Search results for: gradient training method

Authors: V. Radulescu, S. Dumitru

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Introduction: Determination of the temperature field inside a fluid in motion has many practical issues, especially in the case of turbulent flow. The phenomenon is greater when the solid walls have a different temperature than the fluid. The turbulent heat and mass transfer have an essential role in case of the thermal pollution, as it was the recorded during the damage of the Thermoelectric Power-plant Oradea (closed even today). Basic Methods: Solving the theoretical turbulent thermal pollution represents a particularly difficult problem. By using the semi-empirical theories or by simplifying the made assumptions, based on the experimental measurements may be assured the elaboration of the mathematical model for further numerical simulations. The three zones of flow are analyzed separately: the vicinity of the solid wall, the turbulent transition zone, and the turbulent core. For each area are determined the distribution law of temperature. It is determined the dependence of between the Stanton and Prandtl numbers with correction factors, based on measurements experimental. Major Findings/Results: The limitation of the laminar thermal substrate was determined based on the theory of Landau and Levice, using the assumption that the longitudinal component of the velocity pulsation and the pulsation’s frequency varies proportionally with the distance to the wall. For the calculation of the average temperature, the formula is used a similar solution as for the velocity, by an analogous mediation. On these assumptions, the numerical modeling was performed with a gradient of temperature for the turbulent flow in pipes (intact or damaged, with cracks) having 4 different diameters, between 200-500 mm, as there were in the Thermoelectric Power-plant Oradea. Conclusions: It was made a superposition between the molecular viscosity and the turbulent one, followed by addition between the molecular and the turbulent transfer coefficients, necessary to elaborate the theoretical and the numerical modeling. The concept of laminar boundary layer has a different thickness when it is compared the flow with heat transfer and that one without a temperature gradient. The obtained results are within the margin of error of 5%, between the semi-empirical classical theories and the developed model, based on the experimental data. Finally, it is obtained a general correlation between the Stanton number and the Prandtl number, for a specific flow (with associated Reynolds number).

Keywords: experimental measurements, numerical correlations, thermal pollution through pipelines, turbulent thermal flow

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Authors: Jiří Barta

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The paper deals with simulation programs of spread of harmful substances. Air pollution has a direct impact on the quality of human life and environmental protection is currently a very hot topic. Therefore, the paper focuses on the simulation of release of harmful substances. The first part of article deals with perspectives and possibilities of implementation outputs of simulations programs into the system which is education and of practical training of the management staff during emergency events in the frame of critical infrastructure. The last part shows the practical testing and evaluation of simulation programs. Of the tested simulations software been selected Symos97. The tool offers advanced features for setting leakage. Gradually allows the user to model the terrain, location, and method of escape of harmful substances.

Keywords: Computer Simulation, Symos97, Spread, Simulation Software, Harmful Substances

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Authors: Martha Salinas, Valkyria Bernal

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Creativity is a possible response to the profound social, economic, and global changes society is living and education is the source to develop this kind of capacity. However, institutional pressures often prevent teachers from engaging in creative teaching practices and make innovation not the main curricular focus when building learning scenarios and experiences. This study proposes and validates the use of a prototype of Educative Video – Capsules from the perspective of teacher training, presenting the different stages of design, the content plan, as well as the influences of its components and characteristics from the perspective of creativity. The paper presents literature findings of the factors that influence the innovative behavior of teachers, the beliefs of teachers about creativity and its nature, as well as the creative pedagogies that have generated better results. The results show that the disposition of teachers towards creative pedagogies improves significantly with the use of a tool that is based on the principles of microlearning and is developed in a non-academic, autonomous, and non-imposed family environment as traditional teacher training processes usually occur.

