Search results for: Squared Error (SE) loss function

Authors: Basant Kumar Singh, S. Subhachandhar, Vineet Ranjan Tripathi, Amit Kumar Singh, Uttam Singh, Santosh Kumar Lal

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Productivity of Blast Furnace is largely impacted by fuel efficiency and controlling heat loss is one of the enabling parameters for achieving lower fuel rate. 'I' Blast Furnace is the latest and largest Blast Furnace of Tata Steel Jamshedpur with working volume of 3230 m³ and with rated capacity of 3.055 million tons per annum. Optimizing heat losses in Belly and Bosh zone remained major challenge for blast furnace operators after its commissioning. 'I' Blast has installed Cast Iron & Copper Staves cooling members where copper staves are installed in Belly, Bosh & Lower Stack whereas cast iron staves are installed in upper stack area. Stave cooled Blast Furnaces are prone to higher heat losses in Belly and Bosh region with an increase in coal injection rate as Bosh gas volume increases. Under these conditions, managing gas flow pattern through proper burden distribution, casting techniques & by maintaining desired raw material qualities are of utmost importance for sustaining high injection rates. This study details, the burden distribution control by Ore & Coke ratio adjustment at wall and center of Blast Furnace as the coal injection rates increased from 140 kg/thm to 210 kg/thm. Control of blowing parameters, casting philosophy, specification for raw materials & devising operational practice for controlling heat losses is also elaborated with the model that is used to visualize heat loss pattern in different zones of Blast Furnace.

Keywords: blast furnace, staves, gas flow pattern, belly/bosh heat losses, ore/coke ratio, blowing parameters, casting, operation practice

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Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

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Authors: Ayman M. Othman, Hassan Y. Ahmed, Tallat A. Ali

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Inadequate maintenance programs and funds allocated for highway networks in the developed countries have led to fast deterioration of road side elements. Therefore, this research focuses on developing a performance model for road side elements periodic maintenance activities. Road side elements that receive periodic maintenance include; earthen shoulder, road signs and traffic markings. Using the level of service concept, the developed model can determine the optimal periodic maintenance intervals for those elements based on a selected level of service suitable with the available periodic maintenance budget. Data related to time periods for progressive deterioration stages for the chosen elements were collected. Ten maintenance experts in Aswan, Sohag and Assiut cities were interviewed for that purpose. Time in months related to 10%, 25%, 40%, 50%, 75%, 90% and 100% deterioration of each road side element was estimated based on the experts opinion. Least square regression analysis has shown that a power function represents the best fit for earthen shoulders edge drop-off and damage of road signs with time. It was also evident that, the progressive dirtiness of road signs could be represented by a quadratic function an a linear function could represent the paint degradation nature of both traffic markings and road signs. Actual measurements of earthen shoulder edge drop-off agree considerably with the developed model.

Keywords: deterioration, level of service, periodic maintenance, performance model, road side element

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Authors: Ramin Rostamkhani, Thurasamy Ramayah

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One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.

Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components

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Authors: W. Rashmi, M. Khalid, O. Seiksan, R. Saidur, A. F. Ismail

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Nanofluids have received much more attention since its discovery. They are believed to be promising coolants in heat transfer applications due to their enhanced thermal conductivity and heat transfer characteristics. In this study, the enhancement in heat transfer of CNT-nanofluids under turbulent flow conditions is investigated experimentally. Carbon nanotube (CNTs) concentration was varied between 0.051-0.085 wt%. The nanofluid suspension was stabilized by gum arabic (GA) through a process of homogenisation and sonication. The flow rates of cold fluid (water) is varied from 1.7-3 L/min and flow rates of the hot fluid is varied between 2-3.5 L/min. Thermal conductivity, density and viscosity of the nanofluids were also measured as a function of temperature and CNT concentration. The experimental results are validated with theoretical correlations for turbulent flow available in the literature. Results showed an enhancement in heat transfer range between 9-67% as a function of temperature and CNT concentration.

Keywords: nanofluids, carbon nanotubes (CNT), heat transfer enhancement, heat transfer

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Authors: Filiz Ersoz, Taner Ersoz, Tugrul Bayraktar

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Renewable energy is referred to as "clean energy" and common popular support for the use of renewable energy (RE) is to provide electricity with zero carbon dioxide emissions. This study provides useful insight into the European Union (EU) RE, especially, into electricity generation obtained from renewables, and their targets. The objective of this study is to identify groups of European countries, using multivariate statistical analysis and selected indicators. The hierarchical clustering method is used to decide the number of clusters for EU countries. The conducted statistical hierarchical cluster analysis is based on the Ward’s clustering method and squared Euclidean distances. Hierarchical cluster analysis identified eight distinct clusters of European countries. Then, non-hierarchical clustering (k-means) method was applied. Discriminant analysis was used to determine the validity of the results with data normalized by Z score transformation. To explore the relationship between the selected indicators, correlation coefficients were computed. The results of the study reveal the current situation of RE in European Union Member States.

