Search results for: fuzzy sets
542 Implementing Service Learning in the Health Education Curriculum
Authors: Karen Butler
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Johnson C. Smith University, one of the nation’s oldest Historically Black Colleges and Universities, has a strong history of service learning and community service. We first integrated service learning and peer education into health education courses in the spring of 2000. Students enrolled in the classes served as peer educators for the semester. Since then, the program has evolved and expanded but remains an integral part of several courses. The purpose of this session is to describe our program in terms of development, successes, and obstacles, and feedback received. A detailed description of the service learning component in HED 235: Drugs and Drug Education and HED 337: Environmental Health will be provided. These classes are required of our Community Health majors but are also popular electives for students in other disciplines. Three sources of student feedback were used to evaluate and continually modify the component: the SIR II course evaluation, service learning reflection papers, and focus group interviews. Student feedback has been largely positive. When criticism was given, it was thoughtful and constructive – given in the spirit of making it better for the next group. Students consistently agreed that the service learning program increased their awareness of pertinent health issues; that both the service providers and service recipients benefited from the project; and that the goals/issues targeted by the service learning component fit the objectives of the course. Also, evidence of curriculum and learning enhancement was found in the reflection papers and focus group sessions. Service learning sets up a win-win situation. It provides a way to respond to campus and community health needs while enhancing the curriculum, as students learn more by doing things that benefit the health and wellness of others. Service learning is suitable for any health education course and any target audience would welcome the effort.Keywords: black colleges, community health, health education, service learning
Procedia PDF Downloads 340541 Flow-Oriented Incentive Spirometry in the Reversal of Diaphragmatic Dysfunction in Bariatric Surgery Postoperative Period
Authors: Eli Maria Forti-Pazzianotto, Carolina Moraes Da Costa, Daniela Faleiros Berteli Merino, Maura Rigoldi Simões Da Rocha, Irineu Rasera-Junior
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There is no conclusive evidence to support the use of one type or brand of incentive espirometry over others. The decision as to which equipment is best, have being based on empirical assessment of patient acceptance, ease of use, and cost. The aim was to evaluate the effects of use of two methodologies of breathing exercises, performed by flow-oriented incentive spirometry, in the reversal of diaphragmatic dysfunction in postoperative bariatric surgery. 38 morbid obese women were selected. Respiratory muscle strength was evaluated through the nasal inspiratory pressure (NIP), and the respiratory muscles endurance, through incremental test by measurement of sustained maximal inspiratory pressure (SMIP). They were randomized in 2 groups: 1- Respiron® Classic (RC) the inspirations were slow, deep and sustained for as long as possible (5 sec). 2- Respiron® Athletic1 (RA1) - the inspirations were explosive, quick and intense, raising balls by the explosive way. 6 sets of 15 repetitions with intervals of 30 to 60 seconds were performed in groups. At the end of the intervention program (second PO), the volunteers were reevaluated. The groups were homogeneous with regard to initial assessment. However on reevaluating there was a significant decline of the variable PIN (p= < 0.0001) and SMIP (p=0.0004) in RC. In the RA1 group there was a maintenance of SMIP (p=0.5076) after surgery. The use of the Respiron Athletic 1, as well as the methodology of application used, can contribute positively to preserve the inspiratory muscle endurance and improve the diaphragmatic dysfunction in postoperative period.Keywords: bariatric surgery, incentive spirometry, respiratory muscle, physiotherapy
Procedia PDF Downloads 373540 Development of IDF Curves for Precipitation in Western Watershed of Guwahati, Assam
Authors: Rajarshi Sharma, Rashidul Alam, Visavino Seleyi, Yuvila Sangtam
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The Intensity-Duration-Frequency (IDF) relationship of rainfall amounts is one of the most commonly used tools in water resources engineering for planning, design and operation of water resources project, or for various engineering projects against design floods. The establishment of such relationships was reported as early as in 1932 (Bernard). Since then many sets of relationships have been constructed for several parts of the globe. The objective of this research is to derive IDF relationship of rainfall for western watershed of Guwahati, Assam. These relationships are useful in the design of urban drainage works, e.g. storm sewers, culverts and other hydraulic structures. In the study, rainfall depth for 10 years viz. 2001 to 2010 has been collected from the Regional Meteorological Centre Borjhar, Guwahati. Firstly, the data has been used to construct the mass curve for duration of more than 7 hours rainfall to calculate the maximum intensity and to form the intensity duration curves. Gumbel’s frequency analysis technique has been used to calculate the probable maximum rainfall intensities for a period of 2 yr, 5 yr, 10 yr, 50 yr, 100 yr from the maximum intensity. Finally, regression analysis has been used to develop the intensity-duration-frequency (IDF) curve. Thus, from the analysis the values for the constants ‘a’,‘b’ &‘c’ have been found out. The values of ‘a’ for which the sum of the squared deviation is minimum has been found out to be 40 and when the corresponding value of ‘c’ and ‘b’ for the minimum squared deviation of ‘a’ are 0.744 and 1981.527 respectively. The results obtained showed that in all the cases the correlation coefficient is very high indicating the goodness of fit of the formulae to estimate IDF curves in the region of interest.Keywords: intensity-duration-frequency relationship, mass curve, regression analysis, correlation coefficient
Procedia PDF Downloads 244539 Space Weather and Earthquakes: A Case Study of Solar Flare X9.3 Class on September 6, 2017
Authors: Viktor Novikov, Yuri Ruzhin
