approaches also implies that communities will be more involved in FRG. It is suggested that effective flood risk governance influences resilience through meaningful community involvement, and effective community engagement is vital in shaping community resilience to floods. Successful community participation not only uses context-specific indigenous knowledge but also develops a sense of ownership and responsibility. Through capacity development initiatives, it can also raise awareness and all these help in building resilience. Recent Flood Risk Management (FRM) projects have thus had increasing community involvement, with varied conceptualizations of such community engagement in the academic literature on FRM. In the context of overland floods, there has been a substantial body of literature on Flood Risk Governance and Management. Yet, groundwater flooding has gotten little attention despite its unique qualities, such as its persistence for weeks or months, slow onset, and near-invisibility. There has been a little study in this area on how successful community involvement in Flood Risk Governance may improve community resilience to groundwater flooding in particular. This paper focuses on a case study of a flood risk management project in the United Kingdom. Buckinghamshire Council is leading Project Groundwater, which is one of 25 significant initiatives sponsored by England's Department for Environment, Food and Rural Affairs (DEFRA) Flood and Coastal Resilience Innovation Programme. DEFRA awarded Buckinghamshire Council and other councils 150 million to collaborate with communities and implement innovative methods to increase resilience to groundwater flooding. Based on a literature review, this paper proposes a new paradigm for effective community engagement in Flood Risk Governance (FRG). This study contends that effective community participation can have an impact on various resilience capacities identified in the literature, including social capital, institutional capital, physical capital, natural capital, human capital, and economic capital. In the case of social capital, for example, successful community engagement can influence social capital through the process of social learning as well as through developing social networks and trust values, which are vital in influencing communities' capacity to resist, absorb, recover, and adapt. The study examines community engagement in Project Groundwater using surveys with local communities and documentary analysis to test this notion. The outcomes of the study will inform community involvement activities in Project Groundwater and may shape DEFRA policies and guidelines for community engagement in FRM.

Keywords: flood risk governance, community, resilience, groundwater flooding

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16316 Motivational Orientation of the Methodical System of Teaching Mathematics in Secondary Schools

Authors: M. Rodionov, Z. Dedovets

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The article analyses the composition and structure of the motivationally oriented methodological system of teaching mathematics (purpose, content, methods, forms, and means of teaching), viewed through the prism of the student as the subject of the learning process. Particular attention is paid to the problem of methods of teaching mathematics, which are represented in the form of an ordered triad of attributes corresponding to the selected characteristics. A systematic analysis of possible options and their methodological interpretation enriched existing ideas about known methods and technologies of training, and significantly expanded their nomenclature by including previously unstudied combinations of characteristics. In addition, examples outlined in this article illustrate the possibilities of enhancing the motivational capacity of a particular method or technology in the real learning practice of teaching mathematics through more free goal-setting and varying the conditions of the problem situations. The authors recommend the implementation of different strategies according to their characteristics in teaching and learning mathematics in secondary schools.

Keywords: education, methodological system, the teaching of mathematics, students motivation

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16315 An Interrogation of Lecturer’s Skills in Assisting Visually Impaired Students during the COVID-19 Lockdown Era in Selected Universities in Zimbabwe

Authors: Esther Mafunda

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The present study interrogated the lecturer’s skills in supporting visually impaired students during the Covid-19 era at the University of Zimbabwe. It particularly assesses how the Covid-19 pandemic affected the learning experience of visually impaired students and which skills the lecturers possessed in order to assist the visually impaired students during online learning. Data was collected from lecturers and visually impaired students at the University of Zimbabwe Disability Resource Centre. Data was collected through the use of interviews and questionnaires. Using content analysis, it was established that visually impaired students faced challenges of lack of familiarity with the Moodle learning platform, marginalization, lack of professional training, and lack of training for parents and guardians. Lecturers faced challenges of lack of training, the curriculum, access, and technical know-how deficit. It was established that lecturers had to resort to social media platforms in order to assist visually impaired students. Visually impaired students also received assistance from their friends and family members. On the basis of the results of the research, it can be concluded that lecturers needed in-service training to be provided with the necessary skills and knowledge to teach students with visual impairments and provide quality education to students with visual impairments.