Keywords: educational innovation, resistance to innovation, creativity, creative pedagogy

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Authors: Sara Nasiri Semnani, Alireza Ramzani

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Background and Aims: Sodium bicarbonate is a supplementation that used to reduce fatigue and increase power output in short-term training. On the other hand, the Ischemic Reperfusion Preconditioning (IRPC) is an appropriate stimulus to increase the submaximal contractile response. Materials and methods: 9 female student-athletes in double-blind randomized crossover design were three mode, sodium bicarbonate + IRPC, sodium bicarbonate and placebo+ IRPC. Participants moved forward single arm dumbbell hand with a weight of 2 kg can be carried out most frequently. Results: The results showed that plasma lactate concentration and records of sodium bicarbonate + IRPC and sodium bicarbonate conditions were significantly different compared to placebo + IRPC (Respectively p=0.001, p=0/02). Conclusion: According to the research findings, bicarbonate supplementation in IRPC training condition increased force and delay fatigue in submaximal dynamic contraction.

Keywords: ischemic reperfusion, preconditioning, sodium bicarbonate, submaximal dynamic force

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Authors: Nana Weng

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Localization in the aspect of human resource means more diversity and more opportunities. The main purpose of this article is to identify the perception of local employees and intermediate managers (non-Japanese) and figure out exploratory factors which have been contributing and blocking the level of localization in the aspect of human resource management by using EFA (Exploratory Factors Analysis). Questionnaires will be designed for local employees and managers to inquire about the perceptions of regulations and implementation regarding recruitment, training and development, promotion and rewarding. The study finds that Japanese firms have worked well in the process of localization, especially in hiring and training local staffs in Taiwan. The significance of this study lies in paying more attention to the perception of local employees and intermediate managers regarding localization rather than interviews results from Japanese expatriates or top HR managers who are in charging of localization policy-making.

Keywords: Japanese firms in Taiwan, localization of human resources, exploratory factors analysis, local employees and intermediate managers

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Authors: Dawit Assefa, Kassaye Tekie, Gebrie Alebachew, Degefu Beyene, Bikila Alemu, Naji Mohammed, Asnakech Agegnehu, Seble Tsehay, Geremew Tasew

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Background: Implementation of a Laboratory Quality Management System (LQMS) is critical to ensure accurate, reliable, and efficient laboratory testing of antimicrobial resistance (AMR). However, limited LQMS implementation and progress toward accreditation in the AMR surveillance laboratory testing setting exist in Ethiopia. By addressing non-conformances (NCs) and working towards accreditation, microbiology laboratories can improve the quality of their services, increase staff competence, and contribute to mitigate the spread of AMR. Methods: Using standard ISO 15189 horizontal and vertical assessment checklists, certified assessors identified NCs at Hawassa and Jimma Hospital microbiology laboratories. The Ethiopian Public Health Institute AMR mentors and IDDS staff prioritized closing the NCs through the implementation of an intensified mentorship program that included ISO 15189 orientation training, resource allocation, and action plan development. Results: For the two facilities to clear their NCs, an intensified mentorship approach was adopted by providing ISO 15189 orientation training, provision of buffer reagents, controls, standards, and axillary equipment, and facilitating equipment maintenance and calibration. Method verification and competency assessment were also conducted along with the implementation of standard operating procedures and recommended corrective actions. This approach enhanced the laboratory's readiness for accreditation. After addressing their NCs, the two laboratories applied to Ethiopian Accreditation Services for ISO 15189 accreditation. Conclusions: Clearing NCs through the implementation of intensified mentorship was crucial in preparing the two laboratories for accreditation and improving quality laboratory test results. This approach can guide other microbiology laboratories’ accreditation attainment efforts.

Keywords: non-conformance clearance, intensified mentorship, accreditation, ISO 15189

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Authors: Imen Debbabi, Hédi BelHadjSalah

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The Improved Element Free Galerkin (IEFG) method is presented to treat the steady states and the transient heat transfer problems. As a result of a combination between the Improved Moving Least Square (IMLS) approximation and the Element Free Galerkin (EFG) method, the IEFG's shape functions don't have the Kronecker delta property and the penalty method is used to impose the Dirichlet boundary conditions. In this paper, two heat transfer problems, transient and steady states, are studied to improve the efficiency of this meshfree method for 2D heat transfer problems. The performance of the IEFG method is shown using the comparison between numerical and analytic results.

