Search results for: computer aided sport training

Authors: Khajeerat Phumphruk

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This research aims to study the knowledge, attitude toward household accounting philosophy of sufficiency economy and study the Expense Behavior Changing of household accounting in Banbolang Samut Songkhram Province. The samples of this research are chief of villages and householders in Banbolang Samut Songkhram. The sampling revealed that chief of villages and 60 of householders. The random sampling was used to collect the data. Tools of this research are structure interview and questionnaires that verified by specialist as the content validity and reliability. The result found that the reasons of doing the household accounting are finding the revenue and expenditure in order to in develop the wealthy of the family and follow the philosophy of sufficiency economy of His Majesty. The reasons of not doing the household accounting are less understanding of the household accounting, less time and useless. Moreover, there are householders who interesting in training about household accounting.

Keywords: expense behavior changing, household accounting, samut songkhram province, sufficiency economy philosophy

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Authors: Jianhua Wang, Ying Zhou, Xi Zhang

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To establish the influential mechanism of learning engagement on interpreter’s performance, the present study submitted a questionnaire to a sample of 927 English major students with 804 valid ones and used the structural equation model as the basis for empirical analysis and statistical inference on the sample data. In order to explore the mechanism for interpreting learning engagement on student interpreters’ performance, a path model of interpreting processes with three variables of ‘input-environment-output’ was constructed. The results showed that the effect of each ‘environment’ variable on interpreting ability was different from and greater than the ‘input’ variable, and learning engagement was the greatest influencing factor. At the same time, peer interaction on interpreting performance has significant influence. Results suggest that it is crucial to provide effective guidance for optimizing learning engagement and interpreting teaching research by both improving the environmental support and building the platform of peer interaction, beginning with learning engagement.

Keywords: learning engagement, interpreting performance, interpreter training, English major students

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Authors: Jose Ramon Calvo-Ferrer

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Video games have been extensively employed in educational contexts to teach contents and skills, upon the premise that they engage students and provide instant feedback, which makes them adequate tools in the field of education and training. Term frequency, along with metacognition and implicit corrective feedback, has often been identified as powerful variables in the learning of vocabulary in a foreign language. This study analyses the learning of L2 mobile operating system terminology by a group of students and uses the data collected by the video game The Conference Interpreter to identify the predictive strength of term frequency (times a term is shown), positive metacognition (times a right answer is provided), and negative metacognition (times a term is shown as wrong) regarding L2 vocabulary learning and perceived learning outcomes. The regression analysis shows that the factor ‘positive metacognition’ is a positive predictor of both dependent variables, whereas the other factors seem to have no statistical effect on any of them.

Keywords: digital game-based learning, feedback, metacognition, frequency, video games

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Authors: Kaustav Mukherjee

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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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Authors: Inuusah Mahama

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The study focused on the importance of diversity and the use of evidence-based practices and strategies in teaching learners with ASD. The study employed a mixed-methods design, including surveys, interviews, and observations. A total of 500 K-12 practitioners participated in the study, including teachers, administrators, and support staff. The study sought to investigate the current understanding and knowledge level of K-12 practitioners regarding diversity, evidence-based practices, and strategies for teaching learners with ASD. The study also examined the challenges that K-12 practitioners face in preparing learners with ASD and the resources they require to improve their practice. The results indicated that K-12 practitioners in Ghana have limited knowledge and skills in teaching learners with ASD, particularly in using evidence-based practices and strategies. Therefore, there is a need for providing training and professional development opportunities for K-12 practitioners, developing and implementing evidence-based practices and strategies, and increasing awareness of ASD and the need for effective teaching strategies. This would go a long way to improve the quality of education for learners with ASD in Ghana and ultimately lead to better outcomes for these students.

