Search results for: differential learning

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

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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: 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

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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: Ajaz Shaheen, Jawaid Ahmed Siddqui

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This world has purely become scientific and technological, and therefore it demands more from our young learners to be more intellectual in learning sciences. A point of concern that is dragging the attention of educationists is that young learners are gradually detaching from science and scientific theory. To deal with this matter, we must arrange such engaging activities that may improve the imaginative skills of our young learners. Our ongoing research program highlights the effects of such activities that demand the learners to interpret scientific information in the form of text they possess. These mixed stories are also known as what we call BioStories. Learners upload their narratives on different websites to let their peers go through their manuscripts. That, as a result, brings more refinement to their works. Moreover, stories allow the learners to read, understand and learn on a broader spectrum. We have conducted separate studies with learners from Grades 6, 9, and 12 that involve case studies and quasi-experimental designs. The conclusion we drew from the analysis of Grade 6 learners was that the alignment of stories helped them become more familiar with the scientific issue. Not only this but also the learners of the respective grade built up their interest in the subject and also developed a clear understanding of related subject topics. On the other hand, results from the 8th and 9th grades study support the argument that learners reflected a positive attitude toward writing scientific information. Lastly, we concluded from the 12th-grade learners that they took pride in their writing skills and built up their strength, determination, and interest. The students became self-conscious as they wrote hybridized scientific narratives in science.

Keywords: BioStories, hybridized writing, scientific literacy, scientific method

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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: Jocelyn L. Alimondo, Juna O. Sabelo

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This study explored the MTB-MLE implementation practices of teachers in one monolingual elementary school and one multilingual elementary school in Benguet, Philippines. It used phenomenological approach employing participant-observation, focus group discussion and individual interview. Data were gathered using a video camera, an audio recorder, and an FGD guide and were treated through triangulation and coding. From the data collected, varied ways in implementing the MTB-MLE program were noted. These are: Teaching using a hybrid first language, teaching using a foreign LOI, using translation and multilingual instruction, and using L2/L3 to unlock L1. However, these practices come with challenges such as the a conflict between the mandated LOI and what pupils need, lack of proficiency of teachers in the mandated LOI, facing unreceptive parents, stagnation of knowledge resulting from over-familiarity of input, and zero learning resulting from an incomprehensible language input. From the practices and challenges experienced by the teachers, a model of MTB-MLE approach, the 3L-in-one approach, to teaching was created to illustrate the practice which teachers claimed to be the best way to address the challenges besetting them while at the same time satisfying the academic needs of their pupils. From the findings, this paper concludes that despite the challenges besetting the teachers, they still displayed creativity in coming up with relevant teaching practices, the unreceptiveness of some teachers and parents sprung from the fact that they do not understand the real concept of MTB-MLE, greater challenges are being faced by teachers in multilingual school due to the diverse linguistic background of their clients, and the most effective approach in implementing MTB-MLE is the multilingual approach, allowing the use of the pupils’ mother tongue, L2 (Filipino), L3 (English), and other languages familiar to the students.

Keywords: MTB-MLE Philippines, MTB-MLE model, first language, multilingual instruction

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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: Carlos Amnael Orozco-Diaz, Robert David Moorehead, Gwendolen Reilly, Fiona Gilchrist, Cheryl Ann Miller

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The current gold-standard for maxillofacial reconstruction surgery (MRS) utilizes auto-grafted cancellous bone as a filler. This study was aimed towards developing a polylactic-acid/hydroxyapatite (PLA-HA) composite suitable for fused-deposition 3D printing. Functionalization of the polymer through the addition of HA was directed to promoting bone-regeneration properties so that the material can rival the performance of cancellous bone grafts in terms of bone-lesion repair. This kind of composite enables the production of MRS implants based off 3D-reconstructions from image studies – namely computed tomography – for anatomically-correct fitting. The present study encompassed in-vitro degradation and in-vitro biocompatibility profiling for 3D-printed PLA and PLA-HA composites. PLA filament (Verbatim Co.) and Captal S hydroxyapatite micro-scale HA powder (Plasma Biotal Ltd) were used to produce PLA-HA composites at 5, 10, and 20%-by-weight HA concentration. These were extruded into 3D-printing filament, and processed in a BFB-3000 3D-Printer (3D Systems Co.) into tensile specimens, and were mechanically challenged as per ASTM D638-03. Furthermore, tensile specimens were subjected to accelerated degradation in phosphate-buffered saline solution at 70°C for 23 days, as per ISO-10993-13-2010. This included monitoring of mass loss (through dry-weighing), crystallinity (through thermogravimetric analysis/differential thermal analysis), molecular weight (through gel-permeation chromatography), and tensile strength. In-vitro biocompatibility analysis included cell-viability and extracellular matrix deposition, which were performed both on flat surfaces and on 3D-constructs – both produced through 3D-printing. Discs of 1 cm in diameter and cubic 3D-meshes of 1 cm3 were 3D printed in PLA and PLA-HA composites (n = 6). The samples were seeded with 5000 MG-63 osteosarcoma-like cells, with cell viability extrapolated throughout 21 days via resazurin reduction assays. As evidence of osteogenicity, collagen and calcium deposition were indirectly estimated through Sirius Red staining and Alizarin Red staining respectively. Results have shown that 3D printed PLA loses structural integrity as early as the first day of accelerated degradation, which was significantly faster than the literature suggests. This was reflected in the loss of tensile strength down to untestable brittleness. During degradation, mass loss, molecular weight, and crystallinity behaved similarly to results found in similar studies for PLA. All composite versions and pure PLA were found to perform equivalent to tissue-culture plastic (TCP) in supporting the seeded-cell population. Significant differences (p = 0.05) were found on collagen deposition for higher HA concentrations, with composite samples performing better than pure PLA and TCP. Additionally, per-cell-calcium deposition on the 3D-meshes was significantly lower when comparing 3D-meshes to discs of the same material (p = 0.05). These results support the idea that 3D-printable PLA-HA composites are a viable resorbable material for artificial grafts for bone-regeneration. Degradation data suggests that 3D-printing of these materials – as opposed to other manufacturing methods – might result in faster resorption than currently-used PLA implants.

