Search results for: ERA-5 analysis data

Authors: Sonika Raj, Amarjeet Singh, Vijay Lakshmi Sharma

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Introduction: In 21st century, due to revolution in Information and Communication Technologies (ICTs), there has been phenomenal development in quality and quantity of knowledge in the field of medical science. So, the access to relevant information to physicians is critical to the delivery of effective healthcare services to patients. The study was conducted to assess the information needs and attitudes of the medical professionals; to determine the sources and channels of information used by them; to ascertain the current usage of ICTs and the barriers faced by them in utilization of ICTs in health information access. Methodology: This descriptive cross-sectional study was carried in 2015 on hundred medical professionals working in public and private sectors of Chandigarh. The study used both quantitative and qualitative method for data collection. A semi structured questionnaire and interview schedule was used to collect data on information seeking needs, access to ICTs and barriers to healthcare information access. Five Data analysis was done using SPSS-16 and qualitative data was analyzed using thematic approach. Results: The most preferred sources to access healthcare information were internet (85%), trainings (61%) and communication with colleagues (57%). They wanted information on new drug therapy and latest developments in respective fields. All had access to computer with but almost half assessed their computer knowledge as average and only 3% had received training regarding usage. Educational status (p=0.004), place of work (p=0.004), number of years in job (p=0.004) and sector of job (p=0.04) of doctors were found to be significantly associated with their active search for information. The major themes that emerged from in-views were need; types and sources of healthcare information; exchange of information among different levels of healthcare providers; usage of ICTs to obtain and share information; barriers to access of healthcare information and quality of health information materials and involvement in their development process Conclusion and Recommendations: The medical professionals need information in their in their due course of work. However, information needs of medical professionals were not being adequately met. There should be training of professional regarding internet skills and the course on bioinformatics should be incorporated in the curricula of medical students. The policy framework must be formulated that will encourage and promote the use of ICTs as tools for health information access and dissemination.

Keywords: health information, ICTs, medical professionals, qualitative

Procedia PDF Downloads 354

Authors: Fadil Elmenfi, Ahmed Gaibani

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This study investigates the role of gender in influencing public speaking anxiety. Questionnaire survey was administered to the samples of the study. Technique of correlation and descriptive analysis will be further applied to the data collected to determine the relationship between gender and public speaking anxiety. This study could serve as a guide to identify the effects of gender differences on public speaking anxiety and provide necessary advice on how to design a way of coping with or overcoming public speaking anxiety.

Keywords: across culture, communication, English language competence, gender, postgraduate students, speaking anxiety

Procedia PDF Downloads 565

Authors: Yi-Lin Chen, Sheng-Jou Hung, Tsunglin Liu

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Adaptive immune system recognizes a wide range of antigens via expressing a large number of structurally distinct T cell and B cell receptor genes. The distinct receptor genes arise from complex rearrangements called V(D)J recombination, and constitute the immune repertoire. A common method of profiling immune repertoire is via amplifying recombined receptor genes using multiple primers and high-throughput sequencing. This multiplex-PCR approach is efficient; however, the resulting repertoire can be distorted because of primer bias. To eliminate primer bias, 5’ RACE is an alternative amplification approach. However, the application of RACE approach is limited by its low efficiency (i.e., the majority of data are non-regular receptor sequences, e.g., containing intronic segments) and lack of the convenient tool for analysis. We propose a computational tool that can correctly identify non-regular receptor sequences in RACE data via aligning receptor sequences against the whole gene instead of only the exon regions as done in all other tools. Using our tool, the remaining regular data allow for an accurate profiling of immune repertoire. In addition, a RACE approach is improved to yield a higher fraction of regular T-cell receptor sequences. Finally, we quantify the degree of primer bias of a multiplex-PCR approach via comparing it to the RACE approach. The results reveal significant differences in frequency of VJ combination by the two approaches. Together, we provide a new experimental and computation pipeline for an unbiased profiling of immune repertoire. As immune repertoire profiling has many applications, e.g., tracing bacterial and viral infection, detection of T cell lymphoma and minimal residual disease, monitoring cancer immunotherapy, etc., our work should benefit scientists who are interested in the applications.

