Search results for: breathing training program

Authors: Zulaikha Reesha Rashaad

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One of the major factors which can contribute greatly to success of catering businesses is to employ food and beverage staff having sound hygiene knowledge. Individuals having sound knowledge of hygiene has a higher chance of following safe food practices in food production. One of the leading causes of food poisoning and food borne illnesses has been identified as lack of hygiene knowledge among food and beverage staff working in catering establishments and restaurants. This research aims to analyze the hygiene knowledge among food and beverage staff working in top five restaurants of Male’, in relation to their age, educational background, occupation and training. The research uses quantitative and descriptive methods in data collection and in data analysis. Data was obtained through random sampling technique with self-administered survey questionnaires which was completed by 60 respondents working in 5 different restaurants operating at top level in Male’. The respondents of the research were service staff and chefs working in these restaurants. The responses to the questionnaires have been analyzed by using SPSS. The results of the research indicated that age, education level, occupation and training correlated with hygiene knowledge perception scores.

Keywords: food and beverage staff, food poisoning, food production, hygiene knowledge

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Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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Authors: Rakesh Prajapati, Purvik Patel, Avadhoot Rajurkar

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Nowadays, manufacturing industries augment their production lines with modern machining centers backed by CAM software. Several attempts are being made to cut down the programming time for machining complex geometries. Special programs/software have been developed to generate the digital numerical data and to prepare NC programs by using suitable post-processors for different machines. By selecting the tools and manufacturing process then applying tool paths and NC program are generated. More and more complex mechanical parts that earlier were being cast and assembled/manufactured by other processes are now being machined. Majority of these parts require lots of pocketing operations and find their applications in die and mold, turbo machinery, aircraft, nuclear, defense etc. Pocketing operations involve removal of large quantity of material from the metal surface. The modeling of warm cast and clamping a piece of food processing parts which the used of Pro-E and MasterCAM^® software. Pocketing operation has been specifically chosen for toolpath optimization. Then after apply Pocketing toolpath, Multi Tool Selection and Reduce Air Time give the results of software simulation time and experimental machining time.

Keywords: toolpath, part program, optimization, pocket

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Authors: Yi Li, Yinan Zheng, Ya Ke, Yungwing Ho

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Motor learning is a process that frequently happens among humans and rodents, which is defined as the changes in the capability to perform a skill that is conformed to have a relatively permanent improvement through practice or experience. There are many ways to learn a behavior, among which is observational learning. Observational learning is the process of learning by watching the behaviors of others, for example, a child imitating parents, learning a new sport by watching the training videos or solving puzzles by watching the solutions. Many research explores observational learning in humans and primates. However, the neuronal mechanism of which, especially observational motor learning, was uncertain. It’s well accepted that mirror neurons are essential in the observational learning process. These neurons fire when the primate performs a goal-directed action and sees someone else demonstrating the same action, which suggests they have high firing activity both completing and watching the behavior. The mirror neurons are assumed to mediate imitation or play a critical and fundamental role in action understanding. They are distributed in many brain areas of primates, i.e., posterior parietal cortex (PPC), premotor cortex (M2), and primary motor cortex (M1) of the macaque brain. However, few researchers report the existence of mirror neurons in rodents. To verify the existence of mirror neurons and the possible role in motor learning in rodents, we performed customised string-pulling behavior combined with multiple behavior analysis methods, photometry, electrophysiology recording, c-fos staining and optogenetics in healthy mice. After five days of training, the demonstrator (demo) mice showed a significantly quicker response and shorter time to reach the string; fast, steady and accurate performance to pull down the string; and more precisely grasping the beads. During three days of observation, the mice showed more facial motions when the demo mice performed behaviors. On the first training day, the observer reduced the number of trials to find and pull the string. However, the time to find beads and pull down string were unchanged in the successful attempts on the first day and other training days, which indicated successful action understanding but failed motor learning through observation in mice. After observation, the post-hoc staining revealed that the c-fos expression was increased in the cognitive-related brain areas (medial prefrontal cortex) and motor cortices (M1, M2). In conclusion, this project indicated that the observation led to a better understanding of behaviors and activated the cognitive and motor-related brain areas, which suggested the possible existence of mirror neurons in these brain areas.

