Search results for: parameters for training needs assessment

Authors: Yiu K. C. Jacky, Tang S. K. Eric, W. Y. Tsang, C. Y. Li, C. K. Leung

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Objectives : (1) To enhance the competence of nurses on using IPMOE for drug administration; (2) To ensure the transition on implementation of IPMOE in safer and smooth way hospital-wide. Methodology: (1) Well-structured Governance: To make provision for IPMOE implementation, multidisciplinary governance structure at Corporate and Local levels are well established. (2) Staff Engagement: A series of staff engagement events were conducted including Staff Forum, IPMOE Hospital Visit, Kick-off Ceremony and establishment of IPMOE Webpage for familiarizing the forthcoming implementation with frontline staff. (3) Well-organized training program: from Workshop to Workplace Two different IPMOE training programs were tailor-made which aimed at introducing the core features of administration module. Fifty-five identical training classes and six train-the-trainer workshops were organized at 2-3Q 2015. Lending Scheme on IPMOE hardware for hands-on practicing was launched and further extended the training from workshop to workplace. (4) Standard Guidelines and Workflow: the related workflow and guidelines are developed which facilitates users to acquire the competence towards IPMOE and fully familiarize with the standardized contingency plan. (5) Facilities and Equipment: The installations of IPMOE hardware were promptly arranged for rollout. Besides, IPMOE training venue was well-established for staff training. (6) Risk Management Strategy: UCH Medication Safety Forum is organized in December 2015 for sharing “Tricks & Tips” on IPMOE which further disseminate at webpage for arousal of medication safety. Hospital-wide annual audit on drug administration was planned to figure out the compliance and deliberate the rooms for improvement. Results: Through the comprehensive training plan, over 1,000 UCH nurses attended the training program with positive feedback. They agreed that their competence on using IPMOE was enhanced. By the end of November 2015, 28 wards (over 1,000 Inpatient-bed) involving departments of M&G, SUR, O&T and O&G have been successfully rolled out IPMOE in 5-month. A smooth and safe transition of implementation of IPMOE was achieved. Eventually, we all get prepared for embedding IPMOE into daily nursing and work altogether for medication safety at UCH.

Keywords: drug administration, inpatient medication order entry system, medication safety, nursing informatics

Procedia PDF Downloads 335

Authors: Rahel Birhanu Kassaye, Ralf Otterpohl, Kumelachew Yeshitila

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Water resource management and land degradation are among the critical issues threatening the suitable livability of many cities in developing countries such as Ethiopia. Rapid expansion of urban areas and fast growing population has increased the pressure on water security. On the other hand, the large transformation of natural green cover and agricultural land loss to settlement and industrial activities such as quarrying is contributing to environmental concerns. Integrated water harvesting is considered to play a crucial role in terms of providing alternative water source to insure water security and helping to improve soil condition, agricultural productivity and regeneration of ecosystem. Moreover, it helps to control stormwater runoff, thus reducing flood risks and pollution, thereby improving the quality of receiving water bodies and the health of inhabitants. The aim of this research was to investigate the potential of applying integrated water harvesting approaches as a provision for water source and enabling land restoration in Jemo river catchment consisting of abandoned quarry site adjacent to a settlement area that is facing serious water shortage in western hilly part of Addis Ababa city, Ethiopia. The abandoned quarry site, apart from its contribution to the loss of aesthetics, has resulted in poor water infiltration and increase in stormwater runoff leading to land degradation and flooding in the downstream. Application of GIS and multi-criteria based analysis are used for the assessment of potential water harvesting technologies considering the technology features and site characteristics of the case study area. Biophysical parameters including precipitation, surrounding land use, surface gradient, soil characteristics and geological aspects are used as site characteristic indicators and water harvesting technologies including retention pond, check dam, agro-forestation employing contour trench system were considered for evaluation with technical and socio-economic factors used as parameters in the assessment. The assessment results indicate the different suitability potential among the analyzed water harvesting and restoration techniques with respect to the abandoned quarry site characteristics. Application of agro-forestation with contour trench system with the revegetation of indigenous plants is found to be the most suitable option for reclamation and restoration of the quarry site. Successful application of the selected technologies and strategies for water harvesting and restoration is considered to play a significant role to provide additional water source, maintain good water quality, increase agricultural productivity at urban peri-urban interface scale and improve biodiversity in the catchment. The results of the study provide guideline for decision makers and contribute to the integration of decentralized water harvesting and restoration techniques in the water management and planning of the case study area.

