Search results for: Deep learning based segmentation

Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Shiyi He, Yan Xia, Xiaoping Ouyang, Liang Chen, Zhongbing Zhang, Jinlu Ruan

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As the key system of the spacecraft, various propelling system have been developing rapidly, including ion thrust, laser thrust, solar sail and other micro-thrusters. However, there still are some shortages in these systems. The ion thruster requires the high-voltage or magnetic field to accelerate, resulting in extra system, heavy quantity and large volume. The laser thrust now is mostly ground-based and providing pulse thrust, restraint by the station distribution and the capacity of laser. The thrust direction of solar sail is limited to its relative position with the Sun, so it is hard to propel toward the Sun or adjust in the shadow.In this paper, a novel nuclear thruster based on alpha decay and spontaneous fission is proposed and the principle of this radiation-thrust with alpha particle has been expounded. Radioactive materials with different released energy, such as 210Po with 5.4MeV and 238Pu with 5.29MeV, attached to a metal film will provides various thrust among 0.02-5uN/cm2. With this repulsive force, radiation is able to be a power source. With the advantages of low system quantity, high accuracy and long active time, the radiation thrust is promising in the field of space debris removal, orbit control of nano-satellite array and deep space exploration. To do further study, a formula lead to the amplitude and direction of thrust by the released energy and decay coefficient is set up. With the initial formula, the alpha radiation elements with the half life period longer than a hundred days are calculated and listed. As the alpha particles emit continuously, the residual charge in metal film grows and affects the emitting energy distribution of alpha particles. With the residual charge or extra electromagnetic field, the emitting of alpha particles performs differently and is analyzed in this paper. Furthermore, three more complex situations are discussed. Radiation element generating alpha particles with several energies in different intensity, mixture of various radiation elements, and cascaded alpha decay are studied respectively. In combined way, it is more efficient and flexible to adjust the thrust amplitude. The propelling model of the spontaneous fission is similar with the one of alpha decay, which has a more complex angular distribution. A new quasi-sphere space propelling system based on the radiation-thrust has been introduced, as well as the collecting and processing system of excess charge and reaction heat. The energy and spatial angular distribution of emitting alpha particles on unit area and certain propelling system have been studied. As the alpha particles are easily losing energy and self-absorb, the distribution is not the simple stacking of each nuclide. With the change of the amplitude and angel of radiation-thrust, orbital variation strategy on space debris removal is shown and optimized.

Keywords: alpha decay, angular distribution, emitting energy, orbital variation, radiation-thruster

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Authors: Li-Ching Hung

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The lack of empirical research on portfolio assessment in aboriginal EFL English classes of junior high schools in Taiwan may inhibit EFL teachers from appreciating the utility of this alternative assessment approach. This study addressed the following research questions: 1) understand how aboriginal EFL students and instructors of junior high schools in Taiwan perceive portfolio assessment, and 2) how portfolio assessment affects Taiwanese aboriginal EFL students’ learning outcomes. Ten classes of five junior high schools in Taiwan (from different regions of Taiwan) participated in this study. Two classes from each school joined the study, and each class was randomly assigned as a control group, and one was the experimental group. These five junior high schools consisted of at least 50% of aboriginal students. A mixed research design was utilized. The instructor of each class implemented a portfolio assessment for 15 weeks of the 2015 Fall Semester. At the beginning of the semester, all participants took a GEPT test (pretest), and in the 15th week, all participants took the same level of GEPT test (post-test). Scores of students’ GEPT tests were checked by the researcher as supplemental data in order to understand each student’s performance. In addition, each instructor was interviewed to provide qualitative data concerning students’ general learning performance and their perception of implementing portfolio assessments in their English classes. The results of this study were used to provide suggestions for EFL instructors while modifying their lesson plans regarding assessment. In addition, the empirical data were used as references for EFL instructors implementing portfolio assessments in their classes effectively.

Keywords: assessment, portfolio assessment, qualitative design, aboriginal ESL students

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Authors: Abdelbasit Gadour

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A great number of children in mainstream schools across Libya are currently living with emotional, behavioral difficulties. This study aims to explore teachers’ perceptions of children’s emotional and behavioral difficulties (EBD) and their attributions of the causes of EBD. The relevance of this area of study to current educational practice is illustrated in the fact that primary school teachers in Libya find classroom behavior problems one of the major difficulties they face. The information presented in this study was gathered from 182 teachers that responded back to the survey, of whom 27 teachers were later interviewed. In general, teachers’ perceptions of EBD reflect personal experience, training, and attitudes. Teachers appear from this study to use words such as indifferent, frightened, withdrawn, aggressive, disobedient, hyperactive, less ambitious, lacking concentration, and academically weak to describe pupils with emotional and behavioral difficulties (EBD). The implications of this study are envisaged as being extremely important to support teachers addressing children’s EBD and shed light on the contributing factors to EBD for a successful teaching-learning process in Libyan primary schools.