Keywords: observation, motor learning, string-pulling behavior, prefrontal cortex, motor cortex, cognitive

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Authors: Jacklyn Yek, Clara Tong, Shin Yuet Chong, Yee Yian Ong

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Background: While emergency manuals and cognitive aids (CA) have been used in high-hazard industries for decades, this has been a nascent field in healthcare. CAs can potentially offset the large cognitive load involved in crisis resource management and possibly facilitate the efficient performance of key steps in treatment. A crisis manual was developed based on local guidelines and the latest evidence-based information and introduced to a tertiary hospital setting in Singapore. Hence, the objective of this study is to evaluate the effectiveness of the crisis manual in guiding response and management of critical events. Methods: 7 surgical teams were recruited to participate in a series of simulated emergencies in high-fidelity operating room simulator over the period of April to June 2018. All teams consisted of a surgical consultant and medical officer/registrar, anesthesia consultant and medical officer/registrar; as well as a circulating, scrub and anesthetic nurse. Each team performed a simulated operation in which 1 or more of the crisis events occurred. The teams were randomly assigned to a scenario of the crisis manual and all teams were deemed to be equal in experience and knowledge. Before the simulation, teams were instructed on proper checklist use but the use of the checklist was optional. Results: 7 simulation sessions were performed, consisting of the following scenarios: Airway fire, Massive Transfusion Protocol, Malignant Hyperthermia, Eclampsia, and Difficult Airway. Out of the 7 surgical teams, 2 teams made use of the crisis manual – of which both teams had encountered a ‘Malignant Hyperthermia’ scenario. These team members reflected that the crisis manual assisted allowed them to work in a team, especially being able to involve the surgical doctors who were unfamiliar with the condition and management. A run chart plotted showed a possible upward trend, suggesting that with increasing awareness and training, staff would become more likely to initiate the use of the crisis manual. Conclusion: Despite the high volume load in this tertiary hospital, certain crises remain rare and clinicians are often caught unprepared. A crisis manual is an effective tool and easy-to-use repository that can improve patient outcome and encourage teamwork. With training, familiarity would allow clinicians to be increasingly comfortable with reaching out for the crisis manual. More simulation training would need to be conducted to determine its effectiveness.

Keywords: crisis resource management, high fidelity simulation training, medical errors, visual aids

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Authors: Mateusz Jeżowski, Jadwiga Fila, Paweł Poszytek

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This abstract summarizes the combined findings of several analyses carried out by the authors on the barriers to accessing international education mobility programs by people with fewer opportunities, especially those with a low level of cultural and social capital. Two flagship educational mobility initiatives of the European Union – the Erasmus+ Program and the European Solidarity Corps are aimed at equipping young people and participants of all ages with the qualifications and skills needed for their meaningful participation in a democratic society intercultural understanding and successful transition in the labour market. The heart of these programs is to come closer to people with fewer opportunities, including people with disabilities, migrants, as well as those facing socio-economic difficulties and displaying a low level of social and cultural capital. Still, people who participate in such initiatives usually demonstrate higher than average cultural and social capital, as understood by Pierre Bourdieu. First of all, the educational attainment of their parents is higher than the average. Secondly, they mostly live in large agglomerations, with good access to education and culture, which affects their foreign language skills as well as social and cultural competencies. Finally, participation in Erasmus+ Program or European Solidarity Corps is not their first educational mobility experience. It is therefore justified to state that their social and cultural capital, already high before taking part in Erasmus+ and European Solidarity Corps, becomes even higher once their international mobility activities have been over, at the expense of those people with fewer opportunities, who, in theory, could participate in those initiatives, nonetheless did not, for the following reasons: lack of sufficient information on such programs, financial obstacles or unappreciation of the value of international mobility. In their work, the authors will discuss what are, in the light of Bourdieu’s perception of social and cultural capital, the main obstacles for young people to participate in international mobility programs of the European Union and will offer comprehensive solutions rooted in their vast experience in management and implementation of Erasmus+ Program and European Solidarity Corps.

