Search results for: decentralized distributed training

Authors: Ana Violante, Jodie Maccarrone, Maria Fimiani

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In the United States, over 30 million people are hospitalized annually for conditions that require acute, 24-hour, supervised care. The experience of hospitalization can be traumatic, exposing the patient to loss of control, autonomy, and productivity. Furthermore, 40% of patients admitted to hospitals for general medical illness have a comorbid psychiatric diagnosis. Research suggests individuals admitted with psychiatric comorbidities experience poorer health outcomes, higher utilization rates and increased overall cost of care. Empirical work suggests hospital settings that include a consultation liaison (CL) service report reduced length of stay, lower costs per patient, improved medical staff and patient satisfaction and reduced readmission after 180 days. Despite the overall positive impact CL services can have on patient care, it is estimated that only 1% - 2.8% of hospital admits receive these services, and most research has been conducted by the field of psychiatry. Health psychologists could play an important role in increasing access to this valuable service, though the extent to which health psychologists participate in CL settings is not well known. Objective: Outline the preliminary findings from an empirical study to understand how many APPIC internship training programs offer adult consultation liaison rotations within inpatient hospital settings nationally, as well as describe the specific nature of these training experiences. Research Method/Design: Data was exported into Excel from the 2022-2023 APPIC Directory categorized as “health psychology” sites. It initially returned a total of 537 health training programs out 1518 total programs (35% of all APPIC programs). A full review included a quantitative and qualitative comprehensive review of the APPIC program summary, the site website, and program brochures. The quantitative review extracted the number of training positions; amount of stipend; location or state of program, patient, population, and rotation. The qualitative review examined the nature of the training experience. Results: 29 (5%) of all APPIC health psychology internship training programs (2%) respectively of all APPIC training internship programs offering internship CL training were identified. Of the 29 internship training programs, 16 were exclusively within a pediatric setting (55%), 11 were exclusively within an adult setting (38%), and two were a mix of pediatric and adult settings (7%). CL training sites were located to 19 states, offering a total of 153 positions nationally, with Florida containing the largest number of programs (4). Only six programs offered 12-month training opportunities while the rest offered CL as a major (6 month) to minor (3-4 month) rotation. The program’s stipend for CL training positions ranged from $25,000 to $62,400, with an average of $32,056. Conclusions: These preliminary findings suggest CL training and services are currently limited. Training opportunities that do exist are mostly limited to minor, short rotations and governed by psychiatry. Health psychologists are well-positioned to better define the role of psychology in consultation liaison services and enhance and formalize existing training protocols. Future research should explore in more detail empirical outcomes of CL services that employ psychology and delineate the contributions of psychology from psychiatry and other disciplines within an inpatient hospital setting.

Keywords: consultation liaison, health psychology, hospital setting, training

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Authors: Samuel Knox, Verdon Crann, Peyman Amiri, William Crowther

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There exists a shortage of open-source firmware for allowing researchers to focus on implementing high-level planning and control strategies for multi aerial robotic systems in simulation and experiment. Within this body of work, practical firmware is presented, which performs all supplementary tasks, including communications, pre and post-experiment procedures, and emergency safety measures. This allows researchers to implement high-level planning and control algorithms for path planning, traffic management, flight formation and swarming of aerial robots. The framework is built in Python using the MAVSDK library, which is compatible with flight controllers running PX4 firmware and onboard computers based on Linux. Communication is performed using Wi-Fi and the MQTT protocol, currently implemented using a centralized broker. Finally, a graphical user interface (GUI) has been developed to send general commands and monitor the agents. This framework enables researchers to prepare customized planning and control algorithms in a modular manner. Studies can be performed experimentally and in simulation using PX4 software in the loop (SITL) and the Gazebo simulator. An example experimental use case of the framework is presented using novel distributed planning and control strategies. The demonstration is performed using off-the-shelf components and minimal setup.

