Search results for: poor performance
5818 Port Governance Model by International Freight Forwarders’ Point of View: A Study at Port of Santos - Brazil
Authors: Guilherme B. B. Vieira, Rafael M. da Silva, Eliana T. P. Senna, Luiz A. S. Senna, Francisco J. Kliemann Neto
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Due to the importance of ports to trade and economic development of the regions in which they are inserted, in recent decades the number of studies devoted to this subject has increased. Part of these studies consider the ports as business agglomerations and focuses on port governance. This is an important approach since the port performance is the result of activities performed by actors belonging to the port-logistics chain, which need to be properly coordinated. This coordination takes place through a port governance model. Given this context, this study aims to analyze the governance model of the port of Santos from the perspective of port customers. To do this, a closed-ended questionnaire based on a conceptual model that considers the key dimensions associated with port governance was applied to the international freight forwarders that operate in the port. The results show the applicability of the considered model and highlight improvement opportunities to be implemented at the port of Santos.Keywords: port governance, model, Port of Santos, customers’ perception
Procedia PDF Downloads 4415817 Exploring the Treatment of Unmarried Female Adolescents (10-19 Years) at Health Facilities during the Maternity Period in Uganda
Authors: Peninah Agaba, Monica Magadi, Bev Orton
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Uganda is one of the countries with high maternal mortality (336/100,000) where adolescents account for 24 percent of the total maternal deaths. Research shows that use of maternal health services may prevent some of these deaths and good provider attitudes attract adolescents to use the services. However, poor health provider’s attitudes discourage adolescents from seeking the services during the maternity period. This study explores the experiences of unmarried female adolescents at the health facilities during the maternity period. The study population is unmarried adolescent girls aged 10-19 years who were pregnant or had given birth within three years before the interview. This is a special interest group that requires attention throughout this period. Most of the pregnancies among unmarried adolescents are unwanted; as a result, many of them have been abused and neglected by parents and close family members including partners who deny fatherhood of the pregnancy/child. These adolescents hope to find comfort from health providers like being listened to during counseling, not abused and judged; unfortunately this is not the case always. The research was approved by the University of Hull, School of Education and Social Sciences ethics review committee, Mildmay Uganda Research Ethics Committee and Uganda National Council of Science and Technology. The study was carried out in Bushenyi and Kibale districts in Western Uganda. Fourteen in-depth interviews and seven focus group discussions were completed in the local languages and later transcribed to English language. Thematic analysis to identify the themes was done. Adolescents were aged 16-19 years, two had become pregnant before 15 years. Most had not completed secondary education; none had tertiary education and three of the 14 IDI adolescent participants wanted to get pregnant. Analysis shows varied experiences; most adolescents were abused verbally and physically by the health providers due to their young age of pregnancy, lack of essential items during this period (maternity dresses, children clothes, delivery kit) and fear of labour pains. Another cause for abuse was these adolescents coming for antenatal care with no partners yet the implementation of a policy on increasing male involvement in reproductive health in Uganda requires them to attend antenatal care with their partners and most of these unmarried adolescents have no partners to accompany them. Despite the above challenges, the study also identified the care some of these unmarried adolescents received during the maternity visits for example they were not abused, were provided with appropriate information and supported with child care. The study identified abuse and support the unmarried adolescents received during the maternity period. Efforts to provide adolescents with adequate information including what to expect during labour by providers and provision of basic needs are essential. Health providers should have trainings on client care especially how to embrace unmarried adolescents when they come to access maternity services. More so, the policy on improving male involvement in RH issues need to be considerate of unmarried adolescents who in most cases do not have the partners to go with to access maternity care.Keywords: abuse, maternity care, Uganda, unmarried, adolescents
Procedia PDF Downloads 1255816 Local Community's Response on Post-Disaster and Role of Social Capital towards Recovery Process: A Case Study of Kaminani Community in Bhaktapur Municipality after 2015 Gorkha Nepal Earthquake
Authors: Lata Shakya, Toshio Otsuki, Saori Imoto, Bijaya Krishna Shrestha, Umesh Bahadur Malla
