Search results for: students’ learning achievements

Authors: Nicola G. G. Cecca

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In Italian IPSSEOAs, high schools that give a vocational education to students that will work in the field of Enogastronomy and Hotel Management, the course of Food Science allows the students to start and see food as a mixture of substances that they will transform during their profession. These substances are characterized not only by a chemical composition but also by a molecular structure that makes them nutritionally active. But the increasing number of new products proposed by Food Industry, the modern techniques of production and transformation, the innovative preparations required by customers have made many information reported in the most wide spread Food Science textbooks not up-to-date or too poor for the people who will work in catering sector. Often Authors offer information aged to Bohr’s Atomic Model and to the ‘Octet Rule’ proposed by G.N. Lewis to describe the Chemical Bond, without giving any reference to new as Orbital Atomic Model and Molecular Orbital Theory that, in the meantime, start to be old themselves. Furthermore, this antiquated information precludes an easy understanding of a wide range of properties of nutritive substances and many reactions in which the food constituents are involved. In this paper, our attention is pointed out to use GEOMAG™ to represent the dynamics with which the chemical bond is formed during the synthesis of the molecules. GEOMAG™ is a toy, produced by the Swiss Company Geomagword S.A., pointed to stimulate in children, aged between 6-10 years, their fantasy and their handling ability and constituted by metallic spheres and metallic magnetic bars coated by coloured plastic materials. The simulation carried out with GEOMAG™ is based on the similitude existing between the Coulomb’s force and the magnetic attraction’s force and in particular between the formulae with which they are calculated. The electrostatic force (F in Newton) that allows the formation of the chemical bond can be calculated by mean Fc = kc q1 q2/d2 where: q1 e q2 are the charge of particles [in Coulomb], d is the distance between the particles [in meters] and kc is the Coulomb’s constant. It is surprising to observe that the attraction’s force (Fm) acting between the magnetic extremities of GEOMAG™ used to simulate the chemical bond can be calculated in the same way by using the formula Fm = km m1 m2/d2 where: m1 e m2 represent the strength of the poles [A•m], d is the distance between the particles [m], km = μ/4π in which μ is the magnetic permeability of medium [N•A-2]. The magnetic attraction can be tested by students by trying to keep the magnetic elements of GEOMAG™ separate by hands or trying to measure by mean an appropriate dynamometric system. Furthermore, by using a dynamometric system to measure the magnetic attraction between the GEOMAG™ elements is possible draw a graphic F=f(d) to verify that the curve obtained during the simulation is very similar to that one hypnotized, around the 1920’s by Linus Pauling to describe the formation of H2+ in according with Molecular Orbital Theory.

Keywords: chemical bond, molecular orbital theory, magnetic attraction force, GEOMAG™

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Authors: Rana Alghamdi

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This study explored teachers’ perceptions of rough-and-tumble (R&T) play in early childhood education in Saudi Arabia. The literature on rough-and-tumble play in Saudi Arabia is limited in scope, and more research is needed to explore teachers’ perceptions on this type of play for early learners. The pertinent literature reveals that R&T play, which includes running, jumping, fighting, wrestling, chasing, pulling, pushing, and climbing, among other rough playful activities, can positively impact learning and development across psychosocial, emotional, and cognitive domains. Teachers’ understanding of R & T play is key, and the attitudes of Saudi early childhood teachers who are responsible for implementing curriculum-based play have not been fully researched. Four early childhood teachers from an urban Saudi preschool participated in the study. The data collected in this study were interpreted through a sociocultural lens. Data sources included in-depth interviews, photo-elicitation interviews, and participant-generated drawings. Three overarching themes emerged: teachers’ concerns about rough-and-tumble play, teachers’ perceptions about the benefits of rough-and-tumble play, and teachers’ expression of gender roles in R & T play as contextualized within Saudi culture. Saudi teachers’ perceptions are discussed in detail, and implications of the findings and recommendations for future research are put forth.

