Search results for: training algorithms
191 A TIPSO-SVM Expert System for Efficient Classification of TSTO Surrogates
Authors: Ali Sarosh, Dong Yun-Feng, Muhammad Umer
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Fully reusable spaceplanes do not exist as yet. This implies that design-qualification for optimized highly-integrated forebody-inlet configuration of booster-stage vehicle cannot be based on archival data of other spaceplanes. Therefore, this paper proposes a novel TIPSO-SVM expert system methodology. A non-trivial problem related to optimization and classification of hypersonic forebody-inlet configuration in conjunction with mass-model of the two-stage-to-orbit (TSTO) vehicle is solved. The hybrid-heuristic machine learning methodology is based on two-step improved particle swarm optimizer (TIPSO) algorithm and two-step support vector machine (SVM) data classification method. The efficacy of method is tested by first evolving an optimal configuration for hypersonic compression system using TIPSO algorithm; thereafter, classifying the results using two-step SVM method. In the first step extensive but non-classified mass-model training data for multiple optimized configurations is segregated and pre-classified for learning of SVM algorithm. In second step the TIPSO optimized mass-model data is classified using the SVM classification. Results showed remarkable improvement in configuration and mass-model along with sizing parameters.
Keywords: TIPSO-SVM expert system, TIPSO algorithm, two-step SVM method, aerothermodynamics, mass-modeling, TSTO vehicle.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2299190 Estimation of Production Function in Fishery on the Coasts of Caspian Sea
Authors: Komeil Jahanifar, Zahra Abedi, Yaghob Zeraatkish
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This research was conducted for the first time at the southeastern coasts of the Caspian Sea in order to evaluate the performance of osteichthyes cooperatives through production (catch) function. Using one of the indirect valuation methods in this research, contributory factors in catch were identified and were inserted into the function as independent variables. In order to carry out this research, the performance of 25 Osteichthyes catching cooperatives in the utilization year of 2009 which were involved in fishing in Miankale wildlife refuge region. The contributory factors in catch were divided into groups of economic, ecological and biological factors. In the mentioned function, catch rate of the cooperative were inserted into as the dependant variable and fourteen partial variables in terms of nine general variables as independent variables. Finally, after function estimation, seven variables were rendered significant at 99 percent reliably level. The results of the function estimation indicated that human resource (fisherman quantity) had the greatest positive effect on catch rate with an influence coefficient of 1.7 while weather conditions had the greatest negative effect on the catch rate of cooperatives with an influence coefficient of -2.07. Moreover, factors like member's share, experience and fisherman training and fishing effort played the main roles in the catch rate of cooperative with influence coefficients of 0.81, 0.5 and 0.21, respectively.Keywords: Production Function, Coefficient, Variable, Osteichthyes, Caspian Sea
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2029189 Decision Algorithm for Smart Airbag Deployment Safety Issues
Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis
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Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4100188 A Cross-Cultural Approach for Communication with Biological and Non-Biological Intelligences
Authors: Thomas Schalow
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This paper posits the need to take a cross-cultural approach to communication with non-human cultures and intelligences in order to meet the following three imminent contingencies: communicating with sentient biological intelligences, communicating with extraterrestrial intelligences, and communicating with artificial super-intelligences. The paper begins with a discussion of how intelligence emerges. It disputes some common assumptions we maintain about consciousness, intention, and language. The paper next explores cross-cultural communication among humans, including non-sapiens species. The next argument made is that we need to become much more serious about communicating with the non-human, intelligent life forms that already exist around us here on Earth. There is an urgent need to broaden our definition of communication and reach out to the other sentient life forms that inhabit our world. The paper next examines the science and philosophy behind CETI (communication with extraterrestrial intelligences) and how it has proven useful, even in the absence of contact with alien life. However, CETI’s assumptions and methodology need to be revised and based on the cross-cultural approach to communication proposed in this paper if we are truly serious about finding and communicating with life beyond Earth. The final theme explored in this paper is communication with non-biological super-intelligences using a cross-cultural communication approach. This will present a serious challenge for humanity, as we have never been truly compelled to converse with other species, and our failure to seriously consider such intercourse has left us largely unprepared to deal with communication in a future that will be mediated and controlled by computer algorithms. Fortunately, our experience dealing with other human cultures can provide us with a framework for this communication. The basic assumptions behind intercultural communication can be applied to the many types of communication envisioned in this paper if we are willing to recognize that we are in fact dealing with other cultures when we interact with other species, alien life, and artificial super-intelligence. The ideas considered in this paper will require a new mindset for humanity, but a new disposition will prepare us to face the challenges posed by a future dominated by artificial intelligence.
Keywords: Artificial intelligence, CETI, communication, culture, language.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 972187 Load Forecasting in Microgrid Systems with R and Cortana Intelligence Suite
Authors: F. Lazzeri, I. Reiter
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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.
Keywords: Time-series, features engineering methods for forecasting, energy demand forecasting, Azure machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1275186 Solar Thermal Aquaculture System Controller Based on Artificial Neural Network
Authors: A. Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah
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Temperature is one of the most principle factors affects aquaculture system. It can cause stress and mortality or superior environment for growth and reproduction. This paper presents the control of pond water temperature using artificial intelligence technique. The water temperature is very important parameter for shrimp growth. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it cause death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. Artificial neural network is proposed to control water temperature due to Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems. Moreover this paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the aquaculture system. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.
Keywords: artificial neural networks, aquaculture, forced circulation hot water system,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2043185 A Profile of Recent Upsurge of Brucellosis of Veterinary Health Care Workers Engaged in Brucella Vaccination Program in West Bengal, India
Authors: Satadal Das, Parthasarathi Sengupta
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With millions of livestock wealth in India including cattle, and buffaloes, the National Animal Disease Control Program targeted a massive Brucella vaccination program. As a part of it in the state of West Bengal Veterinary healthcare assistants participated in the program in 2021. The aim of this study was to elucidate the burden of brucellosis in those healthcare assistants and to pinpoint the main causes of such infection. We contacted the healthcare assistants to find out whether they were infected during the vaccination program. Our findings indicated many Veterinary healthcare assistants who participated in the program developed symptoms and signs suggestive of brucellosis. Laboratory tests indicated many confirmed Brucellosis cases. However, this may not include many asymptomatic cases. Detailed analysis revealed that in most of them there was a history of needle prick injury about a month back during the vaccination program, which was mainly due to ferocious or disturbed animals. Few also complained that they were not properly trained or proper personal protective types of equipment were not provided. All of them were treated in referral hospitals following a standard protocol of the Government Health Department and now they are followed up. Thus we conclude that proper care during the vaccination of animals should be followed, prophylactic treatment for needle prick injuries should be given, and training and supply of personal protective equipment should be monitored.
Keywords: Occupational brucellosis, needle prick injury, brucella vaccination, personal protective equipment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 379184 Performance Comparison of Situation-Aware Models for Activating Robot Vacuum Cleaner in a Smart Home
Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu
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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.Keywords: Situation-awareness, Smart home, IoT, Machine learning, Classifier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1844183 Face Recognition Using Principal Component Analysis, K-Means Clustering, and Convolutional Neural Network
Authors: Zukisa Nante, Wang Zenghui
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Face recognition is the problem of identifying or recognizing individuals in an image. This paper investigates a possible method to bring a solution to this problem. The method proposes an amalgamation of Principal Component Analysis (PCA), K-Means clustering, and Convolutional Neural Network (CNN) for a face recognition system. It is trained and evaluated using the ORL dataset. This dataset consists of 400 different faces with 40 classes of 10 face images per class. Firstly, PCA enabled the usage of a smaller network. This reduces the training time of the CNN. Thus, we get rid of the redundancy and preserve the variance with a smaller number of coefficients. Secondly, the K-Means clustering model is trained using the compressed PCA obtained data which select the K-Means clustering centers with better characteristics. Lastly, the K-Means characteristics or features are an initial value of the CNN and act as input data. The accuracy and the performance of the proposed method were tested in comparison to other Face Recognition (FR) techniques namely PCA, Support Vector Machine (SVM), as well as K-Nearest Neighbour (kNN). During experimentation, the accuracy and the performance of our suggested method after 90 epochs achieved the highest performance: 99% accuracy F1-Score, 99% precision, and 99% recall in 463.934 seconds. It outperformed the PCA that obtained 97% and KNN with 84% during the conducted experiments. Therefore, this method proved to be efficient in identifying faces in the images.
Keywords: Face recognition, Principal Component Analysis, PCA, Convolutional Neural Network, CNN, Rectified Linear Unit, ReLU, feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 471182 Multi-Objective Optimization of Gas Turbine Power Cycle
Authors: Mohsen Nikaein
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Because of importance of energy, optimization of power generation systems is necessary. Gas turbine cycles are suitable manner for fast power generation, but their efficiency is partly low. In order to achieving higher efficiencies, some propositions are preferred such as recovery of heat from exhaust gases in a regenerator, utilization of intercooler in a multistage compressor, steam injection to combustion chamber and etc. However thermodynamic optimization of gas turbine cycle, even with above components, is necessary. In this article multi-objective genetic algorithms are employed for Pareto approach optimization of Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective optimization a number of conflicting objective functions are to be optimized simultaneously. The important objective functions that have been considered for optimization are entropy generation of RIGT cycle (Ns) derives using Exergy Analysis and Gouy-Stodola theorem, thermal efficiency and the net output power of RIGT Cycle. These objectives are usually conflicting with each other. The design variables consist of thermodynamic parameters such as compressor pressure ratio (Rp), excess air in combustion (EA), turbine inlet temperature (TIT) and inlet air temperature (T0). At the first stage single objective optimization has been investigated and the method of Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used for multi-objective optimization. Optimization procedures are performed for two and three objective functions and the results are compared for RIGT Cycle. In order to investigate the optimal thermodynamic behavior of two objectives, different set, each including two objectives of output parameters, are considered individually. For each set Pareto front are depicted. The sets of selected decision variables based on this Pareto front, will cause the best possible combination of corresponding objective functions. There is no superiority for the points on the Pareto front figure, but they are superior to any other point. In the case of three objective optimization the results are given in tables.Keywords: Exergy, Entropy Generation, Brayton Cycle, DesignParameters, Optimization, Genetic Algorithm, Multi-Objective.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2508181 Neuron Efficiency in Fluid Dynamics and Prediction of Groundwater Reservoirs'' Properties Using Pattern Recognition
Authors: J. K. Adedeji, S. T. Ijatuyi
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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p1), fractured layer (p2), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable gr (gravitational resistance) can be deduced from the elevation and apparent resistivity pa. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.
Keywords: Neural network, gravitational resistance, pattern recognition, non-linear.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 782180 The Effectiveness of Cognitive Behavioural Intervention in Alleviating Social Avoidance for Blind Students
Authors: Mohamed M. Elsherbiny
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Social Avoidance is one of the most important problems that face a good number of disabled students. It results from the negative attitudes of non-disabled students, teachers and others. Some of the past research has shown that non-disabled individuals hold negative attitudes toward persons with disabilities. The present study aims to alleviate Social Avoidance by applying the Cognitive Behavioral Intervention. 24 Blind students aged 19–24 (university students) were randomly chosen we compared an experimental group (consisted of 12 students) who went through the intervention program, with a control group (12 students also) who did not go through such intervention. We used the Social Avoidance and Distress Scale (SADS) to assess social anxiety and distress behavior. The author used many techniques of cognitive behavioral intervention such as modeling, cognitive restructuring, extension, contingency contracts, selfmonitoring, assertiveness training, role play, encouragement and others. Statistically, T-test was employed to test the research hypothesis. Result showed that there is a significance difference between the experimental group and the control group after the intervention and also at the follow up stages of the Social Avoidance and Distress Scale. Also for the experimental group, there is a significance difference before the intervention and the follow up stages for the scale. Results showed that, there is a decrease in social avoidance. Accordingly, cognitive behavioral intervention program was successful in decreasing social avoidance for blind students.Keywords: Social avoidance, cognitive behavioral intervention, blind disability, disability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1970179 Eradication of Mental Illness through Buddhism
Authors: Deshar Bashu Dev
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In this modern age, most people in developed and developing countries are affected by mental illness. There are many mental illnesses, and their differing symptoms impact peoples’ lives in different ways. These illnesses affect the way people think and feel, as well as how they behave with others. Mental illness results from compound interactions between the mind, body, and environment. New technologies and sciences make the world a better place. These technologies are becoming smarter and are being developed every day to help make daily life easier However, people suffer from mental illness in every part of the world. The philosophy propounded by the Buddha, Buddhism, teaches that all life is connected, from the microcosm to macrocosm. In the 2,500 years that elapsed since the death of the Buddha, his disciples have spread his teachings and developed sophisticated psycho-therapeutic methodologies. We can find many examples in Buddhist texts and in the modern age where Buddhist philosophy modern science could not solve. The Noble Eightfold Path, which is one of the main philosophies of Buddhism; it eradicates hatred and ill will and cultivates good deeds, kindness, and compassion. Buddhism, as a practice of dialectic conversation and mindfulness training, is full of rich therapeutic tools that the mental health community has adopted to help people. Similarly, Buddhist meditation is very necessary; it purifies thoughts and avoids unnecessary thinking. This research aims to study different causes of mental illness; analyzes the different approaches to eradicate mental illness problems and provides conclusions and recommendations present solutions through Buddhism in this modern age.
Keywords: Mental illness, Buddhism, mindfulness, Buddhist practices.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1883178 An Investigation of Final Tests of Translation as Practiced in Iranian Undergraduate English Translation Program
Authors: Hossein Heidari Tabrizi, Azizeh Chalak
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The present study examined how translation teachers develop final tests as measures for checking on the quality of students’ academic translation in Iranian context. To achieve this goal, thirty experienced male and female translation teachers from the four types of the universities offering the program were invited to an in-depth 30-minute one-session semi-structured interview. The responses provided showed how much discrepancy exists among the Iranian translation teachers (as developers of final translation tests), who are least informed with the current translation evaluation methods. It was also revealed that the criteria they use for developing such tests and scoring student translations are not theory-driven but are highly subjective, mainly based on their personal experience and intuition. Hence, the quality and accountability of such tests are under serious question. The results also confirmed that the dominant method commonly and currently practiced is the purely essay-type format. To remedy the situation, some suggestions are in order. As part of the solution, to improve the reliability and validity of such tests, the present summative, product-oriented evaluation should be accompanied with some formative, process-oriented methods of evaluation. Training the teachers and helping them get acquainted with modern principles of translation evaluation as well as the existing models, and rating scales does improve the quality of academic translation evaluation.Keywords: Iranian universities, students’ academic translations, translation final tests, undergraduate translation programs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2016177 Iterative Estimator-Based Nonlinear Backstepping Control of a Robotic Exoskeleton
Authors: Brahmi Brahim, Mohammad Habibur Rahman, Maarouf Saad, Cristóbal Ochoa Luna
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A repetitive training movement is an efficient method to improve the ability and movement performance of stroke survivors and help them to recover their lost motor function and acquire new skills. The ETS-MARSE is seven degrees of freedom (DOF) exoskeleton robot developed to be worn on the lateral side of the right upper-extremity to assist and rehabilitate the patients with upper-extremity dysfunction resulting from stroke. Practically, rehabilitation activities are repetitive tasks, which make the assistive/robotic systems to suffer from repetitive/periodic uncertainties and external perturbations induced by the high-order dynamic model (seven DOF) and interaction with human muscle which impact on the tracking performance and even on the stability of the exoskeleton. To ensure the robustness and the stability of the robot, a new nonlinear backstepping control was implemented with designed tests performed by healthy subjects. In order to limit and to reject the periodic/repetitive disturbances, an iterative estimator was integrated into the control of the system. The estimator does not need the precise dynamic model of the exoskeleton. Experimental results confirm the robustness and accuracy of the controller performance to deal with the external perturbation, and the effectiveness of the iterative estimator to reject the repetitive/periodic disturbances.Keywords: Backstepping control, iterative control, rehabilitation, ETS-MARSE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1360176 Reasons for Doing Job outside Household and Difficulties Faced by the Working Women of Bangladesh
Authors: Md. Sayeed Akhter, Md. Akhtar Hossain Mazumder, Syeda Afreena Mamun
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Bangladesh is a patriarchal and male dominated country. Traditional, cultural, social, and religious values and practices have reinforced the lower status of women accorded to them in society and have limited their opportunities for education, technical and vocational training, and involvement with earning activities outside their households. After independence numbers of women are doing job outside their households. This study attempts to find out the reasons of engaging in earning activities outside households and difficulties faced by upper and lower class working women in Bangladesh. To explore the objectives and research questions of the study descriptive techniques had been used. Survey was conducted among the women who were working in Rajshahi city of Bangladesh and face-to-face interviews were conducted to collect data. Findings of the study illustrates that most of the upper class working women engaged into job because they wanted to utilized their education and to bring solvency in the family, and they spend their income for meeting the needs of all the members of the family. On the other hand, most of the lower class working women involved into earning activities outside their households because they want to bring solvency in their families and spend their income on household expenditure. Both classes became tensed for their children because they had to stay at their working place for long time. Therefore, day care center should be established besides their working place for their children.
Keywords: Working Women, Reasons for Doing Jobs, Working Environment, Difficulties Faced.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1782175 The Effect of Sport Specific Exercises on the Visual Skills of Rugby Players
Authors: P.J. Du Toit, P. Janse Van Vuuren , S. Le Roux , E. Henning, M. Kleynhans, H.C. Terblanche, D. Crafford, C. Grobbelaar, P.S. Wood, C.C. Grant, L. Fletcher
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Introduction: Visual performance is an important factor in sport excellence. Visual involvement in a sport varies according to environmental demands associated with that sport. These environmental demands are matched by a task specific motor response. The purpose of this study was to determine if sport specific exercises will improve the visual performance of male rugby players, in order to achieve maximal results on the sports field. Materials & Methods: Twenty six adult male rugby players, aged 16-22, were chosen as subjects. In order to evaluate the effect of sport specific exercises on visual skills, a pre-test - post-test experimental group design was adopted for the study. Results: Significant differences (p≤0.05) were seen in the focussing, tracking, vergence, sequencing, eye-hand coordination and visualisation components Discussion & Conclusions: Sport specific exercises improved visual skills in rugby players which may provide them with an advantage over their opponents. This study suggests that these training programs and participation in regular on-line EyeDrills sports vision exercises (www.eyedrills.co.za) aimed at improving the athlete-s visual coordination, concentration, focus, hand-eye co-ordination, anticipation and motor response should be incorpotated in the rugby players exercise regime.
Keywords: Rugby players, sport specific exercises, visual skills.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2240174 Selecting Negative Examples for Protein-Protein Interaction
Authors: Mohammad Shoyaib, M. Abdullah-Al-Wadud, Oksam Chae
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Proteomics is one of the largest areas of research for bioinformatics and medical science. An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. Predicting Protein-Protein Interaction (PPI) is one of the crucial and decisive problems in current research. Genomic data offer a great opportunity and at the same time a lot of challenges for the identification of these interactions. Many methods have already been proposed in this regard. In case of in-silico identification, most of the methods require both positive and negative examples of protein interaction and the perfection of these examples are very much crucial for the final prediction accuracy. Positive examples are relatively easy to obtain from well known databases. But the generation of negative examples is not a trivial task. Current PPI identification methods generate negative examples based on some assumptions, which are likely to affect their prediction accuracy. Hence, if more reliable negative examples are used, the PPI prediction methods may achieve even more accuracy. Focusing on this issue, a graph based negative example generation method is proposed, which is simple and more accurate than the existing approaches. An interaction graph of the protein sequences is created. The basic assumption is that the longer the shortest path between two protein-sequences in the interaction graph, the less is the possibility of their interaction. A well established PPI detection algorithm is employed with our negative examples and in most cases it increases the accuracy more than 10% in comparison with the negative pair selection method in that paper.Keywords: Interaction graph, Negative training data, Protein-Protein interaction, Support vector machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1689173 Knowledge of Operation Rooms’ Staff Toward Sources, Prevention and Control of Fires at Governmental Hospitals in Sana'a, Yemen
Authors: A. Ahmed Haza’a, M. Ali Odhah, S. Ahmed Al-Ahdal, A. Saleh Al-Jaradi, G. Ghaleb Alrubaiee
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Patient safety in hospitals is an essential professional indicator that should be noticed. The threat of fires is potentially the most dangerous risk that could harm patients and personnel. The aim of the study is to assess the knowledge of operating room (OR) staff toward prevention and control sources of fires. Data collection was done between March 1 and March 30, 2022. A descriptive cross-sectional study was conducted. The sample of the study consisted of 89 OR staff from different governmental hospitals. Convenient sampling was applied to select the sample size. Official approvals were obtained from selected settings for start collection data. Data were collected using a close-ended questionnaire and tested for knowledge. This study was conducted in four governmental hospitals in Sana'a, Yemen. Most of the OR staff were male. Of these, 50.6% of them were operation technician professionals. More than two-thirds of OR staff have less than ten years of experience; 93% of OR staff had inadequate knowledge of sources of fires, and inadequate knowledge toward control and prevention of fires (73%, 79.8%), respectively; 77.5% of OR staff had inadequate knowledge of prevention and control sources of fires. The study concluded that most of OR staff had inadequate knowledge of sources, controls, and prevention of fires, while 22.5% of them had adequate knowledge of prevention and control sources of fires. We recommended the implementation of training programs toward sources, controls, and prevention of fires or related workshops in their educational planning for OR staff of hospitals.
Keywords: Staff, fire source, operation room safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 140172 A Cross-Disciplinary Educational Model in Biomanufacturing to Sustain a Competitive Workforce Ecosystem
Authors: Rosa Buxeda, Lorenzo Saliceti-Piazza, Rodolfo J. Romañach, Luis Ríos, Sandra L. Maldonado-Ramírez
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Biopharmaceuticals manufacturing is one of the major economic activities worldwide. Ninety-three percent of the workforce in a biomanufacturing environment concentrates in production-related areas. As a result, strategic collaborations between industry and academia are crucial to ensure the availability of knowledgeable workforce needed in an economic region to become competitive in biomanufacturing. In the past decade, our institution has been a key strategic partner with multinational biotechnology companies in supplying science and engineering graduates in the field of industrial biotechnology. Initiatives addressing all levels of the educational pipeline, from K-12 to college to continued education for company employees have been established along a ten-year span. The Amgen BioTalents Program was designed to provide undergraduate science and engineering students with training in biomanufacturing. The areas targeted by this educational program enhance their academic development, since these topics are not part of their traditional science and engineering curricula. The educational curriculum involved the process of producing a biomolecule from the genetic engineering of cells to the production of an especially targeted polypeptide, protein expression and purification, to quality control, and validation. This paper will report and describe the implementation details and outcomes of the first sessions of the program.
Keywords: Biomanufacturing curriculum, interdisciplinary learning, workforce development, industry-academia partnering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1962171 The Effect of Cooperation Teaching Method on Learning of Students in Primary Schools
Authors: Fereshteh Afkari, Davood Bagheri
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The effect of teaching method on learning assistance Dunn Review .The study, to compare the effects of collaboration on teaching mathematics learning courses, including writing, science, experimental girl students by other methods of teaching basic first paid and the amount of learning students methods have been trained to cooperate with other students with other traditional methods have been trained to compare. The survey on 100 students in Tehran that using random sampling ¬ cluster of girl students between the first primary selections was performed. Considering the topic of semi-experimental research methods used to practice the necessary information by questionnaire, examination questions by the researcher, in collaboration with teachers and view authority in this field and related courses that teach these must have been collected. Research samples to test and control groups were divided. Experimental group and control group collaboration using traditional methods of mathematics courses, including writing and experimental sciences were trained. Research results using statistical methods T is obtained in two independent groups show that, through training assistance will lead to positive results and student learning in comparison with traditional methods, will increase also led to collaboration methods increase skills to solve math lesson practice, better understanding and increased skill level of students in practical lessons such as science and has been writing.Keywords: method of teaching, learning, collaboration
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1621170 Genetic Programming: Principles, Applications and Opportunities for Hydrological Modelling
Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo
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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.
Keywords: Computational modelling, evolutionary algorithms, genetic programming, hydrological modelling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3315169 Communication Styles of Business Students: A Comparison of Four National Cultures
Authors: Tiina Brandt, Isaac Wanasika
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Culturally diverse global companies need to understand cultural differences between leaders and employees from different backgrounds. Communication is culturally contingent and has a significant impact on effective execution of leadership goals. The awareness of cultural variations related to communication and interactions will help leaders modify their own behavior, and consequently improve the execution of goals and avoid unnecessary faux pas. Our focus is on young adults that have experienced cultural integration, culturally diverse surroundings in schools and universities, and cultural travels. Our central research problem is to understand the impact of different national cultures on communication. We focus on four countries with distinct national cultures and spatial distribution. The countries are Finland, Indonesia, Russia and USA. Our sample is based on business students (n = 225) from various backgrounds in the four countries. Their responses of communication and leadership styles were analyzed using ANOVA and post-hoc test. Results indicate that culture impacts on communication behavior. Even young culturally-exposed adults with cultural awareness and experience demonstrate cultural differences in their behavior. Apparently, culture is a deeply seated trait that cannot be completely neutralized by environmental variables. Our study offers valuable input for leadership training programs and for expatriates when recognizing specific differences on leaders’ behavior due to culture.
Keywords: Culture, communication, Finland, Indonesia, Russia, USA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 635168 A Novel GNSS Integrity Augmentation System for Civil and Military Aircraft
Authors: Roberto Sabatini, Terry Moore, Chris Hill
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This paper presents a novel Global Navigation Satellite System (GNSS) Avionics Based Integrity Augmentation (ABIA) system architecture suitable for civil and military air platforms, including Unmanned Aircraft Systems (UAS). Taking the move from previous research on high-accuracy Differential GNSS (DGNSS) systems design, integration and experimental flight test activities conducted at the Italian Air Force Flight Test Centre (CSV-RSV), our research focused on the development of a novel approach to the problem of GNSS ABIA for mission- and safety-critical air vehicle applications and for multi-sensor avionics architectures based on GNSS. Detailed mathematical models were developed to describe the main causes of GNSS signal outages and degradation in flight, namely: antenna obscuration, multipath, fading due to adverse geometry and Doppler shift. Adopting these models in association with suitable integrity thresholds and guidance algorithms, the ABIA system is able to generate integrity cautions (predictive flags) and warnings (reactive flags), as well as providing steering information to the pilot and electronic commands to the aircraft/UAS flight control systems. These features allow real-time avoidance of safety-critical flight conditions and fast recovery of the required navigation performance in case of GNSS data losses. In other words, this novel ABIA system addresses all three cornerstones of GNSS integrity augmentation in mission- and safety-critical applications: prediction (caution flags), reaction (warning flags) and correction (alternate flight path computation).
Keywords: Global Navigation Satellite Systems (GNSS), Integrity Augmentation, Unmanned Aircraft Systems, Aircraft Based Augmentation, Avionics Based Integrity Augmentation, Safety-Critical Applications.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3217167 Construction 4.0: The Future of the Construction Industry in South Africa
Authors: Temidayo. O. Osunsanmi, Clinton Aigbavboa, Ayodeji Oke
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The construction industry is a renowned latecomer to the efficiency offered by the adoption of information technology. Whereas, the banking, manufacturing, retailing industries have keyed into the future by using digitization and information technology as a new approach for ensuring competitive gain and efficiency. The construction industry has yet to fully realize similar benefits because the adoption of ICT is still at the infancy stage with a major concentration on the use of software. Thus, this study evaluates the awareness and readiness of construction professionals towards embracing a full digitalization of the construction industry using construction 4.0. The term ‘construction 4.0’ was coined from the industry 4.0 concept which is regarded as the fourth industrial revolution that originated from Germany. A questionnaire was utilized for sourcing data distributed to practicing construction professionals through a convenience sampling method. Using SPSS v24, the hypotheses posed were tested with the Mann Whitney test. The result revealed that there are no differences between the consulting and contracting organizations on the readiness for adopting construction 4.0 concepts in the construction industry. Using factor analysis, the study discovers that adopting construction 4.0 will improve the performance of the construction industry regarding cost and time savings and also create sustainable buildings. In conclusion, the study determined that construction professionals have a low awareness towards construction 4.0 concepts. The study recommends an increase in awareness of construction 4.0 concepts through seminars, workshops and training, while construction professionals should take hold of the benefits of adopting construction 4.0 concepts. The study contributes to the roadmap for the implementation of construction industry 4.0 concepts in the South African construction industry.
Keywords: Building information technology, Construction 4.0, Industry 4.0, Smart Site.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5755166 A Control Model for Improving Safety and Efficiency of Navigation System Based on Reinforcement Learning
Authors: Almutasim Billa A. Alanazi, Hal S. Tharp
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Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.
Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 170165 The Implications of Technological Advancements on the Constitutional Principles of Contract Law
Authors: Laura Çami (Vorpsi), Xhon Skënderi
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In today's rapidly evolving technological landscape, the traditional principles of contract law are facing significant challenges. The emergence of new technologies, such as electronic signatures, smart contracts, and online dispute resolution mechanisms, is transforming the way contracts are formed, interpreted, and enforced. This paper examines the implications of these technological advancements on the constitutional principles of contract law. One of the fundamental principles of contract law is freedom of contract, which ensures that parties have the autonomy to negotiate and enter into contracts as they see fit. However, the use of technology in the contracting process has the potential to disrupt this principle. For example, online platforms and marketplaces often offer standard-form contracts, which may not reflect the specific needs or interests of individual parties. This raises questions about the equality of bargaining power between parties and the extent to which parties are truly free to negotiate the terms of their contracts. Another important principle of contract law is the requirement of consideration, which requires that each party receives something of value in exchange for their promise. The use of digital assets, such as cryptocurrencies, has created new challenges in determining what constitutes valuable consideration in a contract. Due to the ambiguity in this area, disagreements about the legality and enforceability of such contracts may arise. Furthermore, the use of technology in dispute resolution mechanisms, such as online arbitration and mediation, may raise concerns about due process and access to justice. The use of algorithms and artificial intelligence to determine the outcome of disputes may also raise questions about the impartiality and fairness of the process. Finally, it should be noted that there are many different and complex effects of technical improvements on the fundamental constitutional foundations of contract law. As technology continues to evolve, it will be important for policymakers and legal practitioners to consider the potential impacts on contract law and to ensure that the principles of fairness, equality, and access to justice are preserved in the contracting process.
Keywords: Technological advancements, constitutional principles, contract law, smart contracts, online dispute resolution, freedom of contract.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 193164 Critical Assessment of Scoring Schemes for Protein-Protein Docking Predictions
Authors: Dhananjay C. Joshi, Jung-Hsin Lin
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Protein-protein interactions (PPI) play a crucial role in many biological processes such as cell signalling, transcription, translation, replication, signal transduction, and drug targeting, etc. Structural information about protein-protein interaction is essential for understanding the molecular mechanisms of these processes. Structures of protein-protein complexes are still difficult to obtain by biophysical methods such as NMR and X-ray crystallography, and therefore protein-protein docking computation is considered an important approach for understanding protein-protein interactions. However, reliable prediction of the protein-protein complexes is still under way. In the past decades, several grid-based docking algorithms based on the Katchalski-Katzir scoring scheme were developed, e.g., FTDock, ZDOCK, HADDOCK, RosettaDock, HEX, etc. However, the success rate of protein-protein docking prediction is still far from ideal. In this work, we first propose a more practical measure for evaluating the success of protein-protein docking predictions,the rate of first success (RFS), which is similar to the concept of mean first passage time (MFPT). Accordingly, we have assessed the ZDOCK bound and unbound benchmarks 2.0 and 3.0. We also createda new benchmark set for protein-protein docking predictions, in which the complexes have experimentally determined binding affinity data. We performed free energy calculation based on the solution of non-linear Poisson-Boltzmann equation (nlPBE) to improve the binding mode prediction. We used the well-studied thebarnase-barstarsystem to validate the parameters for free energy calculations. Besides,thenlPBE-based free energy calculations were conducted for the badly predicted cases by ZDOCK and ZRANK. We found that direct molecular mechanics energetics cannot be used to discriminate the native binding pose from the decoys.Our results indicate that nlPBE-based calculations appeared to be one of the promising approaches for improving the success rate of binding pose predictions.
Keywords: protein-protein docking, protein-protein interaction, molecular mechanics energetics, Poisson-Boltzmann calculations
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1788163 Pilot Study on the Impact of VLE on Mathematical Concepts Acquisition within Secondary Education in England
Authors: Aaron A. R. Nwabude
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The research investigates the “impact of VLE on mathematical concepts acquisition of the special education needs (SENs) students at KS4 secondary education sector" in England. The overall aim of the study is to establish possible areas of difficulties to approach for above or below knowledge standard requirements for KS4 students in the acquisition and validation of basic mathematical concepts. A teaching period, in which virtual learning environment (Fronter) was used to emphasise different mathematical perception and symbolic representation was carried out and task based survey conducted to 20 special education needs students [14 actually took part]. The result shows that students were able to process information and consider images, objects and numbers within the VLE at early stages of acquisition process. They were also able to carry out perceptual tasks but with limiting process of different quotient, thus they need teacher-s guidance to connect them to symbolic representations and sometimes coach them through. The pilot study further indicates that VLE curriculum approaches for students were minutely aligned with mathematics teaching which does not emphasise the integration of VLE into the existing curriculum and current teaching practice. There was also poor alignment of vision regarding the use of VLE in realisation of the objectives of teaching mathematics by the management. On the part of teacher training, not much was done to develop teacher-s skills in the technical and pedagogical aspects of VLE that is in-use at the school. The classroom observation confirmed teaching practice will find a reliance on VLE as an enhancer of mathematical skills, providing interaction and personalisation of learning to SEN students.
Keywords: VLE, Mathematical Concepts Acquisition, PilotStudy, SENs, KS4, Education, Teacher
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1440162 Energy Efficient Plant Design Approaches: Case Study of the Sample Building of the Energy Efficiency Training Facilities
Authors: Idil Kanter Otcu
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Nowadays, due to the growing problems of energy supply and the drastic reduction of natural non-renewable resources, the development of new applications in the energy sector and steps towards greater efficiency in energy consumption are required. Since buildings account for a large share of energy consumption, increasing the structural density of buildings causes an increase in energy consumption. This increase in energy consumption means that energy efficiency approaches to building design and the integration of new systems using emerging technologies become necessary in order to curb this consumption. As new systems for productive usage of generated energy are developed, buildings that require less energy to operate, with rational use of resources, need to be developed. One solution for reducing the energy requirements of buildings is through landscape planning, design and application. Requirements such as heating, cooling and lighting can be met with lower energy consumption through planting design, which can help to achieve more efficient and rational use of resources. Within this context, rather than a planting design which considers only the ecological and aesthetic features of plants, these considerations should also extend to spatial organization whereby the relationship between the site and open spaces in the context of climatic elements and planting designs are taken into account. In this way, the planting design can serve an additional purpose. In this study, a landscape design which takes into consideration location, local climate morphology and solar angle will be illustrated on a sample building project.Keywords: Energy efficiency, landscape design, plant design, xeriscape landscape.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1792