Keywords: immune repertoire, T-cell receptor, 5' RACE, high-throughput sequencing, sequence alignment

Procedia PDF Downloads 198

Authors: Mehrnoosh Abouzari, Shahrokh Sahraei

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Today, with the increase in quantity and quality and variety of crimes, the discussion of crime prevention has faced a serious challenge that human resources alone and with traditional methods will not be effective. One of the developments in the modern world is the presence of artificial intelligence in various fields, including criminal law. In fact, the use of artificial intelligence in criminal investigations and fighting crime is a necessity in today's world. The use of artificial intelligence is far beyond and even separate from other technologies in the struggle against crime. Second, its application in criminal science is different from the discussion of prevention and it comes to the prediction of crime. Crime prevention in terms of the three factors of the offender, the offender and the victim, following a change in the conditions of the three factors, based on the perception of the criminal being wise, and therefore increasing the cost and risk of crime for him in order to desist from delinquency or to make the victim aware of self-care and possibility of exposing him to danger or making it difficult to commit crimes. While the presence of artificial intelligence in the field of combating crime and social damage and dangers, like an all-seeing eye, regardless of time and place, it sees the future and predicts the occurrence of a possible crime, thus prevent the occurrence of crimes. The purpose of this article is to collect and analyze the studies conducted on the use of artificial intelligence in predicting and preventing crime. How capable is this technology in predicting crime and preventing it? The results have shown that the artificial intelligence technologies in use are capable of predicting and preventing crime and can find patterns in the data set. find large ones in a much more efficient way than humans. In crime prediction and prevention, the term artificial intelligence can be used to refer to the increasing use of technologies that apply algorithms to large sets of data to assist or replace police. The use of artificial intelligence in our debate is in predicting and preventing crime, including predicting the time and place of future criminal activities, effective identification of patterns and accurate prediction of future behavior through data mining, machine learning and deep learning, and data analysis, and also the use of neural networks. Because the knowledge of criminologists can provide insight into risk factors for criminal behavior, among other issues, computer scientists can match this knowledge with the datasets that artificial intelligence uses to inform them.

Keywords: artificial intelligence, criminology, crime, prevention, prediction

Procedia PDF Downloads 82

Authors: Somaye Ghafarpour, Kamran Yazdanbakhsh, Mohamad Reza Zarbakhsh, Simin Hosseinian, Samira Ghafarpour

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Unsatisfactory sleep quality is one of the most common complications of pregnancy, which can predispose mothers to postpartum depression, requiring implementing effective psychological interventions to prevent and modify behaviors accentuating sleep problems. This study was a randomized clinical controlled trial with a pre-test/post-test design aiming to investigate the effectiveness of sleep behavioral interventions during the third trimester of pregnancy on sleep quality and postpartum depression. A total of 50 pregnant mothers in the 26-30 weeks of pregnancy suffering from sleep problems (based on the score obtained from the Pittsburgh Sleep Questionnaire) were randomized into two groups (control and intervention, n= 25 per group). The data were collected using interviews, the Pittsburgh Sleep Quality Index (PSQI), and the Edinburgh Postnatal Depression Scale (EPDS) were used. The participants in the intervention group received eight 60-minute sessions of combinational training for behavioral therapy techniques. At the end of the intervention and four weeks after delivery, sleep quality and postpartum depression were evaluated. Considering that the Kolmogorov Smirnov test confirmed the normal distribution of the data, the independent t-test and analysis of covariance were used to analyze the data, showing that the behavioral interventions were effective on the overall sleep quality after delivery (p=0.001); however, no statistically significant effects were observed on postpartum depression, the sub-scales of sleep disorders, and daily functioning (p>0.05). Considering the potential effectiveness of behavioral interventions in improving sleep quality and alleviating insomnia symptoms, it is recommended to implement such measures as an effective intervention to prevent or treat these problems during prenatal and postnatal periods.

Keywords: behavioral interventions, sleep quality, postpartum depression, pregnancy, delivery

Procedia PDF Downloads 74

Authors: Prapoj Na Bangchang

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The research aimed to study the satisfaction of Suan Sunandha Rajabhat University students towards the university radio station which broadcasts in both analog on FM 97.25 MHz and online via the university website. The sample used in this study consists of undergraduate students year 1 to year 4 from 6 faculties i.e. Faculty of Education, Faculty of Humanities and Social Sciences, Faculty of Management Science and Faculty of Industrial Technology, and Faculty of Fine and Applied Arts totaling 200 students. The tools used for data collection is survey. Data analysis applied statistics that are percentage, mean and standard deviation. The results showed that Suan Sunandha Rajabhat University students were satisfied to the place of listening service, followed by channels of broadcasting that cover both analog signals on 97.25 MHz FM and online via the Internet. However, the satisfaction level of the content offered was very low. Most of the students want the station to improve the content. Entertainment content was requested the most, followed by sports content. The lowest satisfaction level is with the broadcasting quality through analog signal. Most students asked the station to improve on the issue. However, overall, Suan Sunandha Rajabhat University students were satisfied with the university radio station broadcasted online via the university website.