Keywords: abandoned quarry site, land reclamation and restoration, multi-criteria assessment, water harvesting

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Authors: I. Toumi, Y. Abed, A. Bouafia

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This paper presents a methodology for identifying the cohesive soil parameters that takes into account different constitutive equations. The procedure, applied to identify the parameters of generalized Prager model associated to the Drucker & Prager failure criterion from a pressuremeter expansion curve, is based on an inverse analysis approach, which consists of minimizing the function representing the difference between the experimental curve and the simulated curve using a simplex algorithm. The model response on pressuremeter path and its identification from experimental data lead to the determination of the friction angle, the cohesion and the Young modulus. Some parameters effects on the simulated curves and stresses path around pressuremeter probe are presented. Comparisons between the parameters determined with the proposed method and those obtained by other means are also presented.

Keywords: cohesive soils, cavity expansion, pressuremeter test, finite element method, optimization procedure, simplex algorithm

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Authors: Zahra Okba, Hassan El Ouizgani

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Anticipating an individual’s behavior to the environmental factors allows for having relevant ecological forecasts. The Dynamic Energy Budget model facilitates prediction, and it is mechanically dependent on biology to abiotic factors but is generally field verified under relatively stable physical conditions. Dynamic Energy Budget Theory (DEB) is a robust framework that can link the individual state to environmental factors, and in our work, we have tested its ability to account for variability by looking at model predictions in the Agadir Bay, which is characterized by a semi-arid climate and temperature is strongly influenced by the trade winds front and nutritional availability. From previous works in our laboratory, we have collected different biological DEB model parameters of Mytilus galloprovincialis mussel in Agadir Bay. We mathematically formulated the equations that make up the DEB model and then adjusted our analytical functions with the observed biological data of our local species. We also assumed the condition of constant immersion, and then we integrated the details of the tidal cycles to calculate the metabolic depression at low tide. Our results are quite satisfactory concerning the length and shape of the shell in one part and the gonadosomatic index in another part.

Keywords: dynamic energy budget, mussels, mytilus galloprovincialis, agadir bay, DEB model

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Authors: Taleb Hosni Abderrahmane, Berga Abdelmadjid

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The development of numerical analysis and its application to geomechanics problems have provided geotechnical engineers with extremely powerful tools. One of the most important problems in geotechnical engineering is the slope stability assessment. It is a very difficult task due to several aspects such the nature of the problem, experimental consideration, monitoring, controlling, and assessment. The main objective of this paper is to perform a comparative numerical study between the following methods: The Limit Equilibrium (LEM), Finite Element (FEM), Limit Analysis (LAM) and Distinct Element (DEM). The comparison is conducted in terms of the safety factors and the critical slip surfaces. Through the results, we see the feasibility to analyse slope stability by many methods.

Keywords: comparison, factor of safety, geomechanics, numerical methods, slope analysis, slip surfaces

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Authors: Celeste Lawson

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Learning to embrace and value teamwork assessment at a university level is critical for students, as graduates enter a real-world working environment where teamwork is likely to occur virtually. Student disdain for teamwork exercises is an area often overlooked or disregarded by academics. This research explored the implementation of an online teamwork assessment approach at a regional Australian university with a significant cohort of Distance Education students. Students had disliked teamwork for three reasons: it was not relevant to their study, the grading was unfair amongst team members, and managing the task was challenging in a virtual environment. Teamwork assessment was modified so that the task was an authentic task that could occur in real-world practice; team selection was based on the task topic rather than randomly; grading was based on the individual’s contribution to the task, and students were provided virtual team management skills as part of a the assessment. In this way, management of the team became an output of the task itself. Data was gathered over three years from student satisfaction surveys, failure rates, attrition figures, and unsolicited student comments. In one unit where this approach was adopted (Advanced Public Relations), student satisfaction increased from 3.6 (out of 5) in 2012 to 4.6 in 2016, with positive comments made about the teamwork approach. The attrition rate for another unit (Public Relations and the Media) reduced from 20.7% in 2012 to 2.2% in 2015. In 2012, criticism of teamwork assessment made up 50% of negative student feedback in Public Relations and the Media. By 2015, following the successful implementation of the teamwork assessment approach, only 12.5% of negative comments on the student satisfaction survey were critical of teamwork, while 33% of positive comments related to a positive teamwork experience. In 2016, students explicitly nominated teamwork as the best part of this unit. The approach is transferable to other disciplines and was adopted by other academics within the institution with similar results.

