Search results for: disaster training

Authors: Rui Fonseca-Pinto, Emanuel Silva, Rui Rijo, Ricardo Martinho, Bruno Carreira

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The sedentary lifestyle is associated to the development of chronic noncommunicable diseases (obesity, hypertension, Diabetes Mellitus Type 2) and the World Health Organization, given the evidence that physical activity is determinant for individual and collective health, defined the Physical Activity Level (PAL) as a vital signal. Strategies for increasing the practice of physical activity in all age groups have emerged from the various social organizations (municipalities, universities, health organizations, companies, social groups) by increasingly developing innovative strategies to promote motivation strategies and conditions to the practice of physical activity. The adaptation of cities to the new paradigms of sustainable mobility has provided the adaptation of urban training circles and mobilized citizens to combat sedentarism. This adaptation has accompanied the technological evolution and makes possible the use of mobile technology to monitor outdoor training programs and also, through the network connection (IoT), use the training data to make personalized recommendations. This work presents a physical activity counseling platform to be used in the physical maintenance circuits of urban centers, the MOVIDA.polis. The platform consists of a back office for the management of circuits and training stations, and for a mobile application for monitoring the user performance during workouts. Using a QRcode, each training station is recognized by the App and based on the individual performance records (effort perception, heart rate variation) artificial intelligence algorithms are used to make a new personalized recommendation. The results presented in this work were obtained during the proof of concept phase, which was carried out in the PolisLeiria training circuit in the city of Leiria (Portugal). It was possible to verify the increase in adherence to the practice of physical activity, as well as to decrease the interval between training days. Moreover, the AI-based recommendation acts as a partner in the training and an additional challenging factor. The platform is ready to be used by other municipalities in order to reduce the levels of sedentarism and approach the weekly goal of 150 minutes of moderate physical activity. Acknowledgments: This work was supported by Fundação para a Ciência e Tecnologia FCT- Portugal and CENTRO2020 under the scope of MOVIDA project: 02/SAICT/2016 – 23878.

Keywords: physical activity, mHealth, urban training circuits, health promotion

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Authors: Diana Mitova, Krassimir Mitrev

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To prepare the current generation for the future, education systems need to change. It implies a way of learning that meets the demands of the times and the environment in which we live. Productive interaction in the educational process implies an interactive learning environment and the possibility of personal development of learners based on communication and mutual dialogue, cooperation and good partnership in decision-making. Students need not only theoretical knowledge, but transferable skills that will help them to become inventors and entrepreneurs, to implement ideas. STEM education , is now a real necessity for the modern school. Through learning in a "learning company", students master examples from classroom practice, simulate real life situations, group activities and apply basic interactive learning strategies and techniques. The learning company is the subject of this study, reduced to entrepreneurship training in STEM - technologies that encourage students to think outside the traditional box. STEM learning focuses the teacher's efforts on modeling entrepreneurial thinking and behavior in students and helping them solve problems in the world of business and entrepreneurship. Learning based on the implementation of various STEM projects in extracurricular activities, experiential learning, and an interdisciplinary approach are means by which educators better connect the local community and private businesses. Learners learn to be creative, experiment and take risks and work in teams - the leading characteristics of any innovator and future entrepreneur. This article presents some European policies on STEM and entrepreneurship education. It also shares best practices for training company training , with the integration of STEM in the learning company training environment. The main results boil down to identifying some advantages and problems in STEM entrepreneurship education. The benefits of using integrative approaches to teach STEM within a training company are identified, as well as the positive effects of project-based learning in a training company using STEM. Best practices for teaching entrepreneurship through extracurricular activities using STEM within a training company are shared. The following research methods are applied in this research paper: Theoretical and comparative analysis of principles and policies of European Union countries and Bulgaria in the field of entrepreneurship education through a training company. Experiences in entrepreneurship education through extracurricular activities with STEM application within a training company are shared. A questionnaire survey to investigate the motivation of secondary vocational school students to learn entrepreneurship through a training company and their readiness to start their own business after completing their education. Within the framework of learning through a "learning company" with the integration of STEM, the activity of the teacher-facilitator includes the methods: counseling, supervising and advising students during work. The expectation is that students acquire the key competence "initiative and entrepreneurship" and that the cooperation between the vocational education system and the business in Bulgaria is more effective.

Keywords: STEM, entrepreneurship, training company, extracurricular activities

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Authors: Behailu Shigute Habtemariam

