Search results for: the health improvement network (THIN)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17623

Search results for: the health improvement network (THIN)

15133 Teacher's Health: Evaluation of the Health Status of Portuguese and Spanish Teachers

Authors: Liberata Borralho, Saúl N. de Jesus, Adelinda Candeias, Victória Fernández-Puig

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In the last decades, we have witnessed a deterioration in the health of teachers worldwide, reflecting the constant social, political and economic changes. The quality of teaching and the success of students depends on the health status of the teachers, which justifies the importance of periodically evaluating their health. With this purpose, the Teacher’s Health Questionnaire was applied to 15.394 teachers teaching in Portugal and Spain (6.208 Spanish and 9.186 Portuguese) of primary and secondary education (3.482 men, 11.911 women). This questionnaire is specific and includes both the main risks of the teaching profession and the manifestations of teacher well-being, according to the definition recommended by the World Health Organization. A descriptive analysis of the results was carried out, including a study of the dimensions and the differences according to some sociodemographic and professional variables, from an analysis of variance ANOVA, applying the Bonferroni correction. Cluster analysis (K-means) allowed us to obtain cutoff scores to assess health status. The results allow concluding that Portuguese teachers perceive a poor well-being in the performance of their professional activity and that more than half present manifestations in the various dimensions of health deterioration, highlighting the exhaustion and cognitive disorders. In turn, Spanish teachers demonstrate a high level of well-being, being the musculoskeletal dimensions and cognitive disorders the main manifestations of deterioration of health.

Keywords: job prevention, occupational health, teacher’s health, teachers work risks, teacher’s well-being

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15132 A Comparison of Neural Network and DOE-Regression Analysis for Predicting Resource Consumption of Manufacturing Processes

Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

Procedia PDF Downloads 516
15131 Performance Improvement of The Nano-Composite Based Proton Exchange Membranes (PEMs)

Authors: Yusuf Yılmaz, Kevser Dincer, Derya Saygılı

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In this study, performance of PEMs was experimentally investigated. Coating on the cathode side of the PEMs fuel cells was accomplished with the spray method by using NaCaNiBO. A solution having 0,1 gr NaCaNiBO +10 mL methanol was prepared. This solution was taken out and filled into a spray. Then the cathode side of PEMs fuel cells was cladded with NaCaNiBO by using spray method. After coating, the membrane was left out to dry for 24 hours. The PEM fuel cells were mounted to the system in single, double, triple and fourfold manner in order to spot the best performance. The performance parameter considered was the power to current ratio. The best performance was found to occur at the 300th second with the power/current ratio of 3.55 Watt/Ampere and on the fourfold parallel mounting after the coating; whereas the poorest performance took place at the 210th second, power to current ratio of 0.12 Watt/Ampere and on the twofold parallel connection after the coating.

Keywords: nano-composites, proton exchange membranes, performance improvement, fuel cell

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15130 Anticipation of Bending Reinforcement Based on Iranian Concrete Code Using Meta-Heuristic Tools

Authors: Seyed Sadegh Naseralavi, Najmeh Bemani

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In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.

Keywords: adaptive neuro fuzzy inference system, anticipate method, artificial neural network, concrete design code, multi-variable regression

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15129 A Hybrid Genetic Algorithm and Neural Network for Wind Profile Estimation

Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

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Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

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15128 Wireless Information Transfer Management and Case Study of a Fire Alarm System in a Residential Building

Authors: Mohsen Azarmjoo, Mehdi Mehdizadeh Koupaei, Maryam Mehdizadeh Koupaei, Asghar Mahdlouei Azar

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The increasing prevalence of wireless networks in our daily lives has made them indispensable. The aim of this research is to investigate the management of information transfer in wireless networks and the integration of renewable solar energy resources in a residential building. The focus is on the transmission of electricity and information through wireless networks, as well as the utilization of sensors and wireless fire alarm systems. The research employs a descriptive approach to examine the transmission of electricity and information on a wireless network with electric and optical telephone lines. It also investigates the transmission of signals from sensors and wireless fire alarm systems via radio waves. The methodology includes a detailed analysis of security, comfort conditions, and costs related to the utilization of wireless networks and renewable solar energy resources. The study reveals that it is feasible to transmit electricity on a network cable using two pairs of network cables without the need for separate power cabling. Additionally, the integration of renewable solar energy systems in residential buildings can reduce dependence on traditional energy carriers. The use of sensors and wireless remote information processing can enhance the safety and efficiency of energy usage in buildings and the surrounding spaces.

