Search results for: learning program

Authors: Raymond Li

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In this project a web-based classroom response system (CRS) was used in the teaching an intermediate level economics course. This system allows the instructor to post a question on the screen and students to answer questions using their own electronic mobile devices. The questions and the results summarizing student responses can be shown to students simultaneously and the instructor can make timely feedback to students in class. CRS gives students a chance to respond to the instructor’s question privately, encouraging students who might not typically speak up in class to express their thoughts and opinions. There is a vast literature on the advantages and challenges of using CRS. However, empirical evidence on the student attributes that increase the effectiveness of CRS in improving student learning outcomes is sparse. The purpose of this project is to (1) find out if the use of CRS is beneficial to students taking economics, and (2) discover key student attributes that will likely make CRS more effective. Students’ performance in examinations and an end-of-semester questionnaire were used to assess the effectiveness of CRS in this project. Comparing the examination scores of the CRS treatment group and control group, the treatment group performed considerably better and statistically significant differences were found basing on paired t-tests on the differences. According to the questionnaire results, around 75% of the students in the treatment group generally agreed that CRS allowed them to express their views more freely. We also observed that students who prefer to use instant messaging rather than making conversations are generally more positive towards CRS. The use of CRS also benefits the instructor – students’ rating of the instructor in the teaching evaluation was significantly higher for the CRS treatment group.

Keywords: education technology, classroom response system, student attributes, economics education

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Authors: Eileen K. Africa, Karel J. van Deventer

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Neuro-typical children develop the motor skills necessary to play, do schoolwork and interact with others. However, this is not observed in children who have learning or behavioural problems. Children with Autism Spectrum Disorder (ASD) are often referred to as clumsy because their body parts do not work well together in a sequence. Physical Activity (PA) has shown to be beneficial to the general population, therefore, providing children with ASD opportunities to take part in PA programmes, could prove to be beneficial in many ways and should be investigated. The purpose of this study was to design a specialised group intervention programme, to attempt to improve gross motor skills of selected children diagnosed with ASD between the ages of eight and 13 years. A government school for ASD learners was recruited to take part in this study, and a sample of convenience (N=7) was selected. Children in the experimental group (n=4) participated in a 12-week group intervention programme twice per week, while the control group continued with their normal daily routine. The Movement Assessment Battery for Children-Second Edition (MABC-2), was administered pre- and post-test to determine the children’s gross motor proficiency and to determine if the group intervention programme had an effect on the gross motor skills of the experimental group. Statistically significant improvements were observed in total motor skill proficiency (p < 0.05), of the experimental group. These results demonstrate the importance of gross motor skills interventions for children diagnosed with ASD. Future research should include more participants to ensure that the results can be generalised.

Keywords: autism spectrum disorder, children, gross motor skills, group intervention programme

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Authors: Mohd Iqbal Malik

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Ethical philosophy of Quran pinnacled virtue and economics as the part and parcel of human life. Human beings are to be imagined by the sign of morals. Soul and morality are both among the essences of human personality. Islam lays the foundation of ethics by installation of making a momentous variance between virtue and vice. It suggests for the distribution of wealth in-order to terminate accumulation of economic resources. Quran claims for the ambiguous pavement to attain virtue by saying, ‘Never will you attain the good (reward) until you spend (in the way of Allah) from that which you love. And whatever you spend indeed, Allah knows of it.’ The essence of Quran is to eliminate all the deep-seated approaches through which the wealth of nations is being accumulated within few hands. The paper will study the Quranic Philosophy Of Islamic Economic System. In recent times, to get out of the human resource development mystery of Muslims, Ismail Al-Raji Faruqi led the way in the so-called ‘Islamization’ of knowledge. Rahman and Faruqi formed opposite opinions on this project. Al-Faruqi thought of the Islamization of knowledge in terms of introducing Western learning into received Islamic values and vice versa. This proved to be a mere peripheral treatment of Islamic values in relation to Western knowledge. It is true that out of the programme of Islamization of knowledge arose Islamic universities in many Muslim countries. Yet the academic programmes of these universities were not founded upon a substantive understanding and application of the tawhidi epistemology.

