Search results for: machine learning tools and techniques

Authors: Said Fares, Mary Fares

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It is well documented that introductory computer programming courses are difficult and that failure rates are high. The aim of this project was to reduce the high failure and withdrawal rates in learning to program. This paper presents a number of changes in module organization and instructional delivery system in teaching CS1. Daily out of class help sessions and tutoring services were applied, interactive lectures and laboratories, online resources, and timely feedback were introduced. Five years of data of 563 students in 21 sections was collected and analyzed. The primary results show that the failure and withdrawal rates were cut by more than half. Student surveys indicate a positive evaluation of the modified instructional approach, overall satisfaction with the course and consequently, higher success and retention rates.

Keywords: failure rate, interactive learning, student engagement, CS1

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Authors: Slamet Setioboro, Rahutami Kusumaningsih, Prabowo Setiyawan, Danna Darmayadi

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Designing of cold-formed steel capacity connections often based on the formula used for hot rolled steel. It makes the result of the actual capacity connection doesn’t accurate anymore. When the hot rolled steel receives the axial load pull, it will have different characteristics. As the result, there will be failure result when designing Truss structure made of hot rolled steel. This research aims to determine the capacity of actual cold-formed steel connections section which is loaded by the axial tensile force. It will test the appeal of the connection using bolt grafting tool and screw grafting tool. The variations of the test will be on the type of connection (single and double slap), the number of the connection tools and connection configuration. Bold and screw connections failure mode observed in this research are different each other. Failure mode of bolted connections includes sliding pivot plate, tearing at the plate and cutting of the bolt head. While the failure mode of screw connections includes tilting, hole-bearing, pull over and cutting the screw body out. This research was conducted using a laboratory test of HW2-600S Universal Testing Machine model with ASTM E8. It has done in the materials testing laboratory of Mechanical Engineering Department, Faculty of Engineering UNNES. The results obtained through the laboratory diversification towards theoretical calculations using the standards specified in ISO 7971-2013 Cold-Rolled Steel Structures. Based on the research, it can be concluded that the effective connection in receiving force strength is bolted connections neither single nor double plate. The method used is by applying 4 bolts through 2 parallel lines configuration. Furthermore, this connection deals with the consequences of holding the highest Pmaks, lowest failure risk and getting a little kind of mode of failure.

Keywords: axial load, cold-formed steel, capacity connections, bolted connections, screw connections

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Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Omar Alhamad, Waleed Eid

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Reinforced concrete is a concrete lined with steel so that the materials work together in the resistance forces. Reinforcement rods or mesh are used for tensile, shear, and sometimes intense pressure in a concrete structure. Reinforced concrete is subject to many natural problems or industrial errors. The result of these problems is that it reduces the efficiency of the reinforced concrete or its usefulness. Some of these problems are cracks, earthquakes, high temperatures or fires, as well as corrosion of reinforced iron inside reinforced concrete. There are also factors of ancient buildings or monuments that require some techniques to preserve them. This research presents some general information about reinforced concrete, the pros and cons of reinforced concrete, and then presents a series of literary studies of some of the late published researches on the subject of reinforced concrete and how to preserve it, propose solutions or treatments for the treatment of reinforced concrete problems, raise efficiency and quality for a longer period. These studies have provided advanced and modern methods and techniques in the field of reinforced concrete.

Keywords: reinforced concrete, treatment, concrete, corrosion, seismic, cracks

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Authors: Antonio D. Lee, Steven X. Jiang

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A variety of techniques and methods are available to evaluate cognitive performance in Urban Search and Rescue (USAR) applications. However, traditional cognitive performance evaluation techniques typically incorporate either the conscious or systematic aspect, failing to take into consideration the subconscious or intuitive aspect. This leads to incomplete measures and produces ineffective designs. In order to fill the gaps in past research, this study developed a theoretical framework to facilitate the integration of situation awareness (SA) and intuitive pattern recognition (IPR) to enhance the cognitive performance representation in USAR applications. This framework provides guidance to integrate both SA and IPR in order to evaluate the cognitive performance of the USAR responders. The application of this framework will help improve the system design.

