Search results for: computer aided sport training

Authors: Li Hui, Riyadh Hindi

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Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

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Authors: Kaori Narita, Juan de Dios Tena Horrillo, Claudio Detotto

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Decisions on replacement of leaders are of significance and high prevalence in any organization, and concerns many of its stakeholders, whether it is a leader in a political party or a CEO of a firm, as indicated by high media coverage of such events. This merits an investigation into the consequences and implications of a leadership change on the performances and behavior of organizations and their workers. Sport economics provides a fruitful field to explore these issues due to the high frequencies of managerial changes in professional sports clubs and the transparency and regularity of observations of team performance and players’ abilities. Much of the existing research on managerial change focuses on how this affects the performance of an organization. However, there is scarcely attention paid to the consequences of such events on the behavior of individuals within the organization. Changes in behavior and attitudes of a group of workers due to a managerial change could be of great interest in management science, psychology, and operational research. On the other hand, these changes cannot be observed in the final outcome of the organization, as this is affected by many other unobserved shocks, for example, the stress level of workers with the need to deal with a difficult situation. To fill this gap, this study shows the first attempt to evaluate the impact of managerial change on players’ behaviors such as attack intensity, aggressiveness, and efforts. The data used in this study is from the top tier Italian football league (“Serie A”), where an average of 13 within season replacements of head coaches were observed over the period of seasons from 2000/2001 to 2017/18. The preliminary estimation employs Pooled Ordinary Least Square (POLS) and club-season Fixed Effect (FE) in order to assess the marginal effect of having a new manager on the number of shots, corners and red/yellow cards after controlling for a home-field advantage, ex ante abilities and current positions in the league of a team and their opponent. The results from this preliminary estimation suggest that the teams do not show a significant difference in their behaviors before and after the managerial change. To build on these preliminary results, other methods, including propensity score matching and non-linear model estimates, will be used. Moreover, the study will further investigate these issues by considering other measurements of attack intensity, aggressiveness, and efforts, such as possessions, a number of fouls and the athletic performance of players, respectively. Finally, the study is going to investigate whether these results vary over the characteristics of a new head coach, for example, their age and experience as a manager and a player. Thus far, this study suggests that certain behaviours of individuals in an organisation are not immediately affected by a change in leadership. To confirm this preliminary finding and lead to a more solid conclusion, further investigation will be conducted in the aforementioned manner, and the results will be elaborated in the conference.

Keywords: behaviour, effort, manager characteristics, managerial change, sport economics

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Authors: A. Clementking, C. Jothi Venkateswaran

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Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

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Authors: Shieh Shiow-fang

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Superstitious thoughts or actions often occur during athletic competitions. Often "superstitious rituals" have a positive impact on the performance of competitive athletes. Athletes affirm the many psychological benefits of religious beliefs mostly in a positive way. Method: By snowball sampling, we recruited 10 experienced competitive athletes as participants. We used in-person and online one-to-one in-depth interview to collect their experiences about sport superstition. The total interview time was 795 minutes. We analyzed the raw data with the grounded theory processes suggested by Strauss and Corbin (1990). Results: The factors affecting athlete performance are ritual beliefs, taboo awareness, learning norms, and spontaneous attribution behaviors. Conclusion: We concluded that sports superstition reflects several psychological implications. The analysis results of this paper can provide another research perspective for the future study of sports superstition behavior.

Keywords: superstition, taboo awareness, learning norms, competitive athlete

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Authors: Yulan Wu

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With the rapid development of social media, the issue of fake news has gained considerable prominence, drawing the attention of both the public and governments. The widespread dissemination of false information poses a tangible threat across multiple domains of society, including politics, economy, and health. However, much research has concentrated on supervised training models within specific domains, their effectiveness diminishes when applied to identify fake news across multiple domains. To solve this problem, some approaches based on domain labels have been proposed. By segmenting news to their specific area in advance, judges in the corresponding field may be more accurate on fake news. However, these approaches disregard the fact that news records can pertain to multiple domains, resulting in a significant loss of valuable information. In addition, the datasets used for training must all be domain-labeled, which creates unnecessary complexity. To solve these problems, an unsupervised domain knowledge discovery framework for fake news detection is proposed. Firstly, to effectively retain the multidomain knowledge of the text, a low-dimensional vector for each news text to capture domain embeddings is generated. Subsequently, a feature extraction module utilizing the unsupervisedly discovered domain embeddings is used to extract the comprehensive features of news. Finally, a classifier is employed to determine the authenticity of the news. To verify the proposed framework, a test is conducted on the existing widely used datasets, and the experimental results demonstrate that this method is able to improve the detection performance for fake news across multiple domains. Moreover, even in datasets that lack domain labels, this method can still effectively transfer domain knowledge, which can educe the time consumed by tagging without sacrificing the detection accuracy.