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2015 Gorkha Nepal earthquake have damaged the human settlements in 14 districts of Nepal. Historic core areas of three principal cities namely Kathmandu, Lalitpur and Bhaktapur including numerous traditional ‘newari’ settlements in the peripheral areas have been either collapsed or severely damaged. Despite Government of Nepal and (international) non-government organisations’ attempt towards disaster risk management through the preparation of policies and guidelines and implementation of community-based activities, the recent ‘Gorkha’ earthquake has demonstrated the inadequate preparedness, poor implementation of a legal instrument, resource constraints, and managerial weakness. However, the social capital through community based institutions, self-help attitude, and community bond has helped a lot not only in rescue and relief operation but also in a post-disaster temporary shelter living thereby exhibiting the resilient power of the local community. Conducting a detailed case study of ‘Kaminani’ community with 42 houses at ward no. 16 of Bhaktapur municipality, this paper analyses the local community’s response and activities on the Gorkha earthquake in rescue and relief operation as well as in post disaster work. Leadership, the existence of internal/external aid, physical and human support are also analyzed. Social resource and networking are also explained through critical review of the existing community organisation and their activities. The research methodology includes literature review, field survey, and interview with community leaders and residents based on a semi-structured questionnaire. The study reveals that community carried their recovery process in four different phases: (i) management of emergency evacuation, (ii) constructing community owed temporary shelter for individuals, (iii) demolishing upper floors of the damaged houses, and (iv) planning for collaborative housing reconstruction. As territorial based organization, religion based agency and aim based institution exist in the survey area from pre-disaster time, it can be assumed that the community activists including leaders are well experienced to create aim-based group and manage teamwork to deal with various issues and problems collaboratively. Physical and human support including partial financial aid from external source as a result of community leader’s personal networking is extended to the community members. Thus, human/social resource and personal/social network play a crucial role in the recovery process. And to build such social capital, community should have potential from pre-disaster time.Keywords: Gorkha Nepal earthquake, local community, recovery process, social resource, social network
Procedia PDF Downloads 2475815 Presenting a Job Scheduling Algorithm Based on Learning Automata in Computational Grid
Authors: Roshanak Khodabakhsh Jolfaei, Javad Akbari Torkestani
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As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm.Keywords: computational grid, job scheduling, learning automata, dynamic scheduling
Procedia PDF Downloads 3355814 Evaluation of an Organic Coating Applied on Algerian Oil Tanker in Sea water by EIS
Authors: Nadia Hammouda, Kamel Belmokre
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Organic coatings are widely employed in the corrosion protection of most metal surfaces, particularly steel. They provide a barrier against corrosive species present in the environment, due to their high resistance to oxygen, water and ions transport. This study focuses on the evaluation of corrosion protection performance of epoxy paint on the carbon steel surface in sea water by Electrochemical Impedance Spectroscopy (EIS). The electrochemical behavior of painted surface was estimated by EIS parameters that contained paint film resistance, paint film capacitance and double layer capacitance. On the basis of calculation using EIS spectrums it was observed that pore resistance (Rpore) decreased with the appearance of doubled layer capacitance (Cdl) due to the electrolyte penetration through the film. This was further confirmed by the decrease of diffusion resistance (Rd) which was also the indicator of the deterioration of paint film protectiveness.Keywords: epoxy paints, carbon steel, electrochemical impedance spectroscopy, corrosion mechanisms, seawater
Procedia PDF Downloads 4095813 Solar Power Forecasting for the Bidding Zones of the Italian Electricity Market with an Analog Ensemble Approach
Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva
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The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.Keywords: analog ensemble, electricity market, PV forecast, solar energy
Procedia PDF Downloads 1445812 Solving Single Machine Total Weighted Tardiness Problem Using Gaussian Process Regression
Authors: Wanatchapong Kongkaew
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This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches.Keywords: Gaussian process regression, iterated local search, simulated annealing, single machine total weighted tardiness
Procedia PDF Downloads 3045811 FLEX: A Backdoor Detection and Elimination Method in Federated Scenario
Authors: Shuqi Zhang
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Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%.Keywords: federated learning, secure aggregation, backdoor attack, cluster analysis, neuron pruning