Keywords: visual impairment, disability, covid-19, inclusive learning

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16314 Remembering Route in an Unfamiliar Homogenous Environment

Authors: Ahmed Sameer, Braj Bhushan

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The objective of our study was to compare two techniques (no landmark vs imaginary landmark) of remembering route while traversing in an unfamiliar homogenous environment. We used two videos each having nine identical turns with no landmarks. In the first video participant was required to remember the sequence of turns. In the second video participant was required to imagine a landmark at each turn and associate the turn with it. In both the task the participant was asked to recall the sequence of turns as it appeared in the video. Results showed that performance in the first condition i.e. without use of landmarks was better than imaginary landmark condition. The difference, however, became significant when the participant were tested again about 30 minutes later though performance was still better in no-landmark condition. The finding is surprising given the past research in memory and is explained in terms of cognitive factors such as mental workload.

Keywords: wayfinding, landmarks, unfamiliar environment, cognitive psychology

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16313 Effect of Whole-Body Vibration Training on Self-Reported Physical Disability in Employees with Chronic Low-Back Pain: A Randomized Controlled Trial

Authors: Tobias Stephan Kaeding, Rebecca Schwarz, Momme Kück, Lothar Stein

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Introduction: The goal of this randomized and controlled study is to examine whether whole-body vibration (WBV) training is able to reduce self-reported physical disability in office employees with chronic low-back pain. Materials and methods: 41 subjects (68.3% female/mean age 45.5 ± 9.1 years/mean BMI 26.6 ± 5.2) were randomly allocated to an intervention group (INT (n= 21)) or a control group (CON (n=20). The INT participated in WBV training 2.5 times per week for 3 months. The primary outcome was the change in the Roland and Morris disability questionnaire (RMQ) score over the study period. In addition, secondary outcomes included changes in the Oswestry Disability Index (ODI). Results: The compliance with the intervention in the INT reached a mean of 81.1% ± 31.2% with no long-lasting unwanted side effects. We found significant positive effects of 3 months of WBV training in the INT compared to the CON regarding the RMQ (p=0.027) and the ODI (p=0.002). Conclusions: WBV training seems to be an effective, safe and suitable intervention for the reduction of the self-reported physical disability in seated working employees with chronic low-back pain.

Keywords: back pain, exercise, occupational health management, vibration training

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16312 Predicting Emerging Agricultural Investment Opportunities: The Potential of Structural Evolution Index

Authors: Kwaku Damoah

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The agricultural sector is characterized by continuous transformation, driven by factors such as demographic shifts, evolving consumer preferences, climate change, and migration trends. This dynamic environment presents complex challenges for key stakeholders including farmers, governments, and investors, who must navigate these changes to achieve optimal investment returns. To effectively predict market trends and uncover promising investment opportunities, a systematic, data-driven approach is essential. This paper introduces the Structural Evolution Index (SEI), a machine learning-based methodology. SEI is specifically designed to analyse long-term trends and forecast the potential of emerging agricultural products for investment. Versatile in application, it evaluates various agricultural metrics such as production, yield, trade, land use, and consumption, providing a comprehensive view of the evolution within agricultural markets. By harnessing data from the UN Food and Agricultural Organisation (FAOSTAT), this study demonstrates the SEI's capabilities through Comparative Exploratory Analysis and evaluation of international trade in agricultural products, focusing on Malaysia and Singapore. The SEI methodology reveals intricate patterns and transitions within the agricultural sector, enabling stakeholders to strategically identify and capitalize on emerging markets. This predictive framework is a powerful tool for decision-makers, offering crucial insights that help anticipate market shifts and align investments with anticipated returns.

Keywords: agricultural investment, algorithm, comparative exploratory analytics, machine learning, market trends, predictive analytics, structural evolution index

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16311 From Teaching Methods to Learning Styles: Toward Humanizing Education and Building Rapport with Students at Sultan Qaboos University

Authors: Mounir Ben Zid

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The controversy over the most effective teaching method to facilitate the increase of a student's knowledge has remained a frustration for poetry teachers at Sultan Qaboos University in Oman for the last ten years. Scholars and educationists have pursued answers to this question, and tremendous effort has been marshalled to discover the optimum teaching strategy, with little success. The present study stems from this perpetual frustration among teachers of poetry and the dispute about the repertoire of teaching methods. It attempts to shed light on an alternative direction which, it is believed, has received less scholarly attention than deserved. It emphasizes the need to create a democratic and human atmosphere of learning, arouses students' genuine interest, provides students with aesthetic pleasure, and enable them to appreciate and enjoy the beauty and musicality of words in poems. More important, this teaching-learning style should aim to secure rapport with students, invite teachers to inspire the passion and love of poetry in their students and help them not to lose the sense of wonder and enthusiasm that should be in the forefront of enjoying poetry. Hence, it is the need of the time that, after they have an interest, feeling and desire for poetry, university students can move to heavier tasks and discussions about poetry and how to further understand and analyze what is being portrayed. It is timely that the pendulum swung in support of the humanization of education and building rapport with students at Sultan Qaboos University.