Keywords: cognitive performance, intuitive pattern recognition, situation awareness, urban search and rescue

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Authors: Y. C. Khoo, W. T. Lai

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The single orifice hydraulic flat spray nozzle was evaluated with two global imaging techniques to characterize various aspects of the resulting spray. The two techniques were high resolution flow visualization and Particle Image Velocimetry (PIV). A CCD camera with 29 million pixels was used to capture shadowgraph images to realize ligament formation and collapse as well as droplet interaction. Quantitative analysis was performed to give the sizing information of the droplets and ligaments. This camera was then applied with a PIV system to evaluate the overall velocity field of the spray, from nozzle exit to droplet discharge. PIV images were further post-processed to determine the inclusion angle of the spray. The results from those investigations provided significant quantitative understanding of the spray structure. Based on the quantitative results, detailed understanding of the spray behavior was achieved.

Keywords: spray, flow visualization, PIV, shadowgraph, quantitative sizing, velocity field

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Authors: Le Khanh Huyen

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This dissertation focuses on the psychological study of children, particularly those who lack parental affection or face family pressures. It will analyze the severe consequences of insufficient parental love and familial pressure on children's psychology, including emotional and behavioral disorders, learning difficulties in academics and daily life, loss of faith, and low self-esteem. Additionally, this dissertation will propose solutions to support children in challenging circumstances, contributing to the protection of children's mental health.

Keywords: child psychology, lack of parental love, family pressure, emotional and behavioral disorders, learning difficulties, loss of faith, self-esteem, mental health

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Authors: Kais Siala, Mohamed Kharrat, Mohamed Abid

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Exposure therapies encourage patients to gradually begin facing their painful memories of the trauma in order to reduce fear and anxiety. In this context, virtual reality techniques are widely used for treatment of different kinds of phobia. The particular case of fear of death phobia (thanataphobia) is addressed in this paper. For this purpose, we propose to make a simulation of Near Death Experience (NDE) using augmented reality techniques. We propose in particular to simulate the Out-of-Body experience (OBE) which is the first step of a Near-Death-Experience (NDE). In this paper, we present technical aspects of this simulation as well as short-term impact in terms of physiological measures. The non-linear Poincéré plot is used to describe the difference in Heart Rate Variability between In-Body and Out-Of-Body conditions.

Keywords: Out-of-Body simulation, physiological measure, augmented reality, phobia psychotherapy, HRV, Poincaré plot

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Authors: Lin Shang Neng

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Due to rapid changes in the societal environment, career development and planning have become increasingly crucial, leading more individuals to seek the assistance of career consultations. However, the training process for career consultants often emphasizes the application of assessment tools and guidance in job-seeking behavior. The abilities of case conceptualization and consulting skills require further in-service supervision. This study aims to inquire about the supervised experiences of employment specialists at the Employment Service Center of the Taiwan Ministry of Labor or career consultants who held private clinics for at least three years. The research participants were continuously supervised by the Adlerian approach twice a month for at least one year, helping them integrate the whole picture of the client through Lifestyle Assessment (the qualitative way, specific diagnosis) and other Adlerian assessment tools (the quantitative way, general diagnosis.) The supervisor was familiar with Adlerian Psychology and certified by the North American Society of Adlerian Psychology. The research method involves semi-structured interviews and qualitative analysis. For the ethical considerations, the participants were invited to interview after the supervision sessions finished. The findings of this research were discussed with possible implications, like how they applied Adlerian Psychology to their career consultations, especially to case conceptualizations and consulting skills. Recommendations for further research and training for career consultants are also discussed.

Keywords: supervision, Adlerian psychology, case conceptualization, career consultant

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Authors: Gregory W. Smith, Paul J. Riccomini

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The goal of this empirical inquiry is to explore the effect of noise reducing headphones on the short-term memory recall of college students. Immediately following the presentation (via PowerPoint) of 12 unrelated and randomly selected one- and two-syllable words, students were asked to recall as many words as possible. Using a linear model with conditions marked with binary indicators, we examined the frequency and accuracy of words that were recalled. The findings indicate that for some students, a reduction of noise has a significant positive impact on their ability to recall information. As classrooms become more aurally distracting due to the implementation of cooperative learning activities, these findings highlight the need for a quiet learning environment for some learners.