Keywords: aerial robotics, distributed framework, experimental, planning and control

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Authors: Che Hsiu Chen, Su Yun Chen, Hon Wen Cheng

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Greater core stability may benefit sports performance by providing a foundation for greater force production in the upper and lower extremities. Core stability exercises on instability device (such as the TRX suspension systems) were found to be able to induce higher core muscle activity than performing on a stable surface. However, high intensity interval TRX suspension exercises training on sport performances remain unclear. The purpose of this study was to examine whether high intensity TRX suspension training could improve sport performance. Twenty-four healthy university female students (age 19.0 years, height 157.9 cm, body mass 51.3 kg, fat mass 25.2 %) were voluntarily participated in this study. After a familiarization session, each participant underwent five suspension exercises (e.g., hip abduction in plank alternative, hamstring curl, 45-degree row, lunge and oblique crunch). Each type of exercise was performed for 30 seconds, followed by 30 seconds break, two times per week for eight weeks while each exercise session was increased by 10 seconds every week. The results showed that the fat mass (about 12.92%) decreased significantly, sit and reach test (9%), 1 minute sit-up test (17.5%), standing broad jump (4.8%), physical fitness index (10.3%) increased significantly after 8-week high intensity TRX suspension training. Hence, eight weeks of high intensity interval TRX suspension exercises training can improve hamstring flexibility, trunk endurance, jump ability, aerobic fitness and fat mass percentage decreased substantially.

Keywords: core endurance, jump, flexibility, cardiovascular fitness

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Authors: Ali Karimi, Shabnam Karimifam, Amirhosein Karimi, Farahnaz Pournavvab

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Researches have emphasis on the important role of psychosocial support and appropriate interventions for individuals that involved in serious physical and psychological problems . Patients with AIDS are often discussed in studies, but sometimes the psychological conditions of the people who live with them are ignored. In the present study, while paying attention to the spouses of AIDS patients, the role of supportive interventions has been investigated. the other word , Researchers Show that life skills training causes significant improvement in the mean scores of mothers physical health , mental health, social relationship and ultimately quality of life in the experimental group . The purpose of this study is determine of mental health of Twenty-one wives of patients with HIV+ In Shiraz ( city in sought of Iran) and effects of life skills on promotion of their mental health . Sampling was systematic randomize . These women were selected and invited to the training program based on their husbands' file numbers, who were selected to the counseling center for people with AIDS. first , they filled out GHQ questionnaires . Then , the life skills training for 8 sessions were taught for these women . Results indicated that Psychological condition of wife of patients with HIV+ was not appropriate . Scores of most them were above of cut of point of questionnaires .T test was done . worse scores were Assigned to anxiety and weakness in social functions . In the other hand , life skills have been effective significantly only in social functions of women . Scores of research’s participants in anxiety , depression and total test score were enhanced , but have not been significant . In the main of article , researchers have discussed why life skills training does not have much effect on some emotional problems .Despite the fact that life skills training had a positive effect on these spouses, but due to the stress of women with AIDS spouses, life skills training did not show much effectiveness, and for outstanding effects, there is a need for individual psychological treatments and broader social support.

Keywords: Hiv, aids, social suport, life skills

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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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