Keywords: assessment, distance education, teamwork, virtual

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Evangelos G. Ilias, Panagiotis G. Ilias, Vasileios T. Popotas

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The United Kingdom has one of the oldest railway networks in the world dating back to 1825 when the world’s first passenger railway was opened. The network has some 40,000 bridges of various construction types using a wide range of materials including masonry, steel, cast iron, wrought iron, concrete and timber. It is commonly accepted that the successful operation of the network is vital for the economy of the United Kingdom, consequently the cost effective maintenance of the existing infrastructure is a high priority to maintain the operability of the network, prevent deterioration and to extend the life of the assets. Every bridge on the railway network is required to be assessed every eighteen years and a structured approach to assessments is adopted with three main types of progressively more detailed assessments used. These assessment types include Level 0 (standardized spreadsheet assessment tools), Level 1 (analytical hand calculations) and Level 2 (generally finite element analyses). There is a degree of conservatism in the first two types of assessment dictated to some extent by the relevant standards which can lead to some structures not achieving the required load rating. In these situations, a Level 2 Assessment is often carried out using finite element analysis to uncover ‘latent strength’ and improve the load rating. If successful, the more sophisticated analysis can save on costly strengthening or replacement works and avoid disruption to the operational railway. This paper presents the ‘strengthening by assessment’ achieved by Level 2 analyses. The use of more accurate analysis assumptions and the implementation of non-linear modelling and functions (material, geometric and support) to better understand buckling modes and the structural behaviour of historic construction details that are not specifically covered by assessment codes are outlined. Metallic bridges which are susceptible to loss of section size through corrosion have largest scope for improvement by the Level 2 Assessment methodology. Three case studies are presented, demonstrating the effectiveness of the sophisticated Level 2 Assessment methodology using finite element analysis against the conservative approaches employed for Level 0 and Level 1 Assessments. One rail overbridge and two rail underbridges that did not achieve the required load rating by means of a Level 1 Assessment due to the inadequate restraint provided by U-Frame action are examined and the increase in assessed capacity given by the Level 2 Assessment is outlined.

Keywords: assessment, bridges, buckling, finite element analysis, non-linear modelling, strengthening

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Authors: E. Yu. Yakovlev, A. V. Puchkov

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The study is devoted to experimental work on the assessment of emanation properties of kimberlites and host rocks of the Lomonosov diamond deposit of the Arkhangelsk diamondiferous province. The aim of the study is estimation the factors influencing on formation of the radon field over kimberlite pipes. For various types of rocks composing the kimberlite pipe and near-pipe space, the following parameters were measured: porosity, density, radium-226 activity, activity of free radon and emanation coefficient. The research results showed that the largest amount of free radon is produced by rocks of near-pipe space, which are the Vendian host deposits and are characterized by high values of the emanation coefficient, radium activity and porosity. The lowest values of these parameters are characteristic of vent-facies kimberlites, which limit the formation of activity of free radon in body of the pipe. The results of experimental work confirm the prospects of using emanation methods for prospecting of kimberlite pipes.

Keywords: emanation coefficient, kimberlites, porosity, radon volumetric activity

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Authors: Murat Gunduz, Mustafa Ozdemir

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In this research, a framework is to be proposed to model the safety performance in construction sites. Determinants of safety performance are to be defined through extensive literature review and a multidimensional safety performance model is to be developed. In this context, a questionnaire is to be administered to construction companies with sites. The collected data through questionnaires including linguistic terms are then to be defuzzified to get concrete numbers by using fuzzy set theory which provides strong and significant instruments for the measurement of ambiguities and provides the opportunity to meaningfully represent concepts expressed in the natural language. The validity of the proposed safety performance model, relationships between determinants of safety performance are to be analyzed using the structural equation modeling (SEM) which is a highly strong multi variable analysis technique that makes possible the evaluation of latent structures. After validation of the model, a safety performance index assessment tool is to be proposed by the help of software. The proposed safety performance assessment tool will be based on the empirically validated theoretical model.