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The aim of the study was to examine the effects of training load on some selected fitness performance variables of volleyball players in the case of U-17 female volleyball project players in the central Ethiopia region. Methods: In this study, quasi-experimental design was used. For the purpose of this study, twenty-three volleyball players were used as a subject from the two projects. The data collected through fitness performance assessment were analyzed and interpreted into a meaningful idea using manually as well as with computer in order to compare physical fitness variables and changes observed among participants. Those are taking part in the effects of training load on some selected physical fitness variables. The collected data were analyzed by means of the Statistical Package for Social Science version (SPSS V 20). The independent t-test was used to show the mean differences between the groups, and the paired T-test was used to compare the mean differences of the pre and post-training within each group. The level of significance will be set at Alfa 0.05. Results: The results are displayed using tables and figures. A significant difference was found in the mean differences of pre-test values (19.7 cm) and post-test values (37.5 cm) of the Durame city project on the flexibility test (MD =17.8 cm, P = 0.00). On the other hand, there was a significant difference in the mean difference of pre-test values of (18 cm) and post-test values (26.3 cm) of the Hosana city project on the flexibility test ( MD = 8.3 cm, P = 0.00). Conclusion: According to the results of the present studies, there were significant improvements from pre to post-test at Durame City and Hosana City projects on agility, flexibility, power, and speed fitness tests. On the other hand, a significant difference was not found before beginning the exercise between the two projects; however, a significant difference was found after 12 weeks of training.

Keywords: overload, performance, training, volleyball

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: computer vision, deep learning, object detection, semiconductor

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Authors: Dalia Hanna, Alexander Ferworn

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This research provides detailed proposed training modules for the public safety teams and, specifically, SAR teams responsible for search and rescue operations related to finding lost persons with dementia. Finding a lost person alive is the goal of this training. Time matters if a lost person is to be found alive. Finding lost people living with dementia is quite challenging, as they are unaware they are lost and will not seek help. Even a small contribution to SAR operations could contribute to saving a life. SAR operations will always require expert professional and human volunteers. However, we can reduce their time, save lives, and reduce costs by providing practical training that is based on real-life scenarios. The content for the proposed training is based on the research work done by the researcher in this area. This research has demonstrated that, based on utilizing drones, the algorithmic approach could support a successful search outcome. Understanding the behavior of the lost person, learning where they may be found, predicting their survivability, and automating the search are all contributions of this work, founded in theory and demonstrated in practice. In crisis management, human behavior constitutes a vital aspect in responding to the crisis; the speed and efficiency of the response often get affected by the difficulty of the context of the operation. Therefore, training in this area plays a significant role in preparing the crisis manager to manage the emotional aspects that lead to decision-making in these critical situations. Since it is crucial to gain high-level strategic choices and the ability to apply crisis management procedures, simulation exercises become central in training crisis managers to gain the needed skills to respond critically to these events. The training will enhance the responders’ ability to make decisions and anticipate possible consequences of their actions through flexible and revolutionary reasoning in responding to the crisis efficiently and quickly. As adult learners, search and rescue teams will be approaching training and learning by taking responsibility of the learning process, appreciate flexible learning and as contributors to the teaching and learning happening during that training. These are all characteristics of adult learning theories. The learner self-reflects, gathers information, collaborates with others and is self-directed. One of the learning strategies associated with adult learning is effective elaboration. It helps learners to remember information in the long term and use it in situations where it might be appropriate. It is also a strategy that can be taught easily and used with learners of different ages. Designers must design reflective activities to improve the student’s intrapersonal awareness.

Keywords: training, OER, dementia, drones, search and rescue, adult learning, UDL, instructional design

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Authors: B. S. Akhmetov, S. T. Akhmetova, A. I. Ivanov, T. S. Kartbayev, A. Y. Malygin

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The problem of training of a network of artificial neurons in biometric appendices is that this process has to be completely automatic, i.e. the person operator should not participate in it. Therefore, this article discusses the issues of training the network of artificial neurons and the description of the non-iterative learning algorithm of artificial neuron.

Keywords: artificial neuron, biometrics, biometrical applications, learning of neuron, non-iterative algorithm

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: N. Khiati

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The present paper attempts to report on some findings that emerged out of a larger scale doctorate research into English language needs of a renowned Algerian company of Hydrocarbon industry. From a multifaceted English for specific purposes (ESP) research perspective, the paper considers the English needs of the finance/legal department staff in the midst of the conflicting needs perspectives involving both objective needs indicators (i.e., the pressure of globalised business) and the general negative attitudes among the administrative -mainly jurists- staff towards English (favouring a non-adaptation strategy). The researcher’s unearthing of the latter’s needs is an endeavour to concretise the concepts of unmet, or unconscious needs, among others. This is why, these initially uncovered hidden needs will be detailed questioning educational background, namely previous language of instruction; training experiences and expectations; as well as the actual communicative practices derived from the retrospective interviews and preliminary quantitative data of the questionnaire. Based on these rough clues suggesting real needs, the researcher will tentatively propose some implications for both pre-service and in-service training organisers as well as for educational policy makers in favour of an English course in legal English for the jurists mainly from pre-graduate phases to in-service training.

Keywords: English for specific purposes (ESP), legal and finance staff, needs analysis, unmet/unconscious needs, training implications

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Authors: D. Nam Kim, D. Jin Kim, Jeonghwan Jeon

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Defense Defensive Modeling and Simulation (M&S) is a system which enables impracticable training for reducing constraints of time, space and financial resources. The necessity of defensive M&S has been increasing not only for education and training but also virtual fight. Soldiers who are using defensive M&S for education and training will obtain empirical knowledge and know-how. However, the obtained knowledge of individual soldiers have not been managed and utilized yet since the nature of military organizations: confidentiality and frequent change of members. Therefore, this study aims to develop a management system for the experience of defensive M&S based on data mining approach. Since individual empirical knowledge gained through using the defensive M&S is both quantitative and qualitative data, data mining approach is appropriate for dealing with individual empirical knowledge. This research is expected to be helpful for soldiers and military policy makers.