Keywords: children, emotional and behavior difficulties, learning, teachers'

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Authors: Vânia Graça, Paula Quadros-Flores, Altina Ramos

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The use of Digital Technologies in teaching and learning processes is currently a reality, namely in initial teacher training. This study aims at knowing the digital reality of students in initial teacher training in order to improve training in the educational use of ICT and to promote digital technology integration strategies in an educational context. It is part of the IFITIC Project "Innovate with ICT in Initial Teacher Training to Promote Methodological Renewal in Pre-school Education and in the 1st and 2nd Basic Education Cycle" which involves the School of Education, Polytechnic of Porto and Institute of Education, University of Minho. The Project aims at rethinking educational practice with ICT in the initial training of future teachers in order to promote methodological innovation in Pre-school Education and in the 1st and 2nd Cycles of Basic Education. A qualitative methodology was used, in which a questionnaire survey was applied to teachers in initial training. For data analysis, the techniques of content analysis with the support of NVivo software were used. The results point to the following aspects: a) future teachers recognize that they have more technical knowledge about ICT than pedagogical knowledge. This result makes sense if we consider the objective of Basic Education, so that the gaps can be filled in the Master's Course by students who wish to follow the teaching; b) the respondents are aware that the integration of digital resources contributes positively to students' learning and to the life of children and young people, which also promotes preparation in life; c) to be a teacher in the digital age there is a need for the development of digital literacy, lifelong learning and the adoption of new ways of teaching how to learn. Thus, this study aims to contribute to a reflection on the teaching profession in the digital age.

Keywords: digital technologies, initial teacher training, pedagogical use of ICT, skills

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Authors: Anirudha S. Joshi

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The 21st century classroom is filled with a vibrant assortment of learners. In India the different socio-economic background with culturally diversified experiences need the English teacher of the teenage group to be more dynamic, innovative and competent. The boycott of conventional ways of teaching and the warm reception of modern approaches give place to the modern devices like Television. Instead of calling it an idiot? box why not a dynamic teacher utilize it for the purpose of developing the skills among the students? The teacher applies various strategies for the learners. One of them is selecting a particular popular T.V. program in the national language ‘Hindi’ and motivating the constructivist students to take part in the activities based on it. This bilingual method enables them to develop the speaking, writing and conversational skills in English in a very natural, informal and enthusiastic way.

Keywords: bilingual method, modern approaches, natural way, TV program

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Authors: Hoa Pham

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Code switching, which can be described as the use of students’ first language in second language classrooms, has long been a controversial topic in the area of language teaching and second language acquisition. While this has been widely investigated across different contexts, little empirical research has been undertaken in Vietnam. The findings of this study contribute to our understanding of bilingual discourse and code switching practices in content and language integrated classrooms, which has significant implications for language teaching and learning in general and in particular for language pedagogy at tertiary level in Vietnam. This study examines the accounts the teachers articulated for their code switching practices in content-based Business English in Vietnam. Data were collected from five teachers through the use of stimulated recall interviews facilitated by the video data to garner the teachers' cognitive reflection, and allowed them to vocalise the motivations behind their code switching behaviour in particular contexts. The literature has recommended that when participants are provided with a large amount of stimuli or cues, they will experience an original situation again in their imagination with great accuracy. This technique can also provide a valuable "insider" perspective on the phenomenon under investigation which complements the researcher’s "outsider" observation. This can create a relaxed atmosphere during the interview process, which in turn promotes the collection of rich and diverse data. Also, participants can be empowered by this technique as they can raise their own concerns and discuss instances which they find important or interesting. The data generated through this study were analysed using a constant comparative approach. The study found that the teachers indicated their support for the use of code switching in their pedagogical practices. Particularly, as a pedagogical resource, the teachers saw code switching to the L1 playing a key role in facilitating the students' comprehension of both content knowledge and the target language. They believed the use of the L1 accommodates the students' current language competence and content knowledge. They also expressed positive opinions about the role that code switching plays in stimulating students' schematic language and content knowledge, encouraging retention and interest in learning and promoting a positive affective environment in the classroom. The teachers perceived that their use of code switching to the L1 helps them meet the students' language needs and prepares them for their study in subsequent courses and addresses functional needs so that students can cope with English language use outside the classroom. Several factors shaped the teachers' perceptions of their code switching practices, including their accumulated teaching experience, their previous experience as language learners, their theoretical understanding of language teaching and learning, and their knowledge of the teaching context. Code switching was a typical phenomenon in the observed classes and was supported by the teachers in certain contexts. This study reinforces the call in the literature to recognise this practice as a useful instructional resource.