Keywords: ethical philosophy, modern Islamic finance, knowledge of finance, Islamic banking

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Authors: Umar Mamman

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The study investigated the impact of school environment and peer relations on antisocial behaviour of the students of science secondary schools in Katsina State. The study sought to achieve the following objectives: to determine whether school influences antisocial behaviour among science secondary school students, and to determine whether peer relation influences anti-social behaviour among science secondary school students. The study population composed of all the students in science secondary schools in Katsina State. The study used a sample of 378 students and 18 teachers randomly selected from eleven science secondary schools in Katsina state. Three instruments were used to collect data for the study, thus: socio-economic status background questionnaire, antisocial process screening device (APSD), and inventory of parent and peer relationship questionnaire. The study findings revealed that school environment has significant effect on antisocial behaviour of the students in science secondary school (F (7, 372) = 52.08, p ≤ .01), and there is a significant effect of peer relation on antisocial behaviour of the students in science secondary school (F (7, 372) = 14.229, p ≤ .01). Based on these findings the following major recommendations were made: School environment should be made attractive and conducive for learning and character development. Teachers, as role model, should desist from indecent acts. School environment should be made learner-centered and friendly. Functional guidance and counselling outfits need to be provided in all secondary schools in Katsina state.

Keywords: school environment, peer relation, anti-social behaviour, psychology

Procedia PDF Downloads 355

Authors: Mingming Leng

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Wal-Mart has allocated considerable human resources for its quality assurance program, in which the largest retailer serves its supply chains as a quality gatekeeper. Asda Stores Ltd., the second largest supermarket chain in Britain, is now investing £27m in significantly increasing the frequency of quality control checks in its supply chains and thus enhancing quality across its fresh food business. Moreover, Tesco, the largest British supermarket chain, already constructed a quality assessment center to carry out its gatekeeping responsibility. Motivated by the above practices, we consider a supply chain in which a retailer plays the gatekeeping role in quality assurance by identifying defects among a manufacturer's products prior to selling them to consumers. The impact of a retailer's gatekeeping activity on pricing and quality assurance in a supply chain has not been investigated in the operations management area. We draw a number of managerial insights that are expected to help practitioners judiciously consider the quality gatekeeping effort at the retail level. As in practice, when the retailer identifies a defective product, she immediately returns it to the manufacturer, who then replaces the defect with a good quality product and pays a penalty to the retailer. If the retailer does not recognize a defect but sells it to a consumer, then the consumer will identify the defect and return it to the retailer, who then passes the returned 'unidentified' defect to the manufacturer. The manufacturer also incurs a penalty cost. Accordingly, we analyze a two-stage pricing and quality decision problem, in which the manufacturer and the retailer bargain over the manufacturer's average defective rate and wholesale price at the first stage, and the retailer decides on her optimal retail price and gatekeeping intensity at the second stage. We also compare the results when the retailer performs quality gatekeeping with those when the retailer does not. Our supply chain analysis exposes some important managerial insights. For example, the retailer's quality gatekeeping can effectively reduce the channel-wide defective rate, if her penalty charge for each identified de-fect is larger than or equal to the market penalty for each unidentified defect. When the retailer imple-ments quality gatekeeping, the change in the negotiated wholesale price only depends on the manufac-turer's 'individual' benefit, and the change in the retailer's optimal retail price is only related to the channel-wide benefit. The retailer is willing to take on the quality gatekeeping responsibility, when the impact of quality relative to retail price on demand is high and/or the retailer has a strong bargaining power. We conclude that the retailer's quality gatekeeping can help reduce the defective rate for consumers, which becomes more significant when the retailer's bargaining position in her supply chain is stronger. Retailers with stronger bargaining powers can benefit more from their quality gatekeeping in supply chains.

Keywords: bargaining, game theory, pricing, quality, supply chain

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Authors: Jaypee Limueco

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This research focused on the impact of Peer Instruction and PhET Simulations on the level of motivation and Physics anxiety of Grade 9 students. Two groups of students were used in the study. The experimental group involved 65 registered students while the control group has 64 registered students. To determine the level of motivation of students in learning physics, the Physics Motivation Questionnaire was administered. On the other hand, to determine the level of Physics anxiety of the students in each group, Physics Anxiety Rating Scale was used. Peer Instruction supplemented with PhET simulations was implemented in the experimental group while the traditional lecture method was used in the control group. Both instruments were again administered after the implementation of the two different teaching approaches. “Wilcoxon Signed Rank test” was used to test the significant difference between pretest and posttest of each group. “Mann Whitney U” was used to test if significant differences exist between each group before and after instruction. Results showed that there is no significant difference between the level of motivation and anxiety of the experimental and control group before the implementation at p<0.05 significance level. It implies that the students have the same level of motivation and physics anxiety before instruction. However, the results of both tests have significant differences between the groups after instruction. It is also found that there is a significant positive change in the responses of the students in the experimental group while no change was evident on the control. The result of the analysis of the Mann Whitney U shows that the change in the attributes of the students is caused by the treatment. Therefore, it is concluded that Peer Instruction and PhET simulation helped in alleviating motivation of students and minimizing their anxiety towards Physics.