Keywords: autism, practitioners, diversity, evidence-based practises

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Authors: Neil Morgan

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The notion of Threshold Concepts has offered a fertile new perspective on the transformative effects of mastery of particular concepts on student understanding of subject matter and their developing identities as inductees into disciplinary discourse communities. Only by successfully traversing key knowledge thresholds, it is claimed, can neophytes gain access to the more sophisticated understandings of subject matter possessed by mature members of a discipline. This paper uses thematic analysis of disciplinary guiding principles to identify nine candidate Threshold Concepts that appear to underpin effective TESOL practice. The relationship between these candidate TESOL Threshold Concepts, TESOL principles, and TESOL instructional techniques appears to be amenable to a schematic representation based on superordinate categories of TESOL practitioner concern and, as such, offers an alternative to the view of Threshold Concepts as a privileged subset of disciplinary core concepts. The paper concludes by exploring the potential of a Threshold Concepts framework to productively inform TESOL initial teacher education (ITE) and in-service education and training (INSET).

Keywords: TESOL, threshold concepts, TESOL principles, TESOL ITE/INSET, community of practice

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Authors: K. S. Zaytsev, Y. R. Nartsissov

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Glycine is one of the key inhibitory neurotransmitters in Central nervous system (CNS) meanwhile glycinergic transmission is highly dependable on its appropriate reuptake from synaptic cleft. Glycine transporters (GlyT) of types 1 and 2 are the enzymes providing glycine transport back to neuronal and glial cells along with Na⁺ and Cl⁻ co-transport. The distribution and stoichiometry of GlyT1 and GlyT2 differ in details, and GlyT2 is more interesting for the research as it reuptakes glycine to neuron cells, whereas GlyT1 is located in glial cells. In the process of GlyT2 activity, the translocation of the amino acid is accompanied with binding of both one chloride and three sodium ions consequently (two sodium ions for GlyT1). In the present study, we developed a computer simulator of GlyT2 and GlyT1 activity based on known experimental data for quantitative estimation of membrane glycine transport. The trait of a single protein functioning was described using the probability approach where each enzyme state was considered separately. Created scheme of transporter functioning realized as a consequence of elemental steps allowed to take into account each event of substrate association and dissociation. Computer experiments using up-to-date kinetic parameters allowed receiving the number of translocated glycine molecules, Na⁺ and Cl⁻ ions per time period. Flexibility of developed software makes it possible to evaluate glycine reuptake pattern in time under different internal characteristics of enzyme conformational transitions. We investigated the behavior of the system in a wide range of equilibrium constant (from 0.2 to 100), which is not determined experimentally. The significant influence of equilibrium constant in the range from 0.2 to 10 on the glycine transfer process is shown. The environmental conditions such as ion and glycine concentrations are decisive if the values of the constant are outside the specified range.

Keywords: glycine, inhibitory neurotransmitters, probability approach, single protein functioning

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Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

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Authors: Jinsiang Shaw, Pik-Hoe Chen

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This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

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Authors: Afshan Ejaz, Syed Asim Ali

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The reality is a combination of perception, reconstruction, and interaction. Augmented Reality is the advancement that layer over consistent everyday existence which includes content based interface, voice-based interfaces, voice-based interface and guide based or gesture-based interfaces, so designing augmented reality application interfaces is a difficult task for the maker. Designing a user interface which is not only easy to use and easy to learn but its more interactive and self-explanatory which have high perceived affordability, perceived usefulness, consistency and high discoverability so that the user could easily recognized and understand the design. For this purpose, a lot of interface design principles such as learnability, Affordance, Simplicity, Memorability, Feedback, Visibility, Flexibly and others are introduced but there no such principles which explain the most appropriate interface design principles for designing an Augmented Reality application interfaces. Therefore, the basic goal of introducing design principles for Augmented Reality application interfaces is to match the user efforts and the computer display (‘plot user input onto computer output’) using an appropriate interface action symbol (‘metaphors’) or to make that application easy to use, easy to understand and easy to discover. In this study by observing Augmented reality system and interfaces, few of well-known design principle related to GUI (‘user-centered design’) are identify and through them, few issues are shown which can be determined through the design principles. With the help of multiple studies, our study suggests different interface design principles which makes designing Augmented Reality application interface more easier and more helpful for the maker as these principles make the interface more interactive, learnable and more usable. To accomplish and test our finding, Pokémon Go an Augmented Reality game was selected and all the suggested principles are implement and test on its interface. From the results, our study concludes that our identified principles are most important principles while developing and testing any Augmented Reality application interface.