Keywords: auditory distraction, education, instruction, noise, working memory

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Authors: Onyekachi Onwudike, Russell Lock, Iain Phillips

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The variability that exists across governments, her departments and the provisioning of services has been areas of concern in the E-Government domain. There is a need for reuse and integration across government departments which are accompanied by varying degrees of risks and threats. There is also the need for assessment, prevention, preparation, response and recovery when dealing with these risks or threats. The ability of a government to cope with the emerging changes that occur within it is known as resilience. In order to forge ahead with concerted efforts to manage reuse and integration induced risks or threats to governments, the ambiguities contained within resilience must be addressed. Enhancing resilience in the E-Government domain is synonymous with reducing risks governments face with provisioning of services as well as reuse of components across departments. Therefore, it can be said that resilience is responsible for the reduction in government’s vulnerability to changes. In this paper, we present the use of the ontology to measure the resilience of governments. This ontology is made up of a well-defined construct for the taxonomy of resilience. A specific class known as ‘Resilience Requirements’ is added to the ontology. This class embraces the concept of resilience into the E-Government domain ontology. Considering that the E-Government domain is a highly complex one made up of different departments offering different services, the reliability and resilience of the E-Government domain have become more complex and critical to understand. We present questions that can help a government access how prepared they are in the face of risks and what steps can be taken to recover from them. These questions can be asked with the use of queries. The ontology focuses on developing a case study section that is used to explore ways in which government departments can become resilient to the different kinds of risks and threats they may face. A collection of resilience tools and resources have been developed in our ontology to encourage governments to take steps to prepare for emergencies and risks that a government may face with the integration of departments and reuse of components across government departments. To achieve this, the ontology has been extended by rules. We present two tools for understanding resilience in the E-Government domain as a risk analysis target and the output of these tools when applied to resilience in the E-Government domain. We introduce the classification of resilience using the defined taxonomy and modelling of existent relationships based on the defined taxonomy. The ontology is constructed on formal theory and it provides a semantic reference framework for the concept of resilience. Key terms which fall under the purview of resilience with respect to E-Governments are defined. Terms are made explicit and the relationships that exist between risks and resilience are made explicit. The overall aim of the ontology is to use it within standards that would be followed by all governments for government-based resilience measures.

Keywords: E-Government, Ontology, Relationships, Resilience, Risks, Threats

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Authors: Nazir Amir

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Teaching approaches to present science and mathematics content amongst academically-low-achieving students may need to be different than approaches that are adopted for the more academically-inclined students, primarily due to the different learning needs and learning styles of these students. In crafting out lessons to motivate and engage these students, teachers need to consider the backgrounds of these students and have a good understanding of their interests so that lessons can be presented in ways that appeal to them, and made relevant not just to the world around them, but also to their personal experiences. This presentation highlights how the author worked with a Professional Learning Community (PLC) of teachers in crafting out fun and feasible classroom teaching approaches to present science and mathematics content in ways that are made Relevant, Appealing, and Personal (RAP) to groups of academically-low-achieving students in Singapore. Feedback from the students and observations from their work suggest that they were engaged through the RAP-modes of instruction, and were able to appreciate the role of science and mathematics through a variety of low-cost design-based STEM (Science, Technology, Engineering, and Mathematics) activities. Such results imply that teachers teaching academically-low-achieving students, and those in under-resourced communities, could consider infusing RAP-infused instructions into their lessons in getting students develop positive attitudes towards STEM subjects.