Keywords: satisfaction, students, radio station, Suan Sunandha Rajabhat University

Procedia PDF Downloads 273

Authors: Jelena Vucicevic

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Reliability analysis represents a very important task in different areas of work. In any industry, this is crucial for maintenance, efficiency, safety and monetary costs. There are ways to calculate reliability, unreliability, failure density and failure rate. In this paper, the results for the reliability of diesel generator fans were calculated through Extreme Value Theory. The Extreme Value Theory is not widely used in the engineering field. Its usage is well known in other areas such as hydrology, meteorology, finance. The significance of this theory is in the fact that unlike the other statistical methods it is focused on rare and extreme values, and not on average. It should be noted that this theory is not designed exclusively for extreme events, but for extreme values in any event. Therefore, this is a great opportunity to apply the theory and test if it could be applied in this situation. The significance of the work is the calculation of time to failure or reliability in a new way, using statistic. Another advantage of this calculation is that there is no need for technical details and it can be implemented in any part for which we need to know the time to fail in order to have appropriate maintenance, but also to maximize usage and minimize costs. In this case, calculations have been made on diesel generator fans but the same principle can be applied to any other part. The data for this paper came from a field engineering study of the time to failure of diesel generator fans. The ultimate goal was to decide whether or not to replace the working fans with a higher quality fan to prevent future failures. The results achieved in this method will show the approximation of time for which the fans will work as they should, and the percentage of probability of fans working more than certain estimated time. Extreme Value Theory can be applied not only for rare and extreme events, but for any event that has values which we can consider as extreme.

Keywords: extreme value theory, lifetime, reliability analysis, statistic, time to failure

Procedia PDF Downloads 329

Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim

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A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.

Keywords: butterfly valve, flow coefficient, automatic CFD analysis, FSI analysis

Procedia PDF Downloads 243

Authors: Ren Boyuan

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This study focuses on how the Character and Citizenship Education textbook in Singapore primary schools deliver preferred and desired qualities to students and therefore reveals how discourse in textbooks can facilitate and perpetuate certain social practices. In this way, this study also serves to encourage the critical thinking of textbook writers and school educators by unveiling the nuanced message through language use that facilitates the perpetuation of social practices in a society. In Singapore, Character and Citizenship Education is a compulsory subject for primary school students. Under the framework of 21st Century Competencies, Character and Citizenship Education in Singapore aims to help students thrive in this fast-changing world. The Singapore government is involved in the development of CCE curriculum in schools from primary schools to pre-university. Inevitably, the CCE curriculum is not free from ideological influences. This qualitative study utilizes Fairclough’s three-dimensional theory and his framework of three assumptions to analyze the Character and Citizenship Education textbook for Primary 1 and to reveal ideologies in this textbook. Data for the analysis in this study are the textual parts of the whole textbook for Primary 1 students as this book is used at the beginning of citizenship education in primary schools. It is significant because it promotes messages about CCE to the foundation years of a child's education. The findings of this study show that the four revealed ideologies, namely pragmatism, communitarianism, nationalism, and multiculturalism, are not only dated back in the national history but also updated and explained by the current demands for Singapore’s thriving and prosperity in a sustainable term. This study ends with a discussion of the implications of this study. By pointing out the ideologies in this textbook and how they are embedded in the discourse, this study may help teachers and textbook writers realize the possible political involvement in the book and therefore develop their recognition of the implicit influence of lexical choice on their teaching and writing. In addition, by exploring the ideologies in this book and comparing them with ideologies in past textbooks, this study helps researchers in this area on how language influences readers and reflects certain social demands.