Keywords: GUI, augmented reality, metaphors, affordance, perception, satisfaction, cognitive burden

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Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

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Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

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Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

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Authors: Hediye Saglam

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This research has been carried out to bring in the 6 acquisitions in the 2014 Preschool Teaching Programme of the Turkish Ministry of Education through the method of analogy. This research is practiced based on the experimental pattern with pre-test and final test controlling groups. The working group of the study covers the group between 5-6 ages. The study takes 5 weeks including the 2 weeks spent for pre-test and the final test. It is conducted with the preschool teacher who gives the lesson along with the researcher in the in-class and out-of-class rainbow experiments of the students for 5 weeks. 'One Sample T Test' is used for the evaluation of the pre-test and final test. SPSS 17 programme is applied for the analysis of the data. Results: As an outcome of the study it is observed that analogy method affects children’s learning of the rainbow. For this very reason teachers should receive inservice training for different methods and techniques like analogy. This method should be included in preschool education programme and should be applied by teachers more often.

Keywords: acquisitions of preschool education programme, analogy method, pre-test/final test, rainbow experiments

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Authors: Muhammad Ajmal, Ahmad Shahrul Nizam Bin Isha, Shahrina Md. Nordin, Paras Behrani, Al-Baraa Abdulrahman Al-Mekhlafi

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This study aims to investigate the impact of safety management practices via safety compliance on occupational injuries in the context of downstream the oil and gas industry of Malaysia. However, it is still challenging for researchers and academicians to control occupational injuries in high-safety-sensitive organizations. In this study response rate was 62%, and 280 valid responses were used for analysis through SmartPLS. The study results revealed that safety management practices (management commitment, safety training, safety promotion policies, workers’ involvement) play a significant role in lowering the rate of accidents in downstream the oil and gas industry via safety compliance. Furthermore, the study results also revealed that safety management practices also reduce safety management costs of organizations, e.g., lost work days and employee absenteeism. Moreover, this study is helpful for safety leaders and managers to understand the importance of safety management practices to lower the ratio of occupational injuries.

Keywords: safety management, safety compliance, occupational injuries, oil and gas, Malaysia

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Authors: Faruk Guven, Nurtekin Erkmen, Samet Aktas, Cengiz Taskin

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The aim of this study was to determine effects of field sizes on technical parameters of small-sided games in football players. Eight amateur football players (27.23±3.08 years, heigth: 171.01±5.36 cm, body weigth: 66.86±4.54 kg, sports experience: 12.88±3.28 years) performed 4-a-side small-sided games (SSG) with different field sizes. In SSGs, field sizes were 30 x 40 m and 26 mx24 m. SSGs was conducted as a series of 3 bouts of 6 min with 5 min recovery durations. All SSGs were video recorded using two digital video camcorder positioned on a tripot. Shoot on taget, passes, succesful passes, unsuccesful passes, dripling, tackle, possession in SSGs were counted by Mathball Match Analysis System. The effects of bouts on technical score were examined separately using a Friedman’s test. Mann Whitney U test was applied to analyse differences between field sizes. There were no significant differences in shoots on target, total pass, successful pass, tackle, interception, possession between bouts in 30x40 m field size (p>0.05). Unsuccessful pass in bout 3 for 30x40 m field size was lower than bout 1 and bout 2 (p<0.05) and dripling in bout 3 was lower than bout 2 (p<0.05). There was no significant difference in technical actions between bouts for 26x34 m field size (p>0.05). Shoot on target in SSG with 26 x 34 m field size was higher than SSG with 30x40 m field size (p<0.05). Unsuccessful pass for 26x34 m field size in bout 3 was higher than SSG with 30x40 m field size (p<0.05). There was no significant difference in technical actions between field sizes (p>0.05). In conclusion; in this study demonstrates that technical actions in a-4-side SSG are not influenced by different field sizes (for 30x40 m and 26x34 m field sizes). This consequence is same for both total SSG time and each bout. Dripling and unsuccessful pass decrease in bout 3 during SSG in 30 x 40 m field size.