Keywords: STEM Education, STEAM Education, Curriculum Instruction, Academically At-Risk Students, Singapore

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Authors: Nik Azmah Nik Yusuff, Faridah Hassan Basri, Rosnidar Mansor

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The purpose of the study is to find out the effectiveness of using Graphic calculators (GC) with Calculator Based Laboratory 2 (CBL2) in teaching and learning of form four biology for these topics: Nutrition, Respiration and Dynamic Ecosystem. Sixty form four science stream students were the participants of this study. The participants were divided equally into the treatment and control groups. The treatment group used GC with CBL2 during experiments while the control group used the ordinary conventional laboratory apparatus without using GC with CBL2. Instruments in this study were a set of pre-test and post-test and a questionnaire. T-Test was used to compare the student’s biology achievement while a descriptive statistic was used to analyze the outcome of the questionnaire. The findings of this study indicated the use of GC with CBL2 in biology had significant positive effect. The highest mean was 4.43 for item stating the use of GC with CBL2 had saved collecting experiment result’s time. The second highest mean was 4.10 for item stating GC with CBL2 had saved drawing and labelling graphs. The outcome from the questionnaire also showed that GC with CBL2 were easy to use and save time. Thus, teachers should use GC with CBL2 in support of efforts by Malaysia Ministry of Education in encouraging technology-enhanced lessons.

Keywords: biology experiments, Calculator-Based Laboratory 2 (CBL2), graphic calculators, Malaysia Secondary School, teaching/learning

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Authors: Satoko Yamasaki, Hiromi Kawasaki, Kotomi Yamashita, Susumu Fukita, Kei Sounai

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People are susceptible to rumors when the cause of their health problems is unknown or invisible. In order for individuals to be unaffected by rumors, they need basic knowledge and correct information. Community health nursing classes use cases where basic knowledge of radiation can be utilized on a regular basis, thereby teaching that basic knowledge is important in preventing anxiety caused by rumors. Nursing students need to learn that preventive activities are essential for public health nursing care. This is the same methodology used to reduce COVID-19 anxiety among individuals. This study verifies the learning effect concerning the basic knowledge of radiation necessary for case consultation by emergency distance learning. Sixty third-year nursing college students agreed to participate in this research. The knowledge tests conducted before and after classes were compared, with the chi-square test used for testing. There were five knowledge questions regarding distance lessons. This was considered to be 5% significant. The students’ reports which describe the results of responding to health consultations, were analyzed qualitatively and descriptively. In this case study, a person living in an area not affected by radiation was anxious about drinking water and, thus, consulted with a student. The contents of the lecture were selected the minimum amount of knowledge used for the answers of the consultant; specifically hot spots, internal exposure risk, food safety, characteristics of cesium-137, and precautions for counselors. Before taking the class, the most correctly answered question by students concerned daily behavior at risk of internal exposure (52.2%). The question with the fewest correct answers was the selection of places that are likely to be hot spots (3.4%). All responses increased significantly after taking the class (p < 0.001). The answers to the counselors, as written by the students, were 'Cesium is strongly bound to the soil, so it is difficult to transfer to water' and 'Water quality test results of tap water are posted on the city's website.' These were concrete answers obtained by using specialized knowledge. Even in emergency distance learning, the students gained basic knowledge regarding radiation and created a document to utilize said knowledge while assuming the situation concretely. It was thought that the flipped classroom method, even if conducted remotely, could maintain students' learning. It was thought that setting specific knowledge and scenes to be used would enhance the learning effect. By changing the case to concern that of the anxiety caused by infectious diseases, students may be able to effectively gain the basic knowledge to decrease the anxiety of residents due to infectious diseases.

Keywords: effect of class, emergency distance learning, nursing student, radiation

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Authors: Neneng Hayatul Milah

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The most important reading skill for students is comprehension. Understanding the reading text will have an impact on learning outcomes. However, reading comprehension instruction in Indonesian elementary schools is lacking. A more effective learning model is needed to enhance students' reading comprehension. This study aimed to evaluate the effectiveness of the CIRC (Cooperative Integrated Reading and Composition) model with Padlet integration in improving the reading comprehension skills of grade IV students in elementary schools in Cimahi City, Indonesia. This research methodology was quantitative with a pre-experiment research type and one group pretest-posttest research design. The sample of this study consisted of 30 students. The results of statistical analysis showed that there was a significant effect of using the CIRC learning model using Padlet on improving students' reading comprehension skills of narrative text. The mean score of students' pretest was 67.41, while the mean score of the posttest increased to 84.82. The paired sample t-test resulted in a t-count score of -13.706 with a significance score of <0.001, which is smaller than α = 0.05. This research is expected to provide useful insights for educational practitioners on how the use of the CIRC model using Padlet can improve the reading comprehension skills of elementary school students.