Keywords: cultural capital, educational mobility, Erasmus+, European solidarity corps, inclusion, social capital

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Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

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Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

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Authors: Monika Benedek

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Improvisation is an integral part of music education programmes worldwide since teachers recognize that improvisation helps to broaden stylistic knowledge, develops creativity and various musical skills, in particular, aural skills, and also motivates to learn music theory. In Hungary, where Kodály concept is a core element of music teacher education, improvisation has been relatively neglected subject in both primary school and classical music school curricula. Therefore, improvisation was an important theme of a one-year-long research project carried out at the Liszt Academy of Music in Budapest. The project aimed to develop the music teacher training programme, and among others, focused on testing how improvisation could be used as a teaching tool to improve students’ musical reading and writing skills and creative musical skills. Teacher-researchers first tested various teaching approaches of improvisation with numerous teaching modules in music lessons at public schools and music schools. Data were collected from videos of lessons and from teachers’ reflective notes. After analysing data and developing teaching modules, all modules were tested again in a pilot course in 30 contact lessons for music teachers. Teachers gave written feedback of the pilot programme, tested two modules by their choice in their own teaching and wrote reflecting comments about their experiences in applying teaching modules of improvisation. The overall results indicated that improvisation could be an innovative approach to teaching various musical subjects, in particular, solfege, music theory, and instrument, either in individual or in group instruction. Improvisation, especially with the application of relative solmisation and singing, appeared to have been a beneficial tool to develop various musicianship skills of students and teachers, in particular, the aural, musical reading and writing skills, and creative musical skills. Furthermore, improvisation seemed to have been a motivating teaching tool to learn music theory by creating a bridge between various musical styles. This paper reports on the results of the research project.

Keywords: improvisation, Kodály concept, music school, public school, teacher training

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Authors: Lynn Mcquarrie, Charlotte Enns

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The goal of this project was to develop a visually-based, signed language phonological awareness training program and to pilot the intervention with signing deaf children (ages 6 -10 years/ grades 1 - 4) who were beginning readers to assess the effects of systematic explicit American Sign Language (ASL) phonological instruction on both ASL vocabulary and English print vocabulary learning. Growing evidence that signing learners utilize visually-based signed language phonological knowledge (homologous to the sound-based phonological level of spoken language processing) when reading underscore the critical need for further research on the innovation of reading instructional practices for visual language learners. Multiple single-case studies using a multiple probe design across content (i.e., sign and print targets incorporating specific ASL phonological parameters – handshapes) was implemented to examine if a functional relationship existed between instruction and acquisition of these skills. The results indicated that for all cases, representing a variety of language abilities, the visually-based phonological teaching approach was exceptionally powerful in helping children to build their sign and print vocabularies. Although intervention/teaching studies have been essential in testing hypotheses about spoken language phonological processes supporting non-deaf children’s reading development, there are no parallel intervention/teaching studies exploring hypotheses about signed language phonological processes in supporting deaf children’s reading development. This study begins to provide the needed evidence to pursue innovative teaching strategies that incorporate the strengths of visual learners.

Keywords: American sign language phonological awareness, dual language strategies, vocabulary learning, word reading

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Authors: Robin Ferguson

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The context which this paper explores is the provision of Technical Vocational Education and Training (TVET) of southern African workers at sea on local and foreign vessels using a blended learning approach. The pedagogical challenge of providing quality education in this context is that multiple African and foreign languages and cultural norms are found amongst the all-male crew; and there are widely differing levels of education, low levels of digital literacy and limited connectivity. The methodology used is a nested case study. The study describes the mechanisms used to provide ongoing, real-time workplace TVET on two foreign vessels. Some training was done in person when the vessels came into port, however, the majority of the TVET was achieved from shore to ship using a combination of commonly available Google and Microsoft Apps and WhatsApp. Voice, video and text in multiple languages were used to accommodate different learning styles. The learning was supported by the development of learning networks using social media. This paper also reflects on the shore-based organisational change processes required to support sea learning. The conceptual framework used is the Theory of Practice Architectures (TPA) as is provides a site-ontological perspective of the sayings/thinkings, doings and relatings of this workplace training which is multiplanar as it plays out at sea and ashore, in-person and on-line. Using TPA, the overarching practice architectures and supporting structures which confound or enable these learning practices are revealed. The contribution which this paper makes is an insight into an innovative vocational pedagogy which promotes ICT-mediated learning amongst workers who suffer from low levels of literacies and limited ICT-access and who work and live in remote places. It is a pedagogy of possibility which crosses the digital divide.