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Priyajeet Kaur Kaleka

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Introduction: A dentist is often the first responder in the battle for a patient’s healthy body and maybe the first health professional to observe signs of child abuse, be it physical, emotional, and/or sexual mistreatment. Therefore, it is an ethical responsibility for the dental clinician to detect and report suspected cases of child abuse and neglect (CAN). The main reasons for not reporting suspected cases of CAN, with special emphasis on the third: 1) Uncertainty of the diagnosis, 2) Lack of knowledge of the reporting procedure, and 3) Child abuse and neglect somewhat remained the subject of ignorance among dental professionals because of a lack of advance clinical training. Given these epidemic proportions, there is a scope of further research about dental school curriculum design. Purpose: This study aimed to assess the knowledge and attitude of dentists in Canada regarding signs and symptoms of child abuse and neglect (CAN), reporting procedures, and whether educational strategies followed by dental schools address this sensitive issue. In pursuit of that aim, this abstract summarizes the evidence related to this question. Materials and Methods: Data was collected through a specially designed questionnaire adapted and modified from the author’s previous cross-sectional study on (CAN), which was conducted in Pune, India, in 2016 and is available on the database of PubMed. Design: A random sample was drawn from the targeted population of registered dentists and dental students in Canada regarding their knowledge, professional responsibilities, and behavior concerning child abuse. Questionnaire data were distributed to 200 members. Out of which, a total number of 157 subjects were in the final sample for statistical analysis, yielding response of 78.5%. Results: Despite having theoretical information on signs and symptoms, 55% of the participants indicated they are not confident to detect child physical abuse cases. 90% of respondents believed that recognition and handling the CAN cases should be a part of undergraduate training. Only 4.5% of the participants have correctly identified all signs of abuse due to inadequate formal training in dental schools and workplaces. Although nearly 96.3% agreed that it is a dentist’s legal responsibility to report CAN, only a small percentage of the participants reported an abuse case in the past. While 72% stated that the most common factor that might prevent a dentist from reporting a case was doubt over the diagnosis. Conclusion: The goal is to motivate dental schools to deal with this critical issue and provide their students with consummate training to strengthen their capability to care for and protect children. The educational institutions should make efforts to spread awareness among dental students regarding the management and tackling of CAN. Clinical Significance: There should be modifications in the dental school curriculum focusing on problem-based learning models to assist graduates to fulfill their legal and professional responsibilities. CAN literacy should be incorporated into the dental curriculum, which will eventually benefit future dentists to break this intergenerational cycle of violence.

Keywords: abuse, child abuse and neglect, dentist knowledge, dental school curriculum, problem-based learning

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Authors: Sanjay Rathee, Arti Kashyap

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Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

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Authors: Mariem Saied, Jens Gustedt, Gilles Muller

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We present Dido, a source-to-source auto-generation and optimization framework for multi-dimensional stencil computations. It enables a large programmer community to easily and safely implement stencil codes on distributed-memory parallel architectures with Ordered Read-Write Locks (ORWL) as an execution and communication back-end. ORWL provides inter-task synchronization for data-oriented parallel and distributed computations. It has been proven to guarantee equity, liveness, and efficiency for a wide range of applications, particularly for iterative computations. Dido consists mainly of an implicitly parallel domain-specific language (DSL) implemented as a source-level transformer. It captures domain semantics at a high level of abstraction and generates parallel stencil code that leverages all ORWL features. The generated code is well-structured and lends itself to different possible optimizations. In this paper, we enhance Dido to handle both Jacobi and Gauss-Seidel grid traversals. We integrate temporal blocking to the Dido code generator in order to reduce the communication overhead and minimize data transfers. To increase data locality and improve intra-node data reuse, we coupled the code generation technique with the polyhedral parallelizer Pluto. The accuracy and portability of the generated code are guaranteed thanks to a parametrized solution. The combination of ORWL features, the code generation pattern and the suggested optimizations, make of Dido a powerful code generation framework for stencil computations in general, and for distributed-memory architectures in particular. We present a wide range of experiments over a number of stencil benchmarks.

Keywords: stencil computations, ordered read-write locks, domain-specific language, polyhedral model, experiments

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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: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

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The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, climate change, hydrological modeling, watershed

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Authors: Oliver Takawira, Thembi Hope

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This study will analyse the relationship between Bitcoin price movements and the Johannesburg stock exchange (JSE). The aim is to determine whether Bitcoin price movements affect the stock market performance. As crypto currencies continue to gain prominence as a safe asset during periods of economic distress, this raises the question of whether Bitcoin’s prosperity could affect investment in the stock market. To identify the existence of a short run and long run linear relationship, the study will apply the Autoregressive Distributed Lag Model (ARDL) bounds test and a Vector Error Correction Model (VECM) after testing the data for unit roots and cointegration using the Augmented Dicker Fuller (ADF) and Phillips-Perron (PP). The Non-Linear Auto Regressive Distributed Lag (NARDL) will then be used to check if there is a non-linear relationship between bitcoin prices and stock market prices.