Keywords: small-sided games, football, technical actions, sport science

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Authors: Tanit Pruktara

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The research aimed to study the students’ learning achievement and awareness level on electrical energy consumption and conservation and also to investigate the students’ attitude on the developed multimedia supplemented instructional unit for learning household electrical energy consumption and conservation in grade 10 Thailand student. This study used a quantitative method using MCQ for pre and post-achievement tests and Likert scales for awareness and attitude survey questionnaires. The results from this were employed to improve the multimedia to be appropriate for the classroom and with real life situations in the second phase, the main study. The experimental results showed that the developed learning unit significantly improved the students’ learning achievement as well as their awareness of electric energy conservation. Additional we found the student will enjoy participating in class activities when the lessons are taught using multimedia and helps them to develop the relevance between the course and real world situations.

Keywords: lesson plan, media and animations, training course, vocational school in Thailand

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

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Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

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Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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Authors: Mohammad Anwar, Shah Waliullah

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The development of science and technology in the present era has an urgent demand for the training of thinking of undergraduates. This requirement actively promotes research and teaching of basic theories, beneficial to the career development of students. This study clarified the dialectical relation between the thermodynamic equilibrium constant and reaction rate constant through the contrast thinking method. Findings reveal that both the isobaric Van't Hoff equation and the Arrhenius equation had four similar forms, and the change in the trend of both constants showed a similar law. By the derivation of the formation rate constant of the product (KY) and the consumption rate constant of the reactant (KA), the ratio of both constants at the end state indicated the nature of the equilibrium state in agreement with that of the thermodynamic equilibrium constant (K^θ (T)). This study has thus presented that the thermodynamic equilibrium constant contained the characteristics of microscopic dynamics based on the analysis of the reaction mechanism, and both constants are organically connected and unified. The reaction enthalpy and activation energy are closely related to each other with the same connotation.

Keywords: thermodynamic equilibrium constant, reaction rate constant, PBL teaching, dialectical relation, innovative thinking

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Authors: Vine Petzer, Mirna Nel

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An explanatory mixed method design was used to investigate accounting classroom conditions in the Further Education and Training (FET) Phase in South Africa. A descriptive survey research study with a heterogeneous group of learners and teachers was conducted in the first phase. In the qualitative phase, semi-structured individual interviews with learners and teachers, as well as observations in the accounting classroom, were employed to gain more in depth understanding of the learning conditions in the accounting classroom. The findings of the empirical research informed the development of a model for teachers in accounting, supporting them to use more effective teaching methods and create positive learning conditions for all learners to experience successful learning. A model towards creating positive Accounting classroom conditions that support successful learning was developed and recommended for education policy and decision-makers for use as a classroom intervention capacity building tool. The model identifies and delineates classroom practices that exert significant effect on learner attainment of quality education.

Keywords: accounting classroom conditions, positive education, successful learning, teaching accounting

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Authors: Zongping Wang, Chengjun Cui, Jiacun Wang

