Search results for: distributed training

Authors: Nabil A. Albaser

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Background: There is a serious problem with adverse drug reactions (ADRs) everywhere, including Yemen. Since it helps with the detection, assessment, reporting and prevention of ADRs, pharmacovigilance (PV) is an essential part of the healthcare system. The unbiased reporting of ADRs remains the foundation of PV. Students majoring in healthcare should acquire the knowledge and skills necessary to conduct PV in a range of clinical settings. The primary objective of this study was to evaluate the understanding and attitudes of final-year Pharmacy, Nursing, and Midwifery students at Al-Razi University in Sana'a, Yemen, regarding PV and ADRs reporting. Methods: The study followed descriptive cross-sectional approach. A validated, self-administered questionnaire with three parts—demographic information, knowledge, and perceptions of Pharmacovigilance was online distributed to final-year Pharmacy, Nursing, and Midwifery students. The questionnaire was given to 175 students; 122 of them responded with a percentage (69.7%). Results: The majority of respondents were male (79.5%). More than the tow-third of the students, 68.9%, were beyond the age of 23. Although the majority of students, 80%, heard about the terms of ADRs and PV, but only 50% and 57.4% of the respondents, respectively, could define the both terms correctly. However, only 11.48 % of them, nevertheless, took a PV course. More than a half of them (56.6%) had a positive perceptions towards pharmacovigilance and ADR reporting and had a moderate degree of knowledge (68.9%). Conclusion: The study demonstrated that the participants lacked sufficient knowledge of pharmacovigilance and ADR reporting. They showed a moderate level of understanding of reporting ADRs as well as a favorable opinion of dealing with and reporting ADRs. Yemen's health care curriculum should include lessons on pharmacovigilance.

Keywords: adverse drug reaction reporting, pharmacovigilance, yemen, knowlegde

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Authors: Salina Budin, Shaira Ismail

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Students learn effectively in a learning environment with a suitable teaching approach that matches their learning preferences. The main objective of the study is to examine the learning preferences amongst the students in the Science and Technology (S&T), and Social Science (SS) fields of study at the Universiti Teknologi Mara (UiTM), Pulau Pinang. The measurement instrument is based on the Dunn and Dunn Learning Styles which measure five elements of learning styles; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering and Faculty of Business Management. The respondents comprise of 131 diploma students of the Faculty of Mechanical Engineering and 111 degree students of the Faculty of Business Management. The results indicate that, both S&T and SS students share a similar learning preferences on the environmental aspect, emotional preferences, motivational level, learning responsibility, persistent level in learning and learning structure. Most of the S&T students are concluded as analytical learners and the majority of SS students are global learners. Both S&T and SS students are concluded as visual learners, preferred to be in an active mobility in a relaxing and enjoying mode with some light of refreshments during the learning process and exhibited reflective characteristics in learning. Obviously, the S&T students are considered as left brain dominant, whereas the SS students are right brain dominant. The findings highlighted that both categories of students exhibited similar learning preferences except on psychological preferences.

Keywords: learning preferences, Dunn and Dunn learning style, teaching approach, science and technology, social science

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Authors: Soni Nopembri

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The objective of this research is to evaluate the implementation of teaching games for Understanding model by conducting action to physical education teacher who have got long teaching experience. The research applied Participatory Action Research. The subjects of this research were 19 physical education teachers who had got training of Teaching Games for Understanding. Data collection was conducted intensively through a questionnaire, in-depth interview, Focus Group Discussion (FGD), observation, and documentation. The collected data was analysis zed qualitatively and quantitatively. The result showed that physical education teachers had got an appropriate interpretation on TGfU model. Some indicators that were the focus of this research indicated this points; they are: (1) physical education teachers had good understanding toward TGfU model, (2) PE teachers’ competence in applying TGfU model on Physical Education at school were adequate, though some improvement were needed, (3) the influence factors in the implementation of TGfU model, in sequence, were teacher, facilities, environment, and students factors, (4) PE teachers’ perspective toward TGfU model were positively good, although some teachers were less optimistic toward the development of TGfU model in the future.