Keywords: anxiety, motivation, peer instruction, PhET simulations

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Authors: Chris Schoborg, Morgan C. Wang

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In the realm of the National Football League (NFL), substantial dedication of time and effort is invested by both players and coaches in meticulously analyzing the game footage of their opponents. The primary aim is to anticipate the actions of the opposing team. Defensive players and coaches are especially focused on deciphering their adversaries' intentions to effectively counter their strategies. Acquiring insights into the specific play type and its intended direction on the field would confer a significant competitive advantage. This study establishes pre-snap information as the cornerstone for predicting both the play type (e.g., deep pass, short pass, or run) and its spatial trajectory (right, left, or center). The dataset for this research spans the regular NFL season data for all 32 teams from 2013 to 2022. This dataset is acquired using the nflreadr package, which conveniently extracts play-by-play data from NFL games and imports it into the R environment as structured datasets. In this study, we employ a recently developed machine learning algorithm, XGBoost. The final predictive model achieves an impressive lift of 2.61. This signifies that the presented model is 2.61 times more effective than random guessing—a significant improvement. Such a model has the potential to markedly enhance defensive coaches' ability to formulate game plans and adequately prepare their players, thus mitigating the opposing offense's yardage and point gains.

Keywords: lift, NFL, sports analytics, XGBoost

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Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: Endina P. Purwandari, Yolanda Hervianti, Feri Noperman, Endang W. Winarni

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The earthquakes disaster is an event that can threaten at any moment and cause damage and loss of life. Game earthquake disaster mitigation is a useful educational game to enhance children insight, knowledge, and understanding in the response to the impact of the earthquake. This study aims to build an educational games application on the Android platform as a learning media for earthquake mitigation education and to determine the effect of the application toward children understanding of the earthquake disaster mitigation. The methods were research and development. The development was to develop edugame application for earthquakes mitigation education. The research involved elementary students as a research sample to test the developed application. The research results were valid android-based edugame application, and its the effect of application toward children understanding. The application contains an earthquake simulation video, an earthquake mitigation video, and a game consisting three stages, namely before the earthquake, when the earthquake occur, and after the earthquake. The results of the feasibility test application showed that this application was included in the category of 'Excellent' which the average percentage of the operation of applications by 76%, view application by 67% and contents of application by 74%. The test results of students' responses were 80% that showed that a positive their responses toward the application. The student understanding test results show that the average score of children understanding pretest was 71,33, and post-test was 97,00. T-test result showed that t value by 8,02 more than table t by 2,001. This indicated that the earthquakes disaster mitigation edugame application based on Android platform affects the children understanding about disaster earthquake mitigation.

Keywords: android, edugame, mitigation, earthquakes

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Authors: Rangika Perera, Shyamani Hettiarachchi, Fran Hagstrom

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Dyslexia is the most common reading reading-related difficulty among the school school-aged population and currently, 5-10% are showing the features of dyslexia in Sri Lanka. As there is an insufficient number of speech and language pathologists in the country and few speech and language pathologists working in government mainstream school settings, these children who are at risk of dyslexia are not receiving enough quality early intervention services to develop their reading skills. As teachers are the key professionals who are directly working with these children, using them as the primary facilitators to improve their reading skills will be the most effective approach. This study aimed to identify the efficacy of a two and half a day of intensive training provided to fifteen mainstream government school teachers of grade two classes. The goal of the training was to enhance their knowledge of dyslexia and provide full classroom skills training that could be used to support the development of the students’ reading competencies. A closed closed-ended multiple choice questionnaire was given to these teachers pre and -post-training to measure teachers’ knowledge of dyslexia, the areas in which these children needed additional support, and the best strategies to facilitate reading competencies. The data revealed that the teachers’ knowledge in all areas was significantly poorer prior to the training and that there was a clear improvement in all areas after the training. The gain in target areas of teaching skills selected to improve the reading skills of children was evaluated through peer feedback. Teachers were assigned to three groups and expected to model how they were going to introduce the skills in recommended areas using researcher developed, validated and reliability reliability-tested materials and the strategies which were introduced during the training within the given tasks. Peers and the primary investigator rated teachers’ performances and gave feedback on organizational skills, presentation skills of materials, clarity of instruction, and appropriateness of vocabulary. After modifying their skills according to the feedback the teachers received, they were expected to modify and represent the same tasks to the group the following day. Their skills were re-evaluated by the peers and primary investigator using the same rubrics to measure the improvement. The findings revealed a significant improvement in their teaching skills development. The data analysis of both knowledge and skills gains of the teachers was carried out using quantitative descriptive data analysis. The overall findings of the study yielded promising results that support intensive training as a method for improving teachers’ knowledge and teaching skill development for use with children in a whole class intervention setting who are at risk of dyslexia.