Keywords: share of electricity generation, k-means clustering, discriminant, CO2 emission

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Authors: Subhash Chandra Sharma, Mohammad Soleimani

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Selection of the correct lubricant for the top of rail application is a complex process. In this paper, the selection of the proper lubricant for a Top-Of-Rail (TOR) lubrication system based on graph theory and matrix approach has been developed. Attributes influencing the selection process and their influence on each other has been represented through a digraph and an equivalent matrix. A matrix function which is called the Permanent Function is derived. By substituting the level of inherent contribution of the influencing parameters and their influence on each other qualitatively, a criterion called Suitability Index is derived. Based on these indices, lubricants can be ranked for their suitability. The proposed model can be useful for maintenance engineers in selecting the best lubricant for a TOR application. The proposed methodology is illustrated step–by-step through an example.

Keywords: lubricant selection, top of rail lubrication, graph-theory, Ranking of lubricants

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Authors: Kazeem Ajasa Badmus, Zulkifli Idrus, Goh Yong Meng, Kamalludin Mamat-Hamidi

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This study was aimed at evaluating the roles played by early age in performance, organs weights, meat quality traits, and telomere length integrity. One hundred male Cobb 500® broiler chickens were grouped into ten replicates of ten chickens each. Growth performance, measurement of telomere length, weights of organs, and meat quality traits were determined on days 14, 28, and 42 of the experiment. There were significant (p < 0.05) differences obtained in the chicken growth performance across ages. Telomere length of blood, muscle, liver, and heart on day 14 were significantly (p < 0.05) shorter than telomere length obtained on days 28 and 42 of the age. Weights of organs on day 14 were significantly (p < 0.05) higher than those obtained on days 28 and 42. In this study, birds slaughtered on day 14 presented the highest (p < 0.05) pH, drip loss, redness, and yellowness. They, however, showed lower (p < 0.05) cooking loss, shear force, and lightness. There was a significant association between age, telomere length, and meat quality traits. It is therefore concluded that telomere length attrition is associated with early age metabolic activities and could be used to measure chicks' welfare.

Keywords: age, telomere length, organ weights, meat quality

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Authors: Jiewei Li, Hongyan Cui, Chunqi Chang, Yong Hu

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It was expected to benefit patient with hemiparesis after stroke by extensive arm rehabilitation, to partially regain forearm and hand function. This paper propose a robotic rehabilitation arm in assisting the hemiparetic patient to learn new ways of using and moving their weak arms. In this study, the robotic arm was driven by a somatosensory stimulated brain computer interface (BCI), which is a new modality BCI. The use of somatosensory stimulation is not only an input for BCI, but also a electrical stimulation for treatment of hemiparesis to strengthen the arm and improve its range of motion. A trial of this robotic rehabilitation arm was performed in a stroke patient with pure motor hemiparesis. The initial trial showed a promising result from the patient with great motivation and function improvement. It suggests that robotic rehabilitation arm driven by somatosensory BCI can enhance the rehabilitation performance and progress for hemiparetic patients after stroke.

Keywords: robotic rehabilitation arm, brain computer interface (BCI), hemiparesis, stroke, somatosensory stimulation

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Authors: Dewi Retno Sari Saputro, Purnami Widyaningsih, Hendrika Handayani

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Extreme data on an observation can occur due to unusual circumstances in the observation. The data can provide important information that can’t be provided by other data so that its existence needs to be further investigated. The method for obtaining extreme data is one of them using maxima block method. The distribution of extreme data sets taken with the maxima block method is called the distribution of extreme values. Distribution of extreme values is Gumbel distribution with two parameters. The parameter estimation of Gumbel distribution with maximum likelihood method (ML) is difficult to determine its exact value so that it is necessary to solve the approach. The purpose of this study was to determine the parameter estimation of Gumbel distribution with quasi-Newton BFGS method. The quasi-Newton BFGS method is a numerical method used for nonlinear function optimization without constraint so that the method can be used for parameter estimation from Gumbel distribution whose distribution function is in the form of exponential doubel function. The quasi-New BFGS method is a development of the Newton method. The Newton method uses the second derivative to calculate the parameter value changes on each iteration. Newton's method is then modified with the addition of a step length to provide a guarantee of convergence when the second derivative requires complex calculations. In the quasi-Newton BFGS method, Newton's method is modified by updating both derivatives on each iteration. The parameter estimation of the Gumbel distribution by a numerical approach using the quasi-Newton BFGS method is done by calculating the parameter values that make the distribution function maximum. In this method, we need gradient vector and hessian matrix. This research is a theory research and application by studying several journals and textbooks. The results of this study obtained the quasi-Newton BFGS algorithm and estimation of Gumbel distribution parameters. The estimation method is then applied to daily rainfall data in Purworejo District to estimate the distribution parameters. This indicates that the high rainfall that occurred in Purworejo District decreased its intensity and the range of rainfall that occurred decreased.