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The concept of intelligence has been widely used to access an individual's cognitive abilities to learn, form concepts, understand, apply logic, and reason. According to the multiple intelligence theory, there are eight distinguished types of intelligence. One of them is the bodily-kinaesthetic intelligence that links to the capacity of an individual controlling his body and working with objects. Motor intelligence, on the other hand, reflects the capacity to understand, perceive and solve functional problems by motor behavior. Both bodily-kinaesthetic intelligence and motor intelligence refer directly or indirectly to bodily capacity. Inspired by these two intelligence concepts, this paper introduces motional intelligence (MI). MI is two-fold. (1) Body strength, which is the capacity of various organ functions manifested by muscle activity under the control of the central nervous system during physical exercises. It can be measured by the magnitude of muscle contraction force, the frequency of repeating a movement, the time to finish a movement of body position, the duration to maintain muscles in a working status, etc. Body strength reflects the objective of MI. (2) Level of psychiatric willingness to physical events. It is a subjective thing and determined by an individual’s self-consciousness to physical events and resistance to fatigue. As such, we call it subjective MI. Subjective MI can be improved through education and proper social events. The improvement of subjective MI can lead to that of objective MI. A quantitative score of an individual’s MI is motional quotient (MQ). MQ is affected by several factors, including genetics, physical training, diet and lifestyle, family and social environment, and personal awareness of the importance of physical exercise. Genes determine one’s body strength potential. Physical training, in general, makes people stronger, faster and swifter. Diet and lifestyle have a direct impact on health. Family and social environment largely affect one’s passion for physical activities, so does personal awareness of the importance of physical exercise. The key to the success of the MQ study is developing an acceptable and efficient system that can be used to assess MQ objectively and quantitatively. We should apply different accessing systems to different groups of people according to their ages and genders. Field test, laboratory test and questionnaire are among essential components of MQ assessment. A scientific interpretation of MQ score is part of an MQ assessment system as it will help an individual to improve his MQ. IQ (intelligence quotient) and EQ (emotional quotient) and their test have been studied intensively. We argue that IQ and EQ study alone is not sufficient for an individual’s all round development. The significance of MQ study is that it offsets IQ and EQ study. MQ reflects an individual’s mental level as well as bodily level of intelligence in physical activities. It is well-known that the American Springfield College seal includes the Luther Gulick triangle with the words “spirit,” “mind,” and “body” written within it. MQ, together with IQ and EQ, echoes this education philosophy. Since its inception in 2012, the MQ research has spread rapidly in China. By now, six prestigious universities in China have established research centers on MQ and its assessment.

Keywords: motional Intelligence, motional quotient, multiple intelligence, motor intelligence, all round development

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Authors: Jarmila Štěpánová, Martin Kudláček, Lukáš Jakubec

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The people with spinal cord injury are one of the least sport active members of our society. Their hypoactivity is determined by primary injury, i.e., the loss of motor function, the injured part of the body is connected with health complications and social handicap. Study performs one part of the standardization process of semi-structured interview PARA-SCI.CZ (Czech version of the Physical Activity Recall Assessment for People with Spinal Cord Injury), which measures the type, frequency, duration, and intensity of physical activity of people with spinal cord injury. The study focused on persons with paraplegia who use a wheelchair as their primary mode of mobility. The aim of this study was to perform a process to determine the criterion validity of PARA-SCI.CZ. The actual physical activity of wheelchair users was monitored during three days by using accelerometers Actigraph GT3X fixed on the non-dominant wrist, and semi-structured interview PARA-SCI.CZ. During the PARA-SCI.CZ interview, participants were asked to recall activities they had done over the past 3 days, starting with the previous day. PARA-SCI.CZ captured frequency, duration, and intensity (low, moderate, and heavy) of two categories of physical activity (leisure time physical activity and activities of a usual day). Accelerometer Actigraph GT3X captured duration and intensity (low and moderate + heavy) of physical activity during three days and nights. The study presented three potential recalculations of measured data. Standardization process of PARA-SCI.CZ is essential to critically approach issues of health and active lifestyle of persons with spinal cord injury in the Czech Republic. Standardized PARA-SCI.CZ can be used in practice by physiotherapists and sports pedagogues from the field of adapted physical activities.