Keywords: renewable energy, intelligentization, wireless sensors, fire alarm system

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15127 Cryptography and Cryptosystem a Panacea to Security Risk in Wireless Networking

Authors: Modesta E. Ezema, Chikwendu V. Alabekee, Victoria N. Ishiwu, Ifeyinwa NwosuArize, Chinedu I. Nwoye

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The advent of wireless networking in computing technology cannot be overemphasized, it opened up easy accessibility to information resources, networking made easier and brought internet accessibility to our doorsteps, but despite all these, some mishap came in with it that is causing mayhem in today ‘s overall information security. The cyber criminals will always compromise the integrity of a message that is not encrypted or that is encrypted with a weak algorithm.In other to correct the mayhem, this study focuses on cryptosystem and cryptography. This ensures end to end crypt messaging. The study of various cryptographic algorithms, as well as the techniques and applications of the cryptography for efficiency, were all considered in the work., present and future applications of cryptography were dealt with as well as Quantum Cryptography was exposed as the current and the future area in the development of cryptography. An empirical study was conducted to collect data from network users.

Keywords: algorithm, cryptography, cryptosystem, network

Procedia PDF Downloads 339
15126 A Cooperative Signaling Scheme for Global Navigation Satellite Systems

Authors: Keunhong Chae, Seokho Yoon

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Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Keywords: global navigation satellite network, cooperative signaling, data combining, nodes

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15125 Sustainability Enhancement of Pedestrian Space Quality in Old Communities from the Perspective of Inclusiveness:Taking Cao Yang New Village, Shanghai as an Example

Authors: Feng Zisu

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Community is the basic unit of the city, community pedestrian space is also an important part of the urban public space, and its quality improvement is also closely related to the residents' happiness and sense of belonging. Domestic and international research perspectives on community pedestrian space have gradually changed to inclusive design for the whole population, paying more attention to the equitable accessibility of urban space and the multiple composite enhancement of spatial connotation. In order to realize the inclusive and sustainable development of pedestrian space in old communities, this article selects Cao Yang New Village in Shanghai as a practice case, and based on the connotation of inclusiveness, the four dimensions of space, traffic, function and emotion are selected as the layers of inclusive connotation of pedestrian space in old communities. This article identifies the objective social needs, dynamic activity characteristics and subjective feelings of multiple subjects, and reconstructs the structural hierarchy of “spatial perception - behavioral characteristics - subjective feelings” of walking. It also proposes a governance strategy of “reconfiguring the pedestrian network, optimizing street quality, integrating ecological space and reshaping the community scene” from the aspects of quality of physical environment and quality of behavioral perception, aiming to provide new ideas for promoting the inclusive and sustainable development of pedestrian space in old communities.

Keywords: inclusivity, old community, pedestrian space, spatial quality, sustainable renovation

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15124 Power Quality Improvement Using Interval Type-2 Fuzzy Logic Controller for Five-Level Shunt Active Power Filter

Authors: Yousfi Abdelkader, Chaker Abdelkader, Bot Youcef

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This article proposes a five-level shunt active power filter for power quality improvement using a interval type-2 fuzzy logic controller (IT2 FLC). The reference compensating current is extracted using the P-Q theory. The majority of works previously reported are based on two-level inverters with a conventional Proportional integral (PI) controller, which requires rigorous mathematical modeling of the system. In this paper, a IT2 FLC controlled five-level active power filter is proposed to overcome the problem associated with PI controller. The IT2 FLC algorithm is applied for controlling the DC-side capacitor voltage as well as the harmonic currents of the five-level active power filter. The active power filter with a IT2 FLC is simulated in MATLAB Simulink environment. The simulated response shows that the proposed shunt active power filter controller has produced a sinusoidal supply current with low harmonic distortion and in phase with the source voltage.

Keywords: power quality, shunt active power filter, interval type-2 fuzzy logic controller (T2FL), multilevel inverter

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15123 Impact of the Oxygen Content on the Optoelectronic Properties of the Indium-Tin-Oxide Based Transparent Electrodes for Silicon Heterojunction Solar Cells