Keywords: rough and tumble play, gender, culture, early childhood, Saudi Arabia

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Authors: Sandra Biewers Grimm

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International studies such as Pisa have shown an increasing social inequality in the education system, which is determined in particular by social origin and migration status. This is especially the case in the Luxembourg school system, which creates challenges for many young people due to the multilingualism in the country. While the international and also the national debate on education in the immediate aftermath of the publications of the Pisa results mainly focused on the further development of school-based learning venues and formal educational processes, it initially remained largely unclear what role exactly out-of-school learning venues and non-formal and informal learning processes could play in this further development. This has changed in the meantime. Both in the political discourses and in the scientific disciplines, those voices have become louder that draw attention to the important educational function and the enormous educational potential of out-of-school learning places as a response to the crisis of the formal education system and more than this. Youth work as an actor and approach of non-formal education is particularly in demand here. Due to its principles of self-education, participation and openness, it is considered to have a special potential in supporting the acquisition of important key competencies. In this context, the study "Educational experiences in non-formal settings" at CCY takes a differentiated look behind the scenes of education-oriented youth work and describes on the basis of empirical data what and how young people learn in youth centers and which significance they attach to these educational experiences for their subjective life situation. In this sense, the aim of the study is to reconstruct the subjective educational experiences of young people in Open Youth Work as well as to explore the value that these experiences have for young people. In doing so, it enables scientifically founded conclusions about the educational potential of youth work from the user's perspective. Initially, the study focuses on defining the concept of education in the context of non-formal education and thus sets a theoretical framework for the empirical analysis. This socio-educational term of education differs from the relevant conception of education in curricular, formal education as the acquisition of knowledge. It also differs from the operationalization of education as competence, or the differentiation into cultural, social and personal or into factual, social or methodological competence, which is often used in the European context and which has long been interpreted as a "social science reading of the question of education" (XX). Now the aim is to define a "broader" concept of education that goes beyond the normative and educational policy dimensions of a "non-formal education" and includes the classical socio-educational dimensions. Furthermore, the study works with different methods of empirical social research: In addition to ethnographic observation and an online survey, group discussions were conducted with the young people. The presentation gives an insight into the context, the methodology and the results of this study.

Keywords: non-formal education, youth research, qualitative research, educational theory

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Authors: A. H. Bekhet, N. Helmy

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Background: Physical therapists are knowledgeable in treatment and prevention of musculoskeletal injuries; however, they have occupational musculoskeletal injuries because Physical therapy profession requires effort that may lead to work-related musculoskeletal disorders. No previous studies among physical therapists have been reported in Egypt. We aim to assess the prevalence and risk factors of musculoskeletal disorders among physical therapist’s seniors versus internship students. Method: We conducted a cross-sectional study in faculty of physical therapy Cairo university Prevalence and risk factors of musculoskeletal injuries were assessed using self-administered questionnaire with closed-ended questions. Seniors therapist was defined as a physical therapist with more than 5 years of work experience. Data were analyzed using SPSS 22.0 for Windows. Results: The study included 106 physical therapists (Junior = 72; senior = 34), the mean age of senior therapists was 30.1 (SD 6.3) years and junior therapists were 22.8 (SD 2.4). Female subjects constituted 83.9% of the studied sample. The mean hours of contact with patients was higher among junior therapists 6.4 (SD 2.6) vs. 5.7 (SD 2.1) among senior therapists. The prevalence of a musculoskeletal injury, once or more in their lifetime, was significantly higher among senior therapists (86% vs. 66.7%; p = 0.04). The highest risk factor in increasing the symptoms of the injury among junior therapists was maintaining a position for a prolonged period of time at 28% while performing manual therapy techniques was the highest risk factor among senior therapists at 32%. 53% of senior therapists have limited their patient contact time as a result of their injury in comparison to 25% of junior therapists (p = 0.09). Conclusion: the presented study shows that the prevalence of musculoskeletal injuries, once or more in their lifetime, is significantly higher among senior therapists.

Keywords: musculoskeletal injuries, occupational injuries, physical therapists, work related disorders