Keywords: parameter estimation, Gumbel distribution, maximum likelihood, broyden fletcher goldfarb shanno (BFGS)quasi newton

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Authors: Donatella Giuliani

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In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

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Authors: Selvia Arokiya Mary

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Introduction: Worldwide, breast cancer comprises 10.4% of all cancer incidence among women. In 2004, breast cancer caused 519,000 deaths worldwide (7% of cancer deaths; almost 1% of all deaths). Many women who undergo breast surgery suffer from ill-defined pain syndromes. STATEMENT OF THE PROBLEM: A study to assess the effectiveness of twin therapeutic approaches on certain bio-physiological parameters in breast cancer patients after breast surgery at selected hospital, Chennai. Objectives: This study is to 1. assess the level of certain biophysiological parameters in women after mastectomy. 2. assess the effectiveness of twin therapeutic approaches on certain biophysiological parameters in women after mastectomy. 3. correlate the practice of twin therapeutic approaches with certain biophysiological parameters. 4. associate the selected demographic variables with certain biophysiological parameters in women after mastectomy Research Design and Method: Pre experimental research design was used. Fifty women were selected by using convenient sampling technique at government general hospital, Chennai. Results: The Level of pain shows, in the study group 49(98%) of them had moderate in the pre test and after the intervention all of them had mild pain in the post test. In relation to level of shoulder function before the intervention shows that in the study group 49(98%) of them had movement towards gravity and after intervention 24 (48%) of them had movement against gravity maximum resistance. There was a significant reduction in pain and shoulder stiffness level at a ‘P’ level of < 0.001. There was a negative correlation between the pranayama practice and the level of pain, there was a positive correlation between the arm exercise practice and the level of shoulder function. There was no significant association between demographic and clinical variables with the level of pain and shoulder function in the study. Hypothesis: There is a significant difference in level of pain and shoulder function among women following breast surgery who receive pranayama & arm exercise programme. The pranayama had effect in terms of reduction of pain, arm exercise programme had effect in prevention of arm stiffness among post operative women following breast surgery. Thus the stated hypothesis was accepted. Conclusion: On the basis of the findings of the present study there was Advancing age related to increasing risk of breast cancer, level of pain also the type of surgery was associated with level of pain and shoulder function, There fore it is to be concluded that the study participants may get benefited by practice of pranayama and arm exercise program.

Keywords: biophysiological parameters breast surgery, lumpectomy , mastectomy, radical mastectomy, twin therapeutic approach, pranayama, arm exercise

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Authors: Daeung Jung

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Background: In case of patients with missing teeth, multiple implant restoration has been widely used and is inevitable. To increase its survival rate, it is important to understand the influence of different implant designs on inter-implant crestal bone resorption. There are several implant systems designed to minimize loss of crestal bone, and the Astra Tech and Brånemark Implant are two of them. Aim/Hypothesis: The aim of this 10-year study was to compare the height of inter-implant bone crest in two implant systems; the Astra Tech and the Brånemark implant system. Material and Methods: In this retrospective study, 40 consecutively treated patients were utilized; 23 patients with 30 sites for Astra Tech system and 17 patients with 20 sites for Brånemark system. The implant restoration was comprised of splinted crown in partially edentulous patients. Radiographs were taken immediately after 1st surgery, at impression making, at prosthetics setting, and annually after loading. Lateral distance from implant to bone crest, inter-implant distance was gauged, and crestal bone height was measured from the implant shoulder to the first bone contact. Calibrations were performed with known length of thread pitch distance for vertical measurement, and known diameter of abutment or fixture for horizontal measurement using ImageJ. Results: After 10 years, patients treated with Astra Tech implant system demonstrated less inter-implant crestal bone resorption when implants had a distance of 3mm or less between them. In cases of implants that had a greater than 3 mm distance between them, however, there appeared to be no statistically significant difference in crestal bone loss between two systems. Conclusion and clinical implications: In the situation of partially edentulous patients planning to have more than two implants, the inter-implant distance is one of the most important factors to be considered. If it is impossible to make sure of having sufficient inter-implant distance, the implants with less micro gap in the fixture-abutment junction, less traumatic 2nd surgery approach, and the adequate surface topography would be choice of appropriate options to minimize inter-implant crestal bone resorption.