Keywords: reading comprehension skills, CIRC, Padlet, narrative text

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Authors: Youmen Chaaban, Abdallah Abu-Tineh

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This article examines the development of a professional development (PD) model for educator growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge, and skills of both school leadership and teachers in an attempt to improve students’ learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents the results of a qualitative study examining the perceptions of nineteen instructional coaches about the strengths of the PD program, the challenges they face in their day-to-day implementation of the program, and their suggestions for the betterment of the program’s implementation and outcomes. Data were collected from the instructional coaches through open-ended surveys followed by focus group interviews. The instructional coaches reported several strengths, which were compatible with the literature on effective PD. However, the challenges they faced were deeply rooted within the structure of the program, in addition to external factors operating at the school and Ministry of Education levels. Thus, a general consensus on the way the program should ultimately develop was reached.

Keywords: situated professional development, school reform, instructional coach, school based support program

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Authors: Norbert Csizmadia

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The paper is based on a thorough investigation regarding the recent global, social and geographical processes. The ‘Geofusion’ book series by the author guides the readers with the help of newly illustrated “associative” geographic maps of the global world in the 21st century through the quest for the winning nations, communities, leaders and powers of this age. Hence, the above mentioned represent the research objectives, the preliminary findings of which are presented in this paper. The most significant recognition is that scientists who are recognized as explorers, geostrategists of this century, in this case, are expected to present guidelines for our new world full of global social and economic challenges. To do so, new maps are needed which do not miss the wisdom and tools of the old but complement them with the new structure of knowledge. Using the lately discovered geographic and economic interrelations, the study behind this presentation tries to give a prognosis of the global processes. The methodology applied contains the survey and analysis of many recent publications worldwide regarding geostrategic, cultural, geographical, social, and economic surveys structured into global networks. In conclusion, the author presents the result of the study, which is a collage of the global map of the 21st century as mentioned above, and it can be considered as a potential contribution to the recent scientific literature on the topic. In summary, this paper displays the results of several-year-long research giving the audience an image of how economic navigation tools can help investors, politicians and travelers to get along in the changing new world.

Keywords: geography, economic geography, geo-fusion, geostrategy

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Authors: V. Biasi, A. M. Ciraci, G. Domenici, N. Patrizi

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We present two studies centered on the teacher’s perception of self-efficacy and professional competences. The first study aims to evaluate the levels of self-efficacy as attitude in 200 teachers of primary and secondary schools. Teacher self-efficacy is related to many educational outcomes: such as teachers’ persistence, enthusiasm, commitment and instructional behavior. High level of teacher self-efficacy beliefs enhance student motivation and pupil’s learning level. On this theoretical and empirical basis we are planning a second study oriented to assess teacher self-perception of competences that are linked to teacher self-efficacy. With the CDVR Questionnaire, 287 teachers graduated in Education Sciences in e-learning mode, showed an increase in their self-perception of didactic-evaluation and relational competences and an increased confidence also in their own professionalism.

Keywords: teacher competence, teacher self-efficacy, selfperception, self-report evaluation