Authors: Brahim Aissa

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Transparent conductive oxides (TCOs) used as front electrodes in solar cells must feature simultaneously high electrical conductivity, low contact resistance with the adjacent layers, and an appropriate refractive index for maximal light in-coupling into the device. However, these properties may conflict with each other, motivating thereby the search for TCOs with high performance. Additionally, due to the presence of temperature sensitive layers in many solar cell designs (for example, in thin-film silicon and silicon heterojunction (SHJ)), low-temperature deposition processes are more suitable. Several deposition techniques have been already explored to fabricate high-mobility TCOs at low temperatures, including sputter deposition, chemical vapor deposition, and atomic layer deposition. Among this variety of methods, to the best of our knowledge, magnetron sputtering deposition is the most established technique, despite the fact that it can lead to damage of underlying layers. The Sn doped In₂O₃ (ITO) is the most commonly used transparent electrode-contact in SHJ technology. In this work, we studied the properties of ITO thin films grown by RF sputtering. Using different oxygen fraction in the argon/oxygen plasma, we prepared ITO films deposited on glass substrates, on one hand, and on a-Si (p and n-types):H/intrinsic a-Si/glass substrates, on the other hand. Hall Effect measurements were systematically conducted together with total-transmittance (TT) and total-reflectance (TR) spectrometry. The electrical properties were drastically affected whereas the TT and TR were found to be slightly impacted by the oxygen variation. Furthermore, the time of flight-secondary ion mass spectrometry (TOF-SIMS) technique was used to determine the distribution of various species throughout the thickness of the ITO and at various interfaces. The depth profiling of indium, oxygen, tin, silicon, phosphorous, boron and hydrogen was investigated throughout the various thicknesses and interfaces, and obtained results are discussed accordingly. Finally, the extreme conditions were selected to fabricate rear emitter SHJ devices, and the photovoltaic performance was evaluated; the lower oxygen flow ratio was found to yield the best performance attributed to lower series resistance.

Keywords: solar cell, silicon heterojunction, oxygen content, optoelectronic properties

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15122 The Iraqi Fibre-to-the-Home Networks, Problems, Challenges, and Solutions along with Less Expense

Authors: Hasanein Hasan, Mohammed Al-Taie, Basil Shanshool, Khalaf Abd-Ali

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This approach aims to deal with establishing and operating Iraqi Fibre-To-The-Home (FTTH) projects. The problems they suffer from are organized sabotage, vandalism, accidental damage and poor planning. It provides practical solutions that deal with the aforementioned problems. These solutions consist of both technical and financial clarifications that ensure the achievement of the FTTH network’s stability for the purpose of equipping citizens, private sector companies, and governmental institutions with services, data transmission, the Internet, and other services. They aim to solve problems and obstacles accompanying the operation and maintenance of FTTH projects implemented by the Informatics and Telecommunications Public Company (ITPC)/ Iraqi Ministry of Communications (MoC). This approach takes the FTTH network of AlMaalif-AlMuaslat districts/ Baghdad-Iraq as a case study.

Keywords: CCTV, FTTH, ITPC, MoC, NVR, PTZ

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15121 Scale up of Isoniazid Preventive Therapy: A Quality Management Approach in Nairobi County, Kenya

Authors: E. Omanya, E. Mueni, G. Makau, M. Kariuki

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HIV infection is the strongest risk factor for a person to develop TB. Isoniazid preventive therapy (IPT) for People Living with HIV (PLWHIV) not only reduces the individual patients’ risk of developing active TB but mitigates cross infection. In Kenya, IPT for six months was recommended through the National TB, Leprosy and Lung Disease Program to treat latent TB. In spite of this recommendation by the national government, uptake of IPT among PLHIV remained low in Kenya by the end of 2015. The USAID/Kenya and East Africa Afya Jijini project, which supports 42 TBHIV health facilities in Nairobi County, began addressing low uptake of IPT through Quality Improvement (QI) teams set up at the facility level. Quality is characterized by WHO as one of the four main connectors between health systems building blocks and health systems outputs. Afya Jijini implements the Kenya Quality Model for Health, which involves QI teams being formed at the county, sub-county and facility levels. The teams review facility performance to identify gaps in service delivery and use QI tools to monitor and improve performance. Afya Jijini supported the formation of these teams in 42 facilities and built the teams’ capacity to review data and use QI principles to identify and address performance gaps. When the QI teams began working on improving IPT uptake among PLHIV, uptake was at 31.8%. The teams first conducted a root cause analysis using cause and effect diagrams, which help the teams to brainstorm on and to identify barriers to IPT uptake among PLHIV at the facility level. This is a participatory process where program staff provides technical support to the QI teams in problem identification and problem-solving. The gaps identified were inadequate knowledge and skills on the use of IPT among health care workers, lack of awareness of IPT by patients, inadequate monitoring and evaluation tools, and poor quantification and forecasting of IPT commodities. In response, Afya Jijini trained over 300 health care workers on the administration of IPT, supported patient education, supported quantification and forecasting of IPT commodities, and provided IPT data collection tools to help facilities monitor their performance. The facility QI teams conducted monthly meetings to monitor progress on implementation of IPT and took corrective action when necessary. IPT uptake improved from 31.8% to 61.2% during the second year of the Afya Jijini project and improved to 80.1% during the third year of the project’s support. Use of QI teams and root cause analysis to identify and address service delivery gaps, in addition to targeted program interventions and continual performance reviews, can be successful in increasing TB related service delivery uptake at health facilities.