Keywords: Fuzzy set theory, safety performance assessment, safety index, structural equation modeling (SEM), construction sites

Procedia PDF Downloads 519

Authors: Cruz, G. P., Nagamatsu, R. N., Scacchetti, F. A. P., Merlin, F. K.

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This study aims to assess a set of technical parameters that provide quality products to the companies that produce caps, APL Apucarana / PR, the city that produces most Brazilian caps, in order to verify the potential of Brazilian caps to compete with international brands, recognized by the standard of excellence when it comes to quality of its products. The determination of the technical parameters was arbitrated from textile ABNT, a total of six technical parameters, providing eight tests for cotton caps. For the evaluation, we used as reference a leading brand recognized worldwide (based on their sales volume in $) for comparison with 3 companies of the APL Apucarana. The results showed that, of the 8 tests, of 8 tests, the companies Apucarana did not obtain better performance than the competitor. They obtained the same results in three tests and lower performance in 5. Given these values, it is concluded that local caps are not far from reaching the quality of leading brand. It is recommended that the APL companies use the parameters to evaluate their products, using this information to support decision-making that seek to improve both the product design and its production process, enabling the feasibility for faster international recognition . Thus, they may have an edge over its main competitor.

Keywords: technical parameters, making caps, quality, evaluation

Procedia PDF Downloads 342

Authors: Marutani M, Kawajiri H, Usui C, Takai Y, Kawaguchi T

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Background: To build the inclusive society, the Japanese government provides “transition support for employment system” for Persons with Disabilities (PWDs). It is, however, difficult to provide appropriate accommodations due to their changeable health conditions. Mobile phone applications (App) are useful to monitor their health conditions and their environments, and effective to improve reasonable accommodations for PWDs. Purpose: This study aimed to develop an App that PWDs input their self-assessment and make their health conditions and environment conditions visible. To attain the goal, we investigated the items of the App for the first step. Methods: Qualitative and descriptive design was used for this study. Study participants were recruited by snowball sampling in July and August 2023. They had to have had minimum of five-years of experience to support PWDs’ employment. Semi-structured interviews were conducted on their assessment regarding PWDs’ conditions of daily activities, their health conditions, and living and working environment. Verbatim transcript was created from each interview content. We extracted the following items in tree groups from each verbatim transcript: daily activities, health conditions, and living and working. Results: Fourteen participants were involved (average years of experience: 10.6 years). Based on the interviews, tree item groups were enriched. The items of daily activities were divided into fifty-five. The example items were as follows: “have meals on one’s style” “feel like slept well” “wake-up time, bedtime, and mealtime are usually fixed.” “commute to the office and work without barriers.” Thirteen items of health conditions were obtained like “feel no anxiety” “relieve stress” “focus on work and training” “have no pain” “have the physical strength to work for one day.” The items of categories of living and working environments were divided into fifteen-two. The example items were as follows: “have no barrier in home” “have supportive family members” “have time to take medication on time while at work” “commute time is just right” “people at the work understand the symptoms” “room temperature and humidity are just right” “get along well with friends in my own way.” The participants also mentioned the styles to input self-assessment like that a face scale would be preferred to number scale. Conclusion: The items were enriched existent paper-based assessment items in terms of living and working environment because those were obtained from the perspective of PWDs. We have to create the app and examine its usefulness with PWDs toward inclusive society.

Keywords: occupational health, innovatiove tool, people with disability, employment

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Authors: Rafid Saeed Abdulrazak Alshkaki

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In this paper, zero-one inflated negative binomial distribution is considered, along with some of its structural properties, then its parameters were estimated using the method of moments. It is found that the method of moments to estimate the parameters of the zero-one inflated negative binomial models is not a proper method and may give incorrect conclusions.