Keywords: fake news, deep learning, natural language processing, multiple domains

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Authors: Mehmet Balci, Sakir Tasdemir, Mustafa Altin, Ozlem Bozok

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Our globalizing world has become almost a small village and everyone can access any information at any time. Everyone lets each other know who does whatever in which place. We can learn which social events occur in which place in the world. From the perspective of education, the course notes that a lecturer use in lessons in a university in any state of America can be examined by a student studying in a city of Africa or the Far East. This dizzying communication we have mentioned happened thanks to fast developments in computer technologies and in parallel with this, internet technology. While these developments in the world, has a very large young population and a rapidly evolving electronic communications infrastructure Turkey has been affected by this situation. Researches has shown that almost all young people in Turkey has an account in a social network. Especially becoming common of mobile devices causes data traffic in social networks to increase. In this study, has been surveyed on students in the different age groups and at the Selcuk University Vocational School of Technical Sciences Department of Computer Technology. Student’s opinions about the use of internet and social media has been gotten. Using the Internet and social media skills, purposes, operating frequency, access facilities and tools, social life and effects on vocational education etc. have been explored. Both internet and use of social media positive and negative effects on this department students results have been obtained by the obtained findings evaluating from various aspects. Relations and differences have been found out with statistic.

Keywords: computer technologies, internet use, social network, higher vocational school

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Mohanad Moustafa, Julia Sieberer, Rhys Davies

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Background: Orbital compartment syndrome (OCS) is a sight-threatening Ophthalmologic emergency caused by rapidly increasing intraorbital pressure. It is usually caused by a retrobulbar hemorrhage as a result of trauma. If not treated in a timely manner, permanent vision loss can occur. Lateral canthotomy and cantholysis are minor procedures that can be performed bedside with equipment available in the emergency department. The aim of the procedure is to release the attachments between the suspensory ligaments of the eye and the bony orbital wall, leading to a decrease in intraorbital pressure and preventing irreversible loss of vision. As most Ophthalmologists across the UK provide non-resident on-call service, this may lead to a delay in the treatment of OCS and stresses the need for Emergency medical staff to be able to provide this sight-saving procedure independently. Aim: To survey current training, experience, and confidence levels among Emergency Medicine doctors in performing emergency lateral canthotomy and to establish whether these variables change the following teaching from experienced ophthalmologists. RESULTS: Most EM registrars had little to no experience in performing lateral canthotomy and cantholysis. The majority of them showed a significant increase in their confidence to perform the procedure following ophthalmic-led teaching. The survey also showed that the registrars felt such training should be added to/part of the EM curriculum. Conclusion: The involvement of Ophthalmologists in the teaching of EM doctors to recognise and treat OCS independently may prevent delays in treatment and reduce the risk of permanent sight loss. This project showed potential in improving patient care and will lead to a National Survey of EM doctors across the UK.

Keywords: lateral canthotomy, retrobulbar hemorrhage, Ophthalmology, orbital compartment syndrome, sight loss, blindness

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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Authors: Ravi Vishwanath, Saumya Kumaar, S. N. Omkar

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Brain-computer interfacing (BCI) is a technology that is almost four decades old, and it was developed solely for the purpose of developing and enhancing the impact of neuroprosthetics. However, in the recent times, with the commercialization of non-invasive electroencephalogram (EEG) headsets, the technology has seen a wide variety of applications like home automation, wheelchair control, vehicle steering, etc. One of the latest developed applications is the mind-controlled quadrotor unmanned aerial vehicle. These applications, however, do not require a very high-speed response and give satisfactory results when standard classification methods like Support Vector Machine (SVM) and Multi-Layer Perceptron (MLPC). Issues are faced when there is a requirement for high-speed control in the case of fixed-wing unmanned aerial vehicles where such methods are rendered unreliable due to the low speed of classification. Such an application requires the system to classify data at high speeds in order to retain the controllability of the vehicle. This paper proposes a novel method of classification which uses a combination of Common Spatial Paradigm and Linear Discriminant Analysis that provides an improved classification accuracy in real time. A non-linear SVM based classification technique has also been discussed. Further, this paper discusses the implementation of the proposed method on a fixed-wing and VTOL unmanned aerial vehicles.