Keywords: isoniazid, quality, health care workers, people leaving with HIV

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15120 A Review of Brain Implant Device: Current Developments and Applications

Authors: Ardiansyah I. Ryan, Ashsholih K. R., Fathurrohman G. R., Kurniadi M. R., Huda P. A

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The burden of brain-related disease is very high. There are a lot of brain-related diseases with limited treatment result and thus raise the burden more. The Parkinson Disease (PD), Mental Health Problem, or Paralysis of extremities treatments had risen concern, as the patients for those diseases usually had a low quality of life and low chance to recover fully. There are also many other brain or related neural diseases with the similar condition, mainly the treatments for those conditions are still limited as our understanding of the brain function is insufficient. Brain Implant Technology had given hope to help in treating this condition. In this paper, we examine the current update of the brain implant technology. Neurotechnology is growing very rapidly worldwide. The United States Food and Drug Administration (FDA) has approved the use of Deep Brain Stimulation (DBS) as a brain implant in humans. As for neural implant both the cochlear implant and retinal implant are approved by FDA too. All of them had shown a promising result. DBS worked by stimulating a specific region in the brain with electricity. This device is planted surgically into a very specific region of the brain. This device consists of 3 main parts: Lead (thin wire inserted into the brain), neurostimulator (pacemaker-like device, planted surgically in the chest) and an external controller (to turn on/off the device by patient/programmer). FDA had approved DBS for the treatment of PD, Pain Management, Epilepsy and Obsessive Compulsive Disorder (OCD). The target treatment of DBS in PD is to reduce the tremor and dystonia symptoms. DBS has been showing the promising result in animal and limited human trial for other conditions such as Alzheimer, Mental Health Problem (Major Depression, Tourette Syndrome), etc. Every surgery has risks of complications, although in DBS the chance is very low. DBS itself had a very satisfying result as long as the subject criteria to be implanted this device based on indication and strictly selection. Other than DBS, there are several brain implant devices that still under development. It was included (not limited to) implant to treat paralysis (In Spinal Cord Injury/Amyotrophic Lateral Sclerosis), enhance brain memory, reduce obesity, treat mental health problem and treat epilepsy. The potential of neurotechnology is unlimited. When brain function and brain implant were fully developed, it may be one of the major breakthroughs in human history like when human find ‘fire’ for the first time. Support from every sector for further research is very needed to develop and unveil the true potential of this technology.

Keywords: brain implant, deep brain stimulation (DBS), deep brain stimulation, Parkinson

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15119 Integration of an Evidence-Based Medicine Curriculum into Physician Assistant Education: Teaching for Today and the Future

Authors: Martina I. Reinhold, Theresa Bacon-Baguley

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Background: Medical knowledge continuously evolves and to help health care providers to stay up-to-date, evidence-based medicine (EBM) has emerged as a model. The practice of EBM requires new skills of the health care provider, including directed literature searches, the critical evaluation of research studies, and the direct application of the findings to patient care. This paper describes the integration and evaluation of an evidence-based medicine course sequence into a Physician Assistant curriculum. This course sequence teaches students to manage and use the best clinical research evidence to competently practice medicine. A survey was developed to assess the outcomes of the EBM course sequence. Methodology: The cornerstone of the three-semester sequence of EBM are interactive small group discussions that are designed to introduce students to the most clinically applicable skills to identify, manage and use the best clinical research evidence to improve the health of their patients. During the three-semester sequence, the students are assigned each semester to participate in small group discussions that are facilitated by faculty with varying background and expertise. Prior to the start of the first EBM course in the winter semester, PA students complete a knowledge-based survey that was developed by the authors to assess the effectiveness of the course series. The survey consists of 53 Likert scale questions that address the nine objectives for the course series. At the end of the three semester course series, the same survey was given to all students in the program and the results from before, and after the sequence of EBM courses are compared. Specific attention is paid to overall performance of students in the nine course objectives. Results: We find that students from the Class of 2016 and 2017 consistently improve (as measured by percent correct responses on the survey tool) after the EBM course series (Class of 2016: Pre- 62% Post- 75%; Class of 2017: Pre- 61 % Post-70%). The biggest increase in knowledge was observed in the areas of finding and evaluating the evidence, with asking concise clinical questions (Class of 2016: Pre- 61% Post- 81%; Class of 2017: Pre- 61 % Post-75%) and searching the medical database (Class of 2016: Pre- 24% Post- 65%; Class of 2017: Pre- 35 % Post-66 %). Questions requiring students to analyze, evaluate and report on the available clinical evidence regarding diagnosis showed improvement, but to a lesser extend (Class of 2016: Pre- 56% Post- 77%; Class of 2017: Pre- 56 % Post-61%). Conclusions: Outcomes identified that students did gain skills which will allow them to apply EBM principles. In addition, the outcomes of the knowledge-based survey allowed the faculty to focus on areas needing improvement, specifically the translation of best evidence into patient care. To address this area, the clinical faculty developed case scenarios that were incorporated into the lecture and discussion sessions, allowing students to better connect the research studies with patient care. Students commented that ‘class discussion and case examples’ contributed most to their learning and that ‘it was helpful to learn how to develop research questions and how to analyze studies and their significance to a potential client’. As evident by the outcomes, the EBM courses achieved the goals of the course and were well received by the students. 