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The studies completed to-date on a relation of the Earth's seismicity and solar processes provide the fuzzy and contradictory results. For verification of an idea that solar flares can trigger earthquakes, we have analyzed a case of a powerful surge of solar flash activity early in September 2017 during approaching the minimum of 24th solar cycle was accompanied by significant disturbances of space weather. On September 6, 2017, a group of sunspots AR2673 generated a large solar flare of X9.3 class, the strongest flare over the past twelve years. Its explosion produced a coronal mass ejection partially directed towards the Earth. We carried out a statistical analysis of the catalogs of earthquakes USGS and EMSC for determination of the effect of solar flares on global seismic activity. New evidence of earthquake triggering due to the Sun-Earth interaction has been demonstrated by simple comparison of behavior of Earth's seismicity before and after the strong solar flare. The global number of earthquakes with magnitude of 2.5 to 5.5 within 11 days after the solar flare has increased by 30 to 100%. A possibility of electric/electromagnetic triggering of earthquake due to space weather disturbances is supported by results of field and laboratory studies, where the earthquakes (both natural and laboratory) were initiated by injection of electrical current into the Earth crust. For the specific case of artificial electric earthquake triggering the current density at a depth of earthquake, sources are comparable with estimations of a density of telluric currents induced by variation of space weather conditions due to solar flares. Acknowledgment: The work was supported by RFBR grant No. 18-05-00255.Keywords: solar flare, earthquake activity, earthquake triggering, solar-terrestrial relations
Procedia PDF Downloads 143538 A Quinary Coding and Matrix Structure Based Channel Hopping Algorithm for Blind Rendezvous in Cognitive Radio Networks
Authors: Qinglin Liu, Zhiyong Lin, Zongheng Wei, Jianfeng Wen, Congming Yi, Hai Liu
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The multi-channel blind rendezvous problem in distributed cognitive radio networks (DCRNs) refers to how users in the network can hop to the same channel at the same time slot without any prior knowledge (i.e., each user is unaware of other users' information). The channel hopping (CH) technique is a typical solution to this blind rendezvous problem. In this paper, we propose a quinary coding and matrix structure-based CH algorithm called QCMS-CH. The QCMS-CH algorithm can guarantee the rendezvous of users using only one cognitive radio in the scenario of the asynchronous clock (i.e., arbitrary time drift between the users), heterogeneous channels (i.e., the available channel sets of users are distinct), and symmetric role (i.e., all users play a same role). The QCMS-CH algorithm first represents a randomly selected channel (denoted by R) as a fixed-length quaternary number. Then it encodes the quaternary number into a quinary bootstrapping sequence according to a carefully designed quaternary-quinary coding table with the prefix "R00". Finally, it builds a CH matrix column by column according to the bootstrapping sequence and six different types of elaborately generated subsequences. The user can access the CH matrix row by row and accordingly perform its channel, hoping to attempt rendezvous with other users. We prove the correctness of QCMS-CH and derive an upper bound on its Maximum Time-to-Rendezvous (MTTR). Simulation results show that the QCMS-CH algorithm outperforms the state-of-the-art in terms of the MTTR and the Expected Time-to-Rendezvous (ETTR).Keywords: channel hopping, blind rendezvous, cognitive radio networks, quaternary-quinary coding
Procedia PDF Downloads 91537 Copper Price Prediction Model for Various Economic Situations
Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin
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Copper is an essential raw material used in the construction industry. During the year 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war, which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two ANN-LSTM price prediction models, using Python, that can forecast the average monthly copper prices traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022, and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices and economic indicators of the three major exporting countries of copper, depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-Month prediction model is better than the 1-Month prediction model, but still, both models can act as predicting tools for diverse economic situations.Keywords: copper prices, prediction model, neural network, time series forecasting
Procedia PDF Downloads 113536 Molecular Characterization of Polyploid Bamboo (Dendrocalamus hamiltonii) Using Microsatellite Markers
Authors: Rajendra K. Meena, Maneesh S. Bhandari, Santan Barthwal, Harish S. Ginwal
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Microsatellite markers are the most valuable tools for the characterization of plant genetic resources or population genetic analysis. Since it is codominant and allelic markers, utilizing them in polyploid species remained doubtful. In such cases, the microsatellite marker is usually analyzed by treating them as a dominant marker. In the current study, it has been showed that despite losing the advantage of co-dominance, microsatellite markers are still a powerful tool for genotyping of polyploid species because of availability of large number of reproducible alleles per locus. It has been studied by genotyping of 19 subpopulations of Dendrocalamus hamiltonii (hexaploid bamboo species) with 17 polymorphic simple sequence repeat (SSR) primer pairs. Among these, ten primers gave typical banding pattern of microsatellite marker as expected in diploid species, but rest 7 gave an unusual pattern, i.e., more than two bands per locus per genotype. In such case, genotyping data are generally analyzed by considering as dominant markers. In the current study, data were analyzed in both ways as dominant and co-dominant. All the 17 primers were first scored as nonallelic data and analyzed; later, the ten primers giving standard banding patterns were analyzed as allelic data and the results were compared. The UPGMA clustering and genetic structure showed that results obtained with both the data sets are very similar with slight variation, and therefore the SSR marker could be utilized to characterize polyploid species by considering them as a dominant marker. The study is highly useful to widen the scope for SSR markers applications and beneficial to the researchers dealing with polyploid species.Keywords: microsatellite markers, Dendrocalamus hamiltonii, dominant and codominant, polyploids
Procedia PDF Downloads 144535 The Use of the Limit Cycles of Dynamic Systems for Formation of Program Trajectories of Points Feet of the Anthropomorphous Robot
Authors: A. S. Gorobtsov, A. S. Polyanina, A. E. Andreev