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Authors: Mary Jane Suarez

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A massive educational overhaul has taken place at the onset of the 21st century addressing the mismatches of employability skills with that of scholastic skills taught in schools. For a community to thrive in an ever-developing economy, the teaching of the necessary skills for job competencies should be realized by every educational institution. However, in harnessing 21st-century skills amongst learners, teachers, who often lack familiarity and thorough insights into the emerging 21st-century skills, are chained with the restraint of the need to comprehend the physiognomies of 21st-century skills learning and the requisite to implement the tenets of 21st-century skills teaching. With the endeavor to espouse 21st-century skills learning and teaching, a United States-based national coalition called Partnership 21st Century Skills (P21) has identified the four most important skills in 21st-century learning: critical thinking, communication, collaboration, and creativity and innovation with an established framework for 21st-century skills standards. Assessment of skills is the lifeblood of every teaching and learning encounter. It is correspondingly crucial to look at the 21st century standards and the assessment guides recognized by P21 to ensure that learners are 21st century ready. This mixed-method study sought to discover and describe what classroom assessments were used by English teachers in a public secondary school in the Philippines with course offerings on science, technology, engineering, and mathematics (STEM). The research evaluated the assessment tools implemented by English teachers and how these assessment tools were congruent to the 21st assessment standards of P21. A convergent parallel design was used to analyze assessment tools and practices in four phases. In the data-gathering phase, survey questionnaires, document reviews, interviews, and classroom observations were used to gather quantitative and qualitative data simultaneously, and how assessment tools and practices were consistent with the P21 framework with the four Cs as its foci. In the analysis phase, the data were treated using mean, frequency, and percentage. In the merging and interpretation phases, a side-by-side comparison was used to identify convergent and divergent aspects of the results. In conclusion, the results yielded assessments tools and practices that were inconsistent, if not at all, used by teachers. Findings showed that there were inconsistencies in implementing authentic assessments, there was a scarcity of using a rubric to critically assess 21st skills in both language and literature subjects, there were incongruencies in using portfolio and self-reflective assessments, there was an exclusion of intercultural aspects in assessing the four Cs and the lack of integrating collaboration in formative and summative assessments. As a recommendation, a harmonized assessment scheme of P21 skills was fashioned for teachers to plan, implement, and monitor classroom assessments of 21st-century skills, ensuring the alignment of such assessments to P21 standards for the furtherance of the institution’s thrust to effectively integrate 21st-century skills assessment standards to its curricula.

Keywords: 21st-century skills, 21st-century skills assessments, assessment standards, congruency, four Cs

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Authors: Marcelo T. Okano, Oduvaldo Vendrametto, Osmildo S. Santos, Marcelo E. Fernandes, Heide Landi

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Teaching of entrepreneurship and innovation in Brazilian universities has increased in recent years due to several factors such as the emergence of disciplines like biotechnology increased globalization reduced basic funding and new perspectives on the role of the university in the system of knowledge production Innovation is increasingly seen as an evolutionary process that involves different institutional spheres or sectors in society Entrepreneurship is a milestone on the road towards economic progress, and makes a huge contribution towards the quality and future hopes of a sector, economy or even a country. Entrepreneurship is as important in small and medium-sized enterprises (SMEs) and local markets as in large companies, and national and international markets, and is just as key a consideration for public companies as or private organizations. Entrepreneurship helps to encourage the competition in the current environment that leads to the effects of globalization. There is an increasing tendency for government policy to promote entrepreneurship for its apparent economic benefit. Accordingly, governments seek to employ entrepreneurship education as a means to stimulate increased levels of economic activity. Entrepreneurship education and training (EET) is growing rapidly in universities and colleges throughout the world, and governments are supporting it both directly and through funding major investments in advice-provision to would-be entrepreneurs and existing small businesses. The Triple Helix of university–industry–government relations is compared with alternative models for explaining the current research system in its social contexts. Communications and negotiations between institutional partners generate an overlay that increasingly reorganizes the underlying arrangements. To achieve the objective of this research was a survey of the literature on the entrepreneurship and innovation and then a field research with 100 students of Fatec. To collect the data needed for analysis, we used the exploratory research of a qualitative nature. We asked to respondents what degree of knowledge over ten related to entrepreneurship and innovation topics, responses were answered in a Likert scale with 4 levels, none, small, medium and large. We can conclude that the terms such as entrepreneurship and innovation are known by most students because the university propagates them across disciplines, lectures, and institutes innovation. The more specific items such as canvas and Design thinking model are unknown by most respondents. The importance of the University in teaching innovation and entrepreneurship in the transmission of this knowledge to the students in order to equalize the knowledge. As a future project, these items will be re-evaluated to create indicators for measuring the knowledge level.

Keywords: Brazilian universities, entrepreneurship, innovation, entrepreneurship, globalization

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Authors: Levi Corallo

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Typed language made by humans on computers and cell phones has made a significant distinction from previous modes of written language exchanges. While acronyms remain one of the most predominant markings of typed language, another and perhaps more recent revolution in the way humans communicate has been with the use of symbols or glyphs, primarily Emojis—globally introduced on the iPhone keyboard by Apple in 2008. This paper seeks to analyze the use of symbols in typed communication from both a linguistic and machine learning perspective. The Unicode system will be explored and methods of encoding will be juxtaposed with the current machine and human perception. Topics in how typed symbol usage exists in conversation will be explored as well as topics across current research methods dealing with Emojis like sentiment analysis, predictive text models, and so on. This study proposes that sequential analysis is a significant feature for analyzing unicode characters in a corpus with machine learning. Current models that are trying to learn or translate the meaning of Emojis should be starting to learn using bi- and tri-grams of Emoji, as well as observing the relationship between combinations of different Emoji in tandem. The sociolinguistics of an entire new vernacular of language referred to here as ‘typed language’ will also be delineated across my analysis with unicode glyphs from both a semantic and technical perspective.