Keywords: codeswitching, language teaching, teacher beliefs, tertiary level

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Authors: Norshaffika I. Zaiedy Nor, Andrew P. Smith

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Background: Training is essential to develop individuals’ expertise to meet current and future job demands and to improve work performance. At the same time, individuals’ well-being is crucial to ensure that they can fully and positively carry out their daily duties. In addition to the studies that have examined what constitutes well-being and the factors behind it, many researchers have investigated the predictors of training effectiveness and transfer of training. However, there has been very little integration between them. This study was an attempt to bridge the gap between training effectiveness predictors and well-being. Purpose: This research paper aimed to investigate the association between well-being among employees and psychosocial characteristics, together with training variables. Training variables consist of motivation to learn; learning; implementation intention; and cognitive dissonance. Methodology: In total, 210 workers who had undergone various training programs completed an online survey measuring various psychosocial characteristics, four training variables, and level of well-being. Findings: The results showed that certain types of positive psychosocial characteristics (e.g., positive personality, positive work behaviors, positive work and resources) predict motivation to learn, learning and implementation intention. Meanwhile, negative psychosocial characteristics (e.g. negative work demands and resources, negative coping) predict cognitive dissonance. Also, all the training variables had a moderate to high correlation with well-being. However, after controlling other variables (age, gender, education and psychosocial characteristics), none of the training variables predicted well-being. Self-determination theory, cognitive dissonance theory, and the DRIVE model were used to explain these findings. Conclusion: As there is limited research on the integration of training variables with well-being, this study gives a new perspective in the field of both training and well-being. Further investigations are needed to examine the relationships between them.

Keywords: cognitive dissonance, implementation intention, learning, motivation to learn, psychosocial characteristics, well-being

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Authors: Edidiong Enyeneokpon Ukoh, Olutayo Toyin Omole

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This study investigates classroom interaction patterns across various academic disciplines in Nigerian universities, utilizing the Teaching Dimension Observation Protocol (TDOP) as a primary instrument for data collection. A survey-type non-experimental research design was employed, incorporating a multi-stage sampling approach to ensure representation from diverse faculties, including agriculture, education, engineering, medicine, science, social sciences, and humanities. The findings reveal significant differences in teaching methods, with traditional lectures dominating in technical fields such as science and engineering, while non-technical fields like social sciences and arts exhibit greater engagement with interactive teaching strategies. The results highlight a concerning trend of passive learning environments that may hinder the development of critical skills necessary for graduates' employability. This study underscores the urgent need for Nigerian universities to reassess their pedagogical approaches and adopt more interactive methods that foster active learning. Recommendations include promoting discipline-specific training for educators, implementing regular assessments of teaching practices, and strengthening partnerships with industry stakeholders to align educational outcomes with workforce demands. By embracing these changes, universities can enhance student engagement and contribute effectively to national development through the cultivation of a skilled workforce.

Keywords: classroom interaction patterns, Nigerian universities, teaching dimension observation protocol, active learning, pedagogical approaches

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Authors: Hui Fang Huang Su, Jia Borror

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This study compared two interventions for teaching math to preschool-aged students with autism spectrum disorder (ASD). The first is considered the business as usual (BAU) intervention, which uses the Strategies for Teaching Based on Autism Research (STAR) curriculum and discrete trial teaching as the instructional methodology. The second is the Math is Not Difficult (Project MIND) activity-embedded, naturalistic intervention. These interventions were randomly assigned to four preschool students with ASD classrooms and implemented over three months for Project Mind. We used measurement gained during the same three months for the STAR intervention. In addition, we used A quasi-experimental, pre-test/post-test design to compare the effectiveness of these two interventions in building mathematical knowledge and skills. The pre-post measures include three standardized instruments: the Test of Early Math Ability-3, the Problem Solving and Calculation subtests of the Woodcock-Johnson Test of Achievement IV, and the Bracken Test of Basic Concepts-3 Receptive. The STAR curriculum-based assessment is administered to all Baudhuin students three times per year, and we used the results in this study. We anticipated that implementing these two approaches would improve the mathematical knowledge and skills of children with ASD. Still, it is crucial to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: early learning, autism, math for pre-schoolers, special education, teaching strategies