Keywords: citizenship education, critical discourse analysis, sociolinguistics, textbook analysis

Procedia PDF Downloads 67

Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: M. Lobzhanidze, N. Damenia

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The article analyzes the current structural changes in the economy of Georgia, liberalization and integration processes of the economy. In accordance with this analysis, the peculiarities and the problems of youth employment are revealed. In the paper, the Georgian labor market and its contradictions are studied. Based on the analysis of materials, the socio-economic losses caused by the long-term and mass unemployment of young people are revealed, the objective and subjective circumstances of getting higher education are studied. The youth employment and unemployment rates are analyzed. Based on the research, the factors that increase unemployment are identified. According to the analysis of the youth employment, it has appeared that the unemployment share in the number of economically active population has increased in the younger age group. It demonstrates the high requirements of the labour market in terms of the quality of the workforce. Also, it is highlighted that young people are exposed to a highly paid job. The following research methods are applied in the presented paper: statistical (selection, grouping, observation, trend, etc.) and qualitative research (in-depth interview), as well as analysis, induction and comparison methods. The article presents the data by the National Statistics Office of Georgia and the Ministry of Agriculture of Georgia, policy documents of the Parliament of Georgia, scientific papers by Georgian and foreign scientists, analytical reports, publications and EU research materials on similar issues. The work estimates the students and graduates employment problems existing in the state development strategy and priorities. The measures to overcome the challenges are defined. The article describes the mechanisms of state regulation of youth employment and the ways of improving this regulatory base. As for major findings, it should be highlighted that the main problems are: lack of experience and incompatibility of youth qualification with the requirements of the labor market. Accordingly, it is concluded that the unemployment rate of young people in Georgia is increasing.

Keywords: migration of youth, youth employment, migration management, youth employment and unemployment

Procedia PDF Downloads 152

Authors: Sarma Binti Aralas

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The relationship between property rights and trade specialization is examined for developing and developed countries using panel data analysis. Property rights is measured using the international property rights index while trade specialization is measured using the comparative advantage index. Cross country differences in property rights are hypothesized to lead to differences in trade specialization. Based on the argument that a weak protection of natural resources implies greater trade in resource-intensive goods, developing countries with less defined property rights are hypothesized to have a comparative advantage in resource-based exports while countries with more defined property rights will not have an advantage in resource-intensive goods. Evidence suggests that developing countries with weaker environmental protection index but are rich in natural resources do specialize in the trade of resource-intensive goods. The finding suggests that institutional frameworks to increase the stringency of environmental protection of resources may be needed to diversify exports away from the trade of resource-intensive goods.

Keywords: environmental protection, panel data, renewable resources, trade specialization

Procedia PDF Downloads 452

Authors: Suzana Leitão Russo, Mayara Laysa de Oliveira Silva, José Augusto Andrade Filho, Vitor Hugo Simon

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Currently, seismic methods and prospecting methods are commonly applied in the oil industry and, according to the information reported every day; oil is a source of non-renewable energy. It is easier to understand why the ownership of areas of oil extraction is coveted by many nations. It is necessary to think about ways that will enable the maximization of oil production. The technique of spectral analysis can be used to analyze the behavior of the variables already defined in oil well the profile. The main objective is to verify the series dependence of variables, and to model the variables using the frequency domain to observe the model residuals.

Keywords: oil, well, spectral analysis, oil extraction

Procedia PDF Downloads 537

Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

Procedia PDF Downloads 160

Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

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Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.

Keywords: data acquisition system, DIALOG library, DIM library, FPGA, Qt framework, TCP/IP

Procedia PDF Downloads 323

Authors: Vanessa G. P. Severino, JOÃO Gabriel M. Junqueira, Michelle N. G. do Nascimento, Francisco W. B. Aquino, João B. Fernandes, Ana P. Terezan

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The scientific interest in analyzing VOCs represents a significant modern research field as a result of importance in most branches of the present life and industry. Therefore it is extremely important to investigate, identify and isolate volatile substances, since they can be used in different areas, such as food, medicine, cosmetics, perfumery, aromatherapy, pesticides, repellents and other household products through methods for extracting volatile constituents, such as solid phase microextraction (SPME), hydrodistillation (HD), solvent extraction (SE), Soxhlet extraction, supercritical fluid extraction (SFE), stream distillation (SD) and vacuum distillation (VD). The Chemometrics is an area of chemistry that uses statistical and mathematical tools for the planning and optimization of the experimental conditions, and to extract relevant chemical information multivariate chemical data. In this context, the focus of this work was the study of the chemical VOCs by SPME of the specie X. aromatica, in search of constituents that can be used in the industrial sector as well as in food, cosmetics and perfumery, since these areas industrial has a considerable role. In addition, by chemometric analysis, we sought to maximize the answers of this research, in order to search for the largest number of compounds. The investigation of flowers from X. aromatica in vitro and in alive mode proved consistent, but certain factors supposed influence the composition of metabolites, and the chemometric analysis strengthened the analysis. Thus, the study of the chemical composition of X. aromatica contributed to the VOCs knowledge of the species and a possible application.