Keywords: physical activity, lifestyle, paraplegia, semi-structure interview, accelerometer

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Authors: Purnima K Bajre, Rujula Talloo

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A variety of vehicles are driven on roads such as private vehicles, commercial vehicles, public vehicles, and emergency service vehicles (EMV). Drivers driving different vehicles can have attitude differences towards emergency service vehicles which in turn affects their likelihood to give way to them. The present review aims to understand the factors that mediate this yielding behavior of drivers towards EMVs. Through extensive review of available literature, factors such as effects of lights and sirens, cognitive load, age of the driver, driving general experience, traffic load, drivers’ experience and training with EMVs and drivers’ attitude towards EMV drivers, have emerged as mediating factors. Whereas cognitive load is the most researched area and is observed to be associated negatively with on road drivers’ attitudes towards EMVs, there is a paucity of research to understand the relationships between empathy, pro-social skills, and on road drivers’ attitude towards EMVs.

Keywords: cognitive load, emergency service vehicle, empathy, traffic load

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Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau, Dong Hun Kwak, Nicolae-Alexandru Colceriu

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Background: Stress management (SM) is a topic of great academic interest and equally a task to accomplish. In addition, it is recognized the beneficial role of unconventional therapies (UCT) in stress modulation. Aims: The aim was to evaluate medical (MS) versus non-medical students’ (NMS) opinions about academic stress management (ASM) using UCT. Methods: MS (n=103, third year males and females) and NMS (n=112, males and females, from humanities faculties, different years of study), out of their academic program, voluntarily answered to a questionnaire concerning: a) Classification of the four most important academic stress factors; b) The extent to which their daily life influences academic stress; c) The most important SM methods they know; d) Which of these methods they are applying; e) the UCT they know or about which they have heard; f) Which of these they know to have stress modulation effects; g) Which of these UCT, participants are using or would like to use for modulating stress; and if participants use UTC for their own choose or following a specialist consultation in those therapies (SCT); h) If they heard about the following UCT and what opinion they have (using visual analogue scale) about their use (following CST) for the ASM: Phytotherapy (PT), apitherapy (AT), homeopathy (H), ayurvedic medicine (AM), traditional Chinese medicine (TCM), music therapy (MT), color therapy (CT), forest therapy (FT). Results: Among the four most important academic stress factors, for MS more than for NMS, are: busy schedule, large amount of information taught; high level of performance required, reduced time for relaxing. The most important methods for SM that MS and NMS know, hierarchically are: listen to music, meeting friends, playing sport, hiking, sleep, regularly breaks, seeing positive side, faith; of which, NMS more than MS, are partially applying to themselves. UCT about which MS and less NMS have heard, are phytotherapy, apitherapy, acupuncture, reiki. Of these UTC, participants know to have stress modulation effects: some plants, bee’s products and music; they use or would like to use for ASM (the majority without SCT) certain teas, honey and music. Most of MS and only some NMS heard about PT, AT, TCM, MT and much less about H, AM, CT, TT. NMS more than MS, would use these UCT, following CST. Conclusions: 1) Academic stress is similarly reflected in MS and NMS opinions. 2) MS and NMS apply similar but very few UCT for stress modulation. 3) Information that MS and NMS have about UCT and their ASM application is reduced. 4) It is remarkable that MS and especially NMS, are open to UCT use for ASM, following an SCT.

Keywords: academic stress, stress management, stress modulation, medical students, non-medical students, unconventional therapies

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Authors: Mohaned G. Abed

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Attention Deficit Hyperactivity Disorder (ADHD) is considered one of the most frequently diagnosed psychiatric childhood disorders. It has an effect on 3–5% of school-aged children, and brings about difficulties in academic and social interaction. This study explored the knowledge and beliefs of parents in Saudi Arabia about children with ADHD. The Knowledge about Attention Deficit Disorder Questionnaire (KADD-Q) was administered to a sample of parents, followed by interviews with a subset of the total respondents. The results indicated that the parents knew more about the characteristics of ADHD than they knew about its related causes and treatment. Overall, the findings indicated that these parents had some knowledge about general characteristics of ADHD, but they had little understanding of causes and possible interventions. These results suggest an important need for more formal parents training regarding all aspects of ADHD in school age children.