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The movement of points feet of the anthropomorphous robot in space occurs along some stable trajectory of a known form. A large number of modifications to the methods of control of biped robots indicate the fundamental complexity of the problem of stability of the program trajectory and, consequently, the stability of the control for the deviation for this trajectory. Existing gait generators use piecewise interpolation of program trajectories. This leads to jumps in the acceleration at the boundaries of sites. Another interpolation can be realized using differential equations with fractional derivatives. In work, the approach to synthesis of generators of program trajectories is considered. The resulting system of nonlinear differential equations describes a smooth trajectory of movement having rectilinear sites. The method is based on the theory of an asymptotic stability of invariant sets. The stability of such systems in the area of localization of oscillatory processes is investigated. The boundary of the area is a bounded closed surface. In the corresponding subspaces of the oscillatory circuits, the resulting stable limit cycles are curves having rectilinear sites. The solution of the problem is carried out by means of synthesis of a set of the continuous smooth controls with feedback. The necessary geometry of closed trajectories of movement is obtained due to the introduction of high-order nonlinearities in the control of stabilization systems. The offered method was used for the generation of trajectories of movement of point’s feet of the anthropomorphous robot. The synthesis of the robot's program movement was carried out by means of the inverse method.Keywords: control, limits cycle, robot, stability
Procedia PDF Downloads 331534 Importance of Flexibility Training for Older Adults: A Narrative Review
Authors: Andrej Kocjan
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Introduction: Mobility has been shown to play an important role of health and quality of life among older adults. Falls, which are often related to decreased mobility, as well as to neuromuscular deficits, represent the most common injury among older adults. Fall risk has been shown to increase with reduced lower extremity flexibility. The aim of the paper is to assess the importance of flexibility training on joint range of motion and functional performance among elderly population. Methods: We performed literature research on PubMed and evaluated articles published until 2000. The articles found in the search strategy were also added. The population of interest included older adults (≥ 65 years of age). Results: Flexibility training programs still represent an important part of several rehabilitation programs. Static stretching and proprioceptive neuromuscular facilitation are the most frequently used techniques to improve the length of the muscle-tendon complex. Although the effectiveness of type of stretching seems to be related to age and gender, static stretching is a more appropriate technique to enhance shoulder, hip, and ankle range of motion in older adults. Stretching should be performed in multiple sets with holds of more than 60 seconds for a single muscle group. Conclusion: The literature suggests that flexibility training is an effective method to increase joint range of motion in older adults. In the light of increased functional outcome, activities such as strengthening, balance, and aerobic exercises should be incorporated into a training program for older people. Due to relatively little published literature, it is still not possible to prescribe detailed recommendations regarding flexibility training for older adults.Keywords: elderly, exercise, flexibility, falls
Procedia PDF Downloads 186533 An Exploration of the Place of Buddhism in the Tham Luang Cave Rescue and Its Aftermath
Authors: Hamish de Nett
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On 23rd June 2018, twelve young footballers from the Wild Boar Academy and their coach went to explore the Tham Luang cave in the Doi Nang Non mountain range in Chiang Rai Province, Northern Thailand. Whilst they were inside the cave, monsoon rains hit, and the complex became partially flooded. In the following days, Thai Navy SEALs and an international team of expert divers assembled at the cave complex in order to rescue the boys. Although it was only marginally reported in the Western press, Buddhism and ritual activities played a major role in the rescue and its aftermath. This paper utilises numerous news articles and books written by reporters who covered the cave rescue to uncover what the place of Buddhism was in the Tham Luang cave rescue. This paper initially sets out the development of Thai Buddhism and the Thai nation state, paying particular note to the tension in Thai Buddhism between Buddhism as it is popularly practised and normative, state-favoured Buddhism. Secondly, this paper demonstrates that, during the Tham Luang cave rescue, Buddhism helped people cope with the disaster, provided an explanation for its occurrence, and allowed bystanders some efficacy in the process. Thirdly, this paper discusses how Buddhism helped people to give thanks after the rescue, achieve reconciliation, and gain closure. Finally, this paper analyses how the government and the political sphere utilised Buddhism during the rescue. The conclusion reached is that the Buddhism practiced during the Tham Luang cave rescue and its aftermath is representative of the wider tension between popular Buddhism and normative state-favoured Buddhism that is currently present within Thai Buddhism and has been for centuries.Keywords: cave rescue, contemporary Buddhism, lived religion, Thai Buddhism, Tham Luang cave rescue
Procedia PDF Downloads 129532 Advances of Image Processing in Precision Agriculture: Using Deep Learning Convolution Neural Network for Soil Nutrient Classification
Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine
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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.Keywords: convolution, feature extraction, image analysis, validation, precision agriculture
Procedia PDF Downloads 316531 A Fact-Finding Analysis on the Expulsions Made under Title 42 in Us
Authors: Avi Shrivastava