Keywords: Dyslexia, knowledge, teaching skills, training program

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Authors: Yael Wolff Sagy, Yiska Loewenberg Weisband, Vered Kaufman Shriqui, Michal Krieger, Arie Ben Yehuda, Ronit Calderon Margalit

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Background: Obesity is both a risk factor and common comorbidity of diabetes. Obesity impedes the achievement of glycemic control, and enhances damage caused by hyperglycemia to blood vessels; thus it increases diabetes-related complications. This study assessed the prevalence of obesity and morbid obesity among Israeli adults with diabetes, and estimated disparities associated with sex and socioeconomic position (SEP). Methods: A cross-sectional study was conducted in the setting of the Israeli National Program for Quality Indicators in Community Healthcare. Data on all the Israeli population is retrieved from electronic medical records of the four health maintenance organizations (HMOs). The study population included all Israeli patients with diabetes aged 20-64 with documented body mass index (BMI) in 2016 (N=180,451). Diabetes was defined as the existence of one or more of the following criteria: (a) Plasma glucose level >200 mg% in at least two tests conducted at least one month apart in the previous year; (b) HbA1c>6.5% at least once in the previous year (c) at least three prescriptions of diabetes medications were dispensed during the previous year. Two measures were included: the prevalence of obesity (defined as last BMI≥ 30 kg/m2 and <35 kg/m2) and the prevalence of morbid obesity (defined as last BMI≥ 35 kg/m2) in individuals aged 20-64 with diabetes. The cut-off value for morbid obesity was set in accordance with the eligibility criteria for bariatric surgery in diabetics. Data were collected by the HMOs and aggregated by age, sex and SEP. SEP was based on statistical areas ranking by the Israeli Central Bureau of Statistics and divided into 4 categories, ranking from 1 (lowest) to 4 (highest). Results: BMI documentation among adults with diabetes was 84.9% in 2016. The prevalence of obesity in the study population was 30.5%. Although the overall rate was similar in both sexes (30.8% in females, 30.3% in males), SEP disparities were stronger in females (32.7% in SEP level 1 vs. 27.7% in SEP level 4; 18.1% relative difference) compared to males (30.6% in SEP level 1 vs. 29.3% in SEP level 4; 4.4% relative difference). The overall prevalence of morbid obesity in this population was 20.8% in 2016. The rate among females was almost double compared to the rate in males (28.1% and 14.6%, respectively). In both sexes, the prevalence of morbid obesity was strongly associated with lower SEP. However, in females, disparities between SEP levels were much stronger (34.3% in SEP level 1 vs. 18.7% in SEP level 4; 83.4% relative difference) compared to SEP-disparities in males (15.7% in SEP level 1 vs. 12.3% in SEP level 4; 27.6% relative difference). Conclusions: The overall prevalence of BMI≥ 30 kg/m2 among adults with diabetes in Israel exceeds 50%; and the prevalence of morbid obesity suggests that 20% meet the BMI-criteria for bariatric surgery. Prevalence rates show major SEP- and sex-disparities; especially strong SEP disparities in morbid obesity among females. These findings highlight the need for greater consideration of different population groups when implementing interventions.

Keywords: diabetes, health disparities, health policy, obesity, socio-economic position

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

Procedia PDF Downloads 319

Authors: Sadeq Al Yaari, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari

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Background & Objectives: Audio-visual aids and computer-assisted language instruction (CALI) effects are strong in teaching language components (sound system, grammatical structures and vocabulary) to students of special needs. To explore the effects of the audio-visual aids and CALI in teaching sound system to this class of students by speech language therapists (SLTs), an experiment has been undertaken to evaluate their performance during their study of the sound system course. Methods: Forty students (males and females) of special needs at al-Malādh school for teaching students of special needs in Dhamar (Yemen) range between 8 and 18 years old underwent this experimental study while they were studying language sound system course. Pre-and-posttests have been administered at the begging and end of the semester. Students' treatment was compared to a similar group (control group) of the same number under the same environment. Whereas the first group was taught using audio-visual aids and CALI, the second was not. Students' performances were linguistically and statistically evaluated. Results & conclusions: Compared with the control group, the treatment group showed significantly higher scores in the posttest (72.32% vs. 31%). Compared with females, males scored higher marks (1421 vs. 1472). Thus, we should take the audio-visual aids and CALI into consideration in teaching sound system to students of special needs.