Keywords: theory of practice architecture, microsoft, google, whatsapp, vocational pedagogy, mariners, distributed workplaces

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Authors: Abhisek Dash

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This study had three neural networks, one for number segmentation, one for number detection and one for number recognition all of which are coupled to one another. All networks were trained on the MNIST dataset and were convolutional. It was assumed that the images had lighter background and darker foreground. The segmentation network took 28x28 images as input and had sixteen outputs. Segmentation training starts when a dark pixel is encountered. Taking a window(7x7) over that pixel as focus, the eight neighborhood of the focus was checked for further dark pixels. The segmentation network was then trained to move in those directions which had dark pixels. To this end the segmentation network had 16 outputs. They were arranged as “go east”, ”don’t go east ”, “go south east”, “don’t go south east”, “go south”, “don’t go south” and so on w.r.t focus window. The focus window was resized into a 28x28 image and the network was trained to consider those neighborhoods which had dark pixels. The neighborhoods which had dark pixels were pushed into a queue in a particular order. The neighborhoods were then popped one at a time stitched to the existing partial image of the number one at a time and trained on which neighborhoods to consider when the new partial image was presented. The above process was repeated until the image was fully covered by the 7x7 neighborhoods and there were no more uncovered black pixels. During testing the network scans and looks for the first dark pixel. From here on the network predicts which neighborhoods to consider and segments the image. After this step the group of neighborhoods are passed into the detection network. The detection network took 28x28 images as input and had two outputs denoting whether a number was detected or not. Since the ground truth of the bounds of a number was known during training the detection network outputted in favor of number not found until the bounds were not met and vice versa. The recognition network was a standard CNN that also took 28x28 images and had 10 outputs for recognition of numbers from 0 to 9. This network was activated only when the detection network votes in favor of number detected. The above methodology could segment connected and overlapping numbers. Additionally the recognition unit was only invoked when a number was detected which minimized false positives. It also eliminated the need for rules of thumb as segmentation is learned. The strategy can also be extended to other characters as well.

Keywords: convolutional neural networks, OCR, text detection, text segmentation

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Doaa Alhaboby

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Behavior change is a complex process that often requires ongoing support and guidance. Telecoaching programs have emerged as effective tools in facilitating behavior change by providing personalized support remotely. This abstract explores the lessons learned from a randomized controlled trial (RCT) evaluation of a telecoaching program focused on behavior change for Diabetics and discusses strategies for implementing these lessons to overcome the challenge of making physical activity a habit. The telecoaching program involved participants engaging in regular coaching sessions delivered via phone calls. These sessions aimed to address various aspects of behavior change, including goal setting, self-monitoring, problem-solving, and social support. Over the course of the program, participants received personalized guidance tailored to their unique needs and preferences. One of the key lessons learned from the RCT was the importance of engagement, readiness to change and the use of technology. Participants who set specific, measurable, attainable, relevant, and time-bound (SMART) goals were more likely to make sustained progress toward behavior change. Additionally, regular self-monitoring of behavior and progress was found to be instrumental in promoting accountability and motivation. Moving forward, implementing the lessons learned from the RCT can help individuals overcome the hardest part of behavior change: making physical activity a habit. One strategy is to prioritize consistency and establish a regular routine for physical activity. This may involve scheduling workouts at the same time each day or week and treating them as non-negotiable appointments. Additionally, integrating physical activity into daily life routines and taking into consideration the main challenges that can stop the process of integrating physical activity routines into the daily schedule can help make it more habitual. Furthermore, leveraging technology and digital tools can enhance adherence to physical activity goals. Mobile apps, wearable activity trackers, and online fitness communities can provide ongoing support, motivation, and accountability. These tools can also facilitate self-monitoring of behavior and progress, allowing individuals to track their activity levels and adjust their goals as needed. In conclusion, telecoaching programs offer valuable insights into behavior change and provide strategies for overcoming challenges, such as making physical activity a habit. By applying the lessons learned from these programs and incorporating them into daily life, individuals can cultivate sustainable habits that support their long-term health and well-being.