Keywords: brain-computer interface, classification, machine learning, unmanned aerial vehicles

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Authors: Shaista Meghani, Rozina Karmaliani, Khairulnissa Ajani, Shireen Shahzad, Nadeem Ullah Khan

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Background: The concept of Family Presence During Resuscitation (FPDR) is gradually gaining recognition in western countries, however, it is rarely considered in South Asian countries including Pakistan. Over time, patients’ and families’ rights have gained recognition and healthcare has progressed to become more patient-family centered. Objectives: The objective of this study was to evaluate the impact of an educational program on the Knowledge, Attitude, and Practices (KAP) of healthcare professionals (HCPs) towards FPDR in Emergency Department (ED), at a tertiary care setting, in Karachi, Pakistan. Methods: This was a Pre-test and Post-test study design. A convenient universal sampling was done, and all ED nurses and physicians with more than one year of experience were eligible. The intervention included one-hour training sessions for physicians (three sessions) and nurses (eight sessions), The KAP of nurses and physicians were assessed immediately after (post-test I), and two weeks(post-test II) after the intervention using a pretested questionnaire. Results: The findings of the study revealed that the mean scores of knowledge and attitude of HCPs at both time points were statistically significant (p-value=<0.001), however, an insignificant difference was found on practice of FPDR (p-value=>0.05). Conclusion: The study findings recommend that the educational program on FPDR for HCPs needs to be offered on an ongoing basis. Moreover, training modules need to be developed for the staff, and formal guidelines need to be proposed for FPDR, through a multidisciplinary team approach.

Keywords: family presence, cardiopulmonary resuscitation, attitude, education, practices, health care professionals

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Authors: L. K. Nivedha, V. Maruthapandian, R. Kothandaraman

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Rechargeable zinc-air batteries (ZAB) are gaining significant research attention owing to their high energy density and copious zinc resources worldwide. However, the unsolved obstacles such as dendrites, passivation, depth of discharge and the lack of an efficient cathode catalyst restrict their practical application1. By and large, non-noble transition metal-based catalysts are well-reputed materials for catalysing oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) with greater stability in alkaline medium2. Herein, we report the synthesis and application of Mn₃O4-NiFeLDH/Carbon composite as a cathode catalyst for rechargeable ZAB. The synergetic effects of the mixed transition metals (Mn/Ni/Fe) have aided in catalysing ORR and OER in alkaline electrolyte with a shallow potential gap of 0.7 V. The composite, by its distinctive physicochemical characteristics, shows an excellent OER activity with a current density of 1.5 mA cm⁻² at a potential of 1.6 V and a superior ORR activity with an onset potential of 0.8 V when compared with their counterparts. Nevertheless, the catalyst prefers a two-electron pathway for the electrochemical reduction of oxygen which results in a limiting current density of 2.5 mA cm⁻². The bifunctional activity of the Mn₃O₄-NiFeLDH/Carbon composite was utilized in developing rechargeable ZAB. The fully fabricated ZAB delivers an open circuit voltage of 1.4 V, a peak power density of 70 mW cm⁻², and a specific capacity of 800 mAh g⁻¹ at a current density of 20 mA cm⁻² with an average discharge voltage of 1 V and the cell is operable upto 50 mA cm-2. Rechargeable ZAB demonstrated over 110 h at 10 mA cm⁻². Further, the cause for the diminished charge-discharge performance experienced beyond the 100th cycle was investigated, and carbon corrosion was testified using Infrared spectroscopy.

Keywords: rechargeable zinc-air battery, oxygen evolution reaction, bifunctional catalyst, alkaline medium

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Authors: Samuel Oye Bandele

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A policy is a system of principles to guide activities and strategic decisions of an organisation in order to achieve stated objectives and meeting expected outcomes. A Computer Based Test (CBT) policy is therefore a statement of intent to drive the CBT programmes, and should be implemented as a procedure or protocol. Policies are hence generally adopted by an organization or a nation. The concern here, in this paper, is the consideration and analysis of issues that are significant to evolving the acceptable policy that will drive the new CBT innovation in Nigeria. Public examinations and internal examinations in higher educational institutions in Nigeria are gradually making a radical shift from Paper Based or Paper-Pencil to Computer-Based Testing. The need to make an objective and empirical analysis of Policy issues relating to CBT became expedient. The following are some of the issues on CBT evolution in Nigeria that were identified as requiring policy backing. Prominent among them are requirements for establishing CBT centres, purpose of CBT, types and acquisition of CBT equipment, qualifications of staff: professional, technical and regular, security plans and curbing of cheating during examinations, among others. The descriptive research design was employed based on a population consisting of Principal Officers (Policymakers), Staff (Teaching and non-Teaching-Policy implementors), and CBT staff ( Technical and Professional- Policy supports) and candidates (internal and external). A fifty-item researcher-constructed questionnaire on policy issues was employed to collect data from 600 subjects drawn from higher institutions in South West Nigeria, using the purposive and stratified random sampling techniques. Data collected were analysed using descriptive (frequency counts, means and standard deviation) and inferential (t-test, ANOVA, regression and Factor analysis) techniques. Findings from this study showed, among others, that the factor loadings had significantly weights on the organizational and National policy issues on CBT innovation in Nigeria.