Keywords: evidence-based medicine, clinical education, assessment tool, physician assistant

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15118 Structural, Optical and Electrical Properties of MnxZnO1-X Nanocrystals Synthesized by Sol-Gel Method

Authors: K. C. Gayithri, S. K. Naveen Kumar

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ZnO is one of the most important semiconductor materials, non toxic, biocompatible, antibacterial properties for research and it is used in many biomedical applications. MnxZn1-xO nano thin films were prepared by a spin coating sol-gel method on silicon substrate. The structural, optical, electrical properties of Mn Doped ZnO are studied by using X-rd, FESEM, UV-Visible spectrophotometer. The X-rd reveals that the sample shows hexagonal wurtzits structure. Surface morphology and thickness of the sample are characterized by field emission scanning electron microscopy. Absorption and transmission spectra are studied by UV-Visible spectrophotometer. The electrical properties are measured by TCR meter.

Keywords: transition metals, Mn doped ZnO, Sol-gel, x-ray diffraction

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15117 Proposing an Index for Determining Key Knowledge Management Processes in Decision Making Units Using Fuzzy Quality Function Deployment (QFD), Data Envelopment Analysis (DEA) Method

Authors: Sadegh Abedi, Ali Yaghoubi, Hamidreza Mashatzadegan

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This paper proposes an approach to identify key processes required by an organization in the field of knowledge management and aligning them with organizational objectives. For this purpose, first, organization’s most important non-financial objectives which are impacted by knowledge management processes are identified and then, using a quality house, are linked with knowledge management processes which are regarded as technical elements. Using this method, processes that are in need of improvement and more attention are prioritized based on their significance. This means that if a process has more influence on organization’s objectives and is in a dire situation comparing to others, is prioritized for choice and improvement. In this research process dominance is considered to be an influential element in process ranking (in addition to communication matrix). This is the reason for utilizing DEA techniques for prioritizing processes in quality house. Results of implementing the method in Khuzestan steel company represents this method’s capability of identifying key processes that require improvements in organization’s knowledge management system.

Keywords: knowledge management, organizational performance, fuzzy data, envelopment analysis

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15116 Semantic Network Analysis of the Saudi Women Driving Decree

Authors: Dania Aljouhi

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September 26th, 2017, is a historic date for all women in Saudi Arabia. On that day, Saudi Arabia announced the decree on allowing Saudi women to drive. With the advent of vision 2030 and its goal to empower women and increase their participation in Saudi society, we see how Saudis’ Twitter users deliberate the 2017 decree from different social, cultural, religious, economic and political factors. This topic bridges social media 'Twitter,' gender and social-cultural studies to offer insights into how Saudis’ tweets reflect a broader discourse on Saudi women in the age of social media. The present study aims to explore the meanings and themes that emerge by Saudis’ Twitter users in response to the 2017 royal decree on women driving. The sample used in the current study involves (n= 1000) tweets that were collected from Sep 2017 to March 2019 to account for the Saudis’ tweets before and after implementing the decree. The paper uses semantic and thematic network analysis methods to examine the Saudis’ Twitter discourse on the women driving issue. The paper argues that Twitter as a platform has mediated the discourse of women driving among the Saudi community and facilitated social changes. Finally, framing theory (Goffman, 1974) and Networked framing (Meraz & Papacharissi 2013) are both used to explain the tweets on the decree of allowing Saudi women to drive based on # Saudi women-driving-cars.

Keywords: Saudi Arabia, women, Twitter, semantic network analysis, framing

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15115 Fostering Organizational Learning across the Canadian Sport System through Leadership and Mentorship Development of Sport Science Leaders