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Authors: Lyne Chantal Boudreau, Claudine Auger, Arline Laforest

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As an English-speaking country, Canada faces challenges in French-language education. During both editions of a provincial congress on education planned and conducted under shared cultural leadership, three organizers created a Francophone space where, for the first time in the province of New Brunswick (the only officially bilingual province in Canada), a group of stakeholders from the school, post-secondary and community sectors have succeeded in contributing to reflections on specific topics by sharing winning practices to meet the challenges of learning in a minority Francophone environment. Shared cultural leadership is a hybrid between theories of leadership styles in minority communities and theories of shared leadership. Through shared cultural leadership, the goal is simply to guide leadership and to set up all minority leaderships in minority context through shared leadership. This leadership style requires leaders to transition from a hierarchical to a horizontal approach, that is, to an approach where each individual is at the same level. In this exploratory research, it has been demonstrated that shared leadership exercised under the T-learning model best fosters the mobilization of all partners in advancing in-depth knowledge in a particular field while simultaneously allowing learning of the elements related to the domain in question. This session will present how it is possible to mobilize the whole community through leaders who continually develop their knowledge and skills in their specific field but also in related fields. Leaders in this style of management associated to shared cultural leadership acquire the ability to consider solutions to problems from a holistic perspective and to develop a collective power derived from the leadership of each and everyone in a space where all are rallied to promote the ultimate advancement of society.

Keywords: education, minority context, shared leadership, t-leaning

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Authors: Luisa Carrer, Lorenzo De Masi

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In this paper, we exploit the massive amount of information from Facebook to build a measure of gender attitudes in Italy at a previously impossible resolution—the municipal level. We construct our index via a machine learning method to replicate a benchmark region-level measure. Interestingly, we find that most of the variation in our Gender Norms Index (GNI) is across towns within narrowly defined geographical areas rather than across regions or provinces. In a second step, we show how this local variation in norms can be leveraged for identification purposes. In particular, we use our index to investigate whether these differences in norms carry over to the policy activity of politicians elected in the Italian Parliament. We document that females are more likely to sit in parliamentary committees focused on gender-sensitive matters, labor, and social issues, but not if they come from a relatively conservative town. These effects are robust to conditioning the legislative term and electoral district, suggesting the importance of social norms in shaping legislators’ policy activity.

Keywords: gender equality, gender norms index, Facebook, machine learning, politics

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Authors: Dimitrie Marinceu

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The newest Canadian Used Fuel Container (UFC)- (called also “Mark II”) modifies the design approach for its Assembly Robotic Cell (ARC) in the Canadian Used (Nuclear) Fuel Packing Plant (UFPP). Some of the robotic design solutions are presented in this paper. The design indicates that robots and manipulators are expected to be used in the Canadian UFPP. As normally, the UFPP design will incorporate redundancy of all equipment to allow expedient recovery from any postulated upset conditions. Overall, this paper suggests that robot usage will have a significant positive impact on nuclear safety, quality, productivity, and reliability.

Keywords: used fuel packing plant, robotic assembly cell, used fuel container, deep geological repository

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Authors: Pinzhe Zhao

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This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

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Authors: K. Umbleja, M. Ichino, H. Yaguchi

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In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

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Authors: Dacheng Li, Bo Huang, Qinjin Han, Ming Li

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Remotely sensed imagery with the high spatial and temporal characteristics, which it is hard to acquire under the current land observation satellites, has been considered as a key factor for monitoring environmental changes over both global and local scales. On a basis of the limited high spatial-resolution observations, challenged studies called spatiotemporal fusion have been developed for generating high spatiotemporal images through employing other auxiliary low spatial-resolution data while with high-frequency observations. However, a majority of spatiotemporal fusion approaches yield to satisfactory assumption, empirical but unstable parameters, low accuracy or inefficient performance. Although the spatiotemporal fusion methodology via sparse representation theory has advantage in capturing reflectance changes, stability and execution efficiency (even more efficient when overcomplete dictionaries have been pre-trained), the retrieval of high-accuracy dictionary and its response to fusion results are still pending issues. In this paper, we employ additional image pairs (here each image-pair includes a Landsat Operational Land Imager and a Moderate Resolution Imaging Spectroradiometer acquisitions covering the partial area of Baotou, China) only into the coupled dictionary training process based on K-SVD (K-means Singular Value Decomposition) algorithm, and attempt to improve the fusion results of two existing sparse representation based fusion models (respectively utilizing one and two available image-pair). The results show that more eligible image pairs are probably related to a more accurate overcomplete dictionary, which generally indicates a better image representation, and is then contribute to an effective fusion performance in case that the added image-pair has similar seasonal aspects and image spatial structure features to the original image-pair. It is, therefore, reasonable to construct multi-dictionary training pattern for generating a series of high spatial resolution images based on limited acquisitions.