Keywords: TGfU, physical education teacher, teaching games, FGD

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Authors: Iva Košek Bartošová, Andrea Jokešová, Eva Kozlová, Helena Matějová

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The paper presents results of a research team from Faculty of Education, University of Hradec Králové in the Czech Republic. It introduces with the most reading methods used in the 1^st classes of a primary school and presents results of a pilot research focused on mastering reading techniques and the quality of reading comprehension of pupils in the first half of a school year during training in teaching reading by an analytic-synthetic method and by a genetic method. These methods of practicing reading skills are the most used ones in the Czech Republic. During the school year 2015/16 there has been a measurement made of two groups of pupils of the 1^st year and monitoring of quantitative and qualitative parameters of reading pupils’ outputs by several methods. Both of these methods are based on different theoretical basis and each of them has a specific educational and methodical procedure. This contribution represents results during a piloting project and draws pilot conclusions which will be verified in the subsequent broader research at the end of the school year of the first class of primary school.

Keywords: analytic-synthetic method of reading, genetic method of reading, reading comprehension, reading literacy, reading methods, reading speed

Procedia PDF Downloads 245

Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Fakhrullah Sarwari, Hiroko Ono

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Kabul city has suffered a lot in 40 years of conflict of civil war and “The war on terror”. After the invasion of Afghanistan by the United States of America and its allies in 2001, the Taliban was removed from operational power, but The Taliban and other terrorist groups remained in remote areas of the country, they started suicide attacks and bombings. Hence to protect from these attacks officials surrounded their office buildings and houses with concrete blast walls. It gives a bad landscape to the city and creates traffic congestions. Our research contains; questionnaire, reviewing Kabul Municipality documents and literature review. Questionnaires were distributed to Kabul citizens to find out how people feel by seeing the T-Walls on Kabul streets? And what problems they face with T-Walls. “The T-Walls pull down commission” of Kabul Municipality documents were reviewed to find out what caused the failure of this commission. A literature review has been done to compare Kabul with Washington D.C on how they designed the city against terrorism threat without turning the cities into lock down. Bogota city of Columbia urban happiness movement is reviewed and compared with Kabul. The finding of research revealed that citizens of Kabul want security but not at the expense of public realm and creating the architecture of fear. It also indicates that increasing the T-walls do not give secure feeling but instead; it increases terror, hatred and affect people’s optimism. At the end, a series of recommendation is suggested on the issue.

Keywords: anti-terror design, Kabul, T-Walls, urban happiness

Procedia PDF Downloads 155

Authors: Radovan Bures, Madgalena Streckova, Maria Faberova, Pavel Kurek

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Composite material based on Fe3Si micro-particles and Mn-Zn nano-ferrite was prepared using powder metallurgy technology. The sol-gel followed by autocombustion process was used for synthesis of Mn0.8Zn0.2Fe2O4 ferrite. 3 wt.% of mechanically milled ferrite was mixed with Fe3Si powder alloy. Mixed micro-nano powder system was homogenized by the Resonant Acoustic Mixing using ResodynLabRAM Mixer. This non-invasive homogenization technique was used to preserve spherical morphology of Fe3Si powder particles. Uniaxial cold pressing in the closed die at pressure 600 MPa was applied to obtain a compact sample. Microwave sintering of green compact was realized at 800°C, 20 minutes, in air. Density of the powders and composite was measured by Hepycnometry. Impulse excitation method was used to measure elastic properties of sintered composite. Mechanical properties were evaluated by measurement of transverse rupture strength (TRS) and Vickers hardness (HV). Resistivity was measured by 4 point probe method. Ferrite phase distribution in volume of the composite was documented by metallographic analysis. It has been found that nano-ferrite particle distributed among micro- particles of Fe3Si powder alloy led to high relative density (~93%) and suitable mechanical properties (TRS >100 MPa, HV ~1GPa, E-modulus ~140 GPa) of the composite. High electric resistivity (R~6.7 ohm.cm) of prepared composite indicate their potential application as soft magnetic material at medium and high frequencies.