Procedia PDF Downloads 885810 Prevalence, Antimicrobial Susceptibility Pattern and Public Health Significance for Staphylococcus Aureus of Isolated from Raw Red Meat at Butchery and Abattoir House in Mekelle, Northern Ethiopia
Authors: Haftay Abraha Tadesse
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Background: Staphylococcus is a genus of worldwide distributed bacteria correlated to several infectious of different sites in humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. Objective: The objective of this study was to determine the isolates, antimicrobial susceptibility patterns and Public Health Significance of Staphylococcus aureus in raw meat from butchery and abattoir houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from April to October 2019. Socio-demographic data and Public Health Significance were collected using a predesigned questionnaire. The raw meat samples were collected aseptically in the butchery and abattoir houses and transported using an ice box to Mekelle University, College of Veterinary Sciences, for isolating and identification of Staphylococcus aureus. Antimicrobial susceptibility tests were determined by the disc diffusion method. Data obtained were cleaned and entered into STATA 22.0 and a logistic regression model with odds ratio was calculated to assess the association of risk factors with bacterial contamination. A P-value < 0.05 was considered statistically significant. Results: In the present study, 88 out of 250 (35.2%) were found to be contaminated with Staphylococcus aureus. Among the raw meat specimens, the positivity rate of Staphylococcus aureus was 37.6% (n=47) and (32.8% (n=41), butchery and abattoir houses, respectively. Among the associated risks, factories not using gloves reduces risk was found to (AOR=0.222; 95% CI: 0.104-0.473), Strict Separation b/n clean & dirty (AOR= 1.37; 95% CI: 0.66-2.86) and poor habit of hand washing (AOR=1.08; 95%CI: 0.35 3.35) was found to be statistically significant and have associated with Staphylococcus aureus contamination. All isolates of thirty-seven of Staphylococcus aureus were checked and displayed (100%) sensitive to doxycycline, trimethoprim, gentamicin, sulphamethoxazole, amikacin, CN, Co trimoxazole and nitrofurantoi. Whereas the showed resistance to cefotaxime (100%), ampicillin (87.5%), Penicillin (75%), B (75%), and nalidixic acid (50%) from butchery houses. On the other hand, all isolates of Staphylococcus aureus isolate 100% (n= 10) showed sensitive chloramphenicol, gentamicin and nitrofurantoin, whereas they showed 100% resistance of Penicillin, B, AMX, ceftriaxone, ampicillin and cefotaxime from abattoirs houses. The overall multi-drug resistance pattern for Staphylococcus aureus was 90% and 100% of butchery and abattoir houses, respectively. Conclusion: 35.3% Staphylococcus aureus isolated were recovered from the raw meat samples collected from the butchery and abattoirs houses. More has to be done in the development of hand washing behavior and availability of safe water in the butchery houses to reduce the burden of bacterial contamination. The results of the present finding highlight the need to implement protective measures against the levels of food contamination and alternative drug options. The development of antimicrobial resistance is nearly always a result of repeated therapeutic and/or indiscriminate use of them. Regular antimicrobial sensitivity testing helps to select effective antibiotics and to reduce the problems of drug resistance development towards commonly used antibiotics.Keywords: abattoir house, AMR, butchery house, S. aureus
Procedia PDF Downloads 845809 The Evaluation of Fuel Desulfurization Performance of Choline-Chloride Based Deep Eutectic Solvents with Addition of Graphene Oxide as Catalyst
Authors: Chiau Yuan Lim, Hayyiratul Fatimah Mohd Zaid, Fai Kait Chong
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Deep Eutectic Solvent (DES) is used in various applications due to its simplicity in synthesis procedure, biodegradable, inexpensive and easily available chemical ingredients. Graphene Oxide is a popular catalyst that being used in various processes due to its stacking carbon sheets in layer which theoretically rapid up the catalytic processes. In this study, choline chloride based DESs were synthesized and ChCl-PEG(1:4) was found to be the most effective DES in performing desulfurization, which it is able to remove up to 47.4% of the sulfur content in the model oil in just 10 minutes, and up to 95% of sulfur content after repeat the process for six times. ChCl-PEG(1:4) able to perform up to 32.7% desulfurization on real diesel after 6 multiple stages. Thus, future research works should focus on removing the impurities on real diesel before utilising DESs in petroleum field.Keywords: choline chloride, deep eutectic solvent, fuel desulfurization, graphene oxide
Procedia PDF Downloads 1445808 An Algorithm for Determining the Arrival Behavior of a Secondary User to a Base Station in Cognitive Radio Networks
Authors: Danilo López, Edwin Rivas, Leyla López
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This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.Keywords: cognitive radio, base station, best effort, MLPNN, prediction, real time
Procedia PDF Downloads 3215807 Syndromic Surveillance Framework Using Tweets Data Analytics
Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden
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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza
Procedia PDF Downloads 1065806 Parametric Screening and Design Refinement of Ceiling Fan Blades
Authors: Shamraiz Ahmad, Riaz Ahmad, Adnan Maqsood
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This paper describes the application of 2k-design of experiment in order to screen the geometric parameters and experimental refinement of ceiling fan blades. The ratio of the air delivery to the power consumed is commonly known as service value (SV) in ceiling fan designer’s community. Service value was considered as the response for 56 inch ceiling fan and four geometric parameters (bend position at root, bend position at tip, bent angle at root and bent angle at tip) of blade were analyzed. With two levels, the 4-design parameters along with their eleven interactions were studied and design of experiment was employed for experimental arrangement. Blade manufacturing and testing were done in a medium scale enterprise. The objective was achieved and service value of ceiling fan was increased by 10.4 % without increasing the cost of production and manufacturing system. Experiments were designed and results were analyzed using Minitab® 16 software package.Keywords: parametric screening, 2k-design of experiment, ceiling fan, service value, performance improvement
Procedia PDF Downloads 5545805 Fisheries Education in Karnataka: Trends, Current Status, Performance and Prospects
Authors: A. Vinay, Mary Josephine, Shreesha. S. Rao, Dhande Kranthi Kumar, J. Nandini
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This paper looks at the development of Fisheries education in Karnataka and the supply of skilled human capital to the sector. The study tries to analyse their job occupancy patterns, Compound Growth Rate (CGR) and forecasts the fisheries graduates supply using the Holt method. In Karnataka, fisheries are one of the neglected allied sectors of agriculture in spite of having enormous scope and potential to contribute to the State's agriculture GDP. The State Government has been negligent in absorbing skilled human capital for the development of fisheries, as there are so many vacant positions in both education institutes, as well as the State fisheries department. CGR and forecasting of fisheries graduates shows a positive growth rate and increasing trend, from which we can understand that by proper utilization of skilled human capital can bring development in the fisheries sector of Karnataka.Keywords: compound growth rate, fisheries education, holt method, skilled human capital
Procedia PDF Downloads 2575804 Generating Music with More Refined Emotions
Authors: Shao-Di Feng, Von-Wun Soo
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To generate symbolic music with specific emotions is a challenging task due to symbolic music datasets that have emotion labels are scarce and incomplete. This research aims to generate more refined emotions based on the training datasets that are only labeled with four quadrants in Russel’s 2D emotion model. We focus on the theory of Music Fadernet and map arousal and valence to the low-level attributes, and build a symbolic music generation model by combining transformer and GM-VAE. We adopt an in-attention mechanism for the model and improve it by allowing modulation by conditional information. And we show the music generation model could control the generation of music according to the emotions specified by users in terms of high-level linguistic expression and by manipulating their corresponding low-level musical attributes. Finally, we evaluate the model performance using a pre-trained emotion classifier against a pop piano midi dataset called EMOPIA, and by subjective listening evaluation, we demonstrate that the model could generate music with more refined emotions correctly.Keywords: music generation, music emotion controlling, deep learning, semi-supervised learning
Procedia PDF Downloads 795803 The Use of Biofeedback to Increase Resilience and Mental Health of Supersonic Pilots
Authors: G. Kloudova, S. Kozlova, M. Stehlik
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Pilots are operating in a high-risk environment rich in potential stressors, which negatively affect aviation safety and the mental health of pilots. In the research conducted, the pilots were offered mental training biofeedback therapy. Biofeedback is an objective tool to measure physiological responses to stress. After only six sessions, all of the pilots tested showed significant differences between their initial condition and their condition after therapy. The biggest improvement was found in decreased heart rate (in 83.3% of tested pilots) and respiration rate (66.7%), which are the best indicators of anxiety states and panic attacks. To incorporate all of the variables, we correlated the measured physiological state of the pilots with their personality traits. Surprisingly, we found a high correlation with peripheral temperature and confidence (0.98) and with heart rate and aggressiveness (0.97). A retest made after a one-year interval showed that in majority of the subjects tested their acquired self-regulation ability had been internalized.Keywords: aviation, biofeedback, mental workload, performance psychology