Keywords: implant design, crestal bone loss, inter-implant distance, 10-year retrospective study

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Authors: Zhang Yuqi

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Service facilities are the boosters for the cultivation and development of innovative functions in innovative cluster areas. At the same time, reasonable service facilities planning can better link the internal functional blocks. This paper takes Zhejiang University Zijin Co-Maker Town as the research object, based on the combination of network data mining and field research and verification, combined with the needs of its internal innovative groups. It studies the distribution characteristics and existing problems of service facilities and then proposes a targeted planning suggestion. The main conclusions are as follows: (1) From the perspective of view, the town is rich in general life-supporting services, but lacking of provision targeted and distinctive service facilities for innovative groups; (2) From the perspective of scale structure, small-scale street shops are the main business form, lack of large-scale service center; (3) From the perspective of spatial structure, service facilities layout of each functional block is too fragile to fit the characteristics of 2aggregation- distribution' of innovation and entrepreneurial activities; (4) The goal of optimizing service facilities planning should be guided for fostering function of innovation and entrepreneurship and meet the actual needs of the innovation and entrepreneurial groups.

Keywords: the cultivation of innovative function, Zhejiang University Zijin Co-Maker Town, service facilities, network data mining, space optimization advice

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Authors: Yi Jen Wang, Yu Ju Chen

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Background: Heart rate variability (HRV) biofeedback can promote autonomic nervous function, sleep quality and reduce psychological stress. In HRV biofeedback training, it is hoped that through the guidance of machine video or audio, the patient can breathe slowly according to his own heart rate changes so that the heart and lungs can achieve resonance, thereby promoting the related effects of autonomic nerve function; while, it is also pointed out that if slow breathing of 6 times per minute can also guide the case to achieve the effect of cardiopulmonary resonance. However, there is no relevant research to explore the comparison of the effectiveness of cardiopulmonary resonance by using video or audio HRV biofeedback training and metronome-guided slow breathing. Purpose: To compare the promotion of autonomic nervous function performance between using HRV biofeedback and slow breathing guided by a metronome. Method: This research is a kind of experimental design with convenient sampling; the cases are randomly divided into the heart rate variability biofeedback training group and the slow breathing training group. The HRV biofeedback training group will conduct HRV biofeedback training in a four-week laboratory and use the home training device for autonomous training; while the slow breathing training group will conduct slow breathing training in the four-week laboratory using the mobile phone APP breathing metronome to guide the slow breathing training, and use the mobile phone APP for autonomous training at home. After two groups were enrolled and four weeks after the intervention, the autonomic nervous function-related performance was repeatedly measured. Using the chi-square test, student’s t-test and other statistical methods to analyze the results, and use p <0.05 as the basis for statistical significance. Results: A total of 27 subjects were included in the analysis. After four weeks of training, the HRV biofeedback training group showed significant improvement in the HRV indexes (SDNN, RMSSD, HF, TP) and sleep quality. Although the stress index also decreased, it did not reach statistical significance; the slow breathing training group was not statistically significant after four weeks of training, only sleep quality improved significantly, while the HRV indexes (SDNN, RMSSD, TP) all increased. Although HF and stress indexes decreased, they were not statistically significant. Comparing the difference between the two groups after training, it was found that the HF index improved significantly and reached statistical significance in the HRV biofeedback training group. Although the sleep quality of the two groups improved, it did not reach that level in a statistically significant difference. Conclusion: HRV biofeedback training is more effective in promoting autonomic nervous function than slow breathing training, but the effects of reducing stress and promoting sleep quality need to be explored after increasing the number of samples. The results of this study can provide a reference for clinical or community health promotion. In the future, it can also be further designed to integrate heart rate variability biological feedback training into the development of AI artificial intelligence wearable devices, which can make it more convenient for people to train independently and get effective feedback in time.

Keywords: autonomic nervous function, HRV biofeedback, heart rate variability, slow breathing

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Authors: S. Somerset, D. J. Hoare, P. Leighton