Keywords: computer-based testing, examination, innovation, paper-based testing, paper pencil based testing, policy issues

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Authors: Mohamed A. Abdelnaby

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Relevance of the research: A few people known about Autism and also about Sports for Autism. Children with Autism have difficult experience with sport that makes many problems during the sports activities. There are several areas of motor skills development essential for participating daily life and several sports activities. The object of the research is describe the program for the sports activities for children with Autism, and the aim is to improving their movement skills, motor skills and social skills. Research methods and organization: Twenty-five children with Autism perceived barriers to sports activities participation, and functioning. All the program inside the Pegasus Dreamland Sports Club and all the facilities available for the research. Results and discussion: Standard, children were reported to meet or exceeded general PA occurrence guidelines, belonged to active participated in a variety of sports activities. We identified several barriers to optimal sports activities for their children. Conclusions: Children with Autism can achieve optimal sports activities. Exposure to a variety of sports activities opportunities and experiences aids in identifying the model activity for each individual child.

Keywords: autism, sports activates, movement skills, motor skills

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Authors: Boularas El-Alia, Arbi Raja, Bachir Bouiadjra Sara, Rezk-Kallah Haciba, Rezkkallah Baghdad

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Objectives : To determine the handling practices of cytotoxic drugs and to describe clinical manifestations expressed by hospital personnel of Sidi Bel Abbes during the year 2014. Methods: Sectional descriptive study conducted in 3 center university hospital units (Hematology, Oncology and Urology) and Gynecology of EHS Sidi Bel Abbes. A questionnaire was administered to hospital workers regulary exposed to cytotoxic drugs. A work-place visit was performed to have an overview about working conditions. The Cytotoxic Contact Index (CCI) was calculated for each nurse on a period of 15 working days. Treatment of the results was done using SPSS software. Results: The survey reveals that 22 men and 58 women are exposed to cytotoxic drugs for an average of 7 years. Many symptoms such as ocular irritation (38,75%), throat irritation (56,25%), headache (68,75%), dizziness (43,75%), nausea (37,5%), metallic taste (30%), were reported with high frequency. Are noted in the offspring, 3 congenital anomalies,2 diaphragmatic hernia and a cleft palate. The Cytotoxic Contact Index (CCI) was higher than 3 among Oncology nurses and higher than 1 for most of the nurses of Hematology and Gynecology service. The wearing of personal protective clothing was not respected by all workers: (22/23) wear gloves and (20/23) wear a mask,(5/23) wear a cap, (2/23) wear glasses. Only 3 nurses have benefited from continuous training on handling cytotoxic drugs. Conclusion: This study shows a high occupational exposure risk to cytotoxic drugs among persons handling these drugs and the necessity to apply rigorously all measures related to personal protection awareness and training of personnel to minimize these exposure.

Keywords: cytotoxic drugs, handling, clinical manifestations, hospital staff

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Authors: Areti Okalidou, Paul D. Hatzigiannakoglou, Aikaterini Vatou, George Kyriafinis

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Young children are nowadays adept at using technology. Hence, computer-based auditory training programs (CBATPs) have become increasingly popular in aural rehabilitation for children with hearing loss and/or with cochlear implants (CI). Yet, their clinical utility for prognostic, diagnostic, and monitoring purposes has not been explored. The purposes of the study were: a) to develop an updated version of the auditory rehabilitation tool for Greek-speaking children with cochlear implants, b) to develop a database for behavioral responses, and c) to compare accuracy rates and reaction times in children differing in hearing status and other medical and demographic characteristics, in order to assess the tool’s clinical utility in prognosis, diagnosis, and progress monitoring. The updated version of the auditory rehabilitation tool was developed on a tablet, retaining the User-Centered Design approach and the elements of the Virtual Reality (VR) serious game. The visual stimuli were farm animals acting in simple game scenarios designed to trigger children’s responses to animal sounds, names, and relevant sentences. Based on an extended version of Erber’s auditory development model, the VR game consisted of six stages, i.e., sound detection, sound discrimination, word discrimination, identification, comprehension of words in a carrier phrase, and comprehension of sentences. A familiarization stage (learning) was set prior to the game. Children’s tactile responses were recorded as correct, false, or impulsive, following a child-dependent set up of a valid delay time after stimulus offset for valid responses. Reaction times were also recorded, and the database was in Εxcel format. The tablet version of the auditory rehabilitation tool was piloted in 22 preschool children with Νormal Ηearing (ΝΗ), which led to improvements. The study took place in clinical settings or at children’s homes. Fifteen children with CI, aged 5;7-12;3 years with post-implantation 0;11-5;1 years used the auditory rehabilitation tool. Eight children with CI were monolingual, two were bilingual and five had additional disabilities. The control groups consisted of 13 children with ΝΗ, aged 2;6-9;11 years. A comparison of both accuracy rates, as percent correct, and reaction times (in sec) was made at each stage, across hearing status, age, and also, within the CI group, based on presence of additional disability and bilingualism. Both monolingual Greek-speaking children with CI with no additional disabilities and hearing peers showed high accuracy rates at all stages, with performances falling above the 3rd quartile. However, children with normal hearing scored higher than the children with CI, especially in the detection and word discrimination tasks. The reaction time differences between the two groups decreased in language-based tasks. Results for children with CI with additional disability or bilingualism varied. Finally, older children scored higher than younger ones in both groups (CI, NH), but larger differences occurred in children with CI. The interactions between familiarization of the software, age, hearing status and demographic characteristics are discussed. Overall, the VR game is a promising tool for tracking the development of auditory skills, as it provides multi-level longitudinal empirical data. Acknowledgment: This work is part of a project that has received funding from the Research Committee of the University of Macedonia under the Basic Research 2020-21 funding programme.