Keywords: language components, sound system, audio-visual aids, CALI, students, special needs, SLTs

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Authors: Tae Young Jin, Jin Soo Kim

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Carbon emissions have emerged as global concerns. Intergovernmental Panel of Climate Change (IPCC) have published reports about Green House Gases (GHGs) emissions regularly. United Nations Framework Convention on Climate Change (UNFCCC) have held a conference yearly since 1995. Especially, COP21 held at December 2015 made the Paris agreement which have strong binding force differently from former COP. The Paris agreement was ratified as of 4 November 2016, they finally have legal binding. Participating countries set up their own Intended Nationally Determined Contributions (INDC), and will try to achieve this. Thus, carbon emissions must be reduced. The energy sector is one of most responsible for carbon emissions and fossil fuels particularly are. Thus, this paper attempted to examine the relationship between natural gas consumption and economic growth. To achieve this, we adopted the Cobb-Douglas production function that consists of natural gas consumption, economic growth, capital, and labor using dependent panel analysis. Data were preprocessed with Principal Component Analysis (PCA) to remove cross-sectional dependency which can disturb the panel results. After confirming the existence of time-trended component of each variable, we moved to cointegration test considering cross-sectional dependency and structural breaks to describe more realistic behavior of volatile international indicators. The cointegration test result indicates that there is long-run equilibrium relationship between selected variables. Long-run cointegrating vector and Granger causality test results show that while natural gas consumption can contribute economic growth in the short-run, adversely affect in the long-run. From these results, we made following policy implications. Since natural gas has positive economic effect in only short-run, the policy makers in developing countries must consider the gradual switching of major energy source, from natural gas to sustainable energy source. Second, the technology transfer and financing business suggested by COP must be accelerated. Acknowledgement—This work was supported by the Energy Efficiency & Resources Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20152510101880) and by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-205S1A3A2046684).

Keywords: developing countries, economic growth, natural gas consumption, panel data analysis

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Authors: Joanne Joyce-McCoach

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Short courses are an integral part of the higher education sector, providing a pathway into tertiary qualifications. Recently, the Australian government has implemented a range of initiatives to support the development of short courses and micro-credentials designed to upskill the labor market and meet the needs of the healthcare workforce. While short courses have been an ongoing component of Australian nursing continuing professional development, there is an immediate need for more education opportunities as a response to the workforce shortages. However, despite the support for short courses, there are identified challenges for learners undertaking these courses online. As a result of restrictions to face-to-face classes and limited access to health services caused by the pandemic, education providers have had to transition to an online delivery requiring the redesign of skills acquisition. This paper will outline the transition of an immunisation short course to a fully online format, including the redesign of classes, content and assessment. Concurrently the enrolments for the immunisation short course substantially increased in direct response to the demand for nurse immunisers. In addition to providing a description of the curriculum changes implemented, an analysis of learners’ feedback on their experience of the new format will be discussed. Furthermore, it will explore the principles identified in the transition process for improving the short course design and learning activities. Finally, it will propose recommendations to integrate into the delivery of online short courses and to meet the learners' needs.

Keywords: nurse, immunisation, short course, micro-credential, continuing professional development, online design

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Authors: Craig A. Kaplan

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If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

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Authors: Omotayo Abidemi Funmilayo

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Skill acquisition in professional fields has been prioritized and considered important to demonstrate the mastery of subject matter and present oneself as an expert in such profession. The ability to acquire skills in different fields, however calls for different method from the instructor or teacher during training. Music is not an exception of such profession, where there exist different area of skills acquisition require practical performance. This paper, however, focused on the impact and effects of different methods on acquisition of practical knowledge in the handling of some musical instruments among the students of Emmanuel Alayande College of Education, Oyo. In this study, 30 students were selected and divided into two groups based on the selected area of learning, further division were made on each of the two major groups to consist of five students each, to be trained using different methodology for two months and three hours per week. Comparison of skill acquired were made using standard research instrument at reliable level of significance, test were carried out on the thirty students considered for the study based on area of skill acquisition. The students that were trained on the keyboard and saxophone using play way method, followed by the students that were trained using demonstration method while the set of students that received teaching instruction through lecture method performed below average. In conclusion, the study reveals that ability to acquire professional skill on handling musical instruments are better enhanced using play way method.

Keywords: music education, skill acquisition, keyboard, saxophone

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Authors: Yu-Chu Yeh, WeiChin Hsu, Chih-Yen Chang

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Substitution, combination, modification, putting to other uses, elimination, and rearrangement (SCAMPER) has been regarded as an effective technique that provides a structured way to help people to produce creative ideas and solutions. Although some neuroscience studies regarding creativity training have been conducted, no study has focused on SCAMPER. This study therefore aimed at examining whether the learning of SCAMPER through video tutorials would result in alternations of neural activation. Thirty college students were randomly assigned to the experimental group or the control group. The experimental group was requested to watch SCAMPER videos, whereas the control group was asked to watch natural-scene videos which were regarded as neutral stimulating materials. Each participant was brain scanned in a Functional magnetic resonance imaging (fMRI) machine while undertaking a creativity test before and after watching the videos. Furthermore, a two-way ANOVA was used to analyze the interaction between groups (the experimental group; the control group) and tasks (C task; M task; X task). The results revealed that the left precuneus significantly activated in the interaction of groups and tasks, as well as in the main effect of group. Furthermore, compared with the control group, the experimental group had greater activation in the default mode network (left precuneus and left inferior parietal cortex) and the motor network (left postcentral gyrus and left supplementary area). The findings suggest that the SCAMPER training may facilitate creativity through the stimulation of the default mode network and the motor network.