Procedia PDF Downloads 2445802 Unsupervised Domain Adaptive Text Retrieval with Query Generation
Authors: Rui Yin, Haojie Wang, Xun Li
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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.Keywords: dense retrieval, query generation, unsupervised training, text retrieval
Procedia PDF Downloads 635801 Low-Temperature Silanization of Medical Vials: Chemical Bonding and Performance
Authors: Yuanping Yang, Ruolin Zhou, Xingyu Liu, Lianbin Wu
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Based on the challenges of silanization of pharmaceutical glass packaging materials, the silicone oil high-temperature baking method consumes a lot of energy; silicone oil is generally physically adsorbed on the inner surface of the medical vials, leading to protein adsorption on the surface of the silicone oil and fall off, so that the number of particles in the drug solution increases, which brings potential risks to people. In this paper, a new silanizing method is proposed. High-efficiency silanization is achieved by grafting trimethylsilyl groups to the inner surface of medical vials by chemical bond at low temperatures. The inner wall of the vial successfully obtained stable hydrophobicity, and the water contact Angle of the surface reached 100°~110°. With the increase of silicified reagent concentration, the water resistance of corresponding treatment vials increased gradually. This treatment can effectively reduce the risk of pH value increase and sodium ion leaching.Keywords: low-temperature silanization, medical vials, chemical bonding, hydrophobicity
Procedia PDF Downloads 745800 Using Virtual Reality Exergaming to Improve Health of College Students
Authors: Juanita Wallace, Mark Jackson, Bethany Jurs
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Introduction: Exergames, VR games used as a form of exercise, are being used to reduce sedentary lifestyles in a vast number of populations. However, there is a distinct lack of research comparing the physiological response during VR exergaming to that of traditional exercises. The purpose of this study was to create a foundationary investigation establishing changes in physiological responses resulting from VR exergaming in a college aged population. Methods: In this IRB approved study, college aged students were recruited to play a virtual reality exergame (Beat Saber) on the Oculus Quest 2 (Facebook, 2021) in either a control group (CG) or training group (TG). Both groups consisted of subjects who were not habitual users of virtual reality. The CG played VR one time per week for three weeks and the TG played 150 min/week three weeks. Each group played the same nine Beat Saber songs, in a randomized order, during 30 minute sessions. Song difficulty was increased during play based on song performance. Subjects completed a pre- and posttests at which the following was collected: • Beat Saber Game Metrics: song level played, song score, number of beats completed per song and accuracy (beats completed/total beats) • Physiological Data: heart rate (max and avg.), active calories • Demographics Results: A total of 20 subjects completed the study; nine in the CG (3 males, 6 females) and 11 (5 males, 6 females) in the TG. • Beat Saber Song Metrics: The TG improved performance from a normal/hard difficulty to hard/expert. The CG stayed at the normal/hard difficulty. At the pretest there was no difference in game accuracy between groups. However, at the posttest the CG had a higher accuracy. • Physiological Data (Table 1): Average heart rates were similar between the TG and CG at both the pre- and posttest. However, the TG expended more total calories. Discussion: Due to the lack of peer reviewed literature on c exergaming using Beat Saber, the results of this study cannot be directly compared. However, the results of this study can be compared with the previously established trends for traditional exercise. In traditional exercise, an increase in training volume equates to increased efficiency at the activity. The TG should naturally increase in difficulty at a faster rate than the CG because they played 150 hours per week. Heart rate and caloric responses also increase during traditional exercise as load increases (i.e. speed or resistance). The TG reported an increase in total calories due to a higher difficulty of play. The song accuracy decreases in the TG can be explained by the increased difficulty of play. Conclusion: VR exergaming is comparable to traditional exercise for loads within the 50-70% of maximum heart rate. The ability to use VR for health could motivate individuals who do not engage in traditional exercise. In addition, individuals in health professions can and should promote VR exergaming as a viable way to increase physical activity and improve health in their clients/patients.Keywords: virtual reality, exergaming, health, heart rate, wellness
Procedia PDF Downloads 1785799 Retrofitted Semi-Active Suspension System for a Eelectric Model Vehicle
Authors: Shiuh-Jer Huang, Yun-Han Yeh