Keywords: VR serious games, auditory rehabilitation, auditory training, children with cochlear implants

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Authors: Rosina U. Ndukwe, Diane Crone, Nick Cavill

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Active transport (i.e. walking to school, cycle to work schemes etc.) is an effective approach with multiple social and environmental benefits for transforming urban environments into active urban environments. Although walking and cycling often remain on the margins of urban planning and infrastructure, there are new approaches emerging, along with policy intervention relevant for the creation of sustainable urban active environments conductive to active travel, increasing physical activity levels of involved communities and supporting social inclusion through more active participation. SPAcE - Supporting Policy and Action for Active Environments is a 3 year Erasmus+ project that aims to integrate active transport programmes into public policy across the EU. SPAcE focuses on cities/towns with recorded low physical activity levels to support the development of active environments in 5 sites: Latvia [Tukums], Italy [Palermo], Romania [Brasov], Spain [Castilla-La Mancha] and Greece [Trikala]. The first part of the project involved a review of good practice including case studies from across the EU and project partner countries. This has resulted in the first output from the project, an evidence of good practice summary with case study examples. In the second part of the project, working groups across the 5 sites have carried out co-production to develop Urban Active Environments (UActivE) Action Plans aimed at influencing policy and practice for increasing physical activity primarily through the use of cycling and walking. Action plans are based on international evidence and guidance for healthy urban planning. Remaining project partners include Universities (Gloucestershire, Oxford, Zurich, Thessaly) and Fit for Life programme (National physical activity promotion program, Finland) who provide support and advice incorporating current evidence, healthy urban planning and mentoring. Cooperation and co-production with public health professionals, local government officers, education authorities and transport agencies has been a key approach of the project. The third stage of the project has involved training partners in the WHO HEAT tool to support the implementation of the Action Plans. Project results show how multi-agency, transnational collaboration can produce real-life Action Plans in five EU countries, based on published evidence, real-life experience, consultation and collaborative working with other organisations across the EU. Learning from the processes adopted within this project will demonstrate how public health, local government and transport agencies across the EU, can work together to create healthy environments that have the aim of facilitating active behaviour, even in times of constrained public budgets. The SPAcE project has captured both the challenges and solutions for increasing population physical activity levels, health and wellness in urban spaces and translating evidence into policy and practice ensuring innovation at policy level. Funding acknowledgment: SPAcE (www.activeenvironments.eu) is co-funded by the Sport action of the ERASMUS+ programme.

Keywords: action plans, active transport, SPAcE, UActivE urban active environments, walking and cycling

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Authors: M. Ashadur Rahman

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This study presents the psychological status of basketball and volleyball sportspersons of Bangladesh Krira Shikkha Protifsthan (BKSP) in Bangladesh. The subjects of the study were 34 sportspersons which were 20 Basketball and 14 Volleyball Sportspersons in BKSP. The age ranges of the subjects were 15 to 20 years. The subjects were all male sportspersons and regular students of BKSP. Anxiety control, concentration, confidence, mental preparation, and motivation were selected as psychological variables. Psychological Skill Inventory for Sport (PST) prepared by Mahoney Gabiel, Perking (1987) was used to assess the psychological skills of sportspersons to different sports. Mean standard deviation and independent t-test were used to analyze the data, and level of significance was set at 0.05. Significant differences were not found between psychological status between basketball and volleyball sportspersons of BKSP in Bangladesh.