Keywords: meshfree methods, the Improved Moving Least Square approximation (IMLS), the Improved Element Free Galerkin method (IEFG), heat transfer problems

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Authors: Philippe Judlin, Olivier Morel

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Background: In France, the resident curriculum (RC) in Obstetrics and Gynecology (OBGYN) takes five years. In the course of the last 15 years, this RC has undergone major changes, characterized mainly by successive reductions of work hours. The program used to comprise long and frequent shifts, huge workload, poor supervision and erratic theoretical teaching. A decade ago, the French Ministry of Heath recommended a limitation of shift duration up to 24 hours and a minimum of 11 hours off duty between shifts. Last year, in order to comply with European Union directives, new recommendations have further limited residents’ work hours to 48 hours per week. Methods: Assessment of the residency program adjustments recently made to accommodate the recommendations while improving the training quality in resorting to new methods. Results: The challenge facing program directors was to provide an all-encompassing curriculum to OBGYN residents despite fewer work hours. Program has been dramatically redesigned, and several measures have been put in place: -The resident rotation system has been redesigned. Residents used to make 6-month rotations between 10-12 Departments of OBGYN or Surgery. Fewer Departments, those providing the best teaching, have been kept in the new RC. -Extensive inhouse supervision has been implemented for all kinds of clinical activities. Effectual supervision of residents has proved to be an effective tool to improve the quality of training. -The tutorship system, with academic members individually overseeing residents during their curriculum, has been perfected. It allows a better follow-up of residents’ progresses during the 5-year program. -The set up of an extensive program of lectures encompassing all maters in Obstetrics & Gynecology. These mandatory lectures are available online in a dedicated website. Therefore, face-to-face lectures have been limited in order to fit in the 48-hour limit. -The use of simulation has been significantly increased in obstetrics, materno-fetal medicine and surgery (stressing especially laparoscopic training). -Residents’ feedback has been taken into account in the setup of the new RC. Conclusion: This extensive overhaul of the Obstetrics and Gynecology RC has been in place since last year only. Nevertheless, the new program seems to adequately take into account the new recommendations while providing a better and more consistent teaching to the OBGYN residents.

Keywords: education, laparoscopy, residency, simulation

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Authors: Elissar Mansour, Emily Chen, Tracee Fernandez, Mariam Basheti, Christopher Gordon, Bandana Saini

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Sleep is an essential process for the maintenance of several neurobiological processes such as memory consolidation, mood, and metabolic processes. It is known that sleep patterns vary with age and is affected by multiple factors. While non-pharmacological strategies are generally considered first-line, sedatives are excessively used in the older population. This study aimed to explore the management of sleep in residential aged care facilities (RACFs) by nurse professionals and to identify the key factors that impact provision of optimal sleep health care. An inductive thematic qualitative research method was employed to analyse the data collected from semi-structured interviews with registered nurses working in RACF. Seventeen interviews were conducted, and the data yielded three themes: 1) the nurses’ observations and knowledge of sleep health, 2) the strategies employed in RACF for the management of sleep disturbances, 3) the organizational barriers to evidence-based sleep health management. Nurse participants reported the use of both non-pharmacological and pharmacological interventions. Sedatives were commonly prescribed due to their fast action and accessibility despite the guidelines indicating their use in later stages. Although benzodiazepines are known for their many side effects, such as drowsiness and oversedation, temazepam was the most commonly administered drug. Sleep in RACF was affected by several factors such as aging and comorbidities (e.g., dementia, pain, anxiety). However, the were also many modifiable factors that negatively impacted sleep management in RACF. These include staffing ratios, nursing duties, medication side effects, and lack of training and involvement of allied health professionals. This study highlighted the importance of involving a multidisciplinary team and the urge to develop guidelines and training programs for healthcare professionals to improve sleep health management in RACF.