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Title 42, an emergency health decree, has forced the federal authorities to turn away asylum seekers and all other border crossers since last year. When Title 42 was first deployed in immigration detention centers, where many migrants are held when they arrive at the U.S.-Mexico border, the Trump administration embraced it as a strategy. Expulsions Policy and New Border Challenges will be examined in regard to Title 42 concerns. Humanitarian measures for refugees arriving at the US-Mexico border are the focus of this article. To a large extent, this article addresses the implications of the United States' use of Title 42 in expelling refugees and the possible ramifications of doing away with it. A secondary data collecting strategy was used to gather the information for this study, allowing researchers to examine a large number of previously collected data sets. Information about Title 42 may be found in a variety of places, such as scholarly publications, newspapers, books, and the internet. The inquiry employed qualitative and explanatory research approaches. The claim that 1.7 million individuals were forced to leave the country as a result of it was withdrawn. Since CBP and ICE were limited in their ability to process deportees, it employed a very random patchwork technique in selecting the expelled individuals. As a consequence, repeat offenders, particularly those who were single, got a reduced punishment. The government will be compelled to focus on long-overdue but vital border enhancements if expulsions are halted. Title 42 provisions may help expedite the processing of asylum and other types of humanitarian relief. The government is prepared for an increase in arrivals, but ending the program would lead to a return to arrival levels seen during the Title 42 period.Keywords: migrants, refugees, title 42, medical, trump administration
Procedia PDF Downloads 87530 Empirical Examination of High Performance Work System, Organizational Commitment and Organizational Citizen Behavior: A Mediation of Model of Vietnam Organizations
Authors: Giang Vu, Duong Nguyen, Yuan-Ling Chen
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Vietnam is a fast developing country with highly economic growth, and Vietnam organizations strive to utilize high performance work system (HPWS) in reinforcing employee in-role performance. HPWS, a bundle of human resource (HR) practices, are composed of eight sets of HR practices, namely selective staffing, extensive training, internal mobility, employment security, clear job description, result-oriented appraisal, incentive reward, and participation. However, whether HPWS stimulate employee extra-role behaviors remains understudied in a booming economic context. In this study, we aim to investigate organizational citizenship behavior (OCB) in a Vietnam context and, as a central issue, disentangle how HPWS elicits in employee OCB. On the other hand, recently, a deliberation of so-called 'black-box' HPWS issue has explored the role of employee commitment, suggesting that organizational commitment is a compelling source of employee OCB. We draw upon social exchange theory to predict that when employees perceive the organizational investment, like HPWS, in heightening their abilities, knowledge, and motivation, they are more likely to pay back with commitment; consequently, they will take initiatives in OCB. Hence, we hypothesize an individual level framework, in which organizational commitment mediates the positive relationship between HPWS and OCB. We collected data on HPWS, organizational commitment, OCB, and demographic variables, all at line managers of Vietnamese firms in Hanoi and Hochiminh. We conclude with research findings, implications, and future research suggestions.Keywords: high performance work system, organizational citizenship behavior, organizational commitment, Vietnam
Procedia PDF Downloads 310529 The role of Financial Development and Institutional Quality in Promoting Sustainable Development through Tourism Management
Authors: Hashim Zameer
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Effective tourism management plays a vital role in promoting sustainability and supporting ecosystems. A common principle that has been in practice over the years is “first pollute and then clean,” indicating countries need financial resources to promote sustainability. Financial development and the tourism management both seems very important to promoting sustainable development. However, without institutional support, it is very difficult to succeed. In this context, it seems prominently significant to explore how institutional quality, tourism development, and financial development could promote sustainable development. In the past, no research explored the role of tourism development in sustainable development. Moreover, the role of financial development, natural resources, and institutional quality in sustainable development is also ignored. In this regard, this paper aims to investigate the role of tourism development, natural resources, financial development, and institutional quality in sustainable development in China. The study used time-series data from 2000–2021 and employed the Bayesian linear regression model because it is suitable for small data sets. The robustness of the findings was checked using a quantile regression approach. The results reveal that an increase in tourism expenditures stimulates the economy, creates jobs, encourages cultural exchange, and supports sustainability initiatives. Moreover, financial development and institution quality have a positive effect on sustainable development. However, reliance on natural resources can result in negative economic, social, and environmental outcomes, highlighting the need for resource diversification and management to reinforce sustainable development. These results highlight the significance of financial development, strong institutions, sustainable tourism, and careful utilization of natural resources for long-term sustainability. The study holds vital insights for policy formulation to promote sustainable tourism.Keywords: sustainability, tourism development, financial development, institutional quality
Procedia PDF Downloads 83528 Optimization Modeling of the Hybrid Antenna Array for the DoA Estimation
Authors: Somayeh Komeylian
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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE
Procedia PDF Downloads 100527 Training the Competences for the 'Expert Teacher': A Framework of Skills for Teachers
Authors: Sofia Cramerotti, Angela Cattoni, Laura Biancato, Dario Ianes