Keywords: unicode, text symbols, emojis, glyphs, communication

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Authors: Rostam Abdi, Ahmad Abdi, Zahra Vahedi Langrodi

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The aim of this study is to investigate four-week resistance exercise and milk supplement on NT-proBNP and plasma troponin I of male students. Concerning the methodology of the study, 21 senior high school students of Ardebil city were selected. The selected subjects were randomly shared in three groups of control, exercise- water and exercise- milk. The exercise program includes resistance exercise for a big muscle group. The subjects of control group rested during the study and did not participate in any training. The subjects of exercise- water experimental group immediately received 400 cc water after exercise and exercise- milk group immediately received 400 cc low fat milk. Control-water groups consumed the same amount of water. 48 hours before and after the last exercise session, the blood sample of the subjects were taken for measuring the variables. NT-proBNP and Troponin I concentrations were measured by ELISA. For data analysis, one-way variance analysis test, correlated t-test and Bonferroni post hoc test were used. The significant difference of p ≤ 0.05 was accepted. Resistance training along with milk consumption leads to increase of plasma NT-proBNP, however; this increase has not reached the significant level. Furthermore, meaningful increase was observed in plasma NT–proBNP in exercise group between pretest and posttest values. Furthermore, no meaningful difference was observed between groups in terms of Troponin I after milk consumption. It seems that endurance exercises lead to change in the structure of heart muscle and is along with an increase of NT-proBNP. Furthermore, there is the possibility that milk consumption can lead to release of heart troponin I. The mechanism through which protein supplements have been put on heart troponin I is unknown and requires more research.

Keywords: resistance exercise, milk, NT-proBNP, Troponin I

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Authors: Xiaosheng Chen, Jingjing Chen, Phil Reed, Dan Zhang

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Conscious intention can be a promising point cut to grasp consciousness and orient voluntary action. The current study adopted a random ratio (RR), yoked random interval (RI) reinforcement learning schedule instead of the previous highly repeatable and single decision point paradigms, aimed to induce voluntary action with the conscious intention that evolves from the interaction between short-range-intention and long-range-intention. Readiness potential (RP) -like-EEG amplitude and inter-trial-EEG variability decreased significantly prior to voluntary action compared to cued action for inter-trial-EEG variability, mainly featured during the earlier stage of neural activities. Notably, (RP) -like-EEG amplitudes decreased significantly prior to higher RI-reward rates responses in which participants formed a higher plane of conscious intention. The present study suggests the possible contribution of conscious intention-based processes to the neural activities from the earlier stage prior to voluntary action on reinforcement leanring schedule.

Keywords: Reinforcement leaning schedule, voluntary action, EEG, conscious intention, readiness potential

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Authors: Ahmad Hashim, Thariq Khan Azizuddin Khan, Zulakbal Abd Karim, Nohazira Abdul Karim

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This research aims to obtain the validity and reliability of a survey instrument to evaluate the values, attitudes, and professionalism of sports science students, from the Faculty of Sports Science and Coaching, Universiti Pendidikan Sultan Idris (UPSI). It is a survey which is divided into two components namely first; moral, self-esteem, proactive, self-reliant and voluntary and second; ethics and professionalism. Development of the survey instrument is based on the Malaysian Education Development Plan, Higher Education Malaysia. There are 50 items prepared based on the five-point Likert scale which were tested at the pilot test level. It involved 212 research subjects selected based on random sampling. In addition, the research method applied is in the form of pre-experimental one group pre-test-post-test. Results of the analysis showed that overall field expert validity is r = .89, while the Cronbach alpha reliability correlation value of outdoor education instrument evaluation survey is r = .85. Next, this survey was tested again for construct validity using the factor analysis method for statistical analysis which would validate each item tested was supposed to be in the right component. From the analysis, results show that Bartlett's test is significant p < .05 and Kaiser-Meyer-Olkin index range is r = .87. The result showed 39 survey items are produced out of 50 items of the survey based on this factor analysis method. Research has shown that the survey instrument developed is valid and reliable to be used for the Faculty of Sports Sciences and Coaching, UPSI.