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Limited participation in physical activity and sport has been linked to poorer mental and physical health in children. Studies have shown that children who participate in sports benefit from improved social skills, self-confidence, communication skills and a better quality of life. Children who participate in sport are also more likely to continue their participation into their adult life. Deaf or hard of hearing children should have the same opportunities to participate in sport and receive the benefits as their hearing peers. Anecdotal evidence suggests this isn’t always the case. This is concerning given there are 45,000 children in the UK with permanent hearing loss. The aim of this study was to understand what encourages or discourages deaf or hard of hearing children to take part in sports. Ethical approval for the study was obtained from the University of Nottingham School of Medicine ethics committee. We conducted eight focus groups with deaf or hard of hearing children aged 10 to 15 years. A total of 45 children (19 male, 26 female) recruited from local schools and sports clubs took part. Information was gathered on the children’s thoughts and feelings about participation in sport. This included whether they played sports and who with, whether they did or did not like sport, and why they got involved in sport. Focus groups were audio recorded and transcribed. Transcripts were analysed using thematic analysis. Several key themes were identified as being associated with levels of sports participation. These included friendships, family and communication. Deaf or hard of hearing children with active siblings had participated in more sports. Communication was a common theme throughout regardless of the type of hearing-assistive technology a child used. Children found communication easier during sport if they were allowed to use their technology and had particular difficulty during sports such as swimming. Children expressed a desire not to have to identify themselves at a club as having a hearing loss. This affected their confidence when participating in sport. Not surprisingly, children who are deaf or hard of hearing are more likely to participate in sport if they have a good support network of parents, coaches and friends. The key barriers to participation for these children are communication, lack of visual information, lack of opportunity and a lack of awareness. By addressing these issues more deaf and hard of hearing children will take part in sport and will continue their participation.

Keywords: barrier, children, deaf, participation, hard of hearing, sport

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Authors: James Kinyua Gitonga, Toshio Fujimi

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Vulnerability assessment and analysis is essential to solving the degree of damage and loss as a result of natural disasters. Urban flooding causes a major economic loss and casualties, at Mathare residential area in Nairobi, Kenya. High population caused by rural-urban migration, Unemployment, and unplanned urban development are among factors that increase flood vulnerability in Mathare area. This study aims to analyse flood risk physical vulnerabilities in Mathare based on scientific data, research data that includes the Rainfall data, River Mathare discharge rate data, Water runoff data, field survey data and questionnaire survey through sampling of the study area have been used to develop the risk curves. Three structural types of building were identified in the study area, vulnerability and risk curves were made for these three structural types by plotting the relationship between flood depth and damage for each structural type. The results indicate that the structural type with mud wall and mud floor is the most vulnerable building to flooding while the structural type with stone walls and concrete floor is least vulnerable. The vulnerability of building contents is mainly determined by the number of floors, where households with two floors are least vulnerable, and households with a one floor are most vulnerable. Therefore more than 80% of the residential buildings including the property in the building are highly vulnerable to floods consequently exposed to high risk. When estimating the potential casualties/injuries we discovered that the structural types of houses were major determinants where the mud/adobe structural type had casualties of 83.7% while the Masonry structural type had casualties of 10.71% of the people living in these houses. This research concludes that flood awareness, warnings and observing the building codes will enable reduce damage to the structural types of building, deaths and reduce damage to the building contents.

Keywords: flood loss, Mathare Nairobi, risk curve analysis, vulnerability

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Authors: N. F. Mikhailova, M. E. Fattakhova, M. A. Mironova, E. V. Vyacheslavova

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For the mental and social adaptation of the deaf and hard-of-hearing people, cultural and social aspects - the formation of identity (acculturation) and educational conditions – are highly significant. We studied 137 deaf and hard-of-hearing students in different educational situations. We used these methods: Big Five (Costa & McCrae, 1997), TRF (Becker, 1989), WCQ (Lazarus & Folkman, 1988), self-esteem, and coping strategies (Jambor & Elliott, 2005), self-stigma scale (Mikhailov, 2008). Type of self-identification of students depended on the degree of deafness, type of education, method of communication in the family: large hearing loss, education in schools for deaf, and gesture communication increased the likelihood of a 'deaf' acculturation. Less hearing loss, inclusive education in public school or school for the hearing-impaired, mixed communication in the family contributed to the formation of 'hearing' acculturation. The choice of specific coping depended on the degree of deafness: a large hearing loss increased coping 'withdrawal into the deaf world' and decreased 'bicultural skills' coping. People with mild hearing loss tended to cover-up it. In the context of ongoing discussion, we researched personality characteristics in deaf and hard on-hearing students, coping and other deafness associated factors depending on their acculturation type. Students who identified themselves with the 'hearing world' had a high self-esteem, a higher level of extraversion, self-awareness, personal resources, willingness to cooperate, better psychological health, emotional stability, higher ability to empathy, a greater satiety of life with feelings and sense and high sense of self-worth. They also actively used strategies, problem-solving, acceptance of responsibility, positive revaluation. Student who limited themselves within the culture of deaf people had more severe hearing loss and accordingly had more communication barriers. Lack of use or seldom use of coping strategies by these students point at decreased level of stress in their life. Their self-esteem have not been challenged in the specific social environment of the students with the same severity of defect, and thus this environment provided sense of comfort (we can assume that from the high scores on psychological health, personality resources, and emotional stability). Students with bicultural acculturation had higher level of psychological resources - they used Positive Reappraisal coping more often and had a higher level of psychological health. Lack of belonging to certain culture (marginality) leads to personality disintegration, social and psychological disadaptation: deaf and hard-of-hearing students with marginal identification had a lower self-estimation level, worse psychological health and personal resources, lower level of extroversion, self-confidence and life satisfaction. They, in fact, become 'risk group' (many of them dropped out of universities, divorced, and one even ended up in the ranks of ISIS). All these data argue the importance of cultural 'anchor' for people with hearing deprivation. Supported by the RFBR No 19-013-00406.