Keywords: spatiotemporal fusion, sparse representation, K-SVD algorithm, dictionary learning

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Authors: Samuel Ntsanwisi

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This study investigates the transformative role of Artificial Intelligence (AI) and Virtual Reality (VR) in the preservation of endangered African languages. The study is contextualized within the film and television industry, highlighting disparities in screen representation for certain languages in South Africa, underscoring the need for increased visibility and preservation efforts; with globalization and cultural shifts posing significant threats to linguistic diversity, this research explores approaches to language preservation. By leveraging AI technologies, such as speech recognition, translation, and adaptive learning applications, and integrating VR for immersive and interactive experiences, the study aims to create a framework for teaching and passing on endangered African languages. Through digital documentation, interactive language learning applications, storytelling, and community engagement, the research demonstrates how these technologies can empower communities to revitalize their linguistic heritage. This study employs a dual-method approach, combining a rigorous literature review to analyse existing research on the convergence of AI, VR, and language preservation with primary data collection through interviews and surveys with ten filmmakers. The literature review establishes a solid foundation for understanding the current landscape, while interviews with filmmakers provide crucial real-world insights, enriching the study's depth. This balanced methodology ensures a comprehensive exploration of the intersection between AI, VR, and language preservation, offering both theoretical insights and practical perspectives from industry professionals.

Keywords: language preservation, endangered languages, artificial intelligence, virtual reality, interactive learning

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Authors: Niyti, Aman Deep, Rajesh Kharab, Sahila Chopra, Raj. K. Gupta

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Relatively long-lived transactinide elements (i.e., elements with atomic number Z≥104) up to Z = 108 have been produced in nuclear reactions between low Z projectiles (C to Al) and actinide targets. Cross sections have been observed to decrease steeply with increasing Z. Recently, production cross sections of several picobarns have been reported for comparatively neutron-rich nuclides of 112 through 118 produced via hot fusion reactions with 48Ca and actinide targets. Some of those heavy nuclides are reported to have lifetimes on the order of seconds or longer. The relatively high cross sections in these hot fusion reactions are not fully understood and this has renewed interest in systematic studies of heavy-ion reactions with actinide targets. The main aim of this work is to understand the dynamics hot fusion reactions 18O+ 248Cm and 22Ne+244Pu (carried out at RIKEN and TASCA respectively) using the collective clusterization technique, carried out by undertaking the decay of the compound nucleus 266Rf∗ into 4n, 5n and 6n neutron evaporation channels. Here we extend our earlier study of the excitation functions (EFs) of 266Rf∗, formed in fusion reaction 18O+248Cm, based on Dynamical Cluster-decay Model (DCM) using the pocket formula for nuclear proximity potential, to the use of other nuclear interaction potentials derived from Skyrme energy density formalism (SEDF) based on semiclassical extended Thomas Fermi (ETF) approach and also study entrance channel effects by considering the synthesis of 266Rf* in 22Ne+244Pu reaction. The Skyrme forces used are the old force SIII, and new forces GSkI and KDE0(v1). Here, the EFs for the production of 260Rf, 261Rf and 262Rf isotope via 6n, 5n and 4n decay channel from the 266Rf∗ compound nucleus are studied at Elab = 88.2 to 125 MeV, including quadrupole deformations β2i and ‘hot-optimum’ orientations θi. The calculations are made within the DCM where the neck-length ∆R is the only parameter representing the relative separation distance between two fragments and/or clusters Ai which assimilates the neck formation effects.

Keywords: entrance channel effects, fusion reactions, skyrme force, superheavy nucleus

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Authors: Adhi Susilo

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This paper addresses the roles of distance education in the agricultural extension workers’ education. Agriculture plays an important role in both poverty reduction and economic growth. The technology of agriculture in the developing world should change continuously to keep pace with rising populations and rapidly changing social, economic, and environmental conditions. Therefore, agricultural extension workers should have several competencies in order to carry out their duties properly. One of the essential competencies that they must possess is the professional competency that is directly related to their duties in carrying out extension activities. Such competency can be acquired through studying at Universitas Terbuka (UT). With its distance learning system, agricultural extension workers can study at UT without leaving their duties. This paper presenting sociological analysis and lessons learnt from the specific context of Indonesia. Diversities in geographic, demographic, social cultural and economic conditions of the country provide specific challenges for its distance education practice and the process of social transformation to which distance education can contribute. Extension officers used distance education for personal benefits and increased professional productivity. An increase in awareness is important for the further adoption of distance learning for extension purposes. Organizations in both the public and private sector must work to increase knowledge of ICTs for the benefit of stakeholders. The use of ICTs can increase productivity for extensions officers and expand educational opportunities for learners. The use of distance education by extension to disseminate educational materials around the world is widespread. Increasing awareness and use of distance learning can lead to more productive relationships between extension officers and agricultural stakeholders.