Authors: Jennifer Walinga, Samantha Heron

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The goal of the study was to inform the design of effective leadership and mentorship development programming for sport science leaders within the network of Canadian sport institutes and centers. The LEAD (Learn, Engage, Accelerate, Develop) program was implemented to equip sport science leaders with the leadership knowledge, skills, and practice to foster a high - performance culture, enhance the daily training environment, and contribute to optimal performance in sport. After two years of delivery, this analysis of LEAD’s effect on individual and organizational health and performance factors informs the quality of future deliveries and identifies best practice for leadership development across the Canadian sport system and beyond. A larger goal for this project was to inform the public sector more broadly and position sport as a source of best practice for human and social health, development, and performance. The objectives of this study were to review and refine the LEAD program in collaboration with Canadian Sport Institute and Centre leaders, 40-50 participants from three cohorts, and the LEAD program advisory committee, and to trace the effects of the LEAD leadership development program on key leadership mentorship and organizational health indicators across the Canadian sport institutes and centers so as to capture best practice. The study followed a participatory action research framework (PAR) using semi structured interviews with sport scientist participants, program and institute leaders inquiring into impact on specific individual and organizational health and performance factors. Findings included a strong increase in self-reported leadership knowledge, skill, language and confidence, enhancement of human and organizational health factors, and the opportunity to explore more deeply issues of diversity and inclusion, psychological safety, team dynamics, and performance management. The study was significant in building sport leadership and mentorship development strategies for managing change efforts, addressing inequalities, and building personal and operational resilience amidst challenges of uncertainty, pressure, and constraint in real time.

Keywords: sport leadership, sport science leader, leadership development, professional development, sport education, mentorship

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15114 Strengthening Social and Psychological Resources - Project "Herausforderung" as a (Sports-) Pedagogical Concept in Adolescence

Authors: Kristof Grätz

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Background: Coping with crisis situations (e.g., the identity crisis in adolescence) is omnipresent in today's socialization and should be encouraged as a child. For this reason, students should be given the opportunity to create, endure and manage these crisis situations in a sporting context within the project “Herausforderung.” They should prove themselves by working on a self-assigned task, accompanied by ‚coaches’ in a place outside of their hometown. The aim of the project is to observe this process from a resource-oriented perspective. Health promotion, as called for by the WHO in the Ottawa Charter since 1986, includes strengthening psychosocial resources. These include cognitive, emotional, and social potentials that contribute to improving the quality of life, provide favourable conditions for coping with health burdens and enable people to influence their physical performance and well-being self-confidently and actively. A systematic strengthening of psychosocial resources leads to an improvement in mental health and contributes decisively to the regular implementation and long-term maintenance of this health behavior. Previous studies have already shown significant increases in self-concept following experiential educational measures [Fengler, 2007; Eberle & Fengler, 2018] and positive effects of experience-based school trips on the social competence of students [Reuker, 2009]. Method: The research project examines the influence of the project “Herausforderung” on psychosocial resources such as self-efficacy, self-concept, social support, and group cohesion. The students participating in the project will be tested in a pre-post design in the context of the challenge. This test includes specific questions to capture the different psychosocial resources. For the measurement, modifications of existing scales with good item selectivity and reliability are used to a large extent, so that acceptable item and scale values can be expected. If necessary, the scales were adapted or shortened to the specific context in order to ensure a balanced relationship between reliability and test economy. Specifically, these are already tested scales such as FRKJ 8-16, FSKN, GEQ, and F-SozU. The aim is to achieve a sample size of n ≥ 100. Conclusion: The project will be reviewed with regard to its effectiveness, and implications for a resource-enhancing application in sports settings will be given. Conclusions are drawn as to which extent to specific experiential educational content in physical education can have a health-promoting effect on the participants.

Keywords: children, education, health promotion, psychosocial resources

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15113 The UAV Feasibility Trajectory Prediction Using Convolution Neural Networks

Authors: Adrien Marque, Daniel Delahaye, Pierre Maréchal, Isabelle Berry

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Wind direction and uncertainty are crucial in aircraft or unmanned aerial vehicle trajectories. By computing wind covariance matrices on each spatial grid point, these spatial grids can be defined as images with symmetric positive definite matrix elements. A data pre-processing step, a specific convolution, a specific max-pooling, and a specific flatten layers are implemented to process such images. Then, the neural network is applied to spatial grids, whose elements are wind covariance matrices, to solve classification problems related to the feasibility of unmanned aerial vehicles based on wind direction and wind uncertainty.

Keywords: wind direction, uncertainty level, unmanned aerial vehicle, convolution neural network, SPD matrices

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15112 Improvement of GVPI Insulation System Characteristics by Curing Process Modification

Authors: M. Shadmand

Abstract:

The curing process of insulation system for electrical machines plays a determinative role for its durability and reliability. Polar structure of insulating resin molecules and used filler of insulation system can be taken as an occasion to leverage it to enhance overall characteristics of insulation system, mechanically and electrically. The curing process regime for insulating system plays an important role for its mechanical and electrical characteristics by arranging the polymerization of chain structure for resin. In this research, the effect of electrical field application on in-curing insulating system for Global Vacuum Pressurized Impregnation (GVPI) system for traction motor was considered by performing the dissipation factor, polarization and de-polarization current (PDC) and voltage endurance (aging) measurements on sample test objects. Outcome results depicted obvious improvement in mechanical strength of the insulation system as well as higher electrical characteristics with routing and long-time (aging) electrical tests. Coming together, polarization of insulation system during curing process would enhance the machine life time. 