Keywords: data mining, defensive m&s, management system, knowledge management

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Authors: Lizhi Ma, Chengcheng Hu, Fuxian Wong

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Partial reduce (P-Reduce) has set a state-of-the-art performance on distributed machine learning in the heterogeneous environment over the All-Reduce architecture. The dynamic P-Reduce based on the exponential moving average (EMA) approach predicts all the intermediate model parameters, which raises unreliability. It is noticed that the approximation trick leads the wrong way to obtaining model parameters in all the nodes. In this paper, SAP-Reduce is proposed, which is a variant of the All-Reduce distributed training model with staleness-aware dynamic P-Reduce. SAP-Reduce directly utilizes the EMA-like algorithm to generate the normalized weights. To demonstrate the effectiveness of the algorithm, the experiments are set based on a number of deep learning models, comparing the single-step training acceleration ratio and convergence time. It is found that SAP-Reduce simplifying dynamic P-Reduce outperforms the intermediate approximation one. The empirical results show SAP-Reduce is 1.3× −2.1× faster than existing baselines.

Keywords: collective communication, decentralized distributed training, machine learning, P-Reduce

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Authors: Malathi Balakrishnan, Gananthan M. Nadarajah, Noraini Abd Rahim, Amy Wong On Mei

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The purpose of the study is to investigate the level of intrinsic motivation of trainers after attending a Continuous Professional Development Course (CPD) organized by Institute of Teacher Training Malaysia titled, ‘Transformation of Teaching and Learning the Fun Way’. This study employed a survey whereby 96 teacher trainers were given Situational Intrinsic Motivational Scale (SIMS) Instruments. Confirmatory factor analysis was carried out to get validity of this instrument in local setting. Data were analyzed with SPSS for descriptive statistic. Semi structured interviews were also administrated to collect qualitative data on participants experiences after participating in the two-day fun-filled program. The findings showed that the participants’ level of intrinsic motivation showed higher mean than the amotivation. The results revealed that the intrinsic motivation mean is 19.0 followed by Identified regulation with a mean of 17.4, external regulation 9.7 and amotivation 6.9. The interview data also revealed that the participants were motivated after attending this training program. It can be concluded that this program, which was organized by Institute of Teacher Training Malaysia, was able to enhance participants’ level of motivation. Self-Determination Theory (SDT) as a multidimensional approach to motivation was utilized. Therefore, teacher trainers may have more success using the ‘The fun way approach’ in conducting training program in future.

Keywords: teaching and learning, motivation, teacher trainer, SDT

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Authors: Stephani Ferreira da Silva Manso, Regina M. M. Dias Chiquetano

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This article aims to present a research on one of the main aspects of response in humanitarian causes: agility of operations. Brazil is among the 10 countries with the highest number of people affected by disasters.The main types of disasters in Brazil include floods and mass movements. Focusing on a nongovernmental organization that began in the conflicts of First and Second World Wars, arriving in Brazil in 1984. In 2017, the organization has activated their emergency response mobile unit to reach families following flooding that affected around 9,000 people. In partnership with Truckvan, the mobile unit, has 45 m² of floor space and is divided into three compartments each designed to meet the main needs of the population: the first will be used to prepare hot meals, the second to washing and drying of clothes, and the third for the accomplishment of psychological support. This option will be available for situations where there are more than one thousand victims who are sheltered, even temporarily, and demand immediate care, which will be identified through the National Emergency Plan. In this way, the actions that were already done as donation of blankets, clothes, hygiene kits, among others, will be enhanced. Studies show that one of the biggest difficulties in responding to the disaster is in the first few hours after the disaster. This study aimed to show the organization's innovative results and to propose improvement actions in transportation focused on humanitarian aid as the concepts developed in the manufacture and adaptation of the mobile unit to the rescue environment. Thus, the principles of this humanitarian aid bus are very effective.

Keywords: disasters, humanitarian cause, relief, unit mobile

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Authors: Yogesh Mahor, Subhash Nigam, Abhai Khare

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Road safety education is a composite subject which should be viewed holistically if taken into accoubehavior change communication, safe road infrastructure and low enforcement. Specific and customized road safety education is crucial for each type of road user and learners in the formal and informal teaching and various kind of training programs directly sponsored by state and center government, as they are active contributors to shaping a community and responsible citizens. The aim of this discussion article is to explore a strategy to integrate road safety education into the formal curriculum of schools, higher education institutions, driving schools, skill development centers, various government funded urban and rural development training institutions and their work plans as standing agenda. By applying the desktop research method, the article conceptualizes what the possible focus of road safety education and training should be. The article then explores international common practices in road safety education and training, and considers the necessary synergy between education, road engineering and low enforcement. The article uses secondary data collected from documents which are then analysed in a sectoral way. A well-designed road safety strategy for mainstreaming education and government-sponsored training is urgently needed, facilitating partnerships in various sectors to implement such education in the students and learners in multidisciplinary ways.