Keywords: lifestyle, behavior change, physical activity, chronic conditions

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Authors: Gheorghe Braniste

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The management of the training process in sports is closely related to the awareness of the close connection between performance and the morphological, functional and psychological characteristics of the athlete's body. Achieving high results in Olympic sports is influenced, on the one hand, by the genetically determined characteristics of the body and, on the other hand, by the morphological, functional and motor abilities of the athlete. Taking into account the importance of properly understanding the evolutionary specificity of athletes to assess their competitive potential, this study provides a comparative analysis of the parameters that characterize the growth and development of the level of adaptation of sweeping rowers, considering the growth interval between 12 and 20 years. The study established that, in the multi-annual training process, the bodies of the targeted athletes register significant adaptive changes while analyzing parameters of the morphological, functional, psychomotor and sports-technical spheres. As a result of the influence of physical efforts, both specific and non-specific, there is an increase in the adaptability of the body, its transfer to a much higher level of functionality within the parameters, useful and economical adaptive reactions influenced by environmental factors, be they internal or external. The research was carried out for 7 years, on a group of 28 athletes, following their evolution and recording the specific parameters of each age stage. In order to determine the level of physical, morpho-functional, psychomotor development and technical training of rowers, the screening data were applied at the State University of Physical Education and Sports in the Republic of Moldova. During the research, measurements were made on the waist, in the standing and sitting position, arm span, weight, circumference and chest perimeter, vital capacity of the lungs, with the subsequent determination of the vital index (tolerance level to oxygen deficiency in venous blood in Stange and Genchi breath-taking tests that characterize the level of oxygen saturation, absolute and relative strength of the hand and back, calculation of body mass and morphological maturity indices (Kettle index), body surface area (body gait), psychomotor tests (Romberg test), test-tepping 10 s., reaction to a moving object, visual and auditory-motor reaction, recording of technical parameters of rowing on a competitive distance of 200 m. At the end of the study it was found that highly performance is sports is to be associated on the one hand with the genetically determined characteristics of the body and, on the other hand, with favorable adaptive reactions and energy saving, as well as morphofunctional changes influenced by internal and external environmental factors. The importance of the results obtained at the end of the study was positively reflected in obtaining the maximum level of training of athletes in order to demonstrate performance in large-scale competitions and mostly in the Olympic Games.

Keywords: olympics, parameters, performance, peak

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Authors: Tao Zhang

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As the competition of all kinds of festival events becomes more and more fierce, more and more event organizers try to design a blended festivalscape by integrating multifaceted environmental cues in order to raise the service quality of festival events and then raise visitors’ satisfaction. As the main type of festival events, food festivals are popular in all over the world. The organizers’ of food festivals also try to mix food with multifaceted environmental cues (e.g., music, stage, light, dance) to design a blended festivalscape. However, until now little studies explore the environmental cues of food festivals and their relationship with visitors’ satisfaction. Therefore, the aim of this study is to ascertain the environmental cues of food festival and their relationship with visitors’ satisfaction by using the blended festivalscape theory. Using convenient sampling method, this study investigated 1,000 food festival visitors in Macau. Factor analysis showed there are mainly six environmental cues (i.e., food, atmosphere, program, staff, facility, and information). All six environmental cues are positively related with visitors’ satisfaction, while the most influential factors are food, atmosphere, and program. This study showed that festival event organizers’ should focus on the topic of their festival event, build festival atmosphere, and create interesting programs in order to design a blended festivalscape and then raise visitors’ satisfaction.

Keywords: environmental cue, event, festival, satisfaction

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Authors: Minsung Kim, Hyunkoo Kang, Jinkoo Kim

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In this study, a hybrid energy dissipation device is developed by combining a steel slit plate and friction pads to be used for seismic retrofit of structures, and its effectiveness is investigated by comparing the life cycle costs of the structure before and after the retrofit. The seismic energy dissipation capability of the dampers is confirmed by cyclic loading tests. The probabilities of reaching various damage states are obtained by fragility analysis, and the life cycle costs of the model structures are computed using the PACT (Performance Assessment Calculation Tool) program based on FEMA P-58 methodology. The fragility analysis shows that the probabilities of reaching limit states are minimized by the seismic retrofit with hybrid dampers and increasing column size. The seismic retrofit with increasing column size and hybrid dampers results in the lowest repair cost and shortest repair time. This research was supported by a grant (13AUDP-B066083-01) from Architecture & Urban Development Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Keywords: FEMA P-58, friction dampers, life cycle cost, seismic retrofit

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Authors: P. Kavuma, J. Mukasa, M. Lusunku