Keywords: values, attitudes, professionalism, ethics, professionalism

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Authors: Sarah P. Wuebbolt, Ashlee N. Sawyer-Mays

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Non-medical prescription and other drug (NMPOD) use has been a significant public health issue for the last few decades, with problematic use increasing among university students more recently. The current study focused on associations between NMPOD use and mental health, well-being, and world beliefs among young adults. Young adults (N=513) completed online questionnaires assessing stress, demographic characteristics, self-esteem, NMPOD use, coping mechanisms, and anxiety. A substantial portion of participants reported using cannabis (48.5%, n=249), while smaller portions of participants reported using stimulants (26.7%, n = 137), sedatives (17.2%, n=88), opioids (10.8%, n=55), and hallucinogens (14.4%, n=74). Five hierarchical logistic regressions were performed to determine the independent relationships between mental health, well-being, and world belief factors and NMPOD use for the five classes of substances. After controlling for demographic factors (age, gender, race/ethnicity, sexual orientation, and religious affiliation), depression was associated with increased non-medical stimulant, opioid, and cannabis use; coping self-efficacy was associated with increased hallucinogen use, and attendance of worship services was associated with decreased non-medical cannabis and hallucinogen use. Results suggest that depression was strongly associated with non-medical stimulant, opioid, and cannabis use, and attendance of worship services was protective against cannabis and hallucinogen use. To the best of our knowledge, this is one of the first studies to investigate the relationships between mental health, well-being, world beliefs, and NMPOD use among young adults. The present study illuminates future targets for intervention, such as increased access to mental health diagnosis and treatment and the exploration of the roles of religion and shared community in the prevention of drug use among young adults.

Keywords: cannabis, mental health, non-medical prescription and other drug use, world beliefs

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Authors: Clinton Chidiebere Anyanwu

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Secondary education is a vital part of a virtuous circle of economic growth within the context of a globalised knowledge economy. The teaching of Business Education entails teaching learners the essentials, rudiments, assumptions, and methods of business. Hence, it was deemed necessary for the study to investigate technology integration in Business Education. Drawing from the theoretical frameworks of technological pedagogical content knowledge (TPACK), and unified theory of acceptance and use of technology (UTAUT), the study observes teachers’ level of technology use in Business Education classrooms. Using a mixed-methods sequential explanatory design, probability, and purposive sampling, the majority of participants were found to be not integrating technology to an acceptable level and a small percentage was. After an analysis of constructs from UTAUT, some of this could be attributed to the lack of facilitating conditions in the teaching and learning of Business Education. The implication of the study findings is that poor investment in technology integration in secondary schools in Nigeria affects pedagogical implementations and effective teaching and learning of Business Education subjects. The study concludes that if facilitating conditions and professional development are considered to address the shortfalls in terms of TPACK, technology integration will become a reality in secondary schools in Nigeria.

Keywords: business education, secondary education, technology integration, TPACK, UTAUT

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Authors: Masoud Safarishaal

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Detecting the location of pole-to-earth faults is essential for the safe operation of the electrical system of the railroad. This paper aims to use a combination of evolutionary algorithms and neural networks to increase the accuracy of single pole-to-earth fault detection and location on the Tehran railroad power supply system. As a result, the Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to train the neural network to improve the accuracy and convergence of the learning process. Due to the system's nonlinearity, fault detection is an ideal application for the proposed method, where the 600 Hz harmonic ripple method is used in this paper for fault detection. The substations were simulated by considering various situations in feeding the circuit, the transformer, and typical Tehran metro parameters that have developed the silicon rectifier. Required data for the network learning process has been gathered from simulation results. The 600Hz component value will change with the change of the location of a single pole to the earth's fault. Therefore, 600Hz components are used as inputs of the neural network when fault location is the output of the network system. The simulation results show that the proposed methods can accurately predict the fault location.

Keywords: single pole-to-pole fault, Tehran railway, ICA, PSO, artificial neural network

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Authors: Moti Zwilling, Srečko Natek

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This paper aims to present an innovative predictive analytics analysis in order to find the best combination between two consumers who strive to find their partner or in internet sites. The methodology shown in this paper is based on analysis of consumer preferences and involves data mining and machine learning search techniques. The study is composed of two parts: The first part examines by means of descriptive statistics the correlations between a set of parameters that are taken between man and women where they intent to meet each other through the social media, usually the internet. In this part several hypotheses were examined and statistical analysis were taken place. Results show that there is a strong correlation between the affiliated attributes of man and woman as long as concerned to how they present themselves in a social media such as "Facebook". One interesting issue is the strong desire to develop a serious relationship between most of the respondents. In the second part, the authors used common data mining algorithms to search and classify the most important and effective attributes that affect the response rate of the other side. Results exhibit that personal presentation and education background are found as most affective to achieve a positive attitude to one's profile from the other mate.