Keywords: road safety education, curriculum-based road safety education, behavior change communication, low enforcement, road engineering, safe system approach, infrastructure development consultants

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Authors: Bjornar Kjellstadli, Shaher A. I. Shalfawi

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The aim of this study was to investigate the effect of strength training Cluster set-method compared to traditional set-method 30 m sprinting time and maximum strength in squats and bench-press. Thirteen Physical Education students, 7 males and 6 females between the age of 19-28 years old were recruited. The students were random divided in three groups. Traditional set group (TSG) consist of 2 males and 2 females aged (±SD) (22.3 ± 1.5 years), body mass (79.2 ± 15.4 kg) and height (177.5 ± 11.3 cm). Cluster set group (CSG) consist of 3 males and 2 females aged (22.4 ± 3.29 years), body mass (81.0 ± 24.0 kg) and height (179.2 ± 11.8 cm) and a control group (CG) consist of 2 males and 2 females aged (21.5 ± 2.4 years), body mass (82.1 ± 17.4 kg) and height (175.5 ± 6.7 cm). The intervention consisted of performing squat and bench press at 70% of 1RM (twice a week) for 8 weeks using 10 repetition and 4 sets. Two types of strength-training methods were used , cluster set (CS) where the participants (CSG) performed 2 reps 5 times with a 10 s recovery in between reps and 50 s recovery between sets, and traditional set (TS) where the participants (TSG) performed 10 reps each set with 90 s recovery in between sets. The pre-tests and post-tests conducted were 1 RM in both squats and bench press, and 10 and 30 m sprint time. The 1RM test were performed with Eleiko XF barbell (20 kg), Eleiko weight plates, rack and bench from Hammerstrength. The speed test was measured with the Brower speed trap II testing system (Brower Timing Systems, Utah, USA). The participants received an individualized training program based on the pre-test of the 1RM. In addition, a mid-term test of 1RM was carried out to adjust training intensity. Each training session were supervised by the researchers. Beast sensors (Milano, Italy) were also used to monitor and quantify the training load for the participants. All groups had a statistical significant improvement in bench press 1RM (TSG 1RM from 56.3 ± 28.9 to 66 ± 28.5 kg; CSG 1RM from 69.8 ± 33.5 to 77.2 ± 34.1 kg and CG 1RM from 67.8 ± 26.6 to 72.2 ± 29.1 kg), whereas only the TSG (1RM from 84.3 ± 26.8 to 114.3 ± 26.5 kg) and CSG (1RM from 100.4 ± 33.9 to 129 ± 35.1 kg) had a statistical significant improvement in Squats 1RM (P < 0.05). However, a between groups examination reveals that there were no marked differences in 1RM squat performance between TSG and CSG (P > 0.05) and both groups had a marked improvements compared to the CG (P < 0.05). On the other hand, no differences between groups were observed in Bench press 1RM. The within groups results indicate that none of the groups had any marked improvement in the distances from 0-10 m and 10-30 m except the CSG which had a notable improvement in the distance from 10-30 m (-0.07 s; P < 0.05). Furthermore, no differences in sprinting abilities were observed between groups. The results from this investigation indicate that traditional set strength training at 70% of 1RM gave close results compared to Cluster set strength training at the same intensity. However, the results indicate that the cluster set had an effect on flying time (10-30 m) indicating that the velocity at which those repetitions were performed could be the explanation factor of this this improvement.

Keywords: physical performance, 1RM, pushing velocity, velocity based training

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Authors: Sherin Ahmed El-Badry Sadek

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In this research, it is scientifically examined what contribution the professionalization of teachers can make to the development of a future-oriented vocational education and training system in Egypt. For this purpose, a needs assessment of the Egyptian vocational training system with the central actors and prevailing structures forms the foundation of the study, which theoretically underpinned with the attempt to resolve to some extent the tension between Luhmann's systems theory approach and the actor-centered theory of professional teacher competence. The vocational education system, in particular, must be adaptable and flexible due to the rapidly changing qualification requirements. In view of the pace of technological progress and the associated market changes, vocational training is no longer to be understood only as an educational tool aimed at those who achieve poorer academic performance or are not motivated to take up a degree. Rather, it is to be understood as a cornerstone for the development of society, and international experience shows that it is the core of lifelong learning. But to what extent have the education systems been able to react to these changes in their political, social, and technological systems? And how effective and sustainable are these changes actually? The vocational training system, in particular, has a particular impact on other social systems, which is why the appropriate parameters with the greatest leverage must be identified and adapted. Even if systems and structures are highly relevant, teachers must not hide behind them and must instead strive to develop further and to constantly learn. Despite numerous initiatives and programs to reform vocational training in Egypt, including the EU-funded Technical and Vocational Education and Training (TVET) reform phase I and phase II, the fit of the skilled workers to the needs of the labor market is still insufficient. Surveys show that the majority of employers are very dissatisfied with the graduates that the vocational training system produces. The data was collected through guideline-based interviews with experts from the education system and relevant neighboring systems, which allowed me to reconstruct central in-depth structures, as well as patterns of action and interpretation, in order to subsequently feed these into a matrix of recommendations for action. These recommendations are addressed to different decision-makers and stakeholders and are intended to serve as an impetus for the sustainable improvement of the Egyptian vocational training system. The research findings have shown that education, and in particular vocational training, is a political field that is characterized by a high degree of complexity and which is embedded in a barely manageable, highly branched landscape of structures and actors. At the same time, the vocational training system is not only determined by endogenous factors but also increasingly shaped by the dynamics of the environment and the neighboring social subsystems, with a mutual dependency relationship becoming apparent. These interactions must be taken into account in all decisions, even if prioritization of measures and thus a clear sequence and process orientation are of great urgency.