Keywords: micro- and nano-composite, soft magnetic materials, microwave sintering, mechanical and electric properties

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Aneta Nitsch-Osuch, Katarzyna Zycinska, Ewa Gyrczuk, Agnieszka Topczewska-Cabanek, Kazimierz Wardyn

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Introduction: Influenza is an important clinical and epidemiological problem and should be considered as a possible nosocomial infection. The aim of the study was to determine the influenza vaccine coverage rates among Polish nurses and to find out drivers and barriers for influenza vaccination among this group of health care workers (HCWs). Material and methods: The self- fulfilled survey with 26 questions about the knowledge, perception, and influenza coverage rates was distributed among 461 nurses. Results: Only 15% of nurses were vaccinated against influenza in the consecutive seasons. The majority (75%) of the regularly vaccinated nurses were ambulatory careworkers. The difference between the number of vaccinated hospitals and ambulatory care nurses was statistically significant (p < 0.05). The main motivating factors for an influenza vaccination were: a fear of the illness and its complications (97%) and a free of charge vaccine available at the workplace (87%). Ambulatory care nurses more often declared that they were vaccinated mainly to protect themselves while hospital care nurses more often declared the will to protect their patients, these differences in the perception and attitudes to an influenza vaccination among hospital and ambulatory care nurses were statistically significant (p < 0.05). The main barriers for an influenza vaccination among the nursing staff were: a lack of reimbursement of the vaccine (95%), a lack of insufficient knowledge about the effectiveness, and safety of the influenza vaccine (54%). The ambulatory care nurses more often found influenza vaccination as the ethical duty compared to hospital care nurses (p < 0.05). Conclusions: The influenza vaccine coverage rates among the Polish nurses are low and must be improved in the future. More educational activities dedicated to HCWs may result in the increased awareness of influenza vaccination benefits for both medical professionals and patients.

Keywords: influenza, vaccination, nurses, ambulatory careworkers

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Authors: Bonchan Koo, Junhee Han, Dohyung Lee

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The research attempts to evaluate the accuracy and efficiency of a design optimization procedure which combines wavelets-based solution algorithm and proper orthogonal decomposition (POD) database management technique. Aerodynamic design procedure calls for high fidelity computational fluid dynamic (CFD) simulations and the consideration of large number of flow conditions and design constraints. Even with significant computing power advancement, current level of integrated design process requires substantial computing time and resources. POD reduces the degree of freedom of full system through conducting singular value decomposition for various field simulations. For additional efficiency improvement of the procedure, adaptive wavelet technique is also being employed during POD training period. The proposed design procedure was applied to the optimization of wing aerodynamic performance. Throughout the research, it was confirmed that the POD/wavelets design procedure could significantly reduce the total design turnaround time and is also able to capture all detailed complex flow features as in full order analysis.

Keywords: POD (Proper Orthogonal Decomposition), wavelets, CFD, design optimization, ROM (Reduced Order Model)

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Authors: Chanpen Meenakorn

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This research aimed to examine the relationships between customer expectations and service quality management of Banpaew Hospital Samutsakorn in Thailand. The study sample consisted of 360 customers in patient unit. Data were collected using self-administered questionnaire. Descriptive statistics used were percentage, mean, and standard deviation. The analytical statistics comprised Pearson’s product moment correlation coefficient analysis. The result showed that service quality of nurses was very good with sustainable development trend. Physical evidence was at a high level, and the process and personal were rated at a high level. Additional, the study suggested that head nurse should be encouraged to improve service quality management, management training. Nurse administrators should create an appropriate nursing department climate, and provide necessary resources in the department. In addition, the nurse administrators should continuously follow up the results of customer expectations and focus on patients/customers, process management, information and knowledge management, and evaluation of service quality also.