Keywords: registered nurses, residential aged care facilities, sedative use, sleep

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Authors: Thi Chang Duyen Can

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Althoughthe COVID-19 epidemic is under control, online education technology in Vietnam will still thrive in the learner-centered trend. Most of the Vietnamese students are now ready to familiarize themselves with and access to online learning. Even in some cases, online learning, if combined with new tools, is far more effective and exciting for students than some traditional instruction. However, little research has been conducted to explore Vietnamese teachers’ difficulties in moderating learner-centered E-learning. Therefore, the study employed the mixed method (n=9) to (i) uncover the challenges faced by Vietnamese teachers in English language online classes using learner-centred approach and (ii) propose the recommendations to improve the quality of online training in universities.

Keywords: learner-centered e-learning, english language classes, teachers' challenges, online learning

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Authors: Tanimola Kazeem Abiodun

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In Nigeria, both formal education and distance learning opportunities are used in teacher training. Practical courses aim to improve the skills of teacher candidates in a school environment. Teacher candidates attend kindergarten classes under the supervision of a teacher. In this context, the guiding skills of teachers gain importance in terms of shaping candidates’ perceptions about teaching profession. In this study, the teachers’ perceptions related to the guiding skills within the practical courses were determined. Also, the perceptions and applications related to guiding skills were compared. A Likert scale questionnaire and an open-ended question were used to determine perceptions and applications. 120 questionnaires were taken into consideration and analyses of data were performed by using percentage distribution and QSR Nvivo 8 program. In this study, statements related to teachers’ perceptions about the guiding skills were asked and it is determined that almost all the teachers agreed about the importance of these statements. On the other hand, how these guidance skills are applied by teachers is also queried with an open-ended question. Finally, thoughts and applications related to guidance skills were compared to each other. Based on this comparison, it is seen that there are some differences between the thoughts and applications especially related with time management, planning, feedbacks, curriculum, workload, rules and guidance. It can be said that some guidance skills cannot be controlled only by teachers. For example, candidates’ motivation, attention, population and educational environment are also determinative factors for effective guidance. In summary, it is necessary to have prior conditions for teachers to apply these idealized guidance skills for training more successful candidates to pre-school education era. At this point, organization of practical courses by the faculties gains importance and in this context it is crucial for faculties to revise their applications based on more detailed researches.

Keywords: teacher training, guiding skills, education, practical courses

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Authors: S. M. Ishtiaque, V. K. Yadav, S. D. Joshi, J. K. Chatterjee

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The DIAMETRIC FAULTS system has been developed that captures a bi-directional image of yarn continuously in sequentially manner and provides the detailed classification of faults. A novel mathematical framework developed on the acquired bi-directional images forms the basis of fault classification in four broad categories, namely, Thick1, Thick2, Thin and Normal Yarn. A discretised version of Radon transformation has been used to convert the bi-directional images into one-dimensional signals. Images were divided into training and test sample sets. Karhunen–Loève Transformation (KLT) basis is computed for the signals from the images in training set for each fault class taking top six highest energy eigen vectors. The fault class of the test image is identified by taking the Euclidean distance of its signal from its projection on the KLT basis for each sample realization and fault class in the training set. Euclidean distance applied using various techniques is used for classifying an unknown fault class. An accuracy of about 90% is achieved in detecting the correct fault class using the various techniques. The four broad fault classes were further sub classified in four sub groups based on the user set boundary limits for fault length and fault volume. The fault cross-sectional area and the fault length defines the total volume of fault. A distinct distribution of faults is found in terms of their volume and physical dimensions which can be used for monitoring the yarn faults. It has been shown from the configurational based characterization and classification that the spun yarn faults arising out of mass variation, exhibit distinct characteristics in terms of their contours, sizes and shapes apart from their frequency of occurrences.