Keywords: zero one inflated models, negative binomial distribution, moments estimator, non negative integer sampling

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Authors: Mohita Singh, Sunil Sachdev, Amrita Singh

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Background and Aim: Physical aerobic exercises promote positive changes in one’s mental health, intelligence, and ability to cope with stressful encounters. The present study was designed to explore the correlation between intelligence and stress parameters and to assess the correlation between the same parameters after the practice of one month of moderate-intensity physical exercise. Method: The study was conducted on thirty-five healthy male volunteer students to assess the correlation between stress parameters in subjects with varying level of general intelligence (GI) and emotional intelligence (EI). Correlation studies were again conducted after one month between the same parameters to evaluate the effect of moderate-intensity physical exercise (MIPE). Baseline values were recorded using standard scales. Result: IQ and EQ correlated negatively with both acute and chronic stress parameters and positively with each other. A positive correlation was found between acute and chronic stress. With the practice of one month of moderate-intensity physical exercise, there was significant increment between the parameters under study and hence improved results. Conclusion: MIPE improved correlation between GI, EI, stress parameters, and thus reduced stress and improved intelligence.

Keywords: emotional intelligence, general intelligence, moderate intensity physical exercise, stress response

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Authors: Abdeta Bayissa Mekessa

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The purpose of this study was to examine the effects of plyometric exercises on agility, power, and speed and improvement of U-17 female sprinters in the case of the Burayu Athletics project. The true experimental research design was employed for conducting this study. The total populations of the study were 14 U-17 female sprinters from Burayu athletics project. The populations were small in numbers; therefore, the researcher took all as a sample by using comprehensive sampling techniques. These subjects were classified into the Experimental group (N=7) and the Control group (N=7) by using simple random sampling techniques. The Experimental group participated in plyometric training for 8 weeks, 3 days per week and 60 minutes duration per day in addition to their regular training. But, the control groups were following their only regular training program. The variables selected for the purpose of this study were agility, power and speed. The tests were the Illinois agility test, standing long jump test, and 30m sprint test, respectively. Both groups were tested before (pre-test) and after (post-test) 8 weeks of plyometric training. For data analysis, the researcher used SPSS version 26.0 software. The collected data was analyzed using a paired sample t-test to observe the difference between the pre-test and post-test results of the plyometric exercises of the study. The significant level of p<0.05 was considered. The result of the study shows that after 8 weeks of plyometric training, significant improvements were found in Agility (MD=0.45, p<0.05), power (MD=-1.157, P<0.05) and speed (MD=0.37, P<0.05) for experimental group subjects. On the other hand, there was no significant change (P>0.05) in those variables in the control groups. Finally, the findings of the study showed that eight (8) weeks of plyometric exercises had a positive effect on agility, power and speed improvement of female sprinters. Therefore, Athletics coaches and athletes are highly recommended to include plyometric exercise in their training program.

Keywords: ploymetric exercise, speed power, aglity, female sprinter

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Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate and even exceed some benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. A common facet of many ITS is their use of Bayesian Knowledge Tracing (BKT) to estimate parameters necessary for the implementation of the artificial intelligence component, and for the probability of mastery of a knowledge component relevant to the ITS. While various techniques exist to estimate these parameters and probability of mastery, none directly and reliably ask the user to self-assess these. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course for which detailed transaction-level observations were recorded, and users were also routinely asked direct questions that would lead to such a self-assessment. Comparisons were made between these self-assessed values and those obtained using commonly used estimation techniques. Our findings show that such self-assessments are particularly relevant at the early stages of ITS usage while transaction level data are scant. Once a user’s transaction level data become available after sufficient ITS usage, these can replace the self-assessments in order to eliminate the identifiability problem in BKT. We discuss how these findings are relevant to the number of exercises necessary to lead to mastery of a knowledge component, the associated implications on learning curves, and its relevance to instruction time.

Keywords: Bayesian Knowledge Tracing, Intelligent Tutoring System, in vivo study, parameter estimation

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Authors: Monika Benedek

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This paper intends to present a pilot study of blended ear-training course at a Finnish university. The course ran for ten weeks and included both traditional (offline) group lessons for 90 minutes each week and an online learning platform. Twelve students majored in musicology and music education participated in the course. The aims of pilot research were to develop a new blended ear-training course at university level, to determine the ideal amount of workload in each part of the blended instruction (offline and online) and to develop the course material. The course material was selected from the Classical period in order to develop students’ aural skills together with their stylistic knowledge. Students were asked to provide written feedback of the course content and learning approaches of face-to-face group lessons and online learning platform each week during the course. Therefore, the teaching material is continuously planned for each week. This qualitative data collection and weekly analysis of data are on progress. However, based on the teacher-researcher’s experiences and the students’ feedback already collected, it could be seen that the blended instruction would be an ideal teaching strategy for ear-trainging at the music programmes of universities to develop students’ aural skills and stylistic knowledge. It is also presumed that such blended instruction with less workload would already improve university students’ aural skills and related musicianship skills. The preliminary findings of research also indicated that students generally found those ear-training tasks the most useful to learn online that combined listening, singing, singing and playing an instrument. This paper intends to summarise the final results of the pilot study.