Keywords: psychological variable, anxiety control, concentration, confidence, mental preparation, motivation

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Authors: Bintou Jobe

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Musculo-skeletal disorders (MSDs) are injuries or disorders of the spine disc, muscle strains, and low back injuries. It remains a major cause of occupational illness. Findings: Due to poor grips during handling, it is possible for neck, shoulder, arm, knees, ankle, fingers, waist, lower back injuries, and other muscle joints to be affected. Pregnant women are more prone to physical and hormonal changes, which lead to the relaxation of supporting ligaments. MSD continues to pose a global concern due to its impact on workers worldwide. The prevalence of the disorder is high, according to research into the workforce in Europe and developing countries. The causes are characterized by long working hours, insufficient rest breaks, poor posture, repetitive motion, poor manual handling techniques, psychological stress, and poor nutrition. To prevent MSD, the design mainly involves avoiding and assessing the risk. However, clinical solutions, policy governance, and minimizing manual labour are also an alternative. In addition, eating a balanced diet and teamwork force are key to elements in minimising the risk. This review aims to raise awareness and promote cost effectiveness prevention and understanding of MSD through research and identify proposed solutions to recognise the underlying causes of MSDs in the construction sectors. The methodology involves a literature review approach, engaging with the policy landscape of MSD, synthesising publications on MSD and a wider range of academic publications. In conclusion, training on effective manual handling techniques should be considered, and Personal Protective Equipment should be a last resort. The implementation of training guidelines has yielded significant benefits.

Keywords: musculoskeletal disorder work related, MSD, manual handling, work hazards

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Authors: Caiwei Zhu, Remke Klapwijk

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Spatial thinking, a way of thinking based on the understanding and reasoning of spatial concepts and representations, is embedded in science, technology, engineering, arts, and mathematics (STEAM) learning. Aside from many studies that successfully used targeted training to improve students’ spatial thinking skills, few have closely examined how spatial thinking can be trained in classroom settings. Design and technology education, which receives increasing attention towards its integration into formal curriculums, inherently encompasses a wide range of spatial activities, such as constructing mental representations of design ideas, mentally transforming objects and materials to form designs, visually communicating design plans through annotated drawings, and creating 2D and 3D design artifacts. Among different design topics, biomimicry offers a unique avenue for students to recognize and analyze the shapes and structures in nature. By mapping the forms of plants and animals onto functions, students gain inspiration to solve human design challenges. This study is one of the first to highlight opportunities for training spatial thinking in a biomimicry design project for primary school students. Embracing methodological principles of educational design-based research, this case study is conducted along with iterations in the design of the intervention and collaboration with teachers. Data are harvested from small groups of 10- to 12-year-olds at an international school in the Netherlands. Classroom videos, semi-structured interviews with students, design drawings and artifacts, formative assessment, and the pre- and post-intervention spatial test triangulate evidence for students' spatial thinking. In addition to contributing to a theory of integrating spatial thinking in the primary curriculum, mechanisms underlying such improvement in spatial thinking are explored and discussed.

Keywords: biomimicry, design and technology education, primary education, spatial thinking

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Authors: Ange Meghane Hakizimana, Landry Ndikuriyo

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Retention of employees in the hospitality industry is a recurrent agenda in the organization involving all the combined efforts to maintain the best available laborer. The general objective of this research is to assess the impact of effective employee retention strategies on the success of the hotel industry at Galileo Hotel, Huye District in Rwanda, for the period of 2019-2021. Herzberg Two Factor Theory and Equity Theory were used. The study adopted a descriptive research design. Descriptive research design allowed us to study the elements in their natural form without making any alterations to them. Secondary data and primary data and the data collected were sorted and entered into the statistical packages for social sciences for analysis (SPSS) version 26. Frequencies, descriptive statistics and percentages were used to analyze and establish extent to which employee retention strategies impact the success of the hotel industry of Rwanda and this was analyzed using regression and correlation analysis. The results revealed that employee training and development had an influence of 24.8% on the success of the hotel industry in Rwanda. According to the results of our study, the employee reward system contributes 20.7% to the success of the hotel industry in Rwanda, the value of t is 3.475 and this is greater than the standard t value score of 1.96, p-value is 0.002. Therefore the employee reward system has a great positive impact on the success of the hotel industry in Rwanda. The results also show that 15.7% of the success of the hospitality industry in Rwanda is due to the work environment of employees. With a t-value of 4.384 and a p-value of 0.000, the above statistics show a positive impact of the employees' working environment on success of the hospitality industry in Rwanda. A priority to the retention of their employees should be given by the hotel industry and its managers because it has already been proven that it is an effective approach to offering good customer service. In addition, employee retention reduces expenses associated with employee recruitment and turnover.