Keywords: competence orientation, educational policies, education systems, expert interviews, globalization, organizational development, professionalization, systems theory, teacher training, TVET system, vocational training

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Authors: Bayu Rizky Pratama, Hardiansyah Nur Sahaya

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Riau Province is the worst emitter for forest burning which causes the huge scale of externality such as declining of forest habitat, health disease, and climate change impact. Indonesia forum of budget transparency for Riau Province (FITRA) reported the length of forest burning reached about 186.069 hectares which is 7,13% of total national forest burning disaster, consisted of 107.000 hectares of peatland and the rest 79.069 hectares of mineral land. Anti-fire group, a voluntary group next to the forest, to help in protecting the forest burning and heavily smoke residual has been established but unfortunately the implementation still far from expectation. This research will emphasize on (1) how the anti-fire group contribute to fire hazard tackling; (2) the identification of SWOT analysis to enhance the group benefit; and (3) government policy implication to maximize the role of Anti-fire group and reduce the case of forest burning as well as heavily smoke which can raise climate change impact. As the observation found some weakness from SWOT identification such as (1) lack of education and training; (2) facility in extinguishing the fire damage; (3) law for economic incentive; (4) communication and field experience; (5) also the reporting the fire case.

Keywords: anti-fire group, forest burning impact, SWOT, climate change mitigation

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Authors: Catherine Begin, Jeanne Berthod, Manon Truchon

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In Quebec, there are more than 8,000 community organizations throughout the province, representing more than 72,000 jobs. Working in a community setting involves several particularities (e.g., contact with the suffering of users, feelings of powerlessness, institutional pressure, unstable funding, etc.), which can put workers at risk of fatigue, burnout, and psychological distress. A 2007 study shows that 52% of community workers surveyed have a high psychological distress index. The Ricochet project, founded in 2019, is an initiative aimed at providing various care and services to community workers in the Quebec City region, with a global health approach. Within this program, mindful self-compassion training (MSC) is offered at a low cost. MSC is one of the effective strategies proposed in the literature to help prevent and reduce burnout. Self-compassion is the recognition that suffering, failure, and inadequacies are inherent in the human experience and that everyone, including oneself, deserves compassion. MSC training targets several behavioral, cognitive, and emotional learnings (e.g., motivating oneself with caring, better managing difficult emotions, promoting resilience, etc.). A mixed-method evaluation was conducted with the participants in order to explore the effects of the training on community workers in the Quebec City region. The participants were community workers (management or caregiver). 15 participants completed satisfaction and perceived impact surveys, and 30 participated in structured interviews. Quantitative results showed that participants were generally completely satisfied or satisfied with the training (94%) and perceived that the training allowed them to develop new strategies for dealing with stress (87%). Participants perceived effects on their mood (93%), their contact with others (80%), and their stress level (67%). Some of the barriers raised were scheduling constraints, length of training, and guilt about taking time for oneself. The qualitative results show that individuals experienced long-term benefits, as they were able to apply the tools they received during the training in their daily lives. Some barriers were noted, such as difficulty in getting away from work or problems with the employer, which prevented enrollment. Overall, the results of this evaluation support the use of MSC (mindful self-compassion) training among community workers. Future research could support this evaluation by using a rigorous design and developing innovative ways to overcome the barriers raised.

Keywords: mindful self-compassion, community workers, work stres, burnout, wellbeing at work

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Authors: M. T. Becerra, F. Martín, P. Gutiérrez, S. Cubo, E. Iglesias, A. A. Sáenz del Castillo, P. Cañamero

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The consolidation of the European Higher Education Area (EHEA) in universities has led to significant changes in student training. This paper, part of a Teaching Innovation Project, starts from new training requirements that are fit within Undergraduate Thesis Project, a subject that culminate student learning. Undergraduate Thesis Project is current assessment system that weigh the student acquired training in university education. Students should develop a range of cross curricular competences such as public presentation of ideas, problems and solutions both orally and writing in Undergraduate Thesis Project. Specifically, we intend with our innovation proposal to provide resources that enable university students from Teacher Degree in Education Faculty of University of Extremadura (Spain) to develop the cross curricular competence of public speaking.