Keywords: dating sites, social networks, machine learning, decision trees, data mining

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Authors: Akshay Dirisala

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Humans had developed a highly organized and efficient civilization to live in by improving the basic needs of humans like housing, transportation, and utilities. These developments have made a huge impact on major environmental factors. Air pollution is one prominent environmental factor that needs to be addressed to maintain a sustainable and healthier lifestyle. Textiles have always been at the forefront of helping humans shield from environmental conditions. With the growth in the field of electronic textiles, we now have the capability of monitoring the atmosphere in real time to understand and analyze the environment that a particular person is mostly spending their time at. Integrating textiles with the particulate matter sensors that measure air quality and pollutants that have a direct impact on human health will help to understand what type of air we are breathing. This research idea aims to develop a textile product and a process of collecting the pollutants through particulate matter sensors, which are equipped inside a smart textile product and store the data to develop a machine learning model to analyze the health conditions of the person wearing the garment and periodically notifying them not only will help to be cautious of airborne diseases but will help to regulate the diseases and could also help to take care of skin conditions.

Keywords: air pollution, e-textiles, particulate matter sensors, environment, machine learning models

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Authors: Chrysanthi S. Tiliakou, Katerina T. Frantzi

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Writing has always been considered a most demanding skill for English as a Foreign Language learners as well as for native speakers. Novice foreign language writers are asked to handle a limited range of vocabulary to produce writing tasks at lower levels. Adverbs are the parts of speech that are not used extensively in the early stages of English as a Foreign Language writing. An additional problem with learning new adverbs is that, next to learning their meanings, learners are expected to acquire the proper placement of adverbs in a sentence. The use of adverbs is important as they enhance “expressive richness to one’s message”. By exploring the patterns of use of adverbs, researchers and educators can identify types of adverbs, which appear more taxing for young learners or that puzzle novice English as a Foreign Language writers with their placement, and focus on their teaching. To this end, the study examines the use of adverbs on two written Corpora of young learners of English of A1 – A2 levels and determines the types of adverbs used, their frequencies, problems in their use, and whether there is any differentiation between levels. The Antconc concordancing tool was used for the Greek Learner Corpus, and the Corpuscle concordancing tool for the Norwegian Corpus. The research found a similarity in the normalized frequencies of the adverbs used in the A1-A2 level Greek Learner Corpus with the frequencies of the same adverbs in the Norwegian Learner Corpus.

Keywords: learner corpora, young learners, writing, use of adverbs

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Authors: Bing Li, Zhi Li, Yilong Yang

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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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Authors: Nesrine Boussaoui

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Background: International students often encounter challenges while studying in the UK, including communication and language barriers, lack of social networks, and socio-cultural differences that adversely impact on their mental health. For Algerian international students (AISs), these challenges may be heightened as English is not their first language and the culture of their homeland is substantially different from British culture, yet research has to incorporate their experiences and perspectives. Aim: The current study aimed to explore AISs’ 1) understandings of mental health; 2) issues of disclosure for mental health difficulties; and 3) mental health help-seeking and coping strategies. Method: In-depth, audio recorded semi-structured interviews (n = 20) with AISs in UK universities were conducted. An inductive, reflective thematic approach analysis was used. Finding: The following themes and associated sub-themes were developed: (1) Algerian cultural influences on mental health understanding(socio-cultural comparisons); (2) the paradox of the family (pressure vs. support); (3) stigma and fear of disclosure; (4) Barriers to formal help-seeking (informal disclosure as first step to seeking help); (5) Communication barriers (resort to mother tongue to disclose); (6) Self-reliance and religious coping. Conclusion: Recognising and understanding the challenges faced by AISs in terms of disclosure and mental health help-seeking is essential to reduce barriers to formal help-seeking. Informal disclosure among peers is often the first step to seeking help. Enhancing practitioners’ cultural competences and awareness of diverse understandings of mental health and the role of religious coping among AISs’ may have transferable benefits to a wider international student population.

Keywords: mental health, stegma, coping, disclosure

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Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Stefano Scippo, Damiana Luzzi, Stefano Cuomo, Maria Ranieri