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The recognition of specific standards for new professionals, within the teaching profile, is a necessary process in order to foster an innovative school vision in accordance with the change that school is experiencing. In line with the reform of the national education and training system and with the National Training Plan for teachers, our Research and Development department developed a training project based on a framework (Syllabus) of skills that each 'Expert Teacher' should master in order to fulfill what the different specific profiles request. The syllabus is a fundamental tool for a training process consistent with the teaching profiles, both to guide the to-become teachers entering in service and to provide the in-service teachers with a system of evaluation and improvement of their skills. According to the national and international literature about professional standards for teachers, we aggregated the skills of the syllabus in three macro areas: (1) Area of professional skills related to the teacher profile and their continuous training; (2) area of teaching skills related to the school innovation; (3) area of organizing skills related to school participation for its improvement. The syllabus is a framework that identifies and describes the skills of the expert teacher in all of their roles. However, the various skills take on different importance in the different profiles involved in the school; some of those skills are determining a role, others could be secondary. Therefore, the characterization of the different profiles is represented by suitably weighted skills sets. In this way, the same skill could differently characterize each profile. In the future, we hope that the skills development and training for the teacher could evolve in a skills development and training for the whole school staff ('Expert Team'). In this perspective, the school will, therefore, benefit from a solid team, in which the skills of the various profiles are all properly developed and well represented.Keywords: framework, skills, teachers, training
Procedia PDF Downloads 180526 A Deep Learning Approach to Detect Complete Safety Equipment for Construction Workers Based on YOLOv7
Authors: Shariful Islam, Sharun Akter Khushbu, S. M. Shaqib, Shahriar Sultan Ramit
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In the construction sector, ensuring worker safety is of the utmost significance. In this study, a deep learning-based technique is presented for identifying safety gear worn by construction workers, such as helmets, goggles, jackets, gloves, and footwear. The suggested method precisely locates these safety items by using the YOLO v7 (You Only Look Once) object detection algorithm. The dataset utilized in this work consists of labeled images split into training, testing and validation sets. Each image has bounding box labels that indicate where the safety equipment is located within the image. The model is trained to identify and categorize the safety equipment based on the labeled dataset through an iterative training approach. We used custom dataset to train this model. Our trained model performed admirably well, with good precision, recall, and F1-score for safety equipment recognition. Also, the model's evaluation produced encouraging results, with a [email protected] score of 87.7%. The model performs effectively, making it possible to quickly identify safety equipment violations on building sites. A thorough evaluation of the outcomes reveals the model's advantages and points up potential areas for development. By offering an automatic and trustworthy method for safety equipment detection, this research contributes to the fields of computer vision and workplace safety. The proposed deep learning-based approach will increase safety compliance and reduce the risk of accidents in the construction industry.Keywords: deep learning, safety equipment detection, YOLOv7, computer vision, workplace safety
Procedia PDF Downloads 68525 Reflecting Socio-Political Needs in Education Policy-Making: An Exploratory Study of Vietnam's Key Education Reforms (1945-2017)
Authors: Linh Tong
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This paper aims to contribute to the understanding of key education reforms in Vietnam from 1945 to 2017, which reflects an evolution of socio-political needs of the Socialist Republic of Vietnam throughout this period. It explores the contextual conditions, motivations and ambitions influencing the formation of the education reforms in Vietnam. It also looks, from an applied practical perspective, at the influence of politics on education policy-making. The research methodology includes a content analysis of curriculum designs proposed by the Ministry of Education and Training, relevant resolutions and executive orders passed by the National Assembly and the Prime Minister, as well as interviews with experts and key stakeholders. The results point to a particular configuration of factors which have been inspiring the shape and substance of these reforms and which have most certainly influenced their implementation. This configuration evolves from the immediate needs to erase illiteracy and cultivate socialist economic model at the beginning of Vietnam’s independence in 1945-1975, to a renewed urge to adopt market-oriented economy in 1986 and cautiously communicate with the outside world until 2000s, and to currently a demonstrated desire to fully integrate into the global economy and tackle with rising concerns about national security (the South China Sea Dispute), environmental sustainability, construction of a knowledge economy, and a rule-of-law society. Overall, the paper attempts to map Vietnam’s socio-political needs with the changing sets of goals and expected outcomes in teaching and learning methodologies and practices as introduced in Vietnamese key education reforms.Keywords: curriculum development, knowledge society, national security, politics of education policy-making, Vietnam's education reforms
Procedia PDF Downloads 152524 The Effect of Elastic-Resistance Training on Postural Control in Sedentary Women
Authors: Yagmur Kocaoglu, Nurtekin Erkmen
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The aim of this study was to determine effects of elastic resistance band training on body composition and postural control in sedentary women. Thirty-four sedentary females participated voluntarily for this study. Subjects' age was 21.88 ± 1.63 years, height was 161.50 ± 4.45 cm, and weight was 59.47 ± 7.03 kg. Participants were randomly placed into one of two groups (Experimental = 17, Control = 17). The elastic resistance training program lasted 8 weeks with 3 sessions per week. Experimental Group performed elastic resistance band training with red color for first 3 weeks, blue color for second 3 weeks and for last 2 weeks. The subjects carried out exercises 3 set, 10-15 repetitions with 15 seconds rest between exercises. The rest between sets was 30 seconds. The subjects underwent a standard warm-up for 10 minutes in every session. The elastic resistance training lasted 40 minutes for each session. After the training, all subjects performed a standard cool down for 10 minutes in each session. After and before 8 weeks training period, all subjects in experimental group and control group participated body composition and postural control measurements. Independent t-Test and Mann Whitney U Test were conducted to compare differences between experimental and control groups. Paired t-Test and Wilcoxon Z Test were used to compare differences between pre and posttests. There is no significant difference between pre and posttests in BMI (p>0.05). After the elastic resistance training, postural control scores and body fat significantly decreased in experimental group (p<0.05). In conclusion, it can be concluded that elastic resistance training improves postural control and body composition in sedentary women.Keywords: body composition, elastic resistance band, postural control, sedentary women