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A 40 steps manual adjusting shock absorber was refitted with DC motor driving mechanism to construct as a semi-active suspension system for a four-wheel drive electric vehicle. Accelerometer and potentiometer sensors are installed to measure the sprung mass acceleration and suspension system compression or rebound states for control purpose. A fuzzy logic controller was designed to derive appropriate damping target based on vehicle running condition for semi-active suspension system to follow. The damping ratio control of each wheel axis suspension system is executed with a robust fuzzy sliding mode controller (FSMC). Different road surface conditions are chosen to evaluate the control performance of this semi-active suspension system based on wheel axis acceleration signal.Keywords: semi-active suspension, electric vehicle, fuzzy sliding mode control, accelerometer
Procedia PDF Downloads 4745798 Model-Based Control for Piezoelectric-Actuated Systems Using Inverse Prandtl-Ishlinskii Model and Particle Swarm Optimization
Authors: Jin-Wei Liang, Hung-Yi Chen, Lung Lin
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In this paper feedforward controller is designed to eliminate nonlinear hysteresis behaviors of a piezoelectric stack actuator (PSA) driven system. The control design is based on inverse Prandtl-Ishlinskii (P-I) hysteresis model identified using particle swarm optimization (PSO) technique. Based on the identified P-I model, both the inverse P-I hysteresis model and feedforward controller can be determined. Experimental results obtained using the inverse P-I feedforward control are compared with their counterparts using hysteresis estimates obtained from the identified Bouc-Wen model. Effectiveness of the proposed feedforward control scheme is demonstrated. To improve control performance feedback compensation using traditional PID scheme is adopted to integrate with the feedforward controller.Keywords: the Bouc-Wen hysteresis model, particle swarm optimization, Prandtl-Ishlinskii model, automation engineering
Procedia PDF Downloads 5125797 Design and Development of an Expanded Polytetrafluoroethylene Valved Conduit with Sinus of Valsalva
Authors: Munirah Ismail, Joon Hock Yeo
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Babies born with Tetralogy of Fallot, a congenital heart defect, are required to undergo reconstruction surgery to create a valved conduit. As the child matures, the partially reconstructed pulmonary conduit increases in diameter, while the size of the reconstructed valve remains the same. As a result, follow up surgery is required to replace the undersized valve. Thus, in this project, we evaluated the in-vitro performance of a bi-leaflet valve design in terms of percentage regurgitation with increasing artery (conduit) diameters. Results revealed percentage regurgitations ranging from 13% to 34% for conduits tested. It was observed that percentage of regurgitation increased exponentially with increasing diameters. While the amount of regurgitation may seem severe, it is deemed acceptable, and this valve could potentially reduce the frequency of re-operation in the lifetime of pediatric patients.Keywords: pulmonary heart valve, tetralogy of fallot, expanded polytetrafluoroethylene valve, pediatric heart valve replacement
Procedia PDF Downloads 1695796 Analysis of Different Space Vector Pulse Width Modulation Techniques for a Five-Phase Inverter
Authors: K. A. Chinmaya, M. Udaya Bhaskar
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Multiphase motor drives are now a day considered for numerous applications due to the advantages that they offer when compared to their three-phase counterparts. Proper modeling of inverters and motors are important in devising an appropriate control algorithm. This paper develops a complete modeling of a five-phase inverter and five-phase space vector modulation schemes which can be used for five-phase motor drives. A novel modified algorithm is introduced which enables the sinusoidal output voltages up to certain voltage value. The waveforms of phase to neutral voltage are compared with the different modulation techniques and also different modulation indexes in terms of Low-order Harmonic (LH) voltage of 3rd and 7th present. A detailed performance evolution of existing and newly modified schemes is done in terms of Total Harmonic Distortion (THD).Keywords: multi-phase drives, space vector modulation, voltage source inverter, low order harmonic voltages, total harmonic distortion
Procedia PDF Downloads 3965795 Virtual Reality Technology for Employee Training in High-Risk Industries: Benefits and Advancements
Authors: Yeganeh Jabbari, Sepideh Khalatabad
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This study explores the development of virtual reality (VR) technology for training applications, specifically its the potential benefits of VR technology for employee training and its ability to simulate real-world scenarios in a safe and controlled environment are highlighted, along with the associated cost and time savings. The adoption of VR technology in high-risk industrial organizations such as the oil and gas industry is discussed, with a focus on its ability to improve worker performance. Additionally, the use of VR technology in activities such as simulation and data visualization in the oil and gas industry is explored, leading to enhanced safety measures and collaboration between teams. The integration of advanced technologies such as robotics is mentioned as a way to further promote efficiency and sustainability. Also, the study mentions that the digital transformation of the oil and gas industry is revolutionizing operations and promoting safety, efficiency, and sustainability through the use of VR technology.Keywords: virtual reality training, virtual reality benefits, high-risk industries, digital transformation