Keywords: agricultural extension, demographic and geographic condition, distance education, ICTs

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Authors: Dina L. DiSantis

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Strengthening a sense of responsibility while relating global sustainability concepts such as water quality and pollution to a local water system can be achieved by teaching students to conduct and interpret water quality monitoring tests. When students conduct their own research, they become better stewards of the environment. Providing outdoor learning and place-based opportunities for students helps connect them to the natural world. By conducting stream studies and collecting data, students are able to better understand how the natural environment is a place where everything is connected. Students have been collecting physical, chemical and biological data along the West and East Branches of the Brandywine River, in Pennsylvania for over ten years. The stream studies are part of the advanced placement environmental science and aquatic science courses that are offered as electives to juniors and seniors at the Downingtown High School West Campus in Downingtown, Pennsylvania. Physical data collected includes: temperature, turbidity, width, depth, velocity, and volume of flow or discharge. The chemical tests conducted are: dissolved oxygen, carbon dioxide, pH, nitrates, alkalinity and phosphates. Macroinvertebrates are collected with a kick net, identified and then released. Students collect the data from several locations while traveling by canoe. In the classroom, students prepare a water quality data analysis and interpretation report based on their collected data. The summary of the results from longitudinal water quality data collection by students, as well as the strengths and weaknesses of student data collection will be presented.

Keywords: place-based, student data collection, sustainability, water quality monitoring

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Authors: Headman Hebe, Arnold Taringa

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Background of the study: The benefits derived from Environmental and Sustainability Education (ESE) go beyond obtaining knowledge about the environment and the impact of human beings on the environment. Hence, it is sensible to expose learners to various resources that could enable meaningful environment-inclined pedagogy. The schoolgrounds, where they are utilised to promote ESE, benefit holistic learner development. However, empirical evidence, globally, suggests that young children’s contact with nature is declining due to urbanization, safety concerns by parents/guardians, and greater dependency on technology. Modern children spend much time on videogames and social media with very little time in the natural environment. Furthermore, national education departments in numerous countries have made tangible efforts to embed environmental and place-based learning to their school curricula. South Africa is one of those countries whose national school education curriculum advocates for ESE in pedagogy. Nevertheless, there is paucity of research conducted in South Africa on schoolgrounds as potential enablers of ESE and tools to foster a connection between youngsters and the natural environment. Accordingly, this study was essential as it seeks to determine the extent to which environmental learning is accommodated in pedagogy. Significantly, it investigates efforts made to use schoolgrounds for pedagogical purposes to connect children with the natural environment. Therefore, this study was conducted to investigate the accessibility and use of schoolgrounds for environment-inclined pedagogy in Natural and Social Sciences in two schools located in the Mpumalanga Province of South Africa. It tries to answer the question: To what extent are schoolgrounds used to promote environmental and sustainability education in the selected schools?The sub-questions: How do teachers and learners perceive the use of schoolgrounds for environmental and sustainability education activities? How does the organization of schoolgrounds offer opportunities for environmental education activities and accessibility for learners? Research method: This qualitative–interpretive case study used purposive and convenient sampling for participant selection. Forty-six respondents: 40 learners (twenty grade 7 learners per school), 2 school principals and 4 grade 7 participated in this study. Data collection tools were observations, interviews, audio-visual recordings and questionnaires while data analysis was done thematically. Major findings: The findings of the study point to: The lack of teacher training and infrastructure in the schoolgrounds and, no administrative support. Unclear curriculum guidelines on the use of schoolgrounds for ESE. The availability various elements in the schoolgrounds that could aid ESE activities. Learners denied access to certain parts of the schoolgrounds. Lack of time and curriculum demands constrain teachers from using schoolgrounds.