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Background and Problem: The widespread poverty in Africa- together with the negative impacts of climate change-are two great global challenges that call for everyone’s involvement including Architects. This in particular places serious challenges on architects to have additional skills in both Entrepreneurship and Environmental Design (SEED). Regrettably, while Architectural Training in most African Universities including those from Uganda lack comprehensive implementation of SEED in their curricula, regulatory bodies have not contributed towards the effective integration of SEED in their professional practice. In response to these challenges, Nkumba University (NU) under Architect Kavuma Paul supported by the Uganda Chambers of Architects– initiated the SEED integration in the undergraduate Architectural curricula to cultivate SEED know-how and examples of best practices. Main activities: Initiated in 2007, going beyond the traditional Architectural degree curriculum, the NU Architect department offers SEED courses including provoking passions for creating desirable positive changes in communities. Learning outcomes are assessed theoretically and practically through field projects. The first set of SEED graduates came out in 2012. As part of the NU post-graduation and alumni survey, in October 2014, the pioneer SEED graduates were contacted through automated reminder emails followed by individual, repeated personal follow-ups via email and phone. Out of the 36 graduates who responded to the survey, 24 have formed four (4) private consortium agencies of 5-7 graduates all of whom have pioneered Ugandan-own-cultivated Architectural social projects that include: fishing farming in shipping containers; solar powered mobile homes in shipping containers, solar powered retail kiosks in rural and fishing communities, and floating homes in the flood-prone areas. Primary outcomes: include being business self –reliant in creating the social change the architects desired in the communities. Examples of the SEED project returns to communities reported by the graduates include; employment creation via fabrication, retail business, marketing, improved diets, safety of life and property, decent shelter in the remote mining and oil exploration areas. Negative outcomes-though not yet evaluated include the disposal of used-up materials. Conclusion: The integration of SEED in Architectural Training has established a baseline benchmark and a replicable model based on best practice projects.

Keywords: architectural training, entrepreneurship, environment, integration

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Authors: Lateefat Amao, Misagh Faezipour

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Implementing electronic health records (EHR) in healthcare is a pivotal transition aimed at digitizing and optimizing patient health information management. The expectations associated with this transition are high, even towards other health information systems (HIS) and health technology. This multifaceted process involves careful planning and execution to improve the quality and efficiency of patient care, especially as healthcare technology is a sensitive niche. Key considerations include a thorough needs assessment, judicious vendor selection, robust infrastructure development, and training and adaptation of healthcare professionals. Comprehensive training programs, data migration from legacy systems and models, interoperability, as well as security and regulatory compliance are imperative for healthcare staff to navigate EHR systems adeptly. The purpose of this work is to offer a comprehensive review of the literature on EHR implementation. It explores the impact of this health technology on health practices, highlights challenges and barriers to its successful utility, and offers practical strategies that can impact its success in healthcare. This paper provides a thorough review of studies on the adoption of EHRs, emphasizing the wide range of experiences and results connected to EHR use in the medical field, especially across different types of healthcare organizations.

Keywords: healthcare, electronic health records, EHR implementation, patient care, interoperability

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Authors: Bianca W. O. Silva, Adriana C. M. Andrade, Gustavo C. M. Lucena, Virna M. S. Lima

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Introduction: Basic life support (BLS) involves the immediate recognition of cardiopulmonary arrest. Each year, 359.400 and 275.000 individuals with cardiac arrest are attended in emergency departments in USA and Europe. Brazilian data shows that 200.000 cardiac arrests occur every year, and half of them out of the hospital. Medical schools around the world teach BLS in the first years of the course, but studies show that there is a decline of the knowledge as the years go by, affecting the chain of survival. The objective was to analyze the knowledge of medical students about BLS and the retention of this learning throughout the course. Methods: This study included 150 students who were at the second and third year of a medical school in Salvador, Bahia, Brazil. The instrument of data collection was a structured questionnaire composed of 20 questions based on the 2015 American Heart Association guideline. The Pearson Chi-square test was used in order to study the association between previous training, sex and semester with the degree of knowledge of the students. The Kruskal-Wallis test was used to evaluate the different yields obtained between the various semesters. The number of correct answers was described by average and quartiles. Results: Regarding the degree of knowledge, 19.6% of the female students reached the optimal classification, a better outcome than the achieved by the male participants. Of those with previous training, 33.33% were classified as good and optimal, none of the students reached the optimal classification and only 2.2% of them were classified as bad (those who did not have 52.6% of correct answers). The analysis of the degree of knowledge related to each semester revealed that the 5th semester had the highest outcome: 30.5%. However, the acquaintance presented by the semesters was generally unsatisfactory, since 50% of the students, or more, demonstrated knowledge levels classified as bad or regular. When confronting the different semesters and the achieved scores, the value of p was 0.831. Conclusion: It is important to focus on the training of medical professionals that are capable of facing emergency situations, improving the systematization of care, and thereby increasing the victims' possibility of survival.