Keywords: acculturation, coping, deafness, marginality

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Authors: Ali A. Hammadi

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In this work, a practical study on a commissioned Giga Passive Optical Network (GPON) fiber to the home access network in Kuwait is presented. The work covers the framework of the conceptual design of the deployed Passive Optical Networks (PONs), access network, optical fiber cable network distribution, technologies, and standards. The work also describes methodologies applied by system engineers for design of Optical Network Terminals (ONTs) and Optical Line Terminals (OLTs) transceivers with respect to the distance, operating wavelengths, splitting ratios. The results have demonstrated and justified the limitation of transmission distance of a PON link in Fiber to The Premises (FTTP) to not exceed 20 km. Optical Time Domain Reflector (OTDR) test has been carried for this project to confirm compliance with International Telecommunication Union (ITU) specifications regarding the total length of the deployed optical cable, total loss in dB, and loss per km in dB/km with respect to the operating wavelengths. OTDR test results with traces for segments of implemented fiber network will be provided and discussed.

Keywords: passive optical networks (PONs), fiber to the premises (FTTx), access network, OTDR

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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Authors: Eunsu Jang, Kang Park

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In developing an armored ground combat vehicle (AGCV), it is a very important step to analyze the vulnerability (or the survivability) of the AGCV against enemy’s attack. In the vulnerability analysis, the penetration equations are usually used to get the penetration depth and check whether a bullet can penetrate the armor of the AGCV, which causes the damage of internal components or crews. The penetration equations are derived from penetration experiments which require long time and great efforts. However, they usually hold only for the specific material of the target and the specific type of the bullet used in experiments. Thus, penetration simulation using ANSYS can be another option to calculate penetration depth. However, it is very important to model the targets and select the input parameters in order to get an accurate penetration depth. This paper performed a sensitivity analysis of input parameters of ANSYS on the accuracy of the calculated penetration depth. Two conflicting objectives need to be achieved in adopting ANSYS in penetration analysis: maximizing the accuracy of calculation and minimizing the calculation time. To maximize the calculation accuracy, the sensitivity analysis of the input parameters for ANSYS was performed and calculated the RMS error with the experimental data. The input parameters include mesh size, boundary condition, material properties, target diameter are tested and selected to minimize the error between the calculated result from simulation and the experiment data from the papers on the penetration equation. To minimize the calculation time, the parameter values obtained from accuracy analysis are adjusted to get optimized overall performance. As result of analysis, the followings were found: 1) As the mesh size gradually decreases from 0.9 mm to 0.5 mm, both the penetration depth and calculation time increase. 2) As diameters of the target decrease from 250mm to 60 mm, both the penetration depth and calculation time decrease. 3) As the yield stress which is one of the material property of the target decreases, the penetration depth increases. 4) The boundary condition with the fixed side surface of the target gives more penetration depth than that with the fixed side and rear surfaces. By using above finding, the input parameters can be tuned to minimize the error between simulation and experiments. By using simulation tool, ANSYS, with delicately tuned input parameters, penetration analysis can be done on computer without actual experiments. The data of penetration experiments are usually hard to get because of security reasons and only published papers provide them in the limited target material. The next step of this research is to generalize this approach to anticipate the penetration depth by interpolating the known penetration experiments. This result may not be accurate enough to be used to replace the penetration experiments, but those simulations can be used in the early stage of the design process of AGCV in modelling and simulation stage.

Keywords: ANSYS, input parameters, penetration depth, sensitivity analysis

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Authors: M. Asato, C. Liu, N. Fujima, T. Hoshino, Y. Chen, T. Mohri

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We study the temperature dependence of the interaction energies (IEs) of X (=Ru, Rh) impurities in Pd, due to the Fermi-Dirac (FD) distribution and the thermal vibration effect by the Debye-Grüneisen model. The n-body (n=2~4) IEs among X impurities in Pd, being used to calculate the internal energies in the free energies of the Pd-rich PdX alloys, are determined uniquely and successively from the lower-order to higher-order, by the full-potential Korringa-Kohn-Rostoker Green’s function method (FPKKR), combined with the generalized gradient approximation in the density functional theory. We found that the temperature dependence of IEs due to the FD distribution, being usually neglected, is very important to reproduce the X-concentration dependence of the observed solvus temperatures of the Pd-rich PdX (X=Ru, Rh) alloys.