Keywords: insulation system, GVPI, PDC, aging

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15111 A Neural Network Approach for an Automatic Detection and Localization of an Open Phase Circuit of a Five-Phase Induction Machine Used in a Drivetrain of an Electric Vehicle

Authors: Saad Chahba, Rabia Sehab, Ahmad Akrad, Cristina Morel

Abstract:

Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit (OC) fault diagnosis, artificial neural network

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15110 Mental Health Status among the Transgender Community: A Study of Mumbai

Authors: Mithlesh Chourase

Abstract:

Health of the transgender is as important as any other population sub-groups. However, little is known about the issues of mental health problems and health seeking behaviour of transgender in India. This paper examines the depression, stigma problem and suicidality (risk of suicide) among the transgender people in Mumbai city. The study used the primary survey data conducted in Mumbai city among the transgender community with a total sample of 120 among the transgender. Both qualitative and quantitative data was collected on demographic and socio-economic characteristic, general health and sexual health problems, mental health and health seeking behaviour among transgender. The quantitative results revealed that among the transgender, the prevalence of depression was very high. In this community 58.3% and 45.8 % of the transgender were suffered from depression and stigma problem respectively. On the other hand 42% and 48% of the transgender attempted suicide and experienced discrimination in the society. The qualitative results also revealed that the transgender were suffered from physical violence especially due to being a transgender, stressed due to being a transgender, experienced discrimination everywhere, experienced sexual health problems especially HIV, partner problem etc. As a result the prevalence of depression, self-harm attempt and suicidal attempt was common among this community.

Keywords: transgender, depression, Mumbai, mental health

Procedia PDF Downloads 521
15109 Attention Multiple Instance Learning for Cancer Tissue Classification in Digital Histopathology Images

Authors: Afaf Alharbi, Qianni Zhang

Abstract:

The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper introduces a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple-instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation of an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: attention multiple instance learning, MIL and transfer learning, histopathological slides, cancer tissue classification

Procedia PDF Downloads 100
15108 Maturity Model for Agro-Industrial Logistics

Authors: Erika Tatiana Ruiz, Wilson Adarme Jaimes

Abstract:

This abstract presents the methodology for improving the logistics processes of agricultural production units belonging to the coffee, cocoa, and fruit sectors, starting from the fundamental concepts and detailing each of the phases to carry out the diagnosis, which will be the basis for the formulation of its action plan and implementation of the maturity model. As a result of this work, the maturity model is formulated to improve logistics processes. This model seeks to: generate a progressive model that is useful for all productive units belonging to these sectors at the national level, regardless of their initial conditions, focus on the improvement of logistics processes as a strategy that contributes to improving the competitiveness of the agricultural sector in Colombia and spread the implementation of good logistics practices in postharvest in all departments of the country through autonomous tools. This model has been built through a series of steps that allow the evaluation and improvement of the logistics dimensions or indicators. The potential improvements for each dimension provide the foundation on which to advance to the next level. Within the maturity model, a methodology is indicated for the design and execution of strategies to improve its logistics processes, taking into account the current state of each production unit.

Keywords: agroindustrial, characterization, logistics, maturity model, processes

Procedia PDF Downloads 135
15107 Navigating Government Finance Statistics: Effortless Retrieval and Comparative Analysis through Data Science and Machine Learning

Authors: Kwaku Damoah

Abstract:

This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

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15106 SISSLE in Consensus-Based Ripple: Some Improvements in Speed, Security, Last Mile Connectivity and Ease of Use

Authors: Mayank Mundhra, Chester Rebeiro

Abstract:

Cryptocurrencies are rapidly finding wide application in areas such as Real Time Gross Settlements and Payments Systems. Ripple is a cryptocurrency that has gained prominence with banks and payment providers. It solves the Byzantine General’s Problem with its Ripple Protocol Consensus Algorithm (RPCA), where each server maintains a list of servers, called Unique Node List (UNL) that represents the network for the server, and will not collectively defraud it. The server believes that the network has come to a consensus when members of the UNL come to a consensus on a transaction. In this paper we improve Ripple to achieve better speed, security, last mile connectivity and ease of use. We implement guidelines and automated systems for building and maintaining UNLs for resilience, robustness, improved security, and efficient information propagation. We enhance the system so as to ensure that each server receives information from across the whole network rather than just from the UNL members. We also introduce the paradigm of UNL overlap as a function of information propagation and the trust a server assigns to its own UNL. Our design not only reduces vulnerabilities such as eclipse attacks, but also makes it easier to identify malicious behaviour and entities attempting to fraudulently Double Spend or stall the system. We provide experimental evidence of the benefits of our approach over the current Ripple scheme. We observe ≥ 4.97x and 98.22x in speedup and success rate for information propagation respectively, and ≥ 3.16x and 51.70x in speedup and success rate in consensus.