Keywords: basic life support, cardiopulmonary ressucitacion, education, medical students

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Mohammad Shahid Jamil

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In this study we have investigated students’ learning and satisfaction in one of the course offered in the Foundation Program at Qatar University. We implied innovative teaching methodology that emphasizes on enhancing students’ thinking skills, decision making, and problem solving skills. Some interesting results were found which can be used to further improve the teaching methodology. To make sure the full use of technology in Foundation Program at Qatar University has started implementing new ways of teaching Math course by using Blackboard as an innovative interactive tool to support standard teaching such as Discussion board, Virtual class, and Study plan in My Math Lab “MML”. In MML Study Plan is designed in such a way that the student can improve their skills wherever they face difficulties with in their Homework, Quiz or Test. Discussion board and Virtual Class are collaborative learning tools encourages students to engage outside of class time. These tools are useful to share students’ knowledge and learning experiences, promote independent and active learning and they helps students to improve their critical thinking skills through the learning process.

Keywords: blackboard, discussion board, critical thinking, active learning, independent learning, problem solving

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Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena

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Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.

Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Sheila R. Pai, Rekha D. Kini, Amrutha Mary

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Objective: To assess and compare the cardiac autonomic activity after mental stress among the wards of normal and hypertensive parents. Methods: The study included 67 subjects, 30 of them had a parental history of hypertension and rest 37 had normotensive parents. Subjects were divided into control group (wards of normotensive parents) and Study group (wards of hypertensive parents). The height, weight were noted, and Body Mass Index (BMI) was also calculated. The mental stress test was carried out. Blood pressure (BP) and electro cardiogram (ECG) was recorded during normal breathing and after mental stress test. Heart rate variability (HRV) analysis was done by time domain method HRV was recorded and analyzed by the time-domain method. Analysis of HRV in the time-domain was done using the software version 1.1 AIIMS, New Delhi. The data obtained was analyzed using student’s t-test followed by Mann-Whitney U-test and P < 0.05 was considered significant. Results: There was no significant difference in systolic blood pressure and diastolic blood pressure (DBP) between study group and control group following mental stress. In the time domain analysis, the mean value of pNN50 and RMSSD of the study group was not significantly different from the control group after the mental stress test. Conclusion: The study thus concluded that there was no significant difference in HRV between study group and control group following mental stress.

Keywords: heart rate variability, time domain analysis, mental stress, hypertensive

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Authors: A. Qayed Al-Emadi, C. Schwabenland, Q. Wei, B. Czarnecka

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In 2009, the new HRM policy was implemented in Qatar for public sector organisations. The purpose of this research is to examine how Qatar’s 2009 HRM policy was significant in influencing employee retention in public organisations. The conducted study utilised quantitative methodology to analyse the data on employees’ perceptions of such HRM practices as performance çanagement, rewards and promotion, training and development associated with the HRM policy in public organisations in comparison to semi-private organisations. Employees of seven public and semi-private organisations filled in the questionnaire based on the 5-point likert scale to present quantitative results. The data was analysed with the correlation and multiple regression statistical analyses. It was found that Performance Management had the relationship with Employee Retention, and Rewards and Promotion influenced Job Satisfaction in public organisations. The relationship between Job Satisfaction and Employee Retention was also observed. However, no significant differences were observed in the role of HRM practices in public and semi-private organisations.