Keywords: Banpaew Hospital, Customer Expectations, Service Provided, Samutsakorn

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

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Authors: Felyppe Blum Goncalves, Juliana Sebastiany

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In line with Brazilian legislation on the inclusion of persons with disabilities in the world of work, known as the 'quota law' (Law 8213/91) and in accordance with the prerogatives of the United Nations Convention on Human Rights of people with disabilities, which was ratified by Brazil through Federal Decree No. 6.949 of August 25, 2009, the SESI National Department, through Working Groups, structured the product Affordable Industry. This methodology aims to prepare the industries for the adequate process of inclusion of people with disabilities, as well as the development of an organizational culture that values and respects human diversity. All industries in Brazil with 100 or more employees must comply with current legislation, but due to the lack of information and guidance on the subject, they end up having difficulties in this process. The methodology brings solutions for companies through the professional qualification of the disabled person, preparation of managers, training of human resources teams and employees. It also advocates the survey of the architectural accessibility of the factory and the identification of the possibilities of inclusion of people with disabilities, through the compatibility between work and job requirements, preserving safety, health, and quality of life.

Keywords: inclusion, app, disability, management

Procedia PDF Downloads 145

Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

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This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

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Authors: M. Rodionov, N. Sharapova, Z. Dedovets

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The article describes methods of preparation of future teachers that includes the entire diversity of traditional and computer-oriented methodological approaches. The authors reveal how, in the specific educational environment, a teacher can choose the most effective combination of educational technologies based on the nature of the learning task. The key conditions that determine such a choice are that the methodological approach corresponds to the specificity of the problem being solved and that it is also responsive to the individual characteristics of the students. The article refers to the training of students in the proper use of mathematical electronic tools for educational purposes. The preparation of future mathematics teachers should be a step-by-step process, building on specific examples. At the first stage, students optimally solve problems aided by electronic means of teaching. At the second stage, the main emphasis is on modeling lessons. At the third stage, students develop and implement strategies in the study of one of the topics within a school mathematics curriculum. The article also recommended the implementation of this strategy in preparation of future teachers and stated the possible benefits.

Keywords: education, methodological approaches, teacher, secondary school

Procedia PDF Downloads 157

Authors: Mohamed Ahmed Khalil

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The number of deep well anode ground beds (GBs) have been retrieved due to unoperated anode chains. New identical magnetite anode chains (MAC) have been installed at Raslanuf complex impressed current Cathodic protection (ICCP) system, distributed at different plants (Utility, ethylene and polyethylene). All problems associated with retrieving and installation of MACs have been discussed, rectified and presented. All GB-associated severely corroded wellhead casings were well maintained and/or replaced by new fabricated and modified ones. The main cause of the wellhead casing's severe internal corrosion was discussed and the conducted remedy action to overcome future corrosion problems is presented. All GB-connected anode junction boxes (AJBs) and shunts were closely inspected, maintained and necessary replacement and/or modifications were carried out on shunts. All damaged GB concrete foundations (CF) have been inspected and completely replaced. All GB-associated Transformer-Rectifiers Units (TRU) were subjected to thorough inspection and necessary maintenance was performed on each individual TRU. After completion of all MACs and TRU maintenance activities, each cathodic protection station (CPS) has been re-operated, alternative current (AC), direct current (DC), voltage and structure to soil potential (S/P) measurements have been conducted, recorded and all obtained test results are presented. DC current outputs have been adjusted and DC current outputs of each MAC have been recorded for each GB AJB.

Keywords: magnetite anodes, deep well, ground beds, cathodic protection, transformer rectifier, impressed current, junction boxes

Procedia PDF Downloads 102

Authors: Yizhen Zhao, Adam S. Z. Belloum, Goncalo Maia Da Costa, Zhiming Zhao

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Machine learning has evolved from an area of academic research to a real-word applied field. This change comes with challenges, gaps and differences exist between common practices in academic environments and the ones in production environments. Following continuous integration, development and delivery practices in software engineering, similar trends have happened in machine learning (ML) systems, called MLOps. In this paper we propose a framework that helps to streamline and introduce best practices that facilitate the ML lifecycle in an industrial setting. This framework can be used as a template that can be customized to implement various machine learning experiment. The proposed framework is modular and can be recomposed to be adapted to various use cases (e.g. data versioning, remote training on cloud). The framework inherits practices from DevOps and introduces other practices that are unique to the machine learning system (e.g.data versioning). Our MLOps practices automate the entire machine learning lifecycle, bridge the gap between development and operation.