Procedia PDF Downloads 272523 Photographic Documentation of Archaeological Collections in the Grand Egyptian Museum
Authors: Sameh El Mahdy
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Recording and documenting archaeological collections, especially photographic documentation, is considered one of the very important matters that museums care about and give great priority, as photographic documentation is of great importance. We monitor some of them for example, Photographs of collectibles are considered evidence and an archival record that proves the condition of the collectibles at various stages. A photo of the possessions is placed on the paper record of the possessions registration. These photos are used in inventorying archaeological collections. These pictures are viewed by researchers and scholars interested in studying these collections. These images are used in advertising campaigns for museum displays of archaeological collections. The Grand Egyptian Museum is considered one of the museums that is a unique model in terms of establishing a specific system that is used when photographing archaeological collections. The Grand Egyptian Museum sets standards for the photos that are taken inside the Grand Egyptian Museum. We mention some of them for example, Pictures must be of high quality. It is necessary to set a color scale for the drawing in order to clarify the dimensions of the collectibles in the picture and also in order to clarify the natural colors of the collectibles without any additions. Putting the numbers of the collectibles in the pictures, especially the number of the Grand Egyptian Museum. To take a good photo of the artifacts in the Grand Egyptian Museum, there are many steps: (1) Create a good location, (2) How to handle the Artifacts. (3) Choose the best position for the artifact, (4) Make the light to create a good photo without shadows to make the photo represent all the artifact details. (5) Be sure of the camera settings, and their quality. All of these steps and other ones are the best criteria for taking the best photo, which helps us in the database to represent the details of the artifact in our interface.Keywords: grand egyptian museum, photographing, museum collections, registration and documentation
Procedia PDF Downloads 40522 Accurate Binding Energy of Ytterbium Dimer from Ab Initio Calculations and Ultracold Photoassociation Spectroscopy
Authors: Giorgio Visentin, Alexei A. Buchachenko
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Recent proposals to use Yb dimer as an optical clock and as a sensor for non-Newtonian gravity imply the knowledge of its interaction potential. Here, the ground-state Born-Oppenheimer Yb₂ potential energy curve is represented by a semi-analytical function, consisting of short- and long-range contributions. For the former, the systematic ab initio all-electron exact 2-component scalar-relativistic CCSD(T) calculations are carried out. Special care is taken to saturate diffuse basis set component with the atom- and bond-centered primitives and reach the complete basis set limit through n = D, T, Q sequence of the correlation-consistent polarized n-zeta basis sets. Similar approaches are used to the long-range dipole and quadrupole dispersion terms by implementing the CCSD(3) polarization propagator method for dynamic polarizabilities. Dispersion coefficients are then computed through Casimir-Polder integration. The semiclassical constraint on the number of the bound vibrational levels known for the ¹⁷⁴Yb isotope is used to scale the potential function. The scaling, based on the most accurate ab initio results, bounds the interaction energy of two Yb atoms within the narrow 734 ± 4 cm⁻¹ range, in reasonable agreement with the previous ab initio-based estimations. The resulting potentials can be used as the reference for more sophisticated models that go beyond the Born-Oppenheimer approximation and provide the means of their uncertainty estimations. The work is supported by Russian Science Foundation grant # 17-13-01466.Keywords: ab initio coupled cluster methods, interaction potential, semi-analytical function, ytterbium dimer
Procedia PDF Downloads 154521 Hydrological Response of the Glacierised Catchment: Himalayan Perspective
Authors: Sonu Khanal, Mandira Shrestha
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Snow and Glaciers are the largest dependable reserved sources of water for the river system originating from the Himalayas so an accurate estimate of the volume of water contained in the snowpack and the rate of release of water from snow and glaciers are, therefore, needed for efficient management of the water resources. This research assess the fusion of energy exchanges between the snowpack, air above and soil below according to mass and energy balance which makes it apposite than the models using simple temperature index for the snow and glacier melt computation. UEBGrid a Distributed energy based model is used to calculate the melt which is then routed by Geo-SFM. The model robustness is maintained by incorporating the albedo generated from the Landsat-7 ETM images on a seasonal basis for the year 2002-2003 and substrate map derived from TM. The Substrate file includes predominantly the 4 major thematic layers viz Snow, clean ice, Glaciers and Barren land. This approach makes use of CPC RFE-2 and MERRA gridded data sets as the source of precipitation and climatic variables. The subsequent model run for the year between 2002-2008 shows a total annual melt of 17.15 meter is generate from the Marshyangdi Basin of which 71% is contributed by the glaciers , 18% by the rain and rest being from the snow melt. The albedo file is decisive in governing the melt dynamics as 30% increase in the generated surface albedo results in the 10% decrease in the simulated discharge. The melt routed with the land cover and soil variables using Geo-SFM shows Nash-Sutcliffe Efficiency of 0.60 with observed discharge for the study period.Keywords: Glacier, Glacier melt, Snowmelt, Energy balance
Procedia PDF Downloads 455520 Prioritization Assessment of Housing Development Risk Factors: A Fuzzy Hierarchical Process-Based Approach
Authors: Yusuf Garba Baba