Keywords: interaction, public speaking, student, university

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Authors: Idha Novianti, Suci Nurhayati, Puryati, Elang Krisnadi

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Community service activities are activities of the academic community in practicing and cultivating science, knowledge, and technology to advance the general welfare and educate the nation's life as described in the Higher Education Law. Training activities on the use of GeoGebra software are an option because GeoGebra software is software that is easy to operate and complete in the presentation of graphic design. The training activity was held for 3 hours online via teams and 3 hours offline. Involving 15 junior high school mathematics teachers located around south Tangerang. As a result, all teachers were satisfied with the activity, and they had additional new knowledge and skills to teach mathematics in the topic of geometry and algebra. The existence of new knowledge made the participants increase their confidence in developing mathematical science for students at school.

Keywords: geogebra, Ms. teams, junior high school teacher, mathematics

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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Authors: Laura Rodríguez Amaya

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The impact of natural disasters on food security can be devastating, especially in rural settings where livelihoods are closely tied to their productive assets. In hazards studies, absorptive capacity is seen as a threshold that impacts the degree of people’s recovery after a natural disaster. Increasing our understanding of households’ capacity to absorb natural disaster shocks can provide the international community with viable measurements for assessing at-risk communities’ resilience to food insecurities. The purpose of this study is to identify the most important factors in determining a household’s capacity to absorb the impact of a natural disaster. This is an empirical study conducted in six communities in Costa Rica affected by earthquakes. The Earthquake Impact Index was developed for the selection of the communities in this study. The households coded as total loss in the selected communities constituted the sampling frame from which the sample population was drawn. Because of the study area geographically dispersion over a large surface, the stratified clustered sampling hybrid technique was selected. Of the 302 households identified as total loss in the six communities, a total of 126 households were surveyed, constituting 42 percent of the sampling frame. A list of indicators compiled based on theoretical and exploratory grounds for the absorptive capacity construct served to guide the survey development. These indicators were included in the following variables: (1) use of informal safety nets, (2) Coping Strategy, (3) Physical Connectivity, and (4) Infrastructure Damage. A multivariate data analysis was conducted using Statistical Package for Social Sciences (SPSS). The results show that informal safety nets such as family and friends assistance exerted the greatest influence on the ability of households to absorb the impact of earthquakes. In conclusion, communities that experienced the highest environmental impact and human loss got disconnected from the social networks needed to absorb the shock’s impact. This resulted in higher levels of household food insecurity.

Keywords: absorptive capacity, earthquake, food security, rural

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Authors: Amin Asgarian, Ghyslaine McClure

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Experiences in the past earthquakes have clearly demonstrated the necessity of seismic design and assessment of Non-Structural Components (NSCs) particularly in post-disaster structures such as hospitals, power plants, etc. as they have to be permanently functional and operational. Meeting this objective is contingent upon having proper seismic performance of both structural and non-structural components. Proper seismic design, analysis, and assessment of NSCs can be attained through generation of Floor Design Spectrum (FDS) in a similar fashion as target spectrum for structural components. This paper presents the developed methodology to generate FDS directly from corresponding Uniform Hazard Spectrum (UHS) (i.e. design spectra for structural components). The methodology is based on the experimental and numerical analysis of a database of 27 real Reinforced Concrete (RC) buildings which are located in Montreal, Canada. The buildings were tested by Ambient Vibration Measurements (AVM) and their dynamic properties have been extracted and used as part of the approach. Database comprises 12 low-rises, 10 medium-rises, and 5 high-rises and they are mostly designated as post-disaster\emergency shelters by the city of Montreal. The buildings are subjected to 20 compatible seismic records to UHS of Montreal and Floor Response Spectra (FRS) are developed for every floors in two horizontal direction considering four different damping ratios of NSCs (i.e. 2, 5, 10, and 20 % viscous damping). Generated FRS (approximately 132’000 curves) are statistically studied and the methodology is proposed to generate the FDS directly from corresponding UHS. The approach is capable of generating the FDS for any selection of floor level and damping ratio of NSCs. It captures the effect of: dynamic interaction between primary (structural) and secondary (NSCs) systems, higher and torsional modes of primary structure. These are important improvements of this approach compared to conventional methods and code recommendations. Application of the proposed approach are represented here through two real case-study buildings: one low-rise building and one medium-rise. The proposed approach can be used as practical and robust tool for seismic assessment and design of NSCs especially in existing post-disaster structures.

Keywords: earthquake engineering, operational and functional components, operational modal analysis, seismic assessment and design

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Authors: Muntanavadee Maytapattana

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The purposes of the study were to evaluate the effectiveness of the Parent Training Program for Obesity Reduction (PTPOR) on health behaviors of school-age children. An Ecological Systems Theory (EST) was approached the study and a randomized control trial was used in this study. Participants were school-age overweight or obese children and their parents. One hundred and one parent-child dyads were recruited and random assigned into the PTPOR (N=30), Educational Intervention or EI (N=32), and control group (N=39). The parents in the PTPOR group participated in five sessions including an educational session, a cooking session, aerobic exercise training, 2-time group discussion sessions, and 4-time telephoned counseling sessions. Repeated Measure ANCOVA was used to analyze data. The results presented that the outcomes of the PTPOR group were better than the EI and the control groups at 1st, 8th, and 32nd weeks after finishing the program such as child exercise behavior (F(2,97) = 3.98, p = .02) and child dietary behavior (F(2,97) = 9.42, p = .00). The results suggest that nurses and health care providers should utilize the PTPOR for child weight reduction and for the health promotion of a lifestyle among overweight and obese children.