Keywords: bitcoin, stock market, interest rates, ARDL

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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: Ying-chang Yu, Yuan-lung Lo

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More and more building envelopes consist of the construction of balconies, canopies, handrails, sun-shading, vertical planters or gardens, maintenance platforms, display devices, lightings, ornaments, and also the most commonly seen double skin system. These components form a uniform but three-dimensional disturbance structure and create a complex surface wind field in front of the actual watertight building interface. The distorted wind behavior would affect the façade performance and building ventilation. Comparing with sole windscreen walls, these three-dimensional structures perform like distributed air portal assembly, and each portal generates air turbulence and consume wind pressure and energy simultaneously. In this study, we attempted to compare the behavior of 2D porous windscreens without internal construction, porous tubular portal windscreens, porous tapered portal windscreens, and porous coned portal windscreens. The wind energy reduction phenomenon is then compared to the different distributed air portals. The experiments are conducted in a physical wind tunnel with 1:25 in scale to simulate the three-dimensional structure of a real building envelope. The experimental airflow was set up to smooth flow. The specimen is designed as a plane with a distributed tubular structure behind, and the control group uses different tubular shapes but the same fluid volume to observe the wind damping phenomenon of various geometries.

Keywords: volumized building envelope, porous air portal, wind damping, wind tunnel test, wind energy loss

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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: Verd Shomrom, Gilat Trabelsi

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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: 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: Abdulatif Abdulsalam Mohamed Shaban

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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: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

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Authors: Lucy Tsado

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As cybercrime and cyberattacks continue to increase, the need to respond will follow suit. When cybercrimes occur, the duty to respond sometimes falls on law enforcement. However, criminal justice students are not taught concepts in cybersecurity and digital forensics. There is, therefore, an urgent need for many more institutions to begin teaching cybersecurity and related courses to social science students especially criminal justice students. However, many faculty in universities, colleges, and high schools are not equipped to teach these courses or do not have the knowledge and resources to teach important concepts in cybersecurity or digital forensics to criminal justice students. This research intends to develop curricula and training programs to equip faculty with the skills to meet this need. There is a current call to involve non-technical fields to fill the cybersecurity skills gap, according to experts. There is a general belief among non-technical fields that cybersecurity education is only attainable within computer science and technologically oriented fields. As seen from current calls, this is not entirely the case. Transitioning into the field is possible through curriculum development, training, certifications, internships and apprenticeships, and competitions. There is a need to identify how a cybersecurity eco-system can be created at a university to encourage/start programs that will lead to an interest in cybersecurity education as well as attract potential students. A short-term strategy can address this problem through curricula development, while a long-term strategy will address developing training faculty to teach cybersecurity and digital forensics. Therefore this research project addresses this overall problem in two parts, through curricula development for the criminal justice discipline; and training of faculty in criminal justice to teaching the important concepts of cybersecurity and digital forensics.

Keywords: cybersecurity education, criminal justice, curricula development, nontechnical cybersecurity, cybersecurity, digital forensics