Keywords: Ripple, Kelips, unique node list, consensus, information propagation

Procedia PDF Downloads 139
15105 Burnout in the Resident Physician and a Simple Means of Improvement

Authors: Jacob Dangerfield, Jacob Pollard, Jennifer DeCou

Abstract:

Introduction: Burnout, anxiety, and depression are three conditions that are prevalent in medical providers. This is especially the case in the field of anesthesia, which has a high number of providers suffering from burnout and burnout syndrome. A major contributor to this issue is isolation in the workplace, with a perceived lack of peer support as a major risk factor for burnout. Two organizational interventions that can be done to help improve this issue are small group sessions and providing affordable mental health services. Per American College of Graduate Medical Education (ACGME) Guidelines, these affordable mental health services are a requirement of all residency programs, but for a variety of reasons, many residents do not access them. As physicians, we are often not good at asking for help. With this in mind, we hypothesized that carrying out small group resiliency sessions facilitated by Graduate Medical Education (GME) Wellness Counselors would improve both resident peer support as well as the likelihood that a resident will reach out to GME Wellness in a time of need. Methods: We held small group resiliency sessions with the GME Wellness Mental Health Professionals during protected didactic time. These sessions were small groups, including the members of one’s class (i.e., first-year residents on their own), and were facilitated by 1-2 mental health professionals. After these sessions, we surveyed residents who attended using a short Google Forms survey and using a 5-point Likert Scale, asked residents about some outcomes from the session. A “strongly agree” or “agree” was considered a positive response. Results: Results from our survey showed that the resident sessions had multiple positive outcomes. This survey was sent to 29 residents, and we had a 62% response rate. We found out through this survey that these small group sessions had a perceived positive impact on resident personal well-being, increased perceived peer support from classmates, and made residents more likely to reach out to GME Wellness in the future. Perceived positive impact on well-being was found in 83% of resident respondents, improved perceived peer support in 83% of respondents, and 78% of resident respondents stated that this session increased their likelihood of reaching out to mental health professionals. Conclusions: Through this study, we can conclude that our hypothesis was correct in that Small Group Resiliency Sessions that are facilitated by GME Wellness Counselors improve both resident peer support as well as the likelihood a resident reaches out to these mental health professionals in time of need. We believe these findings are very important as they address two important factors that can aid in decreasing a provider’s risk of experiencing burnout. Through this simple means, we believe other residency programs can help the well-being of their residents, and together, we can decrease the number of cases of burnout in anesthesia.

Keywords: anesthesiology, burnout, wellness, depression, residents, trainees, mental health

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15104 GIS-Based Identification of Overloaded Distribution Transformers and Calculation of Technical Electric Power Losses

Authors: Awais Ahmed, Javed Iqbal

Abstract:

Pakistan has been for many years facing extreme challenges in energy deficit due to the shortage of power generation compared to increasing demand. A part of this energy deficit is also contributed by the power lost in transmission and distribution network. Unfortunately, distribution companies are not equipped with modern technologies and methods to identify and eliminate these losses. According to estimate, total energy lost in early 2000 was between 20 to 26 percent. To address this issue the present research study was designed with the objectives of developing a standalone GIS application for distribution companies having the capability of loss calculation as well as identification of overloaded transformers. For this purpose, Hilal Road feeder in Faisalabad Electric Supply Company (FESCO) was selected as study area. An extensive GPS survey was conducted to identify each consumer, linking it to the secondary pole of the transformer, geo-referencing equipment and documenting conductor sizes. To identify overloaded transformer, accumulative kWH reading of consumer on transformer was compared with threshold kWH. Technical losses of 11kV and 220V lines were calculated using the data from substation and resistance of the network calculated from the geo-database. To automate the process a standalone GIS application was developed using ArcObjects with engineering analysis capabilities. The application uses GIS database developed for 11kV and 220V lines to display and query spatial data and present results in the form of graphs. The result shows that about 14% of the technical loss on both high tension (HT) and low tension (LT) network while about 4 out of 15 general duty transformers were found overloaded. The study shows that GIS can be a very effective tool for distribution companies in management and planning of their distribution network.

Keywords: geographical information system, GIS, power distribution, distribution transformers, technical losses, GPS, SDSS, spatial decision support system

Procedia PDF Downloads 370