Keywords: full-potential KKR-green’s function method, Fermi-Dirac distribution, GGA, phase diagram of Pd-rich PdX (X=Ru, Rh) alloys, thermal vibration effect

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Authors: Muhammad Zubair Khan, Yugyung Lee

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Deep learning has recently achieved enormous response in semantic image segmentation. The previously developed U-Net inspired architectures operate with continuous stride and pooling operations, leading to spatial data loss. Also, the methods lack establishing long-term pixels connection to preserve context knowledge and reduce spatial loss in prediction. This article developed encoder-decoder architecture with bi-directional LSTM embedded in long skip-connections and densely connected convolution blocks. The network non-linearly combines the feature maps across encoder-decoder paths for finding dependency and correlation between image pixels. Additionally, the densely connected convolutional blocks are kept in the final encoding layer to reuse features and prevent redundant data sharing. The method applied batch-normalization for reducing internal covariate shift in data distributions. The empirical evidence shows a promising response to our method compared with other semantic segmentation techniques.

Keywords: deep learning, semantic segmentation, image analysis, pixels connection, convolution neural network

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Authors: Dae-Hee Son, Soon-Ryul Nam

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The power system frequency falls when disturbance such as rapid increase of system load or loss of a generating unit occurs in power systems. Especially, increase in the number of renewable generating units has a bad influence on the power system because of loss of generating unit depending on the circumstance. Conventional technologies use frequency droop control battery output for the frequency regulation and balance between supply and demand. If power is supplied using the fast output characteristic of the battery, power system stability can be further more improved. To improve the power system stability, we propose battery output control using ROCOF (Rate of Change of Frequency) in this paper. The bigger the power difference between the supply and the demand, the bigger the ROCOF drops. Battery output is controlled proportionally to the magnitude of the ROCOF, allowing for faster response to power imbalances. To simulate the control method of battery output system, we develop the user defined model using PSS/E and confirm that power system stability is improved by comparing with frequency droop control.

Keywords: PSS/E user defined model, power deviation, frequency droop control, ROCOF (rate of change of frequency)

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Authors: jihen ayadi sellami

Abstract:

The rapid evolution of the global financial landscape has led to increased attention to corporate tax policies and the need to understand the factors that influence their tax behavior. In order to mitigate any residual loss for shareholders resulting from tax aggressiveness and resolve the agency problem, appropriate systems that separate the function of management from that of controlling are needed. In this context of growing concerns to limit aggressive corporate taxation practices through governance, this study discusses. Its aims is to examine the influence of six key characteristics of the board of directors (board size, diligence, CEO duality, presence of audit committees, gender diversity and independence of directors), given a governance mechanism, on the tax decisions of non-financial corporations in the United State. In fact, using a sample of 90 non-financial US firms from S&P 500 over a period of 4 years going from 2014 to 2017, the results based on a multivariate linear regression highlight significant associations between these characteristics and corporate tax policy. Notably, larger board, gender diversity, diligence and increased director independence appear to play an important role in reducing aggressive taxation. While duality has a positive and significant correlation with tax aggressiveness, that can be explained by the fact that the manager did properly exploit his specific position within the company. These findings contribute to a deeper understanding of how board characteristics can influence corporate tax management, providing avenues for more effective corporate governance and more responsible tax decision-making

Keywords: tax aggressiveness, board of directors, board size, CEO duality, audit committees, gender diversity, director independence, diligence, corporate governance, united states

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Authors: Thidilweli Denga, Bessie Malila, Lucretia Petersen

Abstract:

The Coronavirus Disease of 2019 (COVID-19) pandemic should be taken as a wake-up call on the importance of hearing health care considering amongst other things the electronic methods of communication used. The World Health Organization (WHO) estimated that by 2050, there will be more than 2.5 billion people living with hearing loss. These numbers show that more people will need rehabilitation services. Studies have shown that most people living with hearing loss reside in Low-Middle Income Countries (LIMC). Innovative technological solutions such as digital health interventions that can be used to deliver hearing health services to remote areas now exist. Tele-audiology implementation can potentially enable the delivery of hearing loss services to rural and remote areas. This study aimed to establish the concurrent validity of the tele-audiology practice in school-based hearing screening. The study employed a cross-sectional design with a within-group comparison. The portable KUDUwave Audiometer was used to conduct hearing screening from 50 participants (n=50). In phase I of the study, the audiologist conducted on-site hearing screening, while the synchronous remote hearing screening (tele-audiology) using a 5G network was done in phase II. On-site hearing screening results were obtained for the first 25 participants (aged between 5-6 years). The second half started with the synchronous tele-audiology model to avoid order-effect. Repeated sample t-tests compared threshold results obtained in the left and right ears for onsite and remote screening. There was a good correspondence between the two methods with a threshold average within ±5 dB (decibels). The synchronous tele-audiology model has the potential to reduce the audiologists' case overload, while at the same time reaching populations that lack access due to distance, and shortage of hearing professionals in their areas of reach. With reliable and broadband connectivity, tele-audiology delivers the same service quality as the conventional method while reducing the travel costs of audiologists.

Keywords: hearing screening, low-resource communities, portable audiometer, tele-audiology

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Authors: A. Hadadi, M. Abdollahi, A. Dustmohammadi

Abstract:

The growing use of DGs in distribution networks provide many advantages and also cause new problems which should be anticipated and be solved with appropriate solutions. One of the problems is transient voltage drop and short circuit in the electrical network, in the presence of distributed generation - which can lead to instability. The appearance of the short circuit will cause loss of generator synchronism, even though if it would be able to recover synchronizing mode after removing faulty generator, it will be stable. In order to increase system reliability and generator lifetime, some strategies should be planned to apply even in some situations which a fault prevent generators from separation. In this paper, one fault current limiter is installed due to prevent DGs separation from the grid when fault occurs. Furthermore, an innovative objective function is applied to determine the impedance optimal amount of fault current limiter in order to improve transient stability of distributed generation. Fault current limiter can prevent generator rotor's sudden acceleration after fault occurrence and thereby improve the network transient stability by reducing the current flow in a fast and effective manner. In fact, by applying created impedance by fault current limiter when a short circuit happens on the path of current injection DG to the fault location, the critical fault clearing time improve remarkably. Therefore, protective relay has more time to clear fault and isolate the fault zone without any instability. Finally, different transient scenarios of connection plan sustainability of small scale synchronous generators to the distribution network are presented.

Keywords: critical clearing time, fault current limiter, synchronous generator, transient stability, transient states

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Authors: Sehrish Qayyum

Abstract:

Active military power contention is shifting to economic and cyberwar to retain hegemony. Attuned Pestle analysis confirms that structural stress of hegemon’s power loss drives a containment approach towards caging actions. Ongoing diplomatic, asymmetric, proxy and direct wars are increasing stress hegemon’s power retention due to tangled military and economic alliances. It creates the condition of catalepsy with defective reflexive control which affects the core warfare operations. When one’s own power is doubted it gives power to one’s own doubt to ruin all planning either done with superlative cost-benefit analysis. Strategically calculated estimation of Hegemon’s power game since the early WWI to WWII, WWII-to Cold War and then to the current era in three chronological periods exposits that Thucydides’s trap became the reason for war broke out. Thirst for power is the demise of imagination and cooperation for better sense to prevail instead it drives ashes to dust. Pestle analysis is a wide array of evaluation from political and economic to legal dimensions of the state matters. It helps to develop the Pacification and Security Policy Plan (PSPP) to avoid hegemon’s structural stress of power loss in fact, in turn, creates an alliance with maximum amicable outputs. PSPP may serve to regulate and pause the hurricane of power clashes. PSPP along with a strategic work plan is based on Pestle analysis to deal with any conceivable war condition and approach for saving international peace. Getting tangled into self-imposed epistemic dilemmas results in regret that becomes the only option of performance. It is a generic application of probability tests to find the best possible options and conditions to develop PSPP for any adversity possible so far. Innovation in expertise begets innovation in planning and action-plan to serve as a rheostat approach to deal with any plausible power clash.

Keywords: alliance, hegemon, pestle analysis, pacification and security policy plan, security

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Authors: Qasim M. Kriri

Abstract:

Few Saudi Arabia production companies face financial profit issues until this moment. This work presents a linear integer programming model that solves a production problem of a Saudi Food Company in Saudi Arabia. An optimal solution to the above-mentioned problem is a Linear Programming solution. In this regard, the main purpose of this project is to maximize profit. Linear Programming Technique has been used to derive the maximum profit from production of natural juice at Saudi Food Co. The operations of production of the company were formulated and optimal results are found out by using Lindo Software that employed Sensitivity Analysis and Parametric linear programming in order develop Linear Programming. In addition, the parameter values are increased, then the values of the objective function will be increased.

Keywords: parameter linear programming, objective function, sensitivity analysis, optimize profit

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