Keywords: blended-learning, ear-training, higher music education, online-learning, pilot study

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Authors: K. Sindhu, V. Shubha Rao

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The goal of every faculty is to guide students to learn fundamental concepts and also improve thinking skills. Curriculum questionnaires must be framed, which would facilitate students to improve their thinking skills. Improving thinking skill is a difficult task and one of the ways to achieve this is to frame questionnaires using Bloom’s Taxonomy. Bloom’s Taxonomy helps the faculty to assess the students in a systematic approach which involves students performing successfully at each level in a systematic manner. In this paper, we have discussed on Revised Bloom’s Taxonomy and how to frame our questions based on the taxonomy for assessment. We have also presented mapping the questions with the taxonomy table which shows the mapping of the questions in knowledge and cognitive domain.

Keywords: bloom’s taxonomy, assessment, questions, engineering education

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Authors: Churamani Pokhrel, C. B. Jha, S. R. Niraula, P. R. Pokharel

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Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available.

Keywords: craniofacial, gender, odontometric, stature

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Authors: Rangika Perera, Shyamani Hettiarachchi, Fran Hagstrom

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Dyslexia is the most common reading reading-related difficulty among the school school-aged population and currently, 5-10% are showing the features of dyslexia in Sri Lanka. As there is an insufficient number of speech and language pathologists in the country and few speech and language pathologists working in government mainstream school settings, these children who are at risk of dyslexia are not receiving enough quality early intervention services to develop their reading skills. As teachers are the key professionals who are directly working with these children, using them as the primary facilitators to improve their reading skills will be the most effective approach. This study aimed to identify the efficacy of a two and half a day of intensive training provided to fifteen mainstream government school teachers of grade two classes. The goal of the training was to enhance their knowledge of dyslexia and provide full classroom skills training that could be used to support the development of the students’ reading competencies. A closed closed-ended multiple choice questionnaire was given to these teachers pre and -post-training to measure teachers’ knowledge of dyslexia, the areas in which these children needed additional support, and the best strategies to facilitate reading competencies. The data revealed that the teachers’ knowledge in all areas was significantly poorer prior to the training and that there was a clear improvement in all areas after the training. The gain in target areas of teaching skills selected to improve the reading skills of children was evaluated through peer feedback. Teachers were assigned to three groups and expected to model how they were going to introduce the skills in recommended areas using researcher developed, validated and reliability reliability-tested materials and the strategies which were introduced during the training within the given tasks. Peers and the primary investigator rated teachers’ performances and gave feedback on organizational skills, presentation skills of materials, clarity of instruction, and appropriateness of vocabulary. After modifying their skills according to the feedback the teachers received, they were expected to modify and represent the same tasks to the group the following day. Their skills were re-evaluated by the peers and primary investigator using the same rubrics to measure the improvement. The findings revealed a significant improvement in their teaching skills development. The data analysis of both knowledge and skills gains of the teachers was carried out using quantitative descriptive data analysis. The overall findings of the study yielded promising results that support intensive training as a method for improving teachers’ knowledge and teaching skill development for use with children in a whole class intervention setting who are at risk of dyslexia.

Keywords: Dyslexia, knowledge, teaching skills, training program

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Authors: Abdulhakim Ali Mosleh Alzubidy

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The study's aim was to establish a proposed training program for kindergarten teachers according to their modern professional demands so that they could effectively teach children through movement education and play. The sample, which consisted of (46) teachers and administrators selected at random from the Ibb governorate, represented the study population of kindergarten teachers and administrators. The researcher developed three survey forms as a tool for data collection, and the forms were used with the research sample. The researcher used the descriptive method due to its applicability and the nature of the study, and he also used the appropriate statistical treatment of the data, which is to extract the percentage and the percentage of agreement. The study came to the following conclusions: ● The proposed program is of great importance in preparing the kindergarten teacher in an appropriate manner that keeps pace with modern developments in this field. ● The field of movement education is a necessity for the kindergarten teacher, through which she will be able to prepare the child physically and kinetically and teach him effectively the principles of reading, writing, and numerical and arithmetic concepts.