Keywords: Euclidean distance, fault classification, KLT, Radon Transform

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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This paper presents an iteration method for the numerical solutions of a one-dimensional problem of generalized thermoelasticity with one relaxation time under given initial and boundary conditions. The thermoelastic material with variable properties as a power functional graded has been considered. Adomian’s decomposition techniques have been applied to the governing equations. The numerical results have been calculated by using the iterations method with a certain algorithm. The numerical results have been represented in figures, and the figures affirm that Adomian’s decomposition method is a successful method for modeling thermoelastic problems. Moreover, the empirical parameter of the functional graded, and the lattice design parameter have significant effects on the temperature increment, the strain, the stress, the displacement.

Keywords: Adomian, decomposition method, generalized thermoelasticity, algorithm

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Authors: Meaghan Bowman

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Soldiers are taught about the importance of effective communication with repetition of the phrase, “Communication is key.” They receive training in preparing for, and carrying out, interactions between foreign and domestic leaders to gain crucial information about a mission. These interactions are known as Key Leader Engagements (KLEs). For the training of KLEs, doctrine mandates the skills needed to conduct these “engagements” such as how to: behave appropriately, identify key leaders, and employ effective strategies. Army officers in training learn how to confront leaders, what information to gain, and how to ask questions respectfully. Unfortunately, soldiers rarely learn how to formulate questions optimally. Since less complex questions are easier to understand, we hypothesize that semantic complexity affects content understanding, and that age and education levels may have an effect on one’s ability to form paraphrases and judge their quality. In this study, we looked at paraphrases of queries as well as judgments of both the paraphrases’ naturalness and their semantic similarity to the query. Queries were divided into three complexity categories based on the number of relations (the first number) and the number of knowledge graph edges (the second number). Two crowd-sourced tasks were completed by Amazon volunteer participants, also known as turkers, to answer the research questions: (i) Are more complex queries harder to paraphrase and judge and (ii) Do age and education level affect the ability to understand complex queries. We ran statistical tests as follows: MANOVA for query understanding and two-way ANOVA to understand the relationship between query complexity and education and age. A probe of the number of given-level queries selected for paraphrasing by crowd-sourced workers in seven age ranges yielded promising results. We found significant evidence that age plays a role and marginally significant evidence that education level plays a role. These preliminary tests, with output p-values of 0.0002 and 0.068, respectively, suggest the importance of content understanding in a communication skill set. This basic ability to communicate, which may differ by age and education, permits reproduction and quality assessment and is crucial in training soldiers for effective participation in KLEs.

Keywords: engagement, key leader, paraphrasing, query complexity, understanding

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: artificial neural network, data mining, electroencephalogram, epilepsy, feature extraction, seizure detection, signal processing

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Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

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The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