Keywords: cloud computing, continuous development, data versioning, DevOps, industrial setting, MLOps

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Authors: A. Lashkari, H. Khalafi, H. Khazeminejad, S. Khakshourniya

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In this paper, a numerical model is presented. The model is used to analyze a steady state thermo-hydraulic and reactivity insertion transient in TRR reference cores respectively. The model predictions are compared with the experiments and PARET code results. The model uses the piecewise constant and lumped parameter methods for the coupled point kinetics and thermal-hydraulics modules respectively. The advantages of the piecewise constant method are simplicity, efficiency and accuracy. A main criterion on the applicability range of this model is that the exit coolant temperature remains below the saturation temperature, i.e. no bulk boiling occurs in the core. The calculation values of power and coolant temperature, in steady state and positive reactivity insertion scenario, are in good agreement with the experiment values. However, the model is a useful tool for the transient analysis of most research reactor encountered in practice. The main objective of this work is using simple calculation methods and benchmarking them with experimental data. This model can be used for training proposes.

Keywords: thermal-hydraulic, research reactor, reactivity insertion, numerical modeling

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Authors: Wullapa Wongsinlatam

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Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization

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Authors: Mohamad Saleh Sangin Ostadi, Esmail Safari, Somayeh Akbari, Kaveh Qaderi Bagajan

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The aim of this study is to compare abused and normal male students in Tehran guidance schools with emphasis on the co-dependency of their mothers. The method of this study is based on survey method and comparison (Ex-Post Facto). The method of sampling is also multi-stage cluster. Accordingly, we did sampling from secondary schools of education and training in Tehran, including 12 schools with levels of first, second and third. Each of the schools represents the three – high, medium and low- economic and social conditions. In the following, three classes from every school and 20 students from each class were randomly selected. By (CTQ) abused and normal students were separated that 670 children were recognized as normal and 50 children as abused. Then, 50 children were randomly selected from normal group and compared with abused group. Using Spanned-Fischer Co-dependency Scale, we compared mothers of abused and normal students. The results showed that mothers of the abused children have higher co- dependency average comparing to the mothers of the normal children.

Keywords: co-dependency, child abuse, abused children, parental psychological health

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Authors: Adel. M. Sharaf, Foad H. Gandoman

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Nowadays, Photovoltaic-PV Farms/ Parks and large PV-Smart Grid Interface Schemes are emerging and commonly utilized in Renewable Energy distributed generation. However, PV-hybrid-Dc-Ac Schemes using interface power electronic converters usually has negative impact on power quality and stabilization of modern electrical network under load excursions and network fault conditions in smart grid. Consequently, robust FACTS based interface schemes are required to ensure efficient energy utilization and stabilization of bus voltages as well as limiting switching/fault onrush current condition. FACTS devices are also used in smart grid-Battery Interface and Storage Schemes with PV-Battery Storage hybrid systems as an elegant alternative to renewable energy utilization with backup battery storage for electric utility energy and demand side management to provide needed energy and power capacity under heavy load conditions. The paper presents a robust interface PV-Li-Ion Battery Storage Interface Scheme for Distribution/Utilization Low Voltage Interface using FACTS stabilization enhancement and dynamic maximum PV power tracking controllers. Digital simulation and validation of the proposed scheme is done using MATLAB/Simulink software environment for Low Voltage- Distribution/Utilization system feeding a hybrid Linear-Motorized inrush and nonlinear type loads from a DC-AC Interface VSC-6-pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion Storage Battery.