Procedia PDF Downloads 90

Authors: Magdy Abouzeid, Nancy Abouzeid, Afaf Salem

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Background: The elite child athletes are one who has superior athletic talent. Monofin (a single surface swim fin) swimming already proved to be the most efficient method of swimming for human being. This is a novel descriptive study examining myocardial function indices in prepubertal monofin children. The aim of the present study was to determine the influence of long-term monofin training (LTMT), 36 weeks, 6 times per week, 90 min per unit on Myocardial function adaptation in elite child monofin athletes. Methods: 14 elite monofin children aged 11.95 years (± 1.09 yr) took part for (LTMT). All subjects underwent two-dimension, M-mode, and Doppler echocardiography before and after training to evaluate cardiac dimensions and function; septal and posterior wall thickness. Statistical methods of SPSS, means ± SD and paired t test, % of improvement were used. Findings: There was significant difference (p<0.01) and % improvement for all echocardiography parameter after (LTMT). Inter ventricular septal thickness in diastole and in systole increased by 27.9 % and 42.75 %. Left ventricular end systolic dimension and diastole increased by 16.81 % and 42.7 % respectively. Posterior wall thickness in systole very highly increased by 283.3 % and in diastole increased by 51.78 %. Left ventricular mass in diastole and in systole increased by 44.8 % and 40.1 % respectively. Stroke volume (SV) and resting heart rate (HR) significant changed (sv) 25 %, (HR) 14.7 %. Interpretation: the unique swim fin tool and create propulsion and overcome resistance. Further researches are needed to determine the effects of monofin training on right ventricular in child athletes.

Keywords: prepubertal, monofin training, heart athlete's, elite child athlete, echocardiography

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Authors: Gianna Zou

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Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

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Authors: Adebayo Emmanuel Layi

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Library and Information Science Education is about six (6) decades old in Nigeria. The first Library School was established in 1962 at the University of Ibadan, and since then, several institutions have been running the programme under various certifications, providing the manpower needs of professionals for libraries. As at June 2023, Nigeria has close to a thousand (1000) tertiary institutions and all needing the services of librarians. Apart from the tertiary institutions, several libraries exit in various establishments, both government, private and non-governmental organisations. These has underscored the enormous need for trained librarians for the libraries in these places. The Nexus between LIS Education training and Practice is like a puzzle of egg and chick, which one came first and against this background, this paper examined the roles of the colonial masters in educational development in Africa and vis-à-vis the influence of great library educators such as Melvil Dewey and other educators and the journey through Nigeria institutions. Despite the sound footing of LIS Education, Noise which seems to be a major obstacle on the practice as well as mending the broken link were all examined in the paper. Strategies and the way forward for overall development are suggested.

Keywords: nexus, education, training, synergy

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Authors: Angelika Lau

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One aspect totally underrepresented regarding the effectiveness of gamification in education is gameful experience. To examine the extent to which gameful experience has been considered empirically, a systematic review was conducted. By doing so, comprehensive state-of-the-art research of gameful experience in higher education and organizational training is provided. This way, the actual gameful efficiency of gamification applications is disclosed and summarized. The review indicates that gamification provides positive effects, however, emphasizing the need for further research in this regard.

Keywords: game experience, gameful experience, game-like experience, gamification

Procedia PDF Downloads 268

Authors: E. K. Soyele

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This study is on capacity building and motivation as determinants of productivity among library personnel in colleges of education in South West, Nigeria. This study made use of a descriptive research design of survey type. A total enumeration sampling technique was used for the selected sample. The research sample consisted of 40 library personnel. The instrument used for the study was a structured questionnaire divided into four parts. Statistics data analysis used were descriptive statistics with frequencies, percentages, and regression statistics analysis. Findings from this study revealed that capacity building and motivation have positive impact on library personnel productivity with their percentages greater than 50% acceptance level. A test of null hypotheses at P < 0.05 significant level was tested to see the significance between capacity building and productivity, which was positive at P < 0.05 significant level. This implies that capacity building and motivation significantly determine productivity among library personnel in selected college libraries in Nigeria. The study concluded that there is need for institutions to equip their library personnel via training programmes, in-service, digital training, ICT training, seminars, and conferences, etc. Incentives should be provided to motivate personnel for high productivity. The study, therefore, recommends that government, institutions and library management should fund college libraries adequately so as to enhance capacity building, staff commitment and training for further education

