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The Details of accidents on roadways, in workplaces, or public areas will be addressed in this study paper, it can have severe repercussions. In recent years, there has been an increase in interest in studying mishap data in a bid to comprehend their causes as well as create effective protection strategies. This paper will investigate the different approaches and methods used in the analysis of mishap data and associated effects, emphasizing the advantages and disadvantages of this approach, and giving instances of effective uses in various contexts. Analyzing mishap data and associated factors aids in the identification of patterns and trends, the development of predictive models, and the creation of measures to reduce the risk of accidents as well as improve overall safety. [ABSTRACT FROM AUTHOR]

This is initial research as a test of indicators and variables before taking the data as a whole. The existing indicators reflect the questions and statements in the questionnaire distributed to 63 SMEs respondents around Medan area by using two survey methods. The first survey was conducted in person, and the second survey was conducted online. This test is known as the validity and reliability test. The values generated from the test indicate whether the questionnaire can be continued or repaired before the questionnaire is distributed back to the respondents. In particular, this initial research is one of the requirements that must be carried out to determine the psychometric properties of the characteristics of respondents from a survey, whose purpose is to make an assessment based on the perceptions of the respondents and the perspective of the researcher. The Partial least squares structural equation modelling technique (PLS-SEM) and descriptive information were applied simultaneously in the analysis phase. The results of this study are that four indicators are rejected of the 45 indicators, meaning that there are four questionnaire questions that can be repaired or not used. In comparison, the variable value shows a positive value for the nine variables. The study does not contribute theoretically to the field but provides methodological information on how to conduct an assessment on the questionnaireen. [ABSTRACT FROM AUTHOR]

Learning during the pandemic is still carried out online, so students must have self-regulated learning. Self-regulated learning requires students to be actively involved in education, metacognitively, motivationally, and behaviorally. We evaluate students' self-regulated learning in STEM-based Electromagnetic lectures. This study used Zimmerman's framework of self-regulated learning. We use a time-series experimental design with an Online Self-Regulated Learning Media intervention, an instrument for monitoring self-regulated learning. We find that the intervention we used increased self-regulated learning with a medium N-gain category. Time-series measurements of pre-course self-regulated learning show that the average forethought phase score fluctuated and decreased. Meanwhile, the results of post-course self-regulated learning are the average score of the performance phase and self-reflection phase decreased. The results indicate that students are still adapting to regulate their preparation for learning through self-regulated learning and need to improve self-regulated learning. Hence, as educators, we must guide our students to do self-regulated learning. [ABSTRACT FROM AUTHOR]

Life style disorders like diabetes, cardio vascular diseases (CVD) etc. are spreading like an epidemic to a pandemic. Heart disease (HD) besides other health consequences has serious social and economical implications for the individual and for the country. These conditions have multiple dimensions and can be controlled and prevented, if diagnosed and treated in time, by improving the overall personality/life style of an individual with the help of technology. It has been found from the literature that a huge number and combination of algorithms/classifiers with great performances/accuracies have already been employed to predict the heart disease (HD). SVM classifier has been predominantly deployed for classification. Neural networks (NNs) and ensembles have also been used which have also yielded high accuracy of over 95%. CNNs and deep learning techniques too have yielded significantly high accuracies of over 95% recently. It has already been established that ensemble techniques/models consisting of a combination of several related but different models like bagging, boosting, blending/stacking and Majority voting have performed better on (Cleveland) datasets with 91.6% accuracy than individual constituent models/classifiers-called base learners. Some ensemble algorithms/models like Random Forest algorithm have been found to have achieved 100% accuracy for heart disease prediction. Further, ensemble models solve the problems like over fitting etc. also and are more suitable for the imbalanced data sets like medical/heart datasets. Owing to the unique feature processing capabilities for processing big data which is heterogeneous, high dimensional, multivariate unstructured and unlabelled in nature, deep learning deals best with unstructured and unlabelled data i.e. unsupervised learning and do not need much data pre-processing in comparison with the data mining/machine learning and does not require the processes of filtering, normalization etc. that are manually done in case of machine learning. This review paper aims at analyzing the literature to review and compare different techniques utilized for HD prediction to identify the best base learner so that in future an effective deep learning based ensemble model could be proposed that can be applied for real world heart disease data sets with improved performance. [ABSTRACT FROM AUTHOR]