Keywords: performance management, rewards and promotion, training and development, job satisfaction, employee retention, SHRM, configurational perspective

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Authors: Tamara Thompson

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This presentation will address the vocality of American soprano Sibyl Sanderson (1865–1903) in Massenet’s Manon and Esclarmonde as discernible from documentary sources such as vocal treatises, annotated scores, and correspondence. These sources will then be compared and contrasted with Sanderson’s reception in French press. Sanderson sang Manon in 1888, which Massenet revised for her. She then created the role of Esclarmonde for the 1889 l'Exposition Universelle in Paris. The soprano appeared as the Byzantine Empress more than 100 times in the nine months following the premiere, which secured her fame and an international operatic career frought with controversy and criticism as well as adulation. Before her débuts as Manon and Esclarmonde, Sanderson received musical training in California and Paris from multiple teachers with varied and opposing methods. There will be an exploration of the ways in which the disparate pedagogic influences such as those taught by Giovanni Sbriglia and Jean de Reszké may have guided Sanderson’s vocal strategies, and possibly caused or promoted the severe vocal pathologies she battled in subsequent years. In addition, there is interrogation of the vocal writing and revisions made to the titular roles for Sanderson in order to assess how these factors may have affected her technique and vocal health.

Keywords: French, nineteenth-century, opera, pedagogy, vocality

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Authors: Muhammad Yayat Afianto, Darmawan, Agung Putra Utama, Hari Kushardanto

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Fish Forever, Rare’s innovative coastal fisheries program, combined community-based conservation management approach with spatial management to restore and protect Indonesia’s small-scale fisheries by establishing Fishing Managed Access Area. A ‘TURF-Reserve’ is a fishery management approach that positions fishers at the center of fisheries management, empowering them to take care of and make decisions about the future of their fishery. After two years of the program, social marketing campaigns succeeded in changing their behavior by adopting the new conservation behavior. The Pride-TURF-R campaigns developed an overarching hypothesis of impact that captured the knowledge, attitude and behavior changes needed to reduce threats and achieve conservation results. Rare help Batu Belah fishers to develop their group, developed with their roles, sustainable fisheries plan, and the budget plan. On 12th February 2017, the Head of Loka Kawasan Konservasi Perairan Nasional (LKKPN) which is a Technical Implementation Unit for National Marine Conservation Areas directly responsible to the Directorate General for Marine Spatial Management in the Ministry of Marine Affairs and Fisheries had signed a Partnership Agreement with the Head of Batu Belah Village to manage a TURF+Reserve area as wide as 909 hectares. The fishers group have been collecting the catch and submitting the report monthly, initiated the installation of the buoy markers for the No Take Zone, and formed the Pokmaswas (community-based surveillance group). Prior to this behavior adoption, they don’t have any fisheries data, no group of fishers, and they have still fishing inside the No Take Zone. This is really a new behavior adoption for them. This paper will show the process and success story of the social marketing campaign to conserve marine habitat in Anambas through Pride-TURF-R program.

Keywords: behavior adoption, community participation, no take zone, pride-TURF-R

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Authors: Jin Lin, Shouxiang Lu, Kim Meow Liew

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The requirement for the long-term mission of the submarine and spacecraft has made the removal of CO₂ and trace CO the critical technology to ensure the health and life of the crews. In this work, CuMnCe, a metal oxide catalyst, supporting K₂CO₃ sorbent was prepared by the wet-solid state impregnation method to realize the integrated CO and CO₂ removal, which might also reduce the volume/mass load of the purification units in the limited space. The as-prepared samples with different addition amount of K₂CO₃ were tested using the fixed bed reactor to reveal the CO oxidation and CO₂ absorption behavior. And the regeneration and stability experiments were also conducted. The results showed that the samples realized the catalyst and sorbent integration to capture CO and CO₂ at the same time. The addition amount of the sorbent had a weak influence on the CO oxidation performance. While the addition amount affected the CO₂ sorption efficiency and capacity significantly. Meanwhile, the presence of water vapor could reduce the CO oxidation activity of the samples similarly, whether with K2CO3 sorbent addition or not. Furtherly, regeneration and stability experiment results showed that the samples after 3-5 times regeneration exhibited almost the same performance of CO and CO₂ removal. Summarily, CuMnCe catalyst supporting K₂CO₃ sorbent could be a good attempt to control CO and CO₂ pollutants generated from the daily equipment running and staff breathing in the confined space such as submarine and spacecraft.

Keywords: CO oxidation, CO₂ absorptio, potassium carbonate, CuMnCe metal oxide, confined space

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Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

Procedia PDF Downloads 153