Keywords: training program, professional needs, kindergarten, kindergarten teacher

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Authors: Zongping Wang, Chengjun Cui, Jiacun Wang

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The concept of intelligence has been widely used to access an individual's cognitive abilities to learn, form concepts, understand, apply logic, and reason. According to the multiple intelligence theory, there are eight distinguished types of intelligence. One of them is the bodily-kinaesthetic intelligence that links to the capacity of an individual controlling his body and working with objects. Motor intelligence, on the other hand, reflects the capacity to understand, perceive and solve functional problems by motor behavior. Both bodily-kinaesthetic intelligence and motor intelligence refer directly or indirectly to bodily capacity. Inspired by these two intelligence concepts, this paper introduces motional intelligence (MI). MI is two-fold. (1) Body strength, which is the capacity of various organ functions manifested by muscle activity under the control of the central nervous system during physical exercises. It can be measured by the magnitude of muscle contraction force, the frequency of repeating a movement, the time to finish a movement of body position, the duration to maintain muscles in a working status, etc. Body strength reflects the objective of MI. (2) Level of psychiatric willingness to physical events. It is a subjective thing and determined by an individual’s self-consciousness to physical events and resistance to fatigue. As such, we call it subjective MI. Subjective MI can be improved through education and proper social events. The improvement of subjective MI can lead to that of objective MI. A quantitative score of an individual’s MI is motional quotient (MQ). MQ is affected by several factors, including genetics, physical training, diet and lifestyle, family and social environment, and personal awareness of the importance of physical exercise. Genes determine one’s body strength potential. Physical training, in general, makes people stronger, faster and swifter. Diet and lifestyle have a direct impact on health. Family and social environment largely affect one’s passion for physical activities, so does personal awareness of the importance of physical exercise. The key to the success of the MQ study is developing an acceptable and efficient system that can be used to assess MQ objectively and quantitatively. We should apply different accessing systems to different groups of people according to their ages and genders. Field test, laboratory test and questionnaire are among essential components of MQ assessment. A scientific interpretation of MQ score is part of an MQ assessment system as it will help an individual to improve his MQ. IQ (intelligence quotient) and EQ (emotional quotient) and their test have been studied intensively. We argue that IQ and EQ study alone is not sufficient for an individual’s all round development. The significance of MQ study is that it offsets IQ and EQ study. MQ reflects an individual’s mental level as well as bodily level of intelligence in physical activities. It is well-known that the American Springfield College seal includes the Luther Gulick triangle with the words “spirit,” “mind,” and “body” written within it. MQ, together with IQ and EQ, echoes this education philosophy. Since its inception in 2012, the MQ research has spread rapidly in China. By now, six prestigious universities in China have established research centers on MQ and its assessment.

Keywords: motional Intelligence, motional quotient, multiple intelligence, motor intelligence, all round development

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Authors: Verd Shomrom, Gilat Trabelsi

Abstract:

The goal of the study was to examine the effects of Computerized Cognitive Training (CCT) with and without cognitive mediation on Executive Function (EF) (planning and self- regulation) and on psychological resiliency among adolescents with Attention Deficits Hyperactive Disorder (ADHD) with or without Learning Disabilities (LD). Adolescents diagnosed with Attention Deficit Disorder and / or Learning Disabilities have multidimensional impairments that result from neurological damage. This work explored the possibility of influencing cognitive aspects in the field of Executive Functions (specifically: patterns of planning and self-regulation) among adolescents with a diagnosis of Attention Deficit Disorder and / or Learning Disabilities who study for a 10-12 grades. 46 adolescents with ADHD and/or with LD were randomly applied to experimental and control groups. All the participants were tested (BRC- research version, Resiliency quaternaries) before and after the intervention: mediated/ non-mediated Computerized Cognitive Training (MINDRI). The results indicated significant effects of cognitive modification in the experimental group, between pre and post Phases, in comparison to control group, especially in self- regulation (BRC- research version, Resiliency quaternaries), and on process analysis of Computerized Cognitive Training (MINDRI). The main conclusion was that even short- term mediation synchronized with CCT could greatly enhance the performance of executive functions demands. Theoretical implications for the positive effects of MLE in combination with CCT indicate the ability for cognitive change. The practical implication is the awareness and understanding of efficient intervention processes to enhance EF, learning awareness, resiliency and self-esteem of adolescents in their academic and daily routine.