Keywords: parent training program, obesity reduction, child health behaviors, school-age children

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Authors: P. Weerkamp Bartholomeus

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Autism treatment evaluation is crucial for monitoring the development of an intervention at an early stage. ‘ReAttach’ is a new intervention based on the principles of attachment and social cognitive training. Practical research suggests promising results on a variety of developmental areas. Five years after the first ReAttach sessions these findings can be extended with qualitative research by means of follow-up interviews. The potential impact of this treatment on daily life functioning and well-being of autistic persons becomes clear.

Keywords: autism, innovation, treatment, social cognitive training

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Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: W. Staiano, S. Marcora

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Introduction: It has been proposed that acute negative effect of mental fatigue (MF) could potentially become a training stimulus for the brain (Brain endurance training (BET)) to adapt and improve its ability to attenuate MF states during sport competitions. Purpose: The aim of this study was to test the efficacy of 6 weeks of BET on cognitive and cycling tests in a group of well-trained subjects. We hypothesised that combination of BET and standard physical training (SPT) would increase cognitive capacity and cycling performance by reducing rating of perceived exertion (RPE) and increase resilience to fatigue more than SPT alone. Methods: In a randomized controlled trial design, 26 well trained participants, after a familiarization session, cycled to exhaustion (TTE) at 80% peak power output (PPO) and, after 90 min rest, at 65% PPO, before and after random allocation to a 6 week BET or active placebo control. Cognitive performance was measured using 30 min of STROOP coloured task performed before cycling performance. During the training, BET group performed a series of cognitive tasks for a total of 30 sessions (5 sessions per week) with duration increasing from 30 to 60 min per session. Placebo engaged in a breathing relaxation training. Both groups were monitored for physical training and were naïve to the purpose of the study. Physiological and perceptual parameters of heart rate, lactate (LA) and RPE were recorded during cycling performances, while subjective workload (NASA TLX scale) was measured during the training. Results: Group (BET vs. Placebo) x Test (Pre-test vs. Post-test) mixed model ANOVA’s revealed significant interaction for performance at 80% PPO (p = .038) or 65% PPO (p = .011). In both tests, groups improved their TTE performance; however, BET group improved significantly more compared to placebo. No significant differences were found for heart rate during the TTE cycling tests. LA did not change significantly at rest in both groups. However, at completion of 65% TTE, it was significantly higher (p = 0.043) in the placebo condition compared to BET. RPE measured at ISO-time in BET was significantly lower (80% PPO, p = 0.041; 65% PPO p= 0.021) compared to placebo. Cognitive results in the STROOP task showed that reaction time in both groups decreased at post-test. However, BET decreased significantly (p = 0.01) more compared to placebo despite no differences accuracy. During training sessions, participants in the BET showed, through NASA TLX questionnaires, constantly significantly higher (p < 0.01) mental demand rates compared to placebo. No significant differences were found for physical demand. Conclusion: The results of this study provide evidences that combining BET and SPT seems to be more effective than SPT alone in increasing cognitive and cycling performance in well trained endurance participants. The cognitive overload produced during the 6-week training of BET can induce a reduction in perception of effort at a specific power, and thus improving cycling performance. Moreover, it provides evidence that including neurocognitive interventions will benefit athletes by increasing their mental resilience, without affecting their physical training load and routine.

Keywords: cognitive training, perception of effort, endurance performance, neuro-performance

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Authors: Ali Mohammed Ali Lmbash

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The global refugee crisis points to the vital need for sustainable and resistant solutions to different kinds of problems for displaced persons all over the world. Among the myriads of sustainable concerns, however, there are diverse considerations including energy consumption, waste management, water access, and resiliency of structures. Our research aims to develop distinct ideas for sustainable architecture given the exigent problems in disaster-threatened areas starting with the Hatay Refugee camp in Turkey where the majority of the camp dwellers are Syrian refugees. Commencing community-based participatory research which focuses on the socio-environmental issues of displaced populations, this study will apply two approaches with a specific focus on the Hatay region. The initial experiment uses Richter's predictive model and simulations to forecast earthquake outcomes in refugee campers. The result could be useful in implementing architectural design tactics that enhance structural reliability and ensure the security and safety of shelters through earthquakes. In the second experiment a model is generated which helps us in predicting the quality of the existing water sources and since we understand how greatly water is vital for the well-being of humans, we do it. This research aims to enable camp administrators to employ forward-looking practices while managing water resources and thus minimizing health risks as well as building resilience of the refugees in the Hatay area. On the other side, this research assesses other sustainability problems of Hatay Refugee Camp as well. As energy consumption becomes the major issue, housing developers are required to consider energy-efficient designs as well as feasible integration of renewable energy technologies to minimize the environmental impact and improve the long-term sustainability of housing projects. Waste management is given special attention in this case by imposing recycling initiatives and waste reduction measures to reduce the pace of environmental degradation in the camp's land area. As well, study gives an insight into the social and economic reality of the camp, investigating the contribution of initiatives such as urban agriculture or vocational training to the enhancement of livelihood and community empowerment. In a similar fashion, this study combines the latest research with practical experience in order to contribute to the continuing discussion on sustainable architecture during disaster relief, providing recommendations and info that can be adapted on every scale worldwide. Through collaborative efforts and a dedicated sustainability approach, we can jointly get to the root of the cause and work towards a far more robust and equitable society.