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Authors: Trevor R. Higgins

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The aim of this study was to compare muscle activation of the latissimus dorsi between pin-loaded machine (Lat Pull Down), resistance band (Lat Pull Down) and body-weight (Chin Up) exercises. A convenient sample of male college students with >2 years resistance training experience volunteered for the study. A paired t-test with repeated measures designs was carried out on results from EMG analysis. EMG analysis was conducted with Trigno wireless sensors (Delsys) placed laterally on the latissimus dorsi (left and right) of each participant. By conventional criteria the two-tailed P value suggested that differences between pin-loaded and body-weight was not significantly different (p = 0.93) and differences between pin-loaded and resistance band was not significantly different (p = 0.17) in muscle activity. In relation to conventional criteria the two-tailed P value suggested differences between body-weight and resistance band was not quite significantly different (p = 0.06) in muscle activity. However, effect size trends indicated that both body-weight and pin-loaded exercises where more effective in stimulating muscle electrical activity than a resistance band with male college athletes with >2 years resistance training experience. Although, resistance bands have increased in popularity in health and fitness centres, that for well-trained participants, they may not be effective in stimulating muscles of the latissimus dorsi. Therefore, when considering equipment and exercise selection for experienced resistance training participants pin-loaded machines and body-weight should be prescribed.

Keywords: pin-loaded, resistance bands, body weight, EMG analysis

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Authors: Ogunnaiya Racheal Taiwo

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Children's formative years are crucial to their growth; it is, therefore, necessary for all the stakeholders to ensure that the pupils have an enabling quality of life which is essential for realizing their potential. For children to live and grow, they need a secure home, nutritious food, good health care, and quality education. This paper, therefore, investigates the implications of a depressed economy on the classroom learning of Nigerian children as it is clear that Nigeria is currently experiencing the worst economic depression in several decades, which affects a substantial proportion of children. The study is qualitative research, and it adopts a phenomenological approach where the experiences of respondents are examined qualitatively. Three senatorial districts in Oyo State were considered, and 50 teachers, both male, and female were chosen from each senatorial district for an interview through conversational key informants' interviews. The interviewees were recorded, transcribed, and presented using thematic analysis. Findings showed that more children have dropped out since the beginning of the year than in previous years. It was also recorded that learning has become challenging as children now find it harder to acquire learning materials. It was recommended that the government should reimburse early childhood schools to lessen the effect of the inability to purchase materials and pay school fees. It was also recommended that an intervention be made to approach and resolve issues associated with out-of-school children.

Keywords: childhood, classroom, education, depressed economy, poverty

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Authors: Khaled Al-Badani, James Ren, Lisa Li, David Allanson

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Droplet formation is an important process in many engineering systems and manufacturing procedures, which includes welding, biotechnologies, 3D printing, biochemical, biomedical fields and many more. The volume and the characteristics of droplet formation are generally depended on various material properties, microfluidics and fluid mechanics considerations. Hence, a detailed investigation of this process, with the aid of numerical computational tools, are essential for future design optimization and process controls of many engineering systems. This will also improve the understanding of changes in the properties and the structures of materials, during the formation of the droplet, which is important for new material developments to achieve different functions, pending the requirements of the application. For example, the shape of the formed droplet is critical for the function of some final products, such as the welding nugget during Capacitor Discharge Welding process, or PLA 3D printing, etc. Although, most academic journals on droplet formation, focused on issued with material transfer rate, surface tension and residual stresses, the general emphasis on the characteristics of droplet shape has been overlooked. The proposed work for this project will examine theoretical methodologies, experimental techniques, and numerical modelling, using ANSYS FLUENT, to critically analyse and highlight optimization methods regarding the formation of pendant droplet. The project will also compare results from published data with experimental and numerical work, concerning the effects of key material parameters on the droplet shape. These effects include changes in heating/cooling rates, solidification/melting progression and separation/break-up times. From these tests, a set of objectives is prepared, with an intention of improving quality, stability and productivity in modelling metal welding and 3D printing.