Keywords: success, hotel industry, training and development, employee reward system, employee work environment

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Authors: Matthew Korey, Jeffrey Youngblood, John Howarter

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Background and Significance: Tannic acid (TA) is a bio-based high molecular weight organic, aromatic molecule that has been found to increase thermal stability and flame retardancy of many polymer matrices when used as an additive. Although it is biologically sourced, TA is a pollutant in industrial wastewater streams, and there is a desire to find applications in which to downcycle this molecule after extraction from these streams. Additionally, epoxy thermosets have revolutionized many industries, but are too flammable to be used in many applications without additives which augment their flame retardancy (FR). Many flame retardants used in epoxy thermosets are synthesized from petroleum-based monomers leading to significant environmental impacts on the industrial scale. Many of these compounds also have significant impacts on human health. Various bio-based modifiers have been developed to improve the FR of the epoxy resin; however, increasing FR of the system without tradeoffs with other properties has proven challenging, especially for TA. Methodologies: In this work, TA was incorporated into the thermoset by use of solvent-exchange using methyl ethyl ketone, a co-solvent for TA, and epoxy resin. Samples were then characterized optically (UV-vis spectroscopy and optical microscopy), thermally (thermogravimetric analysis and differential scanning calorimetry), and for their flame retardancy (mass loss calorimetry). Major Findings: Compared to control samples, all samples were found to have increased thermal stability. Further, the addition of tannic acid to the polymer matrix by the use of solvent greatly increased the compatibility of the additive in epoxy thermosets. By using solvent-exchange, the highest loading level of TA found in literature was achieved in this work (40 wt%). Conclusions: The use of solvent-exchange shows promises for circumventing the limitations of TA in epoxy.

Keywords: sustainable, flame retardant, epoxy, tannic acid

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Authors: Aleš Kratochvíl, Svatomír Slavík

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The paper presents an aircraft flutter suppression by active damping of supplementary control surface at trailing edge. The mathematical model of thin oscillation airfoil with control surface driven by pilot is developed. The supplementary control surface driven by control law is added. Active damping of flutter by several control law is present. The structural model of tailplane with an aerodynamic strip theory based on the airfoil model is developed by a finite element method. The optimization process of stiffens parameters is carried out to match the structural model with results from a ground vibration test of a small sport airplane. The implementation of supplementary control surface driven by control law is present. The active damping of tailplane model is shown.

Keywords: active damping, finite element method, flutter, tailplane model

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Authors: Mounir Adal, Baalal Azeddine, Afifi Moulay Larbi

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Numerical analysis is a branch of mathematics devoted to the development of iterative matrix calculation techniques. We are searching for operations optimization as objective to calculate and solve systems of equations of order n with time and energy saving for computers that are conducted to calculate and analyze big data by solving matrix equations. Furthermore, this scientific discipline is producing results with a margin of error of approximation called rates. Thus, the results obtained from the numerical analysis techniques that are held on computer software such as MATLAB or Simulink offers a preliminary diagnosis of the situation of the environment or space targets. By this we can offer technical procedures needed for engineering or scientific studies exploitable by engineers for water.

Keywords: numerical analysis methods, obstacles solving, engineering, simulation, numerical modeling, iteration, computer, MATLAB, water, underground, velocity

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Authors: Rishabh Nagpal, Riya Uchagaonkar, Venkata Naga Narasimha Ashish Mernedi, Ahmed Hambaba

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The rapid evolution of technology in the communication sector continually seeks to bridge the gap between different communities, notably between the deaf community and the hearing world. This project develops a comprehensive American Sign Language (ASL) recognition system, leveraging the advanced capabilities of convolutional neural networks (CNNs) and vision transformers (ViTs) to interpret and translate ASL in real-time. The primary objective of this system is to provide an effective communication tool that enables seamless interaction through accurate sign language interpretation. The architecture of the proposed system integrates dual networks -VGG16 for precise spatial feature extraction and vision transformers for contextual understanding of the sign language gestures. The system processes live input, extracting critical features through these sophisticated neural network models, and combines them to enhance gesture recognition accuracy. This integration facilitates a robust understanding of ASL by capturing detailed nuances and broader gesture dynamics. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing diverse ASL signs, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced ASL recognition system and lays the groundwork for future innovations in assistive communication technologies.

Keywords: sign language, computer vision, vision transformer, VGG16, CNN

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Authors: N. Paparisteidi, D. Rodamitou

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This article focuses on the skills development and path planning of students studying computer science in EPITECH: french private institute of Higher Education. The researchers examine students’ points of view and experience in a blended learning model based on a skills development curriculum. The study is based on the collection of four main categories of data: semi-participant observation, distribution of questionnaires, interviews, and analysis of internal school databases. The findings seem to indicate that a skills-based program on active learning enables students to develop their learning strategies as well as their personal skills and to actively engage in the creation of their career path and contribute to providing additional information to curricula planners and decision-makers about learning design in higher education.