Keywords: AC FACTS, smart grid, stabilization, PV-battery storage, Switched Filter-Compensation (SFC)

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Authors: Michelle Odudu

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Ghana and Nigeria are known for their high levels of Occupational Fraud in public offices. The governments of both countries have emphasised their commitment to reducing the losses caused to the state by pledging their allegiance to the counter-fraud agencies to help tackle Occupational Fraud. Yet it seems that the prosecution of such cases is ineffective as high-profile fraudsters can operate with immunity and their cases remain unprosecuted. This research project was based on in-depth examinations of 50 occupational fraud cases involving high-profile individuals in both countries. In doing so, it established the characteristics of those who were prosecuted; the extent to which prosecutions were effectively managed; the barriers to effective prosecutions; and the similarities or differences between the occurrences in both countries. The aim of the project is to examine the practice of and barriers to prosecution of large-scale occupational fraud of those in senior public positions in Ghana and Nigeria. The study drew on the experiences of stakeholders such as defence and prosecution barristers, academics, and fraud analysts via semi-structured interviews and questionnaires. 13 interviews were conducted in Ghana and in Nigeria, where respondents were recruited using a snowball approach. Questionnaires were physically distributed: 20 of the staff at EOCO and 10 to NGO staff in Ghana; 6 and 5 came back, respectively. The empirical data collected suggests that there is no lack of will on the agencies’ part to at least commence proceedings. However, various impediments hamper a successful completion of prosecution. Challenges were more evident in Nigeria, where agencies are less effective at retrieving stolen assets and changing social norms. This is further compounded by several cultural and political factors, which create limitations leaving many cases ‘still pending’.

Keywords: comparative, prosecution, punishment, international, whitecollar, fraud

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Authors: Thampi Rawther, Jack Cecire, Andrew Sutherland

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Introduction: CT facilitates the diagnosis of potentially life-threatening injuries and facilitates early management. There is evidence that reduced CT acquisition time reduces mortality and length of hospital stay. Currently, there are variable recommendations for ideal timing. Indeed, the NHS standard contract for a major trauma service and STAG both recommend immediate access to CT within a maximum time of 60min and appropriate reporting within 60min of the scan. At Coffs Harbour Health Campus (CHHC), a CT radiographer is on site between 8am-11pm. Aim: To investigate the average time to CT at CHHC and assess for any significant relationship between time to CT and injury severity score (ISS) or time of triage. Method: All major trauma calls between Jan 2021-Oct 2021 were audited (N=87). Patients were excluded if they went from ED to the theatre. Time to CT is defined as the time between triage to the timestamp on the first CT image. Median and interquartile range was used as a measure of central tendency as the data was not normally distributed, and Chi-square test was used to determine association. Results: The median time to CT is 51.5min (IQR 40-74). We found no relationship between time to CT and ISS (P=0.18) and time of triage to time to CT (P=0.35). We compared this to other centres such as John Hunter Hospital and Gold Coast Hospital. We found that the median CT acquisition times were 76min (IQR 52-115) and 43min, respectively. Conclusion: This shows an avenue for improvement given 35% of CT’s were >30min. Furthermore, being proactive and aware of time to CT as an important factor to trauma management can be another avenue for improvement. Based on this, we will re-audit in 12-24months to assess if any improvement has been made.

Keywords: imaging, rural surgery, trauma surgery, improvement

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Authors: Jailan Mohamed El Demerdash

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Millennials are a distinctive and dominant consumer group whose behavior, preferences and purchase decisions are broadly explored but not fully understood yet. Making up the largest market segment in the world, and in Egypt, they have the power to reinvent the hospitality industry and contribute to forming prospective demand for green hotels by showing willingness to adopting their environmental-friendly practices. The current study aims to enhance better understanding of Millennials' perception about sustainable initiatives and to increase the prediction power of their intentions regarding green hotel practices in Egypt. In doing so, the study is exploring the relation among different factors; Millennials' environmental awareness, their acceptance of green practices and their willingness to pay more for them. Millennials' profile, their preferences and environmental decision-making process are brought under light to stimulate actions of hospitality decision-makers and hoteliers. Bearing in mind that responsible consumerism is depending on understanding the different influences on consumption. The study questionnaire was composed of four sections and it was distributed to random Egyptian travelers' blogs and Facebook groups, with approximately 8000 members. Analysis of variance test (ANOVA) was used to examine the study variables. The findings indicated that Millennials' environmental awareness will not be a significant factor in their acceptance of hotel green practices, as well as, their willingness to pay more for them. However, Millennials' acceptance of the level of hotel green practices will have an impact on their willingness to pay more. Millennials were found to have a noticeable level of environmental awareness but lack commitment to tolerating hotel green practices and their associated high prices.