Keywords: smart architecture, Hatay Camp, sustainability, machine learning.

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Authors: Pema Choejey, David Murray, Chun Che Fung

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Bhutan is becoming increasingly dependent on Information and Communications Technologies (ICTs), especially the Internet for performing the daily activities of governments, businesses, and individuals. Consequently, information systems and networks are becoming more exposed and vulnerable to cybersecurity threats. This paper highlights the findings of the survey study carried out to understand the perceptions of cybersecurity implementation among government organizations in Bhutan. About 280 ICT personnel were surveyed about the effectiveness of cybersecurity implementation in their organizations. A questionnaire based on a 5 point Likert scale was used to assess the perceptions of respondents. The questions were asked on cybersecurity practices such as cybersecurity policies, awareness and training, and risk management. The survey results show that less than 50% of respondents believe that the cybersecurity implementation is effective: cybersecurity policy (40%), risk management (23%), training and awareness (28%), system development life cycle (34%); incident management (26%), and communications and operational management (40%). The findings suggest that many of the cybersecurity practices are inadequately implemented and therefore, there exist a gap in achieving a required cybersecurity posture. This study recommends government organizations to establish a comprehensive cybersecurity program with emphasis on cybersecurity policy, risk management, and awareness and training. In addition, the research study has practical implications to both government and private organizations for implementing and managing cybersecurity.

Keywords: awareness and training, cybersecurity policy, risk management, security risks

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Authors: Jui-Chen Huang, Shou-Hsiung Cheng

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This study examined their willingness to use telecare for people who have had experience falling in the last three months in Taiwan. This study adopted convenience sampling and a structural questionnaire to collect data. It was based on the definition and the constructs related to the Health Belief Model (HBM). HBM is comprised of seven constructs: perceived benefits (PBs), perceived disease threat (PDT), perceived barriers of taking action (PBTA), external cues to action (ECUE), internal cues to action (ICUE), attitude toward using (ATT), and behavioral intention to use (BI). This study adopted Fuzzy Neural Network (FNN) to put forward an effective method. It shows the dependence of ATT on PB, PDT, PBTA, ECUE, and ICUE. The training and testing data RMSE (root mean square error) are 0.028 and 0.166 in the FNN, respectively. The training and testing data RMSE are 0.828 and 0.578 in the regression model, respectively. On the other hand, as to the dependence of ATT on BI, as presented in the FNN, the training and testing data RMSE are 0.050 and 0.109, respectively. The training and testing data RMSE are 0.529 and 0.571 in the regression model, respectively. The results show that the FNN method is better than the regression analysis. It is an effective and viable good way.

Keywords: fall, fuzzy neural network, health belief model, telecare, willingness

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Authors: Csilla Marianna Szabó

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In Hungary, the society has changes a lot for the past 25 years, and these changes could be detected in educational situations as well. The number and the intensity of conflicts have been increased in most fields of life, as well as at schools. Teachers have difficulties to be able to handle school conflicts. What is more, the new net generation, generation Z has values and behavioural patterns different from those of the previous one, which might generate more serious conflicts at school, especially with teachers who were mainly socialising in a traditional teacher – student relationships. In Hungary, the bill CCIV, 2011 declared the foundation of Institutes of Teacher Training in higher education institutes. One of the tasks of the Institutes is to survey the competences and needs of teachers working in public education and to provide further trainings and services for them according to their needs and requirements. This job is supported by the Social Renewal Operative Programs 4.1.2.B. The Institute of Teacher Training at the College of Dunaújváros, Hungary carried out a questionnaire and surveyed the needs and the requirements of teachers working in the Central Transdanubian region. Based on the results, the professors of the Institute of Teacher Training decided to meet the requirements of teachers and launch short courses in spring 2015. One of the courses is going to focus on school conflict management through mediation. The aim of the pilot course is to provide conflict management techniques for teachers presenting different mediation techniques to them. The theoretical part of the course (5 hours) will enable participants to understand the main points and the advantages of mediation, while the practical part (10 hours) will involve teachers in role plays to learn how to cope with conflict situations applying mediation. We hope if conflicts could be reduced, it would influence school atmosphere in a positive way and the teaching – learning process could be more successful and effective.

Keywords: conflict resolution, generation Z, mediation, teacher training

Procedia PDF Downloads 410