Keywords: computer modelling, droplet formation, material distortion, materials forming, welding

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Authors: Marziye Hadian, Alireza Jabbari

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Background: The World Health Organization has identified COVID-19 as a public health emergency and is urging governments to stop the virus transmission by adopting appropriate policies. In this regard, the countries have taken different approaches to cutting the chain or controlling the spread of the disease. Methods: The present study was a systematize review of publications relating to prevention strategies for covid-19 disease. The study was carried out based on the PRISMA guidelines and CASP for articles and AACODS for grey literature. Finding: The study findings showed that in order to confront the COVID-19 epidemic, in general, there are three approaches of "mitigation", "active control" and "suppression" and four strategies of "quarantine", "isolation", "social distance" as well as "lockdown" in both individual and social dimensions to deal with epidemics that the choice of each approach requires specific strategies and has different effects when it comes to controlling and inhibiting the disease. Conclusion: The only way to control the disease is to change your behavior and lifestyle. In addition to prevention strategies, use of masks, observance of personal hygiene principles such as regular hand washing and non-contact of contaminated hands with the face, as well as observance of public health principles such as control of sneezing and coughing, safe extermination of personal protective equipment, etc. have not been included in the category of prevention tools. However, it has a great impact on controlling the epidemic, especially the new coronavirus epidemic.

Keywords: novel corona virus, COVID-19, prevention tools, prevention strategies

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Mohd Afif Md Nasir, Mohd Faizal Amin Nur, Jamaluddin Hasim, Abd Samad Hasan Basari, Mohd Halim Sahelan

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This study is aimed to investigate the suitability of Computer-Based Training (CBT) as one of the approaches in skills competency development at the Centre of Instructor and Advanced Skills Training (CIAST) Shah Alam Selangor and National Youth Skills Institute (NYSI) Pagoh Muar Johor. This study has also examined the perception among trainees toward Virtual Learning Environment (VLE) as to realize the development of skills in Welding Technology. The significance of the study is to create a computer-based skills development approach in welding technology among new trainees in CIAST and IKBN as well as to cultivate the element of general skills among them. This study is also important in elevating the number of individual knowledge workers (K-Workers) working in manufacturing industry in order to achieve the national vision which is to be an industrial nation in the year 2020. The design is a survey of research which using questionnaires as the instruments and is conducted towards 136 trainees from CIAST and IKBN. Data from the questionnaires is proceeding in a Statistical Package for Social Science (SPSS) in order to find the frequency, mean and chi-square testing. The findings of the study show the welding technology skills have developed in the trainees as a result of the application of the Virtual Reality simulator at a high level (mean=3.90) and the respondents agreed the skills could be embedded through the application of the Virtual Reality simulator (78.01%). The Study also found that there is a significant difference between trainee skill characteristics through the application of the Virtual Reality simulator (p<0.05). Thereby, the Virtual Reality simulator is suitable to be used in the development of welding skills among trainees through the skills training institute.

Keywords: computer-based training, virtual learning environment, welding technology, virtual reality simulator, virtual learning environment

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

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Authors: Omran Alharbi, Victor Lally

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In recent decades, a number of educational institutions around the world have come to depend on technology such as the Blackboard system to improve their educational environment. On the other hand, there are many factors that delay the usage of this technology, especially in developing nations such as Saudi Arabia. The goal of this study was to investigate learner’s views of the use of Blackboard in one Saudi university in order to gain a comprehensive view of the factors that delay the implementation of technology in Saudi institutions. This study utilizes a qualitative approach, with data being collected through semi-structured interviews. Six participants from different disciplines took part in this study. The findings indicated that there are two levels of factors that affect students’ use of the Blackboard system. These are factors at the institutional level, such as lack of technical support and lack of training support, which lead to insufficient training related to the Blackboard system. The second level of factors is at the individual level, for example, a lack of teacher motivation and encouragement. In addition, students do not have sufficient levels of skills or knowledge related to how to use the Blackboard in their learning. Conclusion: learners confronted and faced two main types of factors (at the institution level and individual level) that delayed and impeded their learning. Institutions in KSA should take steps and implement strategies to remove or reduce these factors in order to allow students to benefit from the latest technology in their learning.