Keywords: millennials, environment, awareness, paying more

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Authors: Peyman Rezaei Hachesu, Vahideh Zareh Gavgani, Zahra Salahzadeh

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To survey the attitudes, awareness, and practice of Evidence Based Medicine (EBM), and to determine the barriers that influence apply’ EBM in therapeutic process among clinical residents in Iran.We conducted a cross sectional survey during September to December 2012 at the teaching hospitals of Tehran University of Medical Sciences among 79 clinical residents from different medical specialties. A valid and reliable questionnaire consisted of five sections and 27 statements were used in this research. We applied Spearman and Mann Whitney test for correlation between variables. Findings showed that the knowledge of residents about EBM is low. Their attitude towards EBM was positive but their knowledge and skills in regard with the evidence based medical information resources were mostly limited to PubMed and Google scholar. The main barrier was the lack of enough time to practicing EBM. There was no significant correlation between residency grade and familiarity and use of electronic EBM resources (Spearman, P = 0.138). Integration of training approaches like journal clubs or workshops with clinical practice is suggested.

Keywords: evidence-based medicine, clinical residents, decision-making, attitude, questionnaire

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Authors: D. S. Malatesh, K. J. Ananda, C. Ansar Kamran, K. Ganesh Udupa

Abstract:

Dirofilaria repens is a mosquito-borne filarioid nematode of dogs and other carnivores and accidentally affects humans. D. repens is reported in many countries, including India. Subcutaneous dirofilariosis caused by D. repens is a zoonotic disease, widely distributed throughout Europe, Asia, and Africa, with higher prevalence reported in dogs from Sri Lanka (30-60%), Iran (61%) and Italy (21-25%). Dirofilariasis in dogs was diagnosed by detection of microfilariae in blood. Identification of different Dirofilaria species was done by using molecular methods like polymerase chain reaction (PCR). Even though many researchers reported molecular evidence of D. repens across India, to our best knowledge there is no data available on molecular diagnosis of D. repens in dogs and its zoonotic implication in Karnataka state a southern state in India. The aim of the present study was to identify the Dirofilaria species occurring in dogs from Karnataka, India. Out of 310 samples screened for the presence of microfilariae using traditional diagnostic methods, 99 (31.93%) were positive for the presence of microfilariae. Based on the morphometry, the microfilariae were identified as D. repens. For confirmation of species, the samples were subjected to PCR using pan filarial primers (DIDR-F1, DIDR-R1) for amplification of internal transcribed spacer region 2 (ITS2) of the ribosomal DNA. The PCR product of 484 base pairs on agarose gel was indicative of D. repens. Hence, a single PCR reaction using pan filarial primers can be used to differentiate filarial species found in dogs. The present study confirms that dirofilarial species occurring in dogs from Karnataka is D. repens and further sequencing studies are needed for genotypic characterization of D. repens.

Keywords: Dirofilaria repens, molecular characterization, polymerase chain reaction, Karnataka, India

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Authors: Keshav Raj Acharya, Thakur Silwal, Neelam C. Poudyal

Abstract:

Buffer zones, the peripheral areas around the national parks and wildlife reserves, are available for the purpose of benefitting the local inhabitants by providing forest products for subsistence needs of basic forest products outside the protected areas. The forest area within the buffer zone has been managed as a buffer zone community forest (BZCF) for the last 25 years after the approval of the buffer zone management regulation 1996. With a case study of select BZCF in Bardia National Park, this study aims to analyze whether the benefit provided by BZCF is equally available to poor users among other socioeconomic classes of the users. The findings are based on the analysis of cross-sectional data involving household surveys (n=305) and key informants’ interviews (n=10) as well as office records available at different 5 buffer zone community forest user groups offices. Results indicate that despite the provisions of subsidized rates for poor; poor households were more deprived due to higher forest products price particularly, the timber price in buffer zone. Evidence also indicate that due to the increased forest coverage, the incidence of wildlife damage has also increased and impacted the poor more due to lack of land ownership as well as limited alternatives. Clear community forest management guidelines with equitable benefit sharing and compensatory mechanisms to the users of poor socioeconomic class have been identified as a solution to increase the benefit to poor users in BZCFUGs.