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Background: In response to the rise in natural disasters linked to climate change, numerous studies on Disaster Risk Reduction Education (DRRE) have emerged since the '90s, mainly using a didactic transmission-based approach. Effective DRRE should align with an interactive, experiential, and participatory educational model, which can be costly and risky. A potential solution is using simulations facilitated by eXtended Reality (XR). Research Question: This study aims to conduct a scoping review to explore educational methodologies that use XR to enhance knowledge among teachers, students, and citizens about environmental risks, natural disasters (including climate-related ones), and their management. Method: A search string of 66 keywords was formulated, spanning three domains: 1) education and target audience, 2) environment and natural hazards, and 3) technologies. On June 21st, 2023, the search string was used across five databases: EBSCOhost, IEEE Xplore, PubMed, Scopus, and Web of Science. After deduplication and removing papers without abstracts, 2,152 abstracts (published between 2013 and 2023) were analyzed and 2,062 papers were excluded, followed by the exclusion of 56 papers after full-text scrutiny. Excluded studies focused on unrelated technologies, non-environmental risks, and lacked educational outcomes or accessible texts. Main Results: The 34 reviewed papers were analyzed for context, risk type, research methodology, learning objectives, XR technology use, outcomes, and educational affordances of XR. Notably, since 2016, there has been a rise in scientific publications, focusing mainly on seismic events (12 studies) and floods (9), with a significant contribution from Asia (18 publications), particularly Japan (7 studies). Methodologically, the studies were categorized into empirical (26) and non-empirical (8). Empirical studies involved user or expert validation of XR tools, while non-empirical studies included systematic reviews and theoretical proposals without experimental validation. Empirical studies were further classified into quantitative, qualitative, or mixed-method approaches. Six qualitative studies involved small groups of users or experts, while 20 quantitative or mixed-method studies used seven different research designs, with most (17) employing a quasi-experimental, one-group post-test design, focusing on XR technology usability over educational effectiveness. Non-experimental studies had methodological limitations, making their results hypothetical and in need of further empirical validation. Educationally, the learning objectives centered on knowledge and skills for surviving natural disaster emergencies. All studies recommended XR technologies for simulations or serious games but did not develop comprehensive educational frameworks around these tools. XR-based tools showed potential superiority over traditional methods in teaching risk and emergency management skills. However, conclusions were more valid in studies with experimental designs; otherwise, they remained hypothetical without empirical evidence. The educational affordances of XR, mainly user engagement, were confirmed by the studies. Authors’ Conclusions: The analyzed literature lacks specific educational frameworks for XR in DRRE, focusing mainly on survival knowledge and skills. There is a need to expand educational approaches to include uncertainty education, developing competencies that encompass knowledge, skills, and attitudes like risk perception.

Keywords: disaster risk reduction education, educational technologies, scoping review, XR technologies

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: Caroline Labib

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This paper reports on a qualitative study exploring the approaches teachers used to integrate computers or smart tablets into their program planning. Their aim was to integrate ICT into children’s play, thereby supporting children’s learning and development. Data was collected in preschool settings in Melbourne in 2016. Interviews with teachers, observations of teacher interactions with children and copies of teachers’ planning and observation documents informed the study. The paper looks closely at findings from two early childhood settings and focuses on exploring the differing approaches two EC teachers have adopted when integrating iPad or computers into their settings. Data analysis revealed three key approaches which have been labelled: free digital play, guided digital play and teacher-led digital use. Importantly, teacher decisions were influenced by the interplay between the opportunities that the ICT tools offered, the teachers’ prior knowledge and experience about ICT and children’s learning needs and contexts. This paper is a snapshot of two early childhood settings, and further research will encompass data from six more early childhood settings in Victoria with the aim of exploring a wide range of motivating factors for early childhood teachers trying to integrate ICT into their programs.

Keywords: early childhood education (ECE), digital play, information and communication technologies (ICT), play, and teachers' interaction approaches

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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Authors: Golak Bihari Mahanta, Bibhuti Bhusan Biswal, B. B. V. L. Deepak, Amruta Rout, Gunji Balamurali

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Robots are widely used in the manufacturing industry for rapid production with higher accuracy and precision. With the help of End-of-Arm Tools (EOATs), robots are interacting with the environment. Robotic grippers are such EOATs which help to grasp the object in an automation system for improving the efficiency. As the robotic gripper directly influence the quality of the product due to the contact between the gripper surface and the object to be grasped, it is necessary to design and optimize the gripper mechanism configuration. In this study, geometric and kinematic modeling of the parallel gripper is proposed. Grey wolf optimizer algorithm is introduced for solving the proposed multiobjective gripper optimization problem. Two objective functions developed from the geometric and kinematic modeling along with several nonlinear constraints of the proposed gripper mechanism is used to optimize the design variables of the systems. Finally, the proposed methodology compared with a previously proposed method such as Teaching Learning Based Optimization (TLBO) algorithm, NSGA II, MODE and it was seen that the proposed method is more efficient compared to the earlier proposed methodology.