Keywords: active learning, blended learning, higher education, skills development

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Authors: Saeid Jalilzadeh

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PID controllers are widely used to control the industrial plants because of their robustness and simple structures. Tuning of the controller's parameters to get a desired response is difficult and time consuming. With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameters tuning methods of PID controller have emerged in endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfect as to be expected. Honey Bee algorithm (HBA) and genetic algorithm (GA) are extensively used for real parameter optimization in diverse fields of study. This paper describes an application of HBA and GA to the problem of designing a PID controller whose parameters comprise proportionality constant, integral constant and derivative constant. Presence of three parameters to optimize makes the task of designing a PID controller more challenging than conventional P, PI, and PD controllers design. The suitability of the proposed approach has been demonstrated through computer simulation using MATLAB/SIMULINK.

Keywords: controller, GA, optimization, PID, PSO

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Authors: Jin Koo

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During the coronavirus pandemic, there has been a further increasing demand for computer-based tests (CBT), and now it has become an important test mode. The main purpose of this study is to investigate the comparability of student scores obtained from computerized-based formats of a standardized test in the two subject areas of reading and mathematics. Also, this study investigates whether there is an interaction effect between test modes of CBT and paper-based tests (PBT) and gender/ability level in each subject area. The test used in this study is a multiple-choice standardized test for students in grades 8-11. For this study, data were collected during four test administrations: 2015-16, 2017-18, and 2020-21. This research used a one-factor between-subjects ANOVA to compute the PBT and CBT groups’ test means for each subject area (reading and mathematics). Also, 2-factor between-subjects ANOVAs were conducted to investigate examinee characteristics: gender (male and female), ethnicity (African-American, Asian, Hispanic, multi-racial, and White), and ability level (low, average, and high-ability groups). The author found that students’ test scores in the two subject areas varied across CBT and PBT by gender and ability level, meaning that gender, ethnicity, and ability level were related to the score difference. These results will be discussed according to the current testing systems. In addition, this study’s results will open up to school teachers and test developers the possible influence that gender, ethnicity, and ability level have on a student’s score based on whether they take the CBT or PBT.

Keywords: ability level, computer-based, gender, paper-based, test

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Authors: Jae Soo Do, Kyoung Seok Kim

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Korea baseball experts reckoned Samsung Lions as the best baseball team. It has the unparalleled records of winning first place in the pennant race for five straight years from 2011 to 2015 and winning the Korean series for four years in a row from 2011 to 2014. However, the team made an unbelievably miserable record of ninth place in the pennant race in 2016 and 2017. How come the strong competitive superiority has gone and what kind of slump made the team how it is now. This study investigates this organizational failure case of Samsung Lions, the professional baseball team in Korea. What factors have brought the organizational failure to Samsung Lions? Based on an in-depth examination on how a league-fore-runner drastically lost its competitive superiority, this verifies the necessity of risk management to which common corporations as well as sport teams can be subject at any time in these days.

Keywords: Samsung Lions, organizational failure, baseball, slump

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Authors: Tadewos Awugchew Wudineh

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Health and safety issues have always been a major problem and concern in the building construction industry. The health and safety regulations are stated to eliminate the potential hazards and to reduce the consequential risks. However, the importance of the regulations seems to be overlooked in building construction sites of Hawassa City. Accordingly, many companies don’t follow the regulations as construction workers are more likely to be injured and killed by construction accident than any other type of employment. This paper aimed to identify factors that affect the implementation of construction health and safety regulations, their effects and mitigation measures in building construction project sites of Hawassa City. To reach this objective, a review of literature as well as the Ethiopian construction health and safety regulations have been undertaken. Mainly a five-point Likert scale questionnaire was distributed, and statistical analysis was used to summarize, interpret the data, and to find the significances of the responses. In addition, interviews were carried out. Accordingly, the findings indicate that the top factors which affect the implementation of CHS regulations are, availability and development of a clear health and safety policy, health and safety inspections by top management, conducting health and safety training and orientation, provision of healthy and safe working environment and employment of trained safety officers. The study revealed that implementation or non-implementation of CHS regulations have effects on the worker’s productivity, job satisfaction, rate of accidents, and cost greatly. Thus, the suggestion to minimize the impact on worker’s job performance are, developing of a clear health and safety policy, management commitment towards implementation of health and safety regulations, health and safety education and training and conducting regular health and safety inspections. It was concluded from the study that good implementation of health and safety regulations are the results from administrative and management commitment which calls for more attention to be paid to improve the implementation of CHS regulations in building construction sites of Hawassa City.

Keywords: construction health and safety regulations, effects, factors, mitigation

Procedia PDF Downloads 260