Keywords: crop depredation, forest products, users, wellbeing ranking

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Authors: Nathalie Piquemal, Faiçal Zellama, Bathélemy Bolivar, Leyla Sall

Abstract:

Canada defines itself as a country of immigration and a multicultural nation, ideologically, politically and programmatically (in terms of its integration practices). As such, principles of hospitality may seem, at first glance, incontestable, given the convergence of the views of the majority of Canadian politicians on the need to welcome, each year, a significant number of immigrants and to offer them the hospitality that facilitates their transition to Canadian citizenship. However, immigrants are welcomed in a Canadian societal context in which power and resources are unevenly distributed, resulting in complex social relationships between hosts and newcomers. Qualitative data obtained from newcomers in Winnipeg, Manitoba, Canada, focuses on experiences of hospitality, with special attention to host-guest social and power dynamics, contested policies on foreign credential and micro spaces of belongingin a multicultural context. The act of welcoming a newcomer is inherently shaped by both macropolitical structures and everyday relational practices that can lead to experiences of belonging, marginalisation, empowerment and/or disempowerment depending on economic agenda, humanitarian and humanistic orientations. We first explore the extent to which immigrants experience hospitality in relation to unequal distribution of power and resources as well as cultural discontinuities. We then examine ways in which immigrants have been able to find sanctuaries of hospitality within their own ethnocultural communities. Finally, we discuss the complexity of hospitality in a multicultural context and offer critical insights on host factors that may produce, develop and nurture hospitable environments.

Keywords: migration, hospitality, diversity, culture, race

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Authors: Rajiv Mishra, Mantun Kumar Singh

Abstract:

The role of educator or teacher in the Indian context is circumscribed by the objective of social transformation as articulated in the Indian National Movement and later enshrined in the Preamble to the Indian Constitution, in the Fundamental Rights and in the Directive Principles of State Policy. Extension, which is the additional dimension of professional practice among teachers at higher education can be used as a revolutionary tool to modify the existing slogan of ‘education for all’ to ‘education for all and for-ever’, thereby making the ‘life-long education’, a reality. This conceptual paper addresses the twin needs of preparing the students for individual growth as also to facilitate them to contribute to social development. It focuses on the inclusion of the measures required to be taken for providing social consciousness and sensitivity, as this happens to be a neglected part of the curriculum. The extra effort so needed to build community based activities presupposes the requirement for professional training to be given to the hospitality and tourism educators as a continuing education initiative.

Keywords: continuing education, extension activities, holistic curriculum, hospitality and tourism educators

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Authors: Chen Zhang, Nan Chen

Abstract:

High-dimensional process monitoring becomes increasingly important in many application domains, where usually the process distribution is unknown and much more complicated than the normal distribution, and the between-stream correlation can not be neglected. However, since the process dimension is generally much bigger than the reference sample size, most traditional nonparametric multivariate control charts fail in high-dimensional cases due to the curse of dimensionality. Furthermore, when the process goes out of control, the influenced variables are quite sparse compared with the whole dimension, which increases the detection difficulty. Targeting at these issues, this paper proposes a new nonparametric monitoring scheme for high-dimensional processes. This scheme first projects the high-dimensional process into several subprocesses using random projections for dimension reduction. Then, for every subprocess with the dimension much smaller than the reference sample size, a local nonparametric control chart is constructed based on the spatial rank test to detect changes in this subprocess. Finally, the results of all the local charts are fused together for decision. Furthermore, after an out-of-control (OC) alarm is triggered, a diagnostic framework is proposed. using the square-root LASSO. Numerical studies demonstrate that the chart has satisfactory detection power for sparse OC changes and robust performance for non-normally distributed data, The diagnostic framework is also effective to identify truly changed variables. Finally, a real-data example is presented to demonstrate the application of the proposed method.

Keywords: random projection, high-dimensional process control, spatial rank, sequential change detection

Procedia PDF Downloads 283