Keywords: attention deficits hyperactive disorder, computerized cognitive training, executive function, mediated learning experience, learning disabilities

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

Abstract:

An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: Lorena Caires Moreira, Marcos Kauffman

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This paper outlines the results of experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance of highly customized and high-risk manual operations. The focus is on operators’ training capabilities and the aim is to test if such technologies can support achieving higher levels of knowledge retention and accuracy of task execution to improve health and safety (H and S) levels. The proposed solution is tested and validated using a real-world case study of electric vehicles’ battery module assembly. The experimental results revealed that the proposed AR method improved the training practices by increasing the knowledge retention levels from 40% to 84% and improved the accuracy of task execution from 20% to 71%, compared to the traditional paper-based method. The results of this research can be used as a demonstration of how emerging technologies are advancing the choice of manual, hybrid, or fully automated processes by promoting the connected worker (Industry 5.0) and supporting manufacturing in becoming more resilient in times of constant market changes.

Keywords: augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly, industry 5.0, smart training, battery assembly

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Authors: A. I. Al-Bassam, A. M. El-Nggar

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Polycrystalline Cu In I-x GaxSe2 thin films have been fabricated. Some physical properties such as lattice parameters, crystal structure and microstructure of Cu In I-x GaxSe2 were determined using X-ray diffractometry and scanning electron microscopy. X-ray diffraction analysis showed that the films with x ≥ 0.5 have a chalcopyrite structure and the films with x ≤ 0.5 have a zinc blende structure. The lattice parameters were found to vary linearly with composition over a wide range from x = 0 to x =1.0. The variation of lattice parameters with composition was found to obey Vegard's law. The variation of the c/a with composition was also linear. The quality of a wide range of Cu In I-xGaxSe2 thin film absorbers from CuInSe to CuGaSe was evaluated by Photoluminescence (PL) measurements.

Keywords: grain size, polycrystalline, solar cells, lattice parameters

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Authors: Abdulatif Abdulsalam Mohamed Shaban

Abstract:

This paper states that the art of Procedure Entry Array (PEA) plan with a focus on control system applications. This paper begins with an impression of PEA technology development, followed by an arrangement of design technologies, and the use of programmable description languages and system-level design tools. They allow a practical approach based on a unique model for complete engineering electronics systems. There are three main design rules are implemented in the system. These are algorithm based fine-tuning, modularity, and the control act and the architectural constraints. An overview of contributions and limits of PEAs is also given, followed by a short survey of PEA-based gifted controllers for recent engineering systems. Finally, two complete and timely case studies are presented to illustrate the benefits of a PEA implementation when using the proposed system modelling and devise attitude. These consist of the direct control for training motor drives and the control of a diesel-driven stand-alone generator with the help of logical design.

Keywords: control (DC), engineering electronics systems, training motor drives, procedure entry array

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Authors: Nicolas Lipchak, Franco Aiducic, Santiago Baieli

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The present work is a part of the research project called ‘Testing of gas turbine KingTech with biodiesel’, carried out by the Department of Industrial Engineering of the National Technological University at Buenos Aires. The research group aims to experiment with biodiesel in a gas turbine Kingtech K-100 to verify the correct operation of it. In this sense, tests have been developed to obtain real data of parameters inherent to the work cycle, to be used later as parameters of comparison and performance analysis. In the first instance, the study consisted in testing the gas turbine with a mixture composition of 50% Biodiesel and 50% Diesel. The parameters arising from the measurements made were compared with the parameters of the gas turbine with a composition of 100% Diesel. In the second instance, the measured parameters were used to calculate the power generated and the thermal efficiency of the Kingtech K-100 turbine. The turbine was also inspected to verify the status of the internals due to the use of biofuels. The conclusions obtained allow empirically demonstrate that it is feasible to use biodiesel in this type of gas turbines, without the use of this fuel generates a loss of power or degradation of internals.

Keywords: biodiesel, efficiency, KingTech, turbine

Procedia PDF Downloads 240