Keywords: education, humanization, learning style, Rapport

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16310 ICT in Education – A Quest for Quality Learning in the 21st Century

Authors: Adam Johnbull

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The paper discusses ICT in Education as a quest for quality learning in the 21st century. Education is the key that unlock the door to development, without adequate education of the citizenry, the development of a nation becomes a sham. Information Communication Technologies (ICTs) has revolutionized the way people work today and are now transforming education systems. As a result, if schools train children in yesterday’s skills and technologies they may not be effective and fit in tomorrow’s world. This is a sufficient reason for ICT’s to win global recognition and attention and thus ensure desire quality in our school system. Thus, the purpose of the paper is to discuss amongst others, what is ICT. The roles of ICT’s in education, limitation and key challenges of integrating ICT to education in the enhancement of student learning and experiences in other to encourage policy makers, school administrators and teachers pay the required attention to integrate this technology in the education system. The paper concludes that regardless of all the limitation characterizing it. ICT benefit education system to provide quality education in the 21st century.

Keywords: ICTs, quest, information, global, sham, century

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16309 The Mediation Effect of PTSD and Aggression on the Relationship of Childhood Physical Abuse and Suicidal Behavior in Homeless People

Authors: Jina Hong, Seongeun Ryu, Sungeun You

Abstract:

Suicide rate among homeless people are much higher than one in the general population. The purpose of this study was to examine the mediating effect of PTSD and aggression in the relationship between childhood physical abuse and suicidal behavior among homeless people. One hundred one homeless were recruited from street and shelters in Korea. Face-to-face interviews were conducted by master’s level graduate students or facility employees of shelters. All participants completed the Suicidal Behaviors Questionnaire-Revised (SBQ-R), Life History of Aggression Questionnaire (LHAQ), Primary Care PTSD (PC-PTSD), and Traumatic Life Events Questionnaire (TLEQ). The average age of homeless people participated in the study was 55.2 years (SD = 10.7) with the age range of 30 to 87. Results indicated that PTSD symptoms and aggression fully mediated the relationship between childhood physical abuse and suicidal behavior among the homeless. These findings suggest the need for trauma-informed care for the homeless, and warrant the need for psychological services for PTSD and aggression in order to reduce suicide risk among homeless people.

Keywords: aggression, homeless, PTSD, suicidal behavior

Procedia PDF Downloads 379
16308 Innovative Screening Tool Based on Physical Properties of Blood

Authors: Basant Singh Sikarwar, Mukesh Roy, Ayush Goyal, Priya Ranjan

Abstract:

This work combines two bodies of knowledge which includes biomedical basis of blood stain formation and fluid communities’ wisdom that such formation of blood stain depends heavily on physical properties. Moreover biomedical research tells that different patterns in stains of blood are robust indicator of blood donor’s health or lack thereof. Based on these valuable insights an innovative screening tool is proposed which can act as an aide in the diagnosis of diseases such Anemia, Hyperlipidaemia, Tuberculosis, Blood cancer, Leukemia, Malaria etc., with enhanced confidence in the proposed analysis. To realize this powerful technique, simple, robust and low-cost micro-fluidic devices, a micro-capillary viscometer and a pendant drop tensiometer are designed and proposed to be fabricated to measure the viscosity, surface tension and wettability of various blood samples. Once prognosis and diagnosis data has been generated, automated linear and nonlinear classifiers have been applied into the automated reasoning and presentation of results. A support vector machine (SVM) classifies data on a linear fashion. Discriminant analysis and nonlinear embedding’s are coupled with nonlinear manifold detection in data and detected decisions are made accordingly. In this way, physical properties can be used, using linear and non-linear classification techniques, for screening of various diseases in humans and cattle. Experiments are carried out to validate the physical properties measurement devices. This framework can be further developed towards a real life portable disease screening cum diagnostics tool. Small-scale production of screening cum diagnostic devices is proposed to carry out independent test.