Keywords: chemometrics, flowers, HS-SPME, Xylopia aromatica

Procedia PDF Downloads 367

Authors: Angelo I. Aquino, Luis Ma. T. Bo-ot

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We use the Homotopy Analysis Method (HAM) to solve the system of equations modeling the two-level system and extract results which will pinpoint to turbulent behavior. We look at multi-valued solutions as indicative of turbulence or turbulent-like behavior. We take dierent specic cases which result in multi-valued velocities. The solutions are in series form and application of HAM ensures convergence in some region.

Keywords: multivalued solutions, homotopy analysis method, two-level system, equation

Procedia PDF Downloads 596

Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 172

Authors: Alonso-Cañadas J., Galán-Valdivieso F., Saraite-Sariene L., García-Tabuyo M., Alonso-Morales N.

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Green Public Procurement (GPP) has recently gained attention in the academic and policy arenas since climate change has shown the need to be addressed by both private companies and public entities. Such growing interest motivates this article, aiming to explore the most influential journals, publishers, categories, and topics, as well as the recent trends and future research lines in GPP. Based on the Web of Science database, 578 articles from 2004 to February 2022 devoted to GPP are analyzed using Bibliometrix, an R-tool to perform bibliometric analysis, and Google’s Big Query and Data Studio. This article introduces a variety of findings. First, the most influential journals by far are “Journal of Cleaner Production” and “Sustainability,” differing in that the latter is open access while the former publishes via traditional subscription. This result also occurs regarding the main publishers (Elsevier and MDPI). These features lead us to split the sample into open-access journals and traditional journals to deepen into the similarities and differences between them, confirming that traditional journals exhibit a higher degree of influence in the literature than their open-access counterparts in terms of the number of documents, number of citations and impact (according to the H index). Second, this research also highlights the recent emergence of green-related terms (sustainable, environment) and, parallelly, the increase in categorizing GPP papers in “green” WoS categories, particularly since 2019. Finally, a number of related topics are emerging and will lead the research, such as food security, infrastructures, and implementation barriers of GPP.

Keywords: bibliometric analysis, green public procurement, open access, traditional journals

Procedia PDF Downloads 113

Authors: Yu Chen, Xiaoguang Yang, Lin Lin

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Traffic engineering construction is an important infrastructure for economic and social development. In the process of construction and operation, the ability to make a correct evaluation of the project's environmental impact appears to be crucial to the rational operation of existing transportation projects, the correct development of transportation engineering construction and the adoption of corresponding measures to scientifically carry out environmental protection work. Most of the existing research work on ecological and environmental impact assessment is limited to individual aspects of the environment and less to the overall evaluation of the environmental system; in terms of research conclusions, there are more qualitative analyses from the technical and policy levels, and there is a lack of quantitative research results and quantitative and operable evaluation models. In this paper, a comprehensive analysis of the ecological and environmental impacts of transportation construction projects is conducted, and factors such as the accessibility of data and the reliability of calculation results are comprehensively considered to extract indicators that can reflect the essence and characteristics. The qualitative evaluation indicators were screened using the expert review method, the qualitative indicators were measured using the fuzzy statistics method, the quantitative indicators were screened using the principal component analysis method, and the quantitative indicators were measured by both literature search and calculation. An environmental impact evaluation index system with the general objective layer, sub-objective layer and indicator layer was established, dividing the environmental impact of the transportation construction project into two periods: the construction period and the operation period. On the basis of the evaluation index system, the index weights are determined using the hierarchical analysis method, and the individual indicators to be evaluated are dimensionless, eliminating the influence of the original background and meaning of the indicators. Finally, the thesis uses the above research results, combined with the actual engineering practice, to verify the correctness and operability of the evaluation method.

Keywords: transportation construction projects, ecological and environmental impact, analysis and evaluation, indicator evaluation system

Procedia PDF Downloads 113

Authors: Delna Shroff