Keywords: affordances, environment and sustainability education, experiential learning, schoolgrounds

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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Authors: Mariem Saadi, Sabri Kanzari, Adel Zghibi

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In semi-arid areas like the Kairouan region, the constant irrigation with saline water and the overuse of groundwater resources, soils and aquifers salinization has become an increasing concern. In this study, a methodology has been developed to evaluate the groundwater contamination risk based on the unsaturated zone hydraulic properties. Two soil profiles with different ranges of salinity, one located in the north of the plain and another one in the south of plain (each 30 m deep) and both characterized by direct recharge of the aquifer were chosen. Simulations were conducted with Hydrus-1D code using measured precipitation data for the period 1998-2003 and calculated evapotranspiration for both chosen profiles. Four combinations of initial conditions of water content and salt concentration were used for the simulation process in order to find the best match between simulated and measured values. The success of the calibration of Hydrus-1D allowed the investigation of some scenarios in order to assess the contamination risk under different natural conditions. The aquifer risk contamination is related to the natural conditions where it increased while facing climate change and temperature increase and decreased in the presence of a clay layer in the unsaturated zone. Hydrus-1D was a useful tool to predict the groundwater level and quality in the case of a direct recharge and in the absence of any information related to the soil layers except for the texture.

Keywords: Hydrus-1D, Kairouan, salinization, semi-arid region, solute transport, unsaturated zone

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Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Neal Rupani

Abstract:

Background: A surgical trainee has limited learning opportunities in the operating room in order to gain an ever-increasing standard of surgical skill, competency, and proficiency. These opportunities continue to decline due to numerous factors such as the European Working Time Directive and increasing requirement for service provision. It is therefore imperative to obtain the highest educational value from each educational opportunity. A measure that has yet to be validated in England on surgical trainees called the Operating Room Educational Environment Measure (OREEM) has been developed to identify and evaluate each component of the educational environment with a view to steer future change in optimising educational events in theatre. Aims: The aims of the study are to assess the reliability of the OREEM within England and to evaluate the surgical trainee’s objective perspective of the current operating room educational environment within one region within England. Methods: Using a quantitative study approach, data was collected over one month from surgical trainees within Health Education Thames Valley (Oxford) using an online questionnaire consisting of demographic data, the OREEM, a global satisfaction score. Results: 140 surgical trainees were invited to the study, with an online response of 54 participants (response rate = 38.6%). The OREEM was shown to have good internal consistency (α = 0.906, variables = 40) and unidimensionality, along with all four of its subgroups. The mean OREEM score was 79.16%. The areas highlighted for improvement predominantly focused on improving learning opportunities (average subscale score = 72.9%) and conducting pre- and post-operative teaching (average score = 70.4%). The trainee perception is most satisfactory for the level of supervision and workload (average subscale score = 82.87%). There was no differences found between gender (U = 191.5, p = 0.535) or type of hospital (U = 258.0, p = 0.099), but the learning environment was favoured towards senior trainees (U = 223.5, p = 0.017). There was strong correlation between OREEM and the global satisfaction score (r = 0.755, p<0.001). Conclusions: The OREEM was shown to be reliable in measuring the educational environment in the operating room. This can be used to identify potentially modifiable components for improvement and as an audit tool to ensure high standards are being met. The current perception of the education environment in Health Education Thames Valley is satisfactory, and modifiable internal and external factors such as reducing service provision requirements, empowering trainees to plan lists, creating a team-working ethic between all personnel, and using tools that maximise learning from each operation have been identified to improve learning in the future. There is a favourable attitude to use of such improvement tools, especially for those currently dissatisfied.

Keywords: education environment, surgery, post-graduate education, OREEM

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Authors: Asmaa Shehata

Abstract:

Prior research indicates that second language (L2) learners encounter difficulty in the distinguishing novel L2 contrasting sounds that are not contrastive in their native languages. L2 orthographic information, however, is found to play a positive role in the acquisition of non-native phoneme contrasts. While most studies have mainly involved a familiar written script (i.e., the Roman script), the influence of a foreign, unfamiliar script is still unknown. Therefore, the present study asks: Does unfamiliar L2 script play a role in creating distinct phonological representations of novel contrasting phonemes? It is predicted that subjects’ performance in the unfamiliar orthography group will outperform their counterparts’ performance in the control group. Thus, training that entails orthographic inputs can yield a significant improvement in L2 adult learners’ identification and lexical encoding of novel L2 consonant contrasts. Results are discussed in terms of their implications for the type of input introduced to L2 learners to improve their language learning.