Keywords: creativity, default mode network, neural activation, SCAMPER

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Authors: Yulin Rao, Zhixuan Li, Burra Venkata Durga Kumar

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Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions.

Keywords: artificial immune system, distributed artificial intelligence, multi-agent, intrusion detection system, neural network

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Authors: Sazzad Hossain Talukder

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Survival in the competitive international market with unforeseen environmental contingencies has always been a concern of the firms that led to adopting different strategies to deal with different situations. Language strategy is considered to enhance the international performance of a firm by organizing language diversity and fostering communications within and outside the firm. Yet there is a lack of theoretical attention or model development on the role of language strategy on firm international survival. From resource dependence perspective, the adoption of language strategy and its relationship with firm survival are determined by the firm´s capability to prevent dependency concentration and/or increase relative power on the external environment. However, the impact of language strategy on firm survival is complex and multifaceted as the strategy influence firm performance indirectly through communication, coordination, learning and value creation. The evidence of various types of language strategies and different forms of firm survival also bring in complexities to understand the effects of a language strategy on the international survival of a firm. Based on language literatures and resource dependence logic, certain propositions are developed to conceptualize the relationship between language strategy and firm international survival in this conceptual paper. For the purpose of this paper, a conceptual model is proposed to examine how different kinds of language strategy foster reduction of resource dependency that lead to firm international survival in respond to local responsiveness and global integration. In this proposed model, it is theorized that language strategy has a positive relationship with the international survival of the firm, as the strategy is likely to reduce external resource dependency and increase the ability to continue independent operations both in short and long term.

Keywords: language strategy, language diversity, firm international survival, resource dependence logic

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Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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Authors: Hamsini Pulugurtha, V.S. Lakshmi Jagadmaba Paluri

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Distributed denial of service attack (DDoS) is one altogether the top-rated cyber threats presently. It runs down the victim server resources like a system of measurement and buffer size by obstructing the server to supply resources to legitimate shoppers. Throughout this text, we tend to tend to propose a mathematical model of DDoS attack; we discuss its relevancy to the choices like inter-arrival time or rate of arrival of the assault customers accessing the server. We tend to tend to further analyze the attack model in context to the exhausting system of measurement and buffer size of the victim server. The projected technique uses an associate in nursing unattended learning technique, self-organizing map, to make the clusters of identical choices. Lastly, the abstract applies mathematical correlation and so the standard likelihood distribution on the clusters and analyses their behaviors to look at a DDoS attack. These systems not exclusively interconnect very little devices exchanging personal data, but to boot essential infrastructures news standing of nuclear facilities. Although this interconnection brings many edges and blessings, it to boot creates new vulnerabilities and threats which might be conversant in mount attacks. In such sophisticated interconnected systems, the power to look at attacks as early as accomplishable is of paramount importance.

Keywords: application attack, bandwidth, buffer correlation, DDoS distribution flooding intrusion layer, normal prevention probability size

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Authors: Tania Lisboa, Angela Voyajolu, Adam Ockelford

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The positive impact of music on the development of children with autism is widely acknowledged: music offers a unique channel for communication, wellbeing and self-regulation, as well as access to culture and a means of creative engagement. Yet, no coherent program exists for parents, carers and teachers to follow with their children in the early years, when the need for interventions is often most acute. Hence, research and the development of resources is urgently required. Autism is a project with children on the autism spectrum. The project aims at promoting the participants’ engagement with music through involvement in specially-designed musical activities with parents and carers. The main goal of the research is to verify the effectiveness of newly designed resources and strategies, which are based on the Sounds of Intent in the Early Years (SoI-EY) framework of musical development. This is a pilot study, comprising case studies of five children with autism in the early years. The data comprises semi-structured interviews, observations of videos, and feedback from parents on resources. Interpretative Phenomenological Analysis was chosen to analyze the interviews. The video data was coded in relation to the SoI-EY framework. The feedback from parents was used to evaluate the resources (i.e. musical activity cards). The participants’ wider development was also assessed through selected elements of the Early Years Foundation Stage (EYFS), a national assessment framework used in England: specifically, communication, language and social-emotional development. Five families of children on the autism spectrum (aged between 4-8 years) participated in the pilot. The research team visited each family 4 times over a 3-month period, during which the children were observed, and musical activities were suggested based on the child’s assessed level of musical development. Parents then trialed the activities, providing feedback and gathering further video observations of their child’s musical engagement between visits. The results of one case study will be featured in this paper, in which the evidence suggests that specifically tailored musical activity may promote communication and social engagement for a child with language difficulties on the autism spectrum. The resources were appropriate for the children’s involvement in musical activities. Findings suggest that non-specialist musical engagement with family and carers can be a powerful means to foster communication. The case study featured in this paper illustrates this with a child of limited verbal ability. There is a need for further research and development of resources that can be made available to all those working with children on the autism spectrum.