Keywords: blackboard, factors, KSA, learners

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Authors: Firas Gerges, Frank Y. Shih

Abstract:

Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: deep learning, skin cancer, image processing, melanoma

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Authors: Hadas Sopher, Davide Schaumann, Yehuda E. Kalay

Abstract:

This paper addresses the shortcomings of architectural computation tools in representing human behavior in built environments, prior to construction and occupancy of those environments. Evaluating whether a design fits the needs of its future users is currently done solely post construction, or is based on the knowledge and intuition of the designer. This issue is of high importance when designing complex buildings such as hospitals, where the quality of treatment as well as patient and staff satisfaction are of major concern. Existing computational pre-occupancy human behavior evaluation methods are geared mainly to test ergonomic issues, such as wheelchair accessibility, emergency egress, etc. As such, they rely on Agent Based Modeling (ABM) techniques, which emphasize the individual user. Yet we know that most human activities are social, and involve a number of actors working together, which ABM methods cannot handle. Therefore, we present an event-based model that manages the interaction between multiple Actors, Spaces, and Activities, to describe dynamically how people use spaces. This approach requires expanding the computational representation of Actors beyond their physical description, to include psychological, social, cultural, and other parameters. The model presented in this paper includes cognitive abilities and rules that describe the response of actors to their physical and social surroundings, based on the actors’ internal status. The model has been applied in a simulation of hospital wards, and showed adaptability to a wide variety of situated behaviors and interactions.

Keywords: agent based modeling, architectural design evaluation, event modeling, human behavior simulation, spatial cognition

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Authors: Chien-Ho Lin, Ho-Ching Yang, Barbara Knowlton, Shin-Leh Huang, Ming-Chang Chiang

Abstract:

Practicing motor tasks arranged in an interleaved order (interleaved practice, or IP) generally leads to better learning than practicing tasks in a repetitive order (repetitive practice, or RP), an example of how desirable difficulty during practice benefits learning. Greater difficulty during practice, e.g. IP, is associated with greater brain activity measured by higher blood-oxygen-level dependent (BOLD) signal in functional magnetic resonance imaging (fMRI) in the sensorimotor areas of the brain. In this study resting-state fMRI was applied to investigate whether increase in resting-state brain connectivity immediately after practice predicts the benefit of desirable difficulty to motor learning. 26 healthy adults (11M/15F, age = 23.3±1.3 years) practiced two sets of three sequences arranged in a repetitive or an interleaved order over 2 days, followed by a retention test on Day 5 to evaluate learning. On each practice day, fMRI data were acquired in a resting state after practice. The resting-state fMRI data was decomposed using a group-level spatial independent component analysis (ICA), yielding 9 independent components (IC) matched to the precuneus network, primary visual networks (two ICs, denoted by I and II respectively), sensorimotor networks (two ICs, denoted by I and II respectively), the right and the left frontoparietal networks, occipito-temporal network, and the frontal network. A weighted resting-state functional connectivity (wRSFC) was then defined to incorporate information from within- and between-network brain connectivity. The within-network functional connectivity between a voxel and an IC was gauged by a z-score derived from the Fisher transformation of the IC map. The between-network connectivity was derived from the cross-correlation of time courses across all possible pairs of ICs, leading to a symmetric nc x nc matrix of cross-correlation coefficients, denoted by C = (pᵢⱼ). Here pᵢⱼ is the extremum of cross-correlation between ICs i and j; nc = 9 is the number of ICs. This component-wise cross-correlation matrix C was then projected to the voxel space, with the weights for each voxel set to the z-score that represents the above within-network functional connectivity. The wRSFC map incorporates the global characteristics of brain networks measured by the between-network connectivity, and the spatial information contained in the IC maps measured by the within-network connectivity. Pearson correlation analysis revealed that greater IP-minus-RP difference in wRSFC was positively correlated with the RP-minus-IP difference in the response time on Day 5, particularly in brain regions crucial for motor learning, such as the right dorsolateral prefrontal cortex (DLPFC), and the right premotor and supplementary motor cortices. This indicates that enhanced resting brain connectivity during the early phase of memory consolidation is associated with enhanced learning following interleaved practice, and as such wRSFC could be applied as a biomarker that measures the beneficial effects of desirable difficulty on motor sequence learning.

Keywords: desirable difficulty, functional magnetic resonance imaging, independent component analysis, resting-state networks

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Authors: Serhat Tuzun, Tufan Demirel

Abstract:

Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

Procedia PDF Downloads 220