Keywords: Arabic, consonant contrasts, foreign script, lexical encoding, orthography, word learning

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Authors: Beate Weyland

Abstract:

The interdisciplinary laboratory EDEN, Educational Environments with Nature, born in 2020 at the Faculty of Education of the Free University of Bolzano, is working on a research path initiated in 2012 on the relationship between pedagogy and architecture in the design process of school buildings. Between 2016 and 2018, advisory support activity for schools was born, which combined the need to qualify the physical spaces of the school with the need to update teaching practices and develop school organization with the aim of improving pupils' and teachers' sense of well-being. The goal of accompanying the development of school communities through research-training paths concerns the process of designing together pedagogical-didactic and architectural environments in which to stage the educational relationship, involving professionals from education, educational research, architecture and design, and local administration. Between 2019 and 2024, more than 30 schools and educational communities throughout Italy have entered into research-training agreements with the university, focusing increasingly on the need to create new spaces and teaching methods capable of imagining educational spaces as places of well-being and where cultural development can be presided over. The paper will focus on the presentation of the research path and on the mixed methods used to support schools and educational communities: identification of the research question, development of the research objective, experimentation, and data collection for analysis and reflection. School and educational communities are involved in a participative and active manner. The quality of the action-research work is enriched by a special focus on the relationship with plants and nature in general. Plants are seen as mediators of processes that unhinge traditional didactics and invite teachers, students, parents, and administrators to think about the quality of learning spaces and relationships based on well-being. The contribution is characterized by a particular focus on research methodologies and tools developed together with teachers to answer the issues raised and to measure the impact of the actions undertaken.

Keywords: school development, learning space, wellbeing, plants and nature

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Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

Abstract:

Coarse-grained soils are known and commonly used in a wide range of geotechnical projects, including high earth dams or embankments for their high shear strength. The most important engineering property of these soils is friction angle which represents the interlocking between soil particles and can be applied widely in designing and constructing these earth structures. Friction angle and dilative behavior of coarse-grained soils can be estimated from empirical correlations with in-situ testing and physical properties of the soil or measured directly in the laboratory performing direct shear or triaxial tests. Unfortunately, large-scale testing is difficult, challenging, and expensive and is not possible in most soil mechanic laboratories. So, it is common to remove the large particles and do the tests, which cannot be counted as an exact estimation of the parameters and behavior of the original soil. This paper describes a new methodology to simulate particles grading distribution of a well-graded gravel sample to a smaller scale sample as it can be tested in an ordinary direct shear apparatus to estimate the stress-strain behavior, friction angle, and dilative behavior of the original coarse-grained soil considering its confining pressure, and relative density using a machine learning method. A total number of 72 direct shear tests are performed in 6 different sizes, 3 different confining pressures, and 4 different relative densities. Multivariate Adaptive Regression Spline (MARS) technique was used to develop an equation in order to predict shear strength and dilative behavior based on the size distribution of coarse-grained soil particles. Also, an uncertainty analysis was performed in order to examine the reliability of the proposed equation.

Keywords: MARS, coarse-grained soil, shear strength, uncertainty analysis

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Authors: Long Zhang, Ian Hampson, Loretta O' Donnell

Abstract:

Practitioners in various industries, especially in the finance industry that conventionally benefit from financial capital and resources, appear to be increasingly aware of the importance of human capital resources (HCR) after the 2008 Global Financial Crisis. Scholars from diverse fields have conducted extensive and fruitful research on HCR within their own disciplines. This review suggests that the mainstream of pure quantitative research alone is insufficient to provide precise or comprehensive understanding of HCR. The complex relationships and interactions in HCR call for more integrative and cross-disciplinary research to more holistically understand complex and intricate HCRs. The complex nature of HCR requires deep qualitative exploration based on in-depth data to capture the everydayness of organizational activities and to register its individuality and variety. Despite previous efforts, a systematic and holistic integration of HCR research among multiple disciplines is lacking. Using a retrospective analysis of articles published in the field of economics, finance and management, including psychology, human resources management (HRM), organizational behaviour (OB), industrial and organizational psychology (I-O psychology), organizational theory, and strategy literatures, this study summaries and compares the major perspectives, theories, and findings on HCR research. A careful examination of the progress of the debates of HCR definitions and measurements in distinct disciplines enables an identification of the limitations and gaps in existing research. It enables an analysis of the interplay of these concepts, as well as that of the related concepts of intellectual capital, social capital, and Chinese guanxi, and how they provide a broader perspective on the HCR-related influences on firms’ competitive advantage. The study also introduces the themes of Environmental, Social and Governance, or ESG based investing, as the burgeoning body of ESG studies illustrates the rising importance of human and non-financial capital in investment process. The ESG literature locates HCR into a broader research context of the value of non-financial capital in explaining firm performance. The study concludes with a discussion of new directions for future research that may help advance our knowledge of HCR.

Keywords: human capital resources, social capital, Chinese guanxi, human resources management

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