Keywords: autism, development, music education, resources

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Authors: Tsung Chieh Ma, I-Ling Chen

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Disclosing family origins to adoptees is an important topic in the adoption process. Adoption agencies usually educate adoptive parents on how to disclose to adoptees, but many adoptive parents worry that the disclosure will affect the parent–child relationship. Thus, how adoptees would like to receive the disclosure and whether they subjectively feel that the parent–child relationship is affected are both topics worthy of further discussion. This research takes a qualitative approach and connects with adoption agencies to interview six adoptees who are now adults. The purpose of the interviews is to learn about their experience receiving disclosures and their subjective feelings after learning of their family origins. The aim is to reveal the changes disclosure brought to the parent–child relationship and whether common concerns are raised due to the adoptive status. We also want to know about factors that affect their identification with their adopted status so that we can consequently give advice to other adoptive families. in this study finds that adoptees see disclosure as a process rather than an isolated event. The majority want to be told their family origin as early and proactively as possible and expect to learn the reasons they were given up for adoption and taken in as adoptees. The disclosure does not necessarily influence the parent–child relationship, and adoptees care more about the positive experiences they had with adoptive parents in their childhood. Moreover, adopted children seek contact with their original family mostly to understand why they were given up for adoption. The effects of disclosure depend on how the adoptive parents or other significant people in the lives of adoptees interpret the identity of the adoptees. That is, their response and attitude toward the identity have a lasting impact on the adoptees. The study suggests that early disclosure gives adoptees a chance to internalize the experience in the process and find self-identification.

Keywords: adoption, adoptees, disclosure of family origins, parent–child relationship, self-identity

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Authors: Elena Krelja Kurelović, Jasminka Tomljanović, Vlatka Davidović

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The development of web technologies and mobile devices makes creating, accessing, using and sharing information or communicating with each other simpler every day. However, while the amount of information constantly increasing it is becoming harder to effectively organize and find quality information despite the availability of web search engines, filtering and indexing tools. Although digital technologies have overall positive impact on students’ lives, frequent use of these technologies and digital media enriched with dynamic hypertext and hypermedia content, as well as multitasking, distractions caused by notifications, calls or messages; can decrease the attention span, make thinking, memorizing and learning more difficult, which can lead to stress and mental exhaustion. This is referred to as “information overload”, “information glut” or “information anxiety”. Objective of this study is to determine whether students show signs of information overload and to identify the possible predictors. Research was conducted using a questionnaire developed for the purpose of this study. The results show that students frequently use technology (computers, gadgets and digital media), while they show moderate level of information literacy. They have sometimes experienced symptoms of information overload. According to the statistical analysis, higher frequency of technology use and lower level of information literacy are correlated with larger information overload. The multiple regression analysis has confirmed that the combination of these two independent variables has statistically significant predictive capacity for information overload. Therefore, the information science teachers should pay attention to improving the level of students’ information literacy and educate them about the risks of excessive technology use.

Keywords: information overload, computers, mobile devices, digital media, information literacy, students

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Authors: Ozgu Hafizoglu

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Analogy is an essential tool of human cognition that enables connecting diffuse and diverse systems with attributional, deep structural, casual relations that are essential to learning, to innovation in artificial worlds, and to discovery in science. Cognitive Model of Analogy (CMA) leads and creates information pattern transfer within and between domains and disciplines in science. This paper demonstrates the Cognitive Model of Analogy (CMA) as an evolutionary approach to scientific research. The model puts forward the challenges of deep uncertainty about the future, emphasizing the need for flexibility of the system in order to enable reasoning methodology to adapt to changing conditions. In this paper, the model of analogical reasoning is created based on brain cells, their fractal, and operational forms within the system itself. Visualization techniques are used to show correspondences. Distinct phases of the problem-solving processes are divided thusly: encoding, mapping, inference, and response. The system is revealed relevant to brain activation considering each of these phases with an emphasis on achieving a better visualization of the brain cells: glial cells, axons, axon terminals, and neurons, relative to matching conditions of analogical reasoning and relational information. It’s found that encoding, mapping, inference, and response processes in four-term analogical reasoning are corresponding with the fractal and operational forms of brain cells: glial, axons, and neurons.