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The construction industry and housing subsector are fraught with risks that have the potential of negatively impacting on the achievement of project objectives. The success or otherwise of most construction projects depends to large extent on how well these risks have been managed. The recent paradigm shift by the subsector to use of formal risk management approach in contrast to hitherto developed rules of thumb means that risks must not only be identified but also properly assessed and responded to in a systematic manner. The study focused on identifying risks associated with housing development projects and prioritisation assessment of the identified risks in order to provide basis for informed decision. The study used a three-step identification framework: review of literature for similar projects, expert consultation and questionnaire based survey to identify potential risk factors. Delphi survey method was employed in carrying out the relative prioritization assessment of the risks factors using computer-based Analytical Hierarchical Process (AHP) software. The results show that 19 out of the 50 risks significantly impact on housing development projects. The study concludes that although significant numbers of risk factors have been identified as having relevance and impacting to housing construction projects, economic risk group and, in particular, ‘changes in demand for houses’ is prioritised by most developers as posing a threat to the achievement of their housing development objectives. Unless these risks are carefully managed, their effects will continue to impede success in these projects. The study recommends the adoption and use of the combination of multi-technique identification framework and AHP prioritization assessment methodology as a suitable model for the assessment of risks in housing development projects.Keywords: risk management, risk identification, risk analysis, analytic hierarchical process
Procedia PDF Downloads 118519 Developing a Green Strategic Management Model with regarding HSE-MS
Authors: Amin Padash, Gholam Reza Nabi Bid Hendi, Hassan Hoveidi
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Purpose: The aim of this research is developing a model for green management based on Health, Safety and Environmental Management System. An HSE-MS can be a powerful tool for organizations to both improve their environmental, health and safety performance, and enhance their business efficiency to green management. Model: The model is developed in this study can be used for industries as guidelines for implementing green management issue by considering Health, Safety and Environmental Management System. Case Study: The Pars Special Economic / Energy Zone Organization on behalf of Iran’s Petroleum Ministry and National Iranian Oil Company (NIOC) manages and develops the South and North oil and gas fields in the region. Methodology: This research according to objective is applied and based on implementing is descriptive and also prescription. We used technique MCDM (Multiple Criteria Decision-Making) for determining the priorities of the factors. Based on process approach the model consists of the following steps and components: first factors involved in green issues are determined. Based on them a framework is considered. Then with using MCDM (Multiple Criteria Decision-Making) algorithms (TOPSIS) the priority of basic variables are determined. The authors believe that the proposed model and results of this research can aid industries managers to implement green subjects according to Health, Safety and Environmental Management System in a more efficient and effective manner. Finding and conclusion: Basic factors involved in green issues and their weights can be the main finding. Model and relation between factors are the other finding of this research. The case is considered Petrochemical Company for promoting the system of ecological industry thinking.Keywords: Fuzzy-AHP method , green management, health, safety and environmental management system, MCDM technique, TOPSIS
Procedia PDF Downloads 411518 Wind Power Mapping and NPV of Embedded Generation Systems in Nigeria
Authors: Oluseyi O. Ajayi, Ohiose D. Ohijeagbon, Mercy Ogbonnaya, Ameh Attabo
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The study assessed the potential and economic viability of stand-alone wind systems for embedded generation, taking into account its benefits to small off-grid rural communities at 40 meteorological sites in Nigeria. A specific electric load profile was developed to accommodate communities consisting of 200 homes, a school and a community health centre. This load profile was incorporated within the distributed generation analysis producing energy in the MW range, while optimally meeting daily load demand for the rural communities. Twenty-four years (1987 to 2010) of wind speed data at a height of 10m utilized for the study were sourced from the Nigeria Meteorological Department, Oshodi. The HOMER® software optimizing tool was engaged for the feasibility study and design. Each site was suited to 3MW wind turbines in sets of five, thus 15MW was designed for each site. This design configuration was adopted in order to easily compare the distributed generation system amongst the sites to determine their relative economic viability in terms of life cycle cost, as well as levelised cost of producing energy. A net present value was estimated in terms of life cycle cost for 25 of the 40 meteorological sites. On the other hand, the remaining sites yielded a net present cost; meaning the installations at these locations were not economically viable when utilizing the present tariff regime for embedded generation in Nigeria.Keywords: wind speed, wind power, distributed generation, cost per kilowatt-hour, clean energy, Nigeria
Procedia PDF Downloads 397517 Omni-Modeler: Dynamic Learning for Pedestrian Redetection
Authors: Michael Karnes, Alper Yilmaz
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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition
Procedia PDF Downloads 76516 Assessing the Seed Yield of Some Varieties of Sesame (Sesami indicum) Under Disease Condition (Cercospora Leaf Spot) Caused by (Cercospora sesami, Zimm) and Identifying Disease Resistant Varieties
Authors: P. S. Akami, H. Nahunnaro, A. Zubainatu
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Cercospora leaf spot (Cercospora sesami. Zimm) has been identified as one of the most prevalent diseases, posing serious constraints to sesame production in producing areas. Two sets of experiments were carried out. The first and second experiments were conducted in the Modibbo Adama University of Technology Yola at the Crop Production and Horticulture and Plant Science Departments, respectively. The field experiment was carried out using a Randomized Complete Block Design and was replicated three times on a plot size of 4m x 5m with four sesame varieties and three Mancob-M fungicide levels (0g, 2g and 4g) to give a total of Twelve treatments. The laboratory experiment involved the isolation of the pathogens from diseased leaves with symptoms of Cercospora leaf spot, which was identified as Cercospora sesami. Data collected were subjected to analysis of variance for a randomized complete block design using SAS (1999) statistical package. The treatment means that are significantly different were separated using the Least Significant Difference at P=0.05. The result revealed that 4g Mancob M recorded the lowest mean value for disease incidence and severity at 8WAS, which was 90.30% and 35.60%, respectively, while the control (0g) recorded the highest mean value for disease incidence and severity at 90.30% and 59.80% respectively. Ex-Sudan recorded the lowest value of 720 kg/ha, while NCRIBEN 03 recorded the highest yield of 834 kg/ha-¹. For the concentrations, 2g recorded a higher yield of 843 kg/ha-¹ followed by 0g, which recorded 765 kg/ha-¹. Conclusively, Cercospora leaf spot of sesame was found to be prevalent. E8 has a higher resistance to the disease, while NCRIBEN 03 tends to be more susceptible. It is therefore recommended that further trials should be carried out using different varieties in different locations.Keywords: disease, evaluation, prevalence, treatment, resistance