This study aims to 1) describe the education transformation and 2) higher-order thinking skills for teachers in the 5.0 society era. This is because 5.0 society provides its own challenges in various fields of life, including learning. The results of research on educational transformation in welcoming the 5.0 society era include: 1) the use of artificial intelligence makes it easier for humans to complete their work better and faster. Information utilization and communication technology (ICT) can help teachers in the learning process in order to achieve results in accordance with expectations. In 5.0 society, humans also remain the center of technology-based activities (artificial intelligence and internet of think). 2) 21st century learning must be directed to support life and career skills, learning and innovation skills, critical thinking and problem solving, communication and collaboration skills, and skills in maximizing information media and technology. Second, the era of 5.0 society requires teachers to transform to be high level thinking skill. For this reason, complex thinking competencies are needed which include skills to apply, analyze, evaluate, and create. Teachers are also required to think critically, logically, systematically, and analytically in order to be able to solve problems and make appropriate decisions. [ABSTRACT FROM AUTHOR]

Deep Learning for analyzing medical images in thoracic diseases is considered necessary in radiology. The thorax examination is the most frequently performed examination in routine examinations. Analytical methods that can explain medical image analysis finding morphological patterns or textures in images are urgently needed. Currently, the interpretation of the thorax is carried out manually by radiologists based on thorax images that are influenced by the cognitive abilities and subjective experience of radiologists, thus allowing human error to occur in reading or analyzing. This study aimed to classify chest diseases such as Edema, Pneumonia, and Pneumothorax using a Convolutional NeurXR) image data used to determine chest disease are normal, edema, pneumonia, and pneumothorax data of 1487, 1022, 1374, and 1128 with an image size of 200×200 pixels. This study also analyzed optimizers RMSprop, Adadelta, Adagrad, Adamax, and Adam in the classification of thorax disease for the CNN algorithm. The results showed that Adam is the best optimizing parameter and can show good accuracy of more than 98% for the classification of thorax diseases such as Edema, Pneumonia, and Pneumothorax with epochs equal to 10. [ABSTRACT FROM AUTHOR]

Science process skills and conceptual understanding of pre-service physics teachers were in the low category. This research was conducted to solve this problem by using worksheets based on virtual phenomenon instructions. This research aims to determine the effectiveness of worksheets and improvement of science process skills and understanding of concepts in pre-service physics teachers during the COVID-19 pandemic. The design of this research is one group pretest-postest with purposive sampling are pre-service physics teachers who take mechanics course in the academic year 2020/2021 (n=81) consists of 21 males and 60 females. There are 6 conceptual understanding questions for pretest and posttests based on Bloom's Taxonomy (C2, C3, C4). Assessment of science process skills includes indicators of observing, classifying, interpreting, predicting and communicating consist of 5 questions. The data analysis technique uses the effect size and N-Gain score. Based on the result of this research, it was found that the improvement of science process skills and conceptual understanding of pre-service physics teachers reached 0.56 and 0.47 which was categorized as moderate. Effect size for science process skills and conceptual understanding are 3.5 and 1.9 are categorized very high so it can be concluded that the effectiveness of kinematics worksheets-based instruction virtual phenomenon is very significant to improve science process skills and conceptual understanding of pre-service physics teachers. [ABSTRACT FROM AUTHOR]

Due to the increasing requirements for social and environmental responsibility, the representatives of the production sectors are forced to consider ways for ensuring a lean and eco-friendly approach to business activities in order to increase the companies' sustainability in the market. In this paper, the issues of establishing an eco-friendly and lean environment are analyzed through a relevant case study, such as the production textile companies of Bangladesh. Following the international trends, the ready-made garment (RMG) sector as a catalyst for the development of Bangladesh is faced with challenges to rethink attitude to the environmental agenda towards the interests of society and stakeholders, including employees. This way, this paper proposes Corporate Social Responsibility (CSR) as a mediator for lean environmental management introduction to improve the social and environmental focus of the RMG industry. The practical and theoretical framework is developed for the integration of the considered concepts to address the environmental impacts caused by the RMG companies' activities. The findings reveal the capability to achieve positive effects during implementation of the eco-friendly and lean practices in the RMG industry enterprises and ensure sustainable development while maintaining long-term benefits. [ABSTRACT FROM AUTHOR]