Keywords: capacity building, library personnel, motivation, productivity

Procedia PDF Downloads 184

Authors: Oludamilare Bode Adewuyi, Yanxia Sun, Isaiah Gbadegesin Adebayo

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Voltage stability analysis is crucial to the reliable and economic operation of power systems. The power system of developing nations is more susceptible to failures due to the continuously increasing load demand, which is not matched with generation increase and efficient transmission infrastructures. Thus, most power systems are heavily stressed, and the planning of extra generation from distributed generation sources needs to be efficiently done so as to ensure the security of the power system. Some voltage stability index-based approach for DG siting has been reported in the literature. However, most of the existing voltage stability indices, though sufficient, are found to be inaccurate, especially for overloaded power systems. In this paper, the performance of a relatively different approach using a line voltage stability margin indicator, which has proven to have better accuracy, has been presented and compared with a conventional line voltage stability index for DG siting using the Nigerian 28 bus system. Critical boundary index (CBI) for voltage stability margin estimation was deployed to identify suitable locations for DG placement, and the performance was compared with DG placement using the Novel Line Stability Index (NLSI) approach. From the simulation results, both CBI and NLSI agreed greatly on suitable locations for DG on the test system; while CBI identified bus 18 as the most suitable at system overload, NLSI identified bus 8 to be the most suitable. Considering the effect of the DG placement at the selected buses on the voltage magnitude profile, the result shows that the DG placed on bus 18 identified by CBI improved the performance of the power system better.

Keywords: voltage stability analysis, voltage collapse, voltage stability index, distributed generation

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Authors: Leif Inge Tjelta, Gerd Lise Nordbotten, Cathrine Nyhus Hagum, Merete Hagen Helland

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Overweight and obesity can lead to numerous health problems, and inactive people are more often overweight and obese compared to physically active people. Even a moderate weight loss can improve cardiovascular and endocrine disease risk factors. The aim of the study was to examine to what extent overweight and obese adults starting up with two weekly intensive running sessions had an increase in aerobic capacity, reduction in BMI and waist circumference and changes in body composition after 33 weeks of training. An additional aim was to see if there were differences between participants who, in addition to training, also received lifestyle modification education, including practical cooking (nutritional guidance and training group (NTG =32)) compared to those who were not given any nutritional guidance (training group (TG=40)). 72 participants (49 women), mean age of 46.1 ( ± 10.4) were included. Inclusion Criteria: Previous untrained and inactive adults in all age groups, BMI ≥ 25, desire to become fitter and reduce their BMI. The two weekly supervised training sessions consisted of 10 min warm up followed by 20 to 21 min effective interval running where the participants’ heart rate were between 82 and 92% of hearth rate maximum. The sessions were completed with ten minutes whole body strength training. Measures of BMI, waist circumference (WC) and 3000m running time were performed at the start of the project (T1), after 15 weeks (T2) and at the end of the project (T3). Measurements of fat percentage, muscle mass, and visceral fat were performed at T1 and T3. Twelve participants (9 women) from both groups, who all scored around average on the 3000 m pre-test, were chosen to do a VO₂max test at T1 and T3. The NTG were given ten theoretical sessions (80 minutes each) and eight practical cooking sessions (140 minutes each). There was a significant reduction in bout groups for WC and BMI from T1 to T2. There was not found any further reduction from T2 to T3. Although not significant, NTG reduced their WC more than TG. For both groups, the percentage reduction in WC was similar to the reduction in BMI. There was a decrease in fat percentage in both groups from pre-test to post-test, whereas, for muscle mass, a small, but insignificant increase was observed for both groups. There was a decrease in 3000m running time for both groups from T1 to T2 as well as from T2 to T3. The difference between T2 and T3 was not statistically significant. The 12 participants who tested VO₂max had an increase of 2.86 ( ± 3.84) mlkg⁻¹ min⁻¹ in VO₂max and 3:02 min (± 2:01 min) reduction in running time over 3000 m from T1 until T3. There was a strong, negative correlation between the two variables. The study shows that two intensive running session in 33 weeks can increase aerobic fitness and reduce BMI, WC and fat percent in inactive adults. Cost guidance in addition to training will give additional effect.

Keywords: interval training, nutritional guidance, fitness, BMI

Procedia PDF Downloads 132