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Authors: Kadhim Alabady

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Background: Autism poses a particularly large public health challenge and an inspiring lifelong challenge for many families; it is a lifelong challenge of a different kind. Purpose: Therefore, it is important to understand what the key challenges are and how to improve the lives of children who are affected with autism in Dubai. Method: In order to carry out this research we have used a qualitative methodology. We performed structured in–depth interviews and focus groups with mental health professionals working at: Al Jalila hospital (AJH), Dubai Autism Centre (DAC), Dubai Rehabilitation Centre for Disabilities, Latifa hospital, Private Sector Healthcare (PSH). In addition to that, we conducted quantitative approach to estimate ASD prevalence or incidence data due to lack of registry. ASD estimates are based on research from national and international documents. This approach was applied to increase the validity of the findings by using a variety of data collection techniques in order to explore issues that might not be highlighted through one method alone. Key findings: Autism is the most common of the Pervasive Developmental Disorders. Dubai Autism Center estimates it affects 1 in 146 births (0.68%). If we apply these estimates to the total number of births in Dubai for 2014, it is predicted there would be approximately 199 children (of which 58 were Nationals and 141 were Non–Nationals) suffering from autism at some stage. 16.4% of children (through their families) seek help for ASD assessment between the age group 6–18+. It is critical to understand and address factors for seeking late–stage diagnosis, as ASD can be diagnosed much earlier and how many of these later presenters are actually diagnosed with ASD. Autism spectrum disorder (ASD) is a public health concern in Dubai. Families do not consult GPs for early diagnosis for a variety of reasons including cultural reasons. Recommendations: Effective school health strategies is needed and implemented by nurses who are qualified and experienced in identifying children with ASD. There is a need for the DAC to identify and develop a closer link with neurologists specializing in Autism, to work alongside and for referrals. Autism can be attributed to many factors, some of those are neurological. Currently, when families need their child to see a neurologist they have to go independently and search through the many that are available in Dubai and who are not necessarily specialists in Autism. Training of GP’s to aid early diagnosis of Autism and increase awareness. Since not all GP’s are trained to make such assessments increasing awareness about where to send families for a complete assessment and the necessary support. There is an urgent need for an adult autism center for when the children leave the safe environment of the school at 18 years. These individuals require a day center or suitable job training/placements where appropriate. There is a need for further studies to cover the needs of people with an Autism Spectrum Disorder (ASD).

Keywords: autism spectrum disorder, autism, pervasive developmental disorders, incidence

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Authors: Khairil I. Othman, Mahfuzah Mahayaddin, Zarina Bibi Ibrahim

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We develop and demonstrate a computationally efficient numerical technique to solve first order stiff differential equations. This technique is based on block method whereby three approximate points are calculated. The Cholistani of varied step sizes are presented in divided difference form. Stability regions of the formulae are briefly discussed in this paper. Numerical results show that this block method perform very well compared to existing methods.

Keywords: block method, divided difference, stiff, computational

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Authors: Kathleen L. Seifert

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Students with special needs are expected to achieve the same academic standards as their general education peers, yet many students with special needs are pulled-out of general content instruction. Because of this, many students with special needs are denied content knowledge from a content expert and instead receive content instruction in a more restrictive setting. Collaborative teaching, where a general education and special education teacher work alongside each other in the same classroom, has become increasingly popular as a means to meet the diverse needs of students in America’s public schools. The idea behind co-teaching is noble; to ensure students with special needs receive content area instruction from a content expert while also receiving the necessary supports to be successful. However, in spite of this noble effort, the effects of co-teaching are not always positive. The reasons why have produced several hypotheses, one of which has to do with lack of proper training and implementation of effective evidence-based co-teaching practices. In order to examine the effects of co-teacher training, eleven teaching pairs from a small mid-western school district in the United States participated in a study. The purpose of the study was to examine the effects of co-teacher training on middle and high school student achievement in Math and Language Arts. A local university instructor provided teachers with training in co-teaching via a three-day workshop. In addition, co-teaching pairs were given the opportunity for direct observation and feedback using the Co-teaching Core Competencies Observation Checklist throughout the academic year. Data are in the process of being collected on both the students enrolled in the co-taught classes as well as on the teachers themselves. Student data compared achievement on standardized assessments and classroom performance across three domains: 1. General education students compared to students with special needs in co-taught classrooms, 2. Students with special needs in classrooms with and without co-teaching, 3. Students in classrooms where teachers were given observation and feedback compared to teachers who refused the observation and feedback. Teacher data compared the perceptions of the co-teaching initiative between teacher pairs who received direct observation and feedback from those who did not. The findings from the study will be shared with the school district and used for program improvement.