Keywords: analogy, analogical reasoning, cognitive model, brain and glials

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Authors: Tanya Kaur Bedi, Shankha Pratim Bhattacharya

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The US Environmental Protection Agency defines indoor air pollution as “The air quality within and around buildings, especially as it relates to the health and comfort of building occupants”. According to the 2021 report by the Energy Policy Institute at Chicago, Indian residents, a country which is home to the highest levels of air pollution in the world, lose about 5.9 years from life expectancy due to poor air quality and yet has numerous dwellings dependent on natural ventilation. Currently the urban population spends 90% of the time indoors, this scenario raises a concern for occupant health and well-being. This study attempts to demonstrate the causal relationship between the indoor air pollution and its determining aspects. Detailed indoor air pollution audits were conducted in residential buildings located in Kolkata, India in the months of December and January 2021. According to the air pollution knowledge assessment city program in India, Kolkata is also the second most polluted mega-city after Delhi. Although the air pollution levels are alarming year-long, the winter months are most crucial due to the unfavourable environmental conditions. While emissions remain typically constant throughout the year, cold air is denser and moves slower than warm air, trapping the pollution in place for much longer and consequently is breathed in at a higher rate than the summers. The air pollution monitoring period was selected considering environmental factors and major pollution contributors like traffic and road dust. This study focuses on the relationship between the built environment and the spatial-temporal distribution of air pollutants in and around it. The measured parameters include, temperature, relative humidity, air velocity, particulate matter, volatile organic compounds, formaldehyde, and benzene. A total of 56 rooms were audited, selectively targeting the most dominant middle-income group in the urban area of the metropolitan. The data-collection was conducted using a set of instruments positioned in the human breathing-zone. The study assesses the relationship between indoor air pollution levels and factors determining natural ventilation and air pollution dispersion such as surrounding environment, dominant wind, openable window to floor area ratio, windward or leeward side openings, and natural ventilation type in the room: single side or cross-ventilation, floor height, residents cleaning habits, etc.

Keywords: indoor air quality, occupant health, air pollution, architecture, urban environment

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Authors: Abdullah Alotaiq, David Wallom, Malcolm McCulloch

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This study presents an archetype-based approach to designing effective strategies for low-carbon transitions in the power sector. To achieve global energy transition goals, a renewable energy transition is critical, and understanding diverse energy landscapes across different countries is essential to design effective renewable energy policies and strategies. Using a clustering approach, this study identifies 12 energy archetypes based on the electricity mix, socio-economic indicators, and renewable energy contribution potential of 187 UN countries. Each archetype is characterized by distinct challenges and opportunities, ranging from high dependence on fossil fuels to low electricity access, low economic growth, and insufficient contribution potential of renewables. Archetype A, for instance, consists of countries with low electricity access, high poverty rates, and limited power infrastructure, while Archetype J comprises developed countries with high electricity demand and installed renewables. The study findings have significant implications for renewable energy policymaking and investment decisions, with policymakers and investors able to use the archetype approach to identify suitable renewable energy policies and measures and assess renewable energy potential and risks. Overall, the archetype approach provides a comprehensive framework for understanding diverse energy landscapes and accelerating decarbonisation of the power sector.

Keywords: fossil fuels, power plants, energy transition, renewable energy, archetypes

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Authors: Sonja Goegele, Petra Kletzenbauer

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The FH JOANNEUM- a university of applied sciences based in Austria - cooperates in teaching and research with well-known international universities and thus aims to foster so-called strategic partnerships. The exchange of university lecturers and other faculty members is a way to achieve and secure strategic company goals, in which excellent research and teaching play a central role in order to improve both the development of academics and administration. Thanks to mobility not only the university but also the involved people truly benefit in their professional development which can be seen on several levels: increased foreign language proficiency, excellent networking possibilities within the scientific community as well as reinforced didactic competencies in the form of different teaching and learning methodologies. The paper discusses mobility in the light of the university’s strategic paper entitled ‘Hands on 2022’ by presenting results from an empirical research study among faculty members who participate in exchange programmes on a regular basis. In the form of an online questionnaire, mobility was discussed from different angles such as networking, collaborative research, professional training for academics and the overall impact of the exchange within and outside the organization. From the findings, it can be concluded that mobility is an asset for any university. However, keeping in constant dialogue with partner universities requires more than the purpose of the exchange itself. Building rapport and keeping a relationship of trust are challenges that need to be addressed more closely in order to run successful mobility programmes. Best Practice examples should highlight the importance of mobility as a vital initiative to transfer disciplines.

Keywords: higher education, internationalization, mobility, strategic partnerships

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Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

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The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

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