Keywords: blood, physical properties, diagnostic, nonlinear, classifier, device, surface tension, viscosity, wettability

Procedia PDF Downloads 373
16307 The Relationship between Elderly People with Depression and Built Environment Factors

Authors: Hung-Chun Lin, Tzu-Yuan Chao

Abstract:

As the population aging has become an inevitable trend globally, issues of improving the well-being of elderly people in urban areas have been a challenging task for urban planners. Recent studies of ageing trend have also expended to explore the relationship between the built environment and mental condition of elderly people. These studies have proved that even though the built environment may not necessarily play the decisive role in affecting mental health, it can have positive impacts on individual mental health by promoting social linkages and social networks among older adults. There has been a great amount of relevant research examined the impact of the built environment attributes on depression in the elderly; however, most were conducted in the Western countries. Little attention has been paid in Asian cities with contrarily high density and mix-use urban contexts such as Taiwan regarding how the built environment attributes related to depression in elderly people. Hence, more empirical cross-principle studies are needed to explore the possible impacts of Asia urban characteristics on older residents’ mental condition. This paper intends to focus on Tainan city, the fourth biggest metropolis in Taiwan. We first analyze with data from National Health Insurance Research Database to pinpoint the empirical study area where residing most elderly patients, aged over 65, with depressive disorders. Secondly, we explore the relationship between specific attributes of the built environment collected from previous studies and elderly individuals who suffer from depression, under different socio-cultural and networking circumstances. To achieve the results, the research methods adopted in this study include questionnaire and database analysis, and the results will be proceeded by correlation analysis. In addition, through literature review, by generalizing the built environment factors that have been used in Western research to evaluate the relationship between built environment and older individuals with depressive disorders, a set of local evaluative indicators of the built environment for future studies will be proposed as well. In order to move closer to develop age-friendly cities and improve the well-being for the elderly in Taiwan, the findings of this paper can provide empirical results to grab planners’ attention for how built environment makes the elderly feel and to reconsider the relationship between them. Furthermore, with an interdisciplinary topic, the research results are expected to make suggestions for amending the procedures of drawing up an urban plan or a city plan from a different point of view.

Keywords: built environment, depression, elderly, Tainan

Procedia PDF Downloads 115
16306 Syndromic Surveillance Framework Using Tweets Data Analytics

Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

Procedia PDF Downloads 108
16305 Biosorption of Methylene Blue and Acid Red-88 from Wastewater by Using Cypress Cones

Authors: Onur Yel

Abstract:

This study represents the removal of harmful dye substances from wastewaters by using waste and cheap adsorbents. Rapid population growth and industrialization occasion anthropogenic pollution which gives irreversible damage to the environment. One of the ways in which water pollution occurs is caused by the release of the dyestuffs in the textile industry. The release of dyestuffs to the environment directly damages the living creatures that have acquired water habitat. Especially, wastewater cannot be used for nutritional purposes. In addition, some adsorbents have mutagenic and/or carcinogenic effects. By blocking photosynthesis, it hinders the inhibition of photosynthetic bacteria in the water, which damages the ecological balance and also causes the formation of malodorous compounds. Moreover, the lack of oxygen can pose a serious danger to the lives of other living organisms that need oxygen. In recent years, some physical and chemical methods are preferred for the removal of dyestuffs. However, the utilization of these methods is expensive. For this reason, the availability of new and cheap adsorbents becomes the more significant issue. In this study, an investigation of various variables on the removal of Methylene Blue and Acid Red-88 dyestuffs from wastewaters by the usage of pulverized cypress cones has been carried out. Thus, various masses of absorbent (0.1-0.25-0.5-1-2-4-5 grams) are used in 50, 100, 150, 200, 300 ppm concentrations of Methylene Blue and Acid Red-88 dyestuffs’ solutions, and with a variety of the interaction time (0.25-0.5-1-2-4-5 hours). The mixtures were centrifuged and the absorbance of the filtrates was measured on a UV spectrophotometer to determine their remaining concentrations. In the study, the highest removal ratio of Acid Red-88 dyestuff was found to be 81% at 200 ppm of dyestuff with 2 grams of adsorbent at 300 minutes. For Methylene Blue experiments, the removal percentage was found as 98% where 2 grams of adsorbent is used in 200 ppm dyestuff solution at 120 minutes of interaction.

Keywords: acid red-88, biosorption, methylene blue, cypress cones, water pollution

Procedia PDF Downloads 138
16304 A Machine Learning Pipeline for Real-Time Activity Detection on Low Computational Power Devices for Metaverse Applications

Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

Abstract:

This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

Procedia PDF Downloads 173
16303 A Mutually Exclusive Task Generation Method Based on Data Augmentation

Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

Procedia PDF Downloads 134