Keywords: attention deficit hyperactivity disorder, childhood disorders, school-aged children, difficulties in academic, social interaction

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: Ilja Käch, Abdul R. Jandali, Nadja Zechmann-Müller

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Introduction: We discuss the treatment of two young male patients suffering from scaphoid non-union after a traumatic scaphoid fracture. The currently propagated techniques for treating a scaphoid non-union in children are either the operative reconstruction of the scaphoid or the conservative treatment with splinting in a scaphoid cast. Cases: In the first case, we operated on a 13 years old male patient with a posttraumatic scaphoid non-union in the middle third with a humpback deformity. We resected the middle third of the scaphoid and grafted the defect with an iliac crest bone, and the DISI-Deformity was reduced. Fixation was performed with K-Wires and immobilisation in a scaphoid cast. In the second case a 13 years old male patient also with a posttraumatic scaphoid non-union in the middle third and humpback deformity, DISI-deformity, was treated conservatively. Immobilisation in a scaphoid cast for four months was performed. Results: Operative: One year postoperatively the patient achieved a painless free arc of motion. Flexion/Extension 70/0/60°, Radial-/Ulnarduction 30/0/30° and Pro-/Supination 90/0/90°. The computer tomogram showed complete consolidation and bony fusion of the iliac crest bone. Conservative: Six to eight months after conservative treatment the patient demonstrated painless motion and AROM Flexion/Extension 80/0/80°, Radial-/Ulnarduction and Pro-/Supination in maximum range. Complete consolidation in the computer tomogram with persistent humpback- and DISI deformity. Conclusion: In the literature, both techniques are described, either the operative scaphoid reconstruction or the conservative treatment with splinting. In our cases, both the operative and conservative treatments showed comparable good results. However, the humpback- and DISI deformity can only be addressed with a surgical approach.

Keywords: scaphoid, non-union, trauma, operative vs. non operative

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Authors: W. R. M. Shehani Shanika

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Selling goods and services using images, names and personalities of celebrities has become a common marketing strategy identified in modern physical and online markets. Two concepts called globalization and open economy have given numerous reasons to develop businesses to earn higher profits. Therefore, global market plus domestic markets in various countries have vigorously endorsing images of famous sport stars, film stars, singing stars and cartoon characters for the purpose of increasing demand for goods and services rendered by them. It has been evident that these trade strategies have become a threat to famous personalities in financially and personally. Right to the image is a basic human right which celebrities owned to avoid themselves from various commercial exploitations. In this respect, this paper aims to assess whether the law relating to character merchandising satisfactorily protects right to image of celebrities. However, celebrities can decide how much they receive for each representation to the general public. Simply they have exclusive right to decide monetary value for their image. But most commonly every country uses law relating to unfair competition to regulate matters arise thereof. Legal norms in unfair competition are not enough to protect image of celebrities. Therefore, celebrities must be able to avoid unauthorized use of their images for commercial purposes by fraudulent traders and getting unjustly enriched, as their images have economic value. They have the right for use their image for any commercial purpose and earn profits. Therefore it is high time to recognize right to image as a new dimension to be protected in the legal framework of character merchandising. Unfortunately, to the author’s best knowledge there are no any uniform, single international standard which recognizes right to the image of celebrities in the context of character merchandising. The paper identifies it as a controversial legal barrier faced by celebrities in the rapidly evolving marketplace. Finally, this library-based research concludes with proposals to ensure the right to image more broadly in the legal context of character merchandising.

Keywords: brand endorsement, celebrity, character merchandising, intellectual property rights, right to image, unfair competition

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Authors: Evgeny A. Rybakov, Dmitry P. Starikov

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This article contains information about creating special unit for scanning 3D objects different nature, different materials, for example plastic, plaster, cardboard, wood, metal and etc. The main part of the unit is infrared transducer, which is sends the wave to the object and receive back wave for calculating distance. After that, microcontroller send to PC data, and computer program create model for printing from the plastic, gypsum, brass, etc.

Keywords: clutch, infrared, microcontroller, plastic, shaft, stage

Procedia PDF Downloads 443