Keywords: gripper optimization, metaheuristics, , teaching learning based algorithm, multi-objective optimization, optimal gripper design

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Authors: Daniel Scherman, Daniel Madani, Shanu Gambhir, Marcus Ling Zhixing, Yingda Li

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Objective: This study aims to identify clinical factors that may predict failed endoscopic lumbar spine surgery to guide surgeons with patient selection during the initial learning curve. Methods: This is an Australasian prospective analysis of the first 105 patients to undergo lumbar endoscopic spine decompression by 3 surgeons. Modified MacNab outcomes, Oswestry Disability Index (ODI) and Visual Analogue Score (VAS) scores were utilized to evaluate clinical outcomes at 6 months postoperatively. Descriptive statistics and Anova t-tests were performed to measure statistically significant (p<0.05) associations between variables using GraphPad Prism v10. Results: Patients undergoing endoscopic lumbar surgery via an interlaminar or transforaminal approach have overall good/excellent modified MacNab outcomes and a significant reduction in post-operative VAS and ODI scores. Regardless of the anatomical location of disc herniations, good/excellent modified MacNab outcomes and significant reductions in VAS and ODI were reported post-operatively; however, not in patients with calcified disc herniations. Patients with central and foraminal stenosis overall reported poor/fair modified MacNab outcomes. However, there were significant reductions in VAS and ODI scores post-operatively. Patients with subarticular stenosis or an associated spondylolisthesis reported good/excellent modified MacNab outcomes and significant reductions in VAS and ODI scores post-operatively. Patients with disc herniation and concurrent degenerative stenosis had generally poor/fair modified MacNab outcomes. Conclusion: The outcomes of endoscopic spine surgery are encouraging, with a low complication and reoperation rate. However, patients with calcified disc herniations, central canal stenosis or a disc herniation with concurrent degenerative stenosis present challenges during the initial learning curve and may benefit from traditional open or other minimally invasive techniques.

Keywords: complications, lumbar disc herniation, lumbar endoscopic spine surgery, predictors of failed endoscopic spine surgery

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Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: Mirza Mujtaba Baig

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Artificial Intelligence (AI) is evolving rapidly, and one of the areas in which this field has influenced is automation. The automobile, healthcare, education, and robotic industries deploy AI technologies constantly, and the automation of tasks is beneficial to allow time for knowledge-based tasks and also introduce convenience to everyday human endeavors. The paper reviews the challenges faced with the current implementations of autonomous self-driving cars by exploring the machine learning, robotics, and artificial intelligence techniques employed for the development of this innovation. The controversy surrounding the development and deployment of autonomous machines, e.g., vehicles, begs the need for the exploration of the configuration of the programming modules. This paper seeks to add to the body of knowledge of research assisting researchers in decreasing the inconsistencies in current programming modules. Blockchain is a technology of which applications are mostly found within the domains of financial, pharmaceutical, manufacturing, and artificial intelligence. The registering of events in a secured manner as well as applying external algorithms required for the data analytics are especially helpful for integrating, adapting, maintaining, and extending to new domains, especially predictive analytics applications.

Keywords: artificial intelligence, automation, big data, self-driving cars, machine learning, neural networking algorithm, blockchain, business intelligence

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Authors: Rolando Barradas, Salviano Soares, António Valente, José Alberto Lencastre, Paulo Oliveira

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This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding.

Keywords: nature inspired algorithms, scratch, micromouse, problem-solving, computational thinking

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Authors: David Chung

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The development of seventeenth-century French harpsichord music is enigmatic in several respects. Although little is known about the formation of this style before 1650 (we have names of composers, but no surviving music), the style has attained a high degree of refinement and sophistication in the music of the earliest known masters (e.g. Chambonnières, Louis Couperin and D’Anglebert). In fact, how the seventeenth-century musicians acquired the skills of their art remains largely steeped in mystery, as the earliest major treatise on French keyboard pedagogy was not published until 1702 by Saint Lambert. This study fills this lacuna by surveying some twenty recently-rediscovered manuscripts, which offer ample materials for revisiting key issues pertaining to seventeenth-century harpsichord pedagogy. By analyzing the musical contents, the verbal information and explicit notation (such as written-out ornaments and rhythmic effects), this study provides a rich picture of the process of learning at the time, with engaging details of performance nuances often lacking in tutors and treatises. Of even greater significance, that creative skills (such as continuo and ornamentation) were taught alongside fundamental knowledge (solfèges, note values, etc.) at the earliest stage of learning offers fresh challenge for modern pedagogues to rethink how harpsichord pedagogy can be revamped to cater for our own pedagogical and aesthetic needs.

Keywords: French, harpsichord, pedagogy, seventeenth century

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