Keywords: bone regeneration implants, 3D-printing, in vitro testing, biocompatibility, polymer degradation, polymer-ceramic composites

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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: 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: Sadeq Al Yaari, Fayza Al Hammadi, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari, Salah Al Yami

Abstract:

Background: When we further take Arabic grammatical issues into account in accordance with applied linguistic investigations on Arabic as Second Language (ASL) learners, a fundamental issue arises at this point as to the production of speech in Arabic: Oral grammatical errors committed by ASL learners. Aims: Using manual rating as well as computational analytic methodology to test a corpus of recorded speech by Second Language (ASL) learners of Arabic, this study aims to find the areas of difficulties in learning Arabic grammar. More specifically, it examines how and why ASL learners make grammatical errors in their oral speech. Methods: Tape recordings of four (4) Arabic as Second Language (ASL) learners who ranged in age from 23 to 30 were naturally collected. All participants have completed an intensive Arabic program (two years) and 20 minute-speech was recorded for each participant. Having the collected corpus, the next procedure was to rate them against Arabic standard grammar. The rating includes four processes: Description, analysis and assessment. Conclusions: Outcomes made from the issues addressed in this paper can be summarized in the fact that ASL learners face many grammatical difficulties when studying Arabic word order, tenses and aspects, function words, subject-verb agreement, verb form, active-passive voice, global and local errors, processes-based errors including addition, omission, substitution or a combination of any of them.

Keywords: grammar, error, oral, Arabic, second language, learner, applied linguistics.

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Authors: Abdullah Alotaiq, David Wallom, Malcolm McCulloch

Abstract:

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

Abstract:

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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Authors: Rafat Alwazna

Abstract:

Translation teaching is a particular activity that includes translators and interpreters training either inside or outside institutionalised settings, such as universities. It can also serve as a means of teaching other fields, such as foreign languages. Translation teaching began in the twentieth century. Teachers of translation hold the responsibilities of educating students, developing their translation competence and training them to be professional translators. The activity of translation teaching involves various tasks, including curriculum design, course delivery, material writing as well as application and implementation. The present paper addresses translation teaching during COVID-19 outbreak, seeking to find out the challenges encountered by translation teachers in online translation teaching and the discoveries/solutions arrived at to resolve them. The paper makes use of a comprehensive questionnaire, containing closed-ended and open-ended questions to elicit both quantitative as well as qualitative data from about sixty translation teachers who have been teaching translation at BA and MA levels during COVID-19 outbreak. The data shows that about 40% of the participants evaluate their online translation teaching experience during COVID-19 outbreak as enjoyable and exhilarating. On the contrary, no participant has evaluated his/her online translation teaching experience as being not good, nor has any participant evaluated his/her online translation teaching experience as being terrible. The data also presents that about 23.33% of the participants evaluate their online translation teaching experience as very good, and the same percentage applies to those who evaluate their online translation teaching experience as good to some extent. Moreover, the data indicates that around 13.33% of the participants evaluate their online translation teaching experience as good. The data also demonstrates that the majority of the participants have encountered obstacles in online translation teaching and have concurrently proposed solutions to resolve them.

Keywords: online translation teaching, electronic learning platform, COVID-19 outbreak, challenges, solutions

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Authors: Rashida Suleiman, Asamoah Jnr. Boakye, Suleiman Ahmed Ibn Ahmed

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In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. MYCIN is a groundbreaking illustration of a clinical decision support system (CDSS), which was developed to assist physicians in the diagnosis and treatment of bacterial infections by providing suggestions for antibiotic regimens. MYCIN was one of the earliest expert systems to demonstrate how CDSSs may assist human decision-making in complicated areas. Relevant databases were searched using google scholar, PubMed and general Google search, which were peculiar to clinical decision support systems. The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of MYCIN, a clinical decision support system. Inferences drawn from the articles showed some usage of MYCIN for problem-based learning among clinicians and students in some countries. Furthermore, the data demonstrated that MYCIN had completed clinical testing at Stanford University Hospital following years of research. The system (MYCIN) was shown to be extremely accurate and effective in diagnosing and treating bacterial infections, and it demonstrated how CDSSs might enhance clinical decision-making in difficult circumstances. Despite the challenges MYCIN presents, the benefits of its usage to clinicians, students and software developers are enormous.

Keywords: clinical decision support system, MYCIN, diagnosis, bacterial infections, support systems

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

Abstract:

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

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

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

Abstract:

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

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

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