Keywords: collabortive teaching, collaboration, co-teaching, professional development

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Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

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Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: Ioanna Koumi

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The aim of the intervention presented is to show the positive effects a mindfulness programme can have on the behaviour of preschoolers (years 4-6). The programme was implemented as part of the psychologist's work in 5 preschool units on the Greek island of Chios. Classroom-based activities of mindfulness were shown and practiced in 5 sessions, in collaboration with teachers, in order to make preschoolers aware of how their brain affects their behaviour, as well as of how they can have more positive behaviours, especially in instances of negative feelings. The outcomes of the intervention were assessed via questionnaire completion before and after the sessions by the teachers, as well as focus groups procedures with students, teachers, and parents. Implications of how mindfulness programmes can also be implemented at home are further discussed. School year in which the programme is being implemented: 2022-23 Intervention method: based on basic mindfulness theory and practice, the 220 students (age 4-6) in 11 classes of the 5 preschools that participated were given lessons of how to become aware of their states of focusing, regulation, attention, emotional situation, as well as body and social situations. Furthermore, the preschoolers were encouraged to make more mindful choices when it came to negative situations and emotions. Assessment method: The school as a caring community Profile II – Questionnaire completed by 20 preschool teachers prior to and after the intervention, Focus group sessions with teachers, students, parents at the end of the intervention Results: the assessment will be completed in May 2023.

Keywords: preschool, mindfulness training, self-awareness, social-emotional development

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Authors: H. Majour, L. Djabri

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Many methods in the groundwater vulnerability have been developed in the world (methods like PRAST, DRIST, APRON/ARAA, PRASTCHIM, GOD). In this study, our choice dealt with two recent complementary methods using category mapping of index with weighting criteria (Point County Systems Model MSCP) namely the standard DRASTIC method and SI (Susceptibility Index). At present, these two methods are the most used for the mapping of the intrinsic vulnerability of groundwater. Two classes of groundwater vulnerability in the Biskra sandy aquifer were identified by the DRASTIC method (average and high) and the SI method (very high and high). Integrated analysis has revealed that the high class is predominant for the DRASTIC method whereas for that of SI the preponderance is for the very high class. Furthermore, we notice that the method SI estimates better the vulnerability for the pollution in nitrates, with a rate of 85 % between the concentrations in nitrates of groundwater and the various established classes of vulnerability, against 75 % for the DRASTIC method. By including the land use parameter, the SI method produced more realistic results.

Keywords: DRASTIC, SI, GIS, Biskra sandy aquifer, Algeria

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Authors: Fazlul Karim, Esa Al-Islam

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Many problems in oceanography and environmental sciences require the solution of shallow water equations on physical domains having curvilinear coastlines and abrupt changes of ocean depth near the shore. Finite-difference technique for the shallow water equations representing the boundary as stair step may give inaccurate results near the coastline where results are of greatest interest for various applications. This suggests the use of methods which are capable of incorporating the irregular boundary in coastal belts. At the same time, large velocity gradient is expected near the beach and islands as water depth vary abruptly near the coast. A nested numerical scheme with fine resolution is the best resort to enhance the numerical accuracy with the least grid numbers for the region of interests where the velocity changes rapidly and which is unnecessary for the away of the region. This paper describes the development of a boundary fitted nested grid (BFNG) model to compute tsunami propagation of 2004 Indonesian tsunami in Southern Thailand coastal waters. In this paper, we develop a numerical model employing the shallow water nested model and an orthogonal boundary fitted grid to investigate the tsunami impact on the Southern Thailand due to the Indonesian tsunami of 2004. Comparisons of water surface elevation obtained from numerical simulations and field measurements are made.

Keywords: Indonesian tsunami of 2004, Boundary-fitted nested grid model, Southern Thailand, finite difference method

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

Abstract:

A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

Abstract:

The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

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Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

Abstract:

Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

Procedia PDF Downloads 118

Authors: Jui-Chen Huang

Abstract:

The purpose of this study is to explore the effects of telecare on preventing and delaying the quality of disability care in elderly people with portable comfort Bluetooth brainwave devices with remote healthcare functions. Through the teaching videos and remotely teaching the elderly, which had ever learned the care courses of the prevent and delay disability, these elderly did muscle strength training. Then this paper explores the effect of training with the data by SPSS 18.0 statistical software. The data is collected with pre-test, post-test and analyze data from the measure of the Bluetooth brain wave equipment including the pressure index, relaxation index, attention and fatigue index of the elderly. In this study, 30 elderly people who had taken preventive and delayed disability care courses were studied to explore the effect of their care quality improvement. The results showed that the pressure index, relaxation index, attention, and fatigue index of the elderly had statistically significant differences in two months. It can be seen that elderly people who have been treated to prevent and delay disability care courses can significantly improve their care quality if they continue to receive intensive training to prevent and delay disability through remote mode. This telecare is applied to the elderly program that has been used to prevent and delay disability care courses. It is worth continuing to promote, and it is recommended that follow-up studies be conducted in a longer-term manner to explore long-term benefits. It can solve the current insufficiency of long-term care resources, but the demand is urgent.

Keywords: telecare, bluetooth brainwave equipment, prevention and delay of disability, the elderly, care quality

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Authors: Philip A. Szlosek, M. Susan Guyer, Mary G. Barnum, Elizabeth M. Mullin

Abstract:

In the United States, athletic training is a healthcare profession that encompasses the prevention, examination, diagnosis, treatment, and rehabilitation of injuries and medical conditions. Athletic trainers work under the direction of or in collaboration with a physician and are recognized by the American Medical Association as allied healthcare professionals. Internationally, this profession is often known as athletic therapy. As healthcare professionals, athletic trainers must be prepared for autonomous practice immediately after graduation. However, new athletic trainers have been shown to have clinical areas of strength and weakness.To better assess professional readiness and improve the preparedness of new athletic trainers, the factors of athletic training professional readiness must be defined. Limited research exists defining the holistic aspects of professional readiness needed for athletic trainers. Confirming the factors of professional readiness in athletic training could enhance the professional preparation of athletic trainers and result in more highly prepared new professionals. The objective of this study was to further explore and confirm the factors of professional readiness in athletic training. Authors useda qualitative design based in grounded theory. Participants included athletic trainers with greater than 24 months of experience from a variety of work settings from each district of the National Athletic Trainer’s Association. Participants took the demographic questionnaire electronically using Qualtrics Survey Software (Provo UT). After completing the demographic questionnaire, 20 participants were selected to complete one-on-one interviews using GoToMeeting audiovisual web conferencing software. IBM Statistical Package for the Social Sciences (SPSS, v. 21.0) was used to calculate descriptive statistics for participant demographics. The first author transcribed all interviews verbatim and utilized a grounded theory approach during qualitative data analysis. Data were analyzed using a constant comparative analysis and open and axial coding. Trustworthiness was established using reflexivity, member checks, and peer reviews. Analysis revealed four overarching themes, including management, interpersonal relations, clinical decision-making, and confidence. Management was categorized as athletic training services not involving direct patient care and was divided into three subthemes, including administration skills, advocacy, and time management. Interpersonal Relations was categorized as the need and ability of the athletic trainer to properly interact with others. Interpersonal relations was divided into three subthemes, including personality traits, communication, and collaborative practice. Clinical decision-making was categorized as the skills and attributes required by the athletic trainer whenmaking clinical decisions related to patient care. Clinical decision-making was divided into three subthemes including clinical skills, continuing education, and reflective practice. The final theme was confidence. Participants discussed the importance of confidence regarding relationships building, clinical and administrative duties, and clinical decision-making. Overall, participants explained the value of a well-rounded athletic trainer and emphasized that athletic trainers need communication and organizational skills, the ability to collaborate, and must value self-reflection and continuing education in addition to having clinical expertise. Future research should finalize a comprehensive model of professional readiness for athletic training, develop a holistic assessment instrument for athletic training professional readiness, and explore the preparedness of new athletic trainers.

Keywords: autonomous practice, newly certified athletic trainer, preparedness for professional practice, transition to practice skills

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Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 127