Procedia PDF Downloads 835794 The Effect of Nylon and Kevlar Stitching on the Mode I Fracture of Carbon/Epoxy Composites
Authors: Nisrin R. Abdelal, Steven L. Donaldson
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Composite materials are widely used in aviation industry due to their superior properties; however, they are susceptible to delamination. Through-thickness stitching is one of the techniques to alleviate delamination. Kevlar is one of the most common stitching materials; in contrast, it is expensive and presents stitching fabrication challenges. Therefore, this study compares the performance of Kevlar with an inexpensive and easy-to-use nylon fiber in stitching to alleviate delamination. Three laminates of unidirectional carbon fiber-epoxy composites were manufactured using vacuum assisted resin transfer molding process. One panel was stitched with Kevlar, one with nylon, and one unstitched. Mode I interlaminar fracture tests were carried out on specimens from the three composite laminates, and the results were compared. Fractographic analysis using optical and scanning electron microscope were conducted to reveal the differences between stitching with Kevlar and nylon on the internal microstructure of the composite with respect to the interlaminar fracture toughness values.Keywords: carbon, delamination, Kevlar, mode I, nylon, stitching
Procedia PDF Downloads 2835793 Estimating Lost Digital Video Frames Using Unidirectional and Bidirectional Estimation Based on Autoregressive Time Model
Authors: Navid Daryasafar, Nima Farshidfar
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In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared.Keywords: error steganography, unidirectional estimation, bidirectional estimation, AR linear estimation
Procedia PDF Downloads 5245792 A Weighted Approach to Unconstrained Iris Recognition
Authors: Yao-Hong Tsai
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This paper presents a weighted approach to unconstrained iris recognition. Nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.Keywords: authentication, iris recognition, adaboost, local binary pattern
Procedia PDF Downloads 2165791 Printed Thai Character Recognition Using Particle Swarm Optimization Algorithm
Authors: Phawin Sangsuvan, Chutimet Srinilta
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This Paper presents the applications of Particle Swarm Optimization (PSO) Method for Thai optical character recognition (OCR). OCR consists of the pre-processing, character recognition and post-processing. Before enter into recognition process. The Character must be “Prepped” by pre-processing process. The PSO is an optimization method that belongs to the swarm intelligence family based on the imitation of social behavior patterns of animals. Route of each particle is determined by an individual data among neighborhood particles. The interaction of the particles with neighbors is the advantage of Particle Swarm to determine the best solution. So PSO is interested by a lot of researchers in many difficult problems including character recognition. As the previous this research used a Projection Histogram to extract printed digits features and defined the simple Fitness Function for PSO. The results reveal that PSO gives 67.73% for testing dataset. So in the future there can be explored enhancement the better performance of PSO with improve the Fitness Function.Keywords: character recognition, histogram projection, particle swarm optimization, pattern recognition techniques
Procedia PDF Downloads 4665790 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries
Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi
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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery
Procedia PDF Downloads 5795789 Analysis and Rule Extraction of Coronary Artery Disease Data Using Data Mining
Authors: Rezaei Hachesu Peyman, Oliyaee Azadeh, Salahzadeh Zahra, Alizadeh Somayyeh, Safaei Naser
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Coronary Artery Disease (CAD) is one major cause of disability in adults and one main cause of death in developed. In this study, data mining techniques including Decision Trees, Artificial neural networks (ANNs), and Support Vector Machine (SVM) analyze CAD data. Data of 4948 patients who had suffered from heart diseases were included in the analysis. CAD is the target variable, and 24 inputs or predictor variables are used for the classification. The performance of these techniques is compared in terms of sensitivity, specificity, and accuracy. The most significant factor influencing CAD is chest pain. Elderly males (age > 53) have a high probability to be diagnosed with CAD. SVM algorithm is the most useful way for evaluation and prediction of CAD patients as compared to non-CAD ones. Application of data mining techniques in analyzing coronary artery diseases is a good method for investigating the existing relationships between variables.Keywords: classification, coronary artery disease, data-mining, knowledge discovery, extract
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