Gandaria (Bouea macrophylla Griff) is a potential source of antioxidant compounds and this study was conducted to analyze the secondary metabolite constituents and antioxidant activity of the ethyl acetate extracted from B. macrophylla stem. The extracts were isolated and fractioned using chromatography techniques such as thin-layer chromatography (TLC) and column chromatography (CC). Moreover, the composition of the secondary metabolites was determined by Liquid Chromatography-Mass Spectrometry (LC-MS) while the antioxidant property of the extracts and fractions was obtained using the 1,1-diphenyl-2-picrylhidrazil (DPPH) method. The ethyl acetate extract was separated with CC and 8 subfractions represented by codes E1-E8 were obtained with E1 subfraction observed to have the most active fraction on the antioxidant assay at a moderate activity with an IC50 value of 232.96 ppm. E1 was further analyzed with LC-MS and two major compounds found were lauric diethanolamide and loganine with their synergy effects suggested to be the reason for the subfraction's moderate antioxidant activity. However, E1 requires purification to determine the most active antioxidant compound isolated from ethyl acetate extract of B. macrophylla stem. [ABSTRACT FROM AUTHOR]

Parenting is very influential on children's daily behavior, especially at school, when children encounter various types of snacks that can have a negative impact on children's health such as diarrhea, typhus and food poisoning for a long time, and can even cause cancer and anemia. This can happen if the child cannot choose healthy foods. So that family parenting plays an important role for children's health. The purpose of this study was to determine the pattern of family care and food consumption in primary school children in Medan. This study used a descriptive design. The population in this study were parents and elementary school students in Medan, totaling 270 students. Sampling using total sampling. The data collection tool uses a questionnaire. Data analysis using frequency distribution. The results showed that 92 respondents (34.3%) applied democratic parenting and from 270 respondents it was found that 173 respondents (64.1%) were in the unfavorable category for snack consumption. This can occur because there are many external factors that influence the food consumption behavior of school children and environmental factors greatly influence children's behavior, especially peer factors. Based on the research results, it is suggested that parents should supervise and provide knowledge to children about the dangers of consuming food carelessly so that children can distinguish foods that are good for consumption at school. [ABSTRACT FROM AUTHOR]

Coal transport by sea transportation method including inter-islands barge system remains important means of bulk material transportation method. Depend upon the distance between the coal mine sites to the power plant sited, the coal transportation could take days or weeks. Prolonged transportation time could lead to self-heating leading to spontaneous combustion of lower rank coal. To prevent this, a heat exchanger submersion method is proposed to reduce the potentials of self-heating problem by means increasing the heat loss from the coal piles. This experiment work was conducted to determine the effect of cooling water flow rate on decreasing temperature of coal. Laboratory-scale experiments were performed using a stainless steel cylinder that opens at the top and insulated by rockwool to reduce heat loss. The heat source comes from the bottom which is heated by a hot plate heater. A U-shaped heat exchanger of laboratory-scale experiments was prepared. In this experiment, subbituminous coal was used. The effect of flow rate on the prevention of spontaneous combustion was studied by providing variations of the flow rates, thus the amount of heat taken from the heated coal bed. In this experiment the greater flow rate is accompanied by a higher decrease in coal temperature. Therefore, this heat exchanger effective for taking heat from the coal bed. [ABSTRACT FROM AUTHOR]

Indonesia is the country with the largest source of coal in the world, one of the region in Tarahan, Sumatera. Many power plants in Indonesia use coal as its main source, one of them in Suralaya. Coal is used as the main source of power generation because it has a heat value and considerable power compared to other generating sources. In addition, the price is relatively cheap to be one consideration of usage. Coal distribution process from Tarahan to Suralaya using barge. The use of barges is still widely used because it can bring considerable capacity and cheap shipping prices compared with other transportation During the shipping process, there is often a fire on coal in barges that greatly affects the safety and quality of coal itself. There have been cases of coal barge fires due to the heat energy incurred by the coal itself. Spontaneous combustion often occur as a result of a pile of coal in barges that are directly exposed by the environment causing spontaneous fires in coal. Environmental factors such as air, temperature, weather, and humidity are very influential. This method to prevent the spontaneous combustion of coal in barges is using the U-tube heat exchanger that is installed on the barge sideboards. The purpose of this research is to have preliminary design and calculate pump capacity of the heat exchanger system in the barge with the consideration of the loading and unloading process of coal so as not to interfere with the work process. Ratio of thermal transfer influence occurring in coal to heat exchanger placement distance to determinate the placement of the heat exchanger. The heat exchanger dimension value uses the pipeline surface area ratio to the coal surface area directly exposed by the environment. The preliminary design drawings of the heat exchanger in the barge are provided. The test results showed the necessary heat exchanger pipe design and placement on the barge to prevent spontaneous combustion. [ABSTRACT FROM AUTHOR]

We report the structural, magneto-electronic, mechanical and thermo-physical properties of barium based Ba2ZnReO6 double perovskite using full potential linearized augmented plane wave method (FPLAPW). The structural characterization in all possible magnetic states and band profile display Fm-3m as stable phase group with half-metallic nature. The optimized lattice parameter of 8.080 Å and band gap of 2.49 eV show fair agreement with experimental results. The magnetic properties define the Re+6 (5d1, t2g1) orbital electron responsible for showing the ferromagnetic interaction together with half-metallic nature and integral spin magnetic moment of 1.0 􀈝B. [ABSTRACT FROM AUTHOR]

The electronic structure and transport properties of Fe2TiSn Heusler alloy are investigated by means of ab-initio calculations. Fe2TiSn alloy crystallize in Fm-3m structure with the lattice constant of 6.02 Å. The spin-polarized electronic band structure for both spin states divulges that Fe2TiSn is an indirect band gap semiconductor with a band gap of 0.6 eV. Influence of pressure shows extensive effect on the electronic structure, though no magnetic transition was observed. Increasing the pressure significantly reduces the band gap of the material, beyond 30 GPa Fe2TiSn becomes metallic in nature. The effect of varying chemical potential on the Seebeck coefficient and power factor were also observed. Fe2TiSn Heusler alloy presents decent Seebeck coefficient and power factor, with both n-type as well as p-type are ideal for achieving high thermoelectric performance. [ABSTRACT FROM AUTHOR]

Here we comment on the structural and mechanical properties of double perovskite Ba2LuSbO6 for first time, via ab-initio method. Full potential Linearized augmented plane wave (FP-LAPW) method in two approximations, local spin density approximation (LSDA) and generalized gradient approximation (GGA), reveal second one predicts the correct ground state properties. The calculated lattice constant is found consistent with the experimental result. Second order elastic constants and other elastic moduli were calculated. The computed mechanical parameters reveal the brittle anisotropic nature of Ba2LuSbO6. [ABSTRACT FROM AUTHOR]

An approach of using conjugate gradient and classic steepest descent search direction onto quasi-Newton search direction had been proposed in this paper and we called it as 'scaled CGSD-QN' search direction. A new coefficient formula had been successfully constructed for being used in the 'scaled CGSD-QN' search direction and proven here that the coefficient formula is globally converge to the minimizer. The Hessian update formula that has been used in the quasi-Newton algorithm is DFP update formula. This new search direction approach was testes with some some standard unconstrained optimization test problems and proven that this new search direction approach had positively affect quasi-Newton method by using DFP update formula. [ABSTRACT FROM AUTHOR]

In this paper we present a new search direction known as the CG-BFGS method, which uses the search direction of the conjugate gradient method approach in the quasi-Newton methods. The new algorithm is compared with the quasi-Newton methods in terms of the number of iterations and CPU-time. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is used as an updating formula for the approximation of the Hessian for both methods. Our numerical analysis provides strong evidence that our CG-BFGS method is more efficient than the ordinary BFGS method. Besides, we also prove that the new algorithm is globally convergent. [ABSTRACT FROM AUTHOR]

The Broyden family update in quasi-Newton method is known as one of the most efficient update method in solving unconstrained optimization. However, by using the standard search direction, sometimes the algorithm may lead to the failure for some complicated problems and this scenario worsen when the cases of the initial points selected are far away from the minimizer. To overcome this scenario, we proposed a new search direction by using the Fletcher Reeves formula in the conjugate gradient method to be fit with the new search direction. We proved that this new search direction globally converge and positively affect the Broyden family update in quasi-Newton method. [ABSTRACT FROM AUTHOR]

Solving the unconstrained optimization problems is not easy and DFP update method is one of the methods that we can work with to solve the problems. In unconstrained optimization, the time computing needed by the method's algorithm to solve the problems is very vital and because of that, we proposed a hybrid search direction for DFP update method in order to reduce the computation time needed for solving unconstrained optimization problems. Some convergence analysis and numerical results of the hybrid search direction were analyzed and the results showed that the proposed hybrid search direction strictly reduce the computation time needed by DFP update method and at the same time increase the method's efficiency which is sometimes fail for some complicated unconstrained optimization problems. [ABSTRACT FROM AUTHOR]

The Broyden family method for unconstrained optimization is known as one of the most efficient method in solving unconstrained optimization problem. Step size and search direction play the most important role to the convergence of the Broyden family method. Step size is proved to be successful method to solve the problem; however, it is definite to solve some complicated optimization problems. In this paper, we introduced the alternative procedure in determining the step size. This alternative procedure will be applied in the hybrid Broyden method. The numerical results based on number of iterations, number of gradient evaluation and number of function evaluation are given at the end of the paper. [ABSTRACT FROM AUTHOR]