Procedia PDF Downloads 93515 Effect of Different Levels of Fibrolytic Enzyme on Feed Digestibility and Production Performance in Lactating Dairy Cows
Authors: Hazrat Salman Sidique, Muhammad Tahir Khan, Haq Aman Ullah, Muhammad Mobashar, Muhammad Ishtiaq Sohail Mehmood
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The poor quality conventional feed for the livestock production in Pakistan are wheat straw, tops of sugar cane and tree leaves. To enhance the nutritive value of feed, this study focused on investigating the effects of fibrolytic enzyme (Fibrozyme®, Alltech Inc. Company, USA) at different levels i.e. 0, 5, 10, and 15g/kg of total mix ration on feed intake, digestibility, milk yield and composition, and economics of the ration in Holstein Friesians cows. Twelve Holstein Friesians cows of almost the same age, and lactation stage were randomly allocated into 4 equal groups i.e. A, B, C, and D. Four experimental rations supplemented with Fibrozyme® 0g, 5g, 10g, and 15g/Kg of total mix ration were assigned to these sets correspondingly. The dry matter intake was linearly and significantly (P<0.05) improved. A significant effect of Fibrozyme® was observed for organic matter digestibility, ether extract digestibility, crude fiber digestibility, nitrogen free extract digestibility, and acid detergent fiber digestibility while the results were statistically non-significant for crude protein digestibility, neutral detergent fiber digestibility, and ash digestibility. Milk yield and composition except fat were significantly (P<0.05) increased in all Fibrozyme® treated groups. This study concludes that supplementation of Fibrozyme® at the rate of 15g/Kg total mix ration improved the dry matter intake, nutrients digestibility, and milk production and constituents like protein, lactose, and solid not fat. Therefore, treatment of total mix ration with Fibrozyme® was desirably reasonable and profitable.Keywords: digestibility, fibrozyme, TMR, digestibility, lactating cow
Procedia PDF Downloads 109514 Effect of the Vertical Pressure on the Electrical Behaviour of the Micro-Copper Polyurethane Composite Films
Authors: Saeid Mehvari, Yolanda Sanchez-Vicente, Sergio González Sánchez, Khalid Lafdi
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Abstract- Materials with a combination of transparency, electrical conductivity, and flexibility are required in the growing electronic sector. In this research, electrically conductive and flexible films have been prepared. These composite films consist of dispersing micro-copper particles into polyurethane (PU) matrix. Two sets of samples were made using both spin coating technique (sample thickness lower than 30 μm) and materials casting (sample thickness lower than 100 μm). Copper concentrations in the PU matrix varied from 0.5 to 20% by volume. The dispersion of micro-copper particles into polyurethane (PU) matrix were characterised using optical microscope and scanning electron microscope. The electrical conductivity measurement was carried out using home-made multimeter set up under pressures from 1 to 20 kPa through thickness and in plane direction. It seems that samples made by casting were not conductive. However, the sample made by spin coating shows through-thickness conductivity when they are under pressure. The results showed that spin-coated films with higher concentration of 2 vol. % of copper displayed a significant increase in the conductivity value, known as percolation threshold. The maximum conductivity of 7.2 × 10-1 S∙m-1 was reached at concentrations of filler with 20 vol. % at 20kPa. A semi-empirical model with adjustable coefficients was used to fit and predict the electrical behaviour of composites. For the first time, the finite element method based on the representative volume element (FE-RVE) was successfully used to predict their electrical behaviour under applied pressures. Keywords: electrical conductivity, micro copper, numerical simulation, percolation threshold, polyurethane, RVE model
Procedia PDF Downloads 197513 To Design an Architectural Model for On-Shore Oil Monitoring Using Wireless Sensor Network System
Authors: Saurabh Shukla, G. N. Pandey
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In recent times, oil exploration and monitoring in on-shore areas have gained much importance considering the fact that in India the oil import is 62 percent of the total imports. Thus, architectural model like wireless sensor network to monitor on-shore deep sea oil well is being developed to get better estimate of the oil prospects. The problem we are facing nowadays that we have very few restricted areas of oil left today. Countries like India don’t have much large areas and resources for oil and this problem with most of the countries that’s why it has become a major problem when we are talking about oil exploration in on-shore areas also the increase of oil prices has further ignited the problem. For this the use of wireless network system having relative simplicity, smallness in size and affordable cost of wireless sensor nodes permit heavy deployment in on-shore places for monitoring oil wells. Deployment of wireless sensor network in large areas will surely reduce the cost it will be very much cost effective. The objective of this system is to send real time information of oil monitoring to the regulatory and welfare authorities so that suitable action could be taken. This system architecture is composed of sensor network, processing/transmission unit and a server. This wireless sensor network system could remotely monitor the real time data of oil exploration and monitoring condition in the identified areas. For wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behaviour is important and location is critical. In this system a communication is done between the server and remotely placed sensors. The server gives the real time oil exploration and monitoring conditions to the welfare authorities.Keywords: sensor, wireless sensor network, oil, sensor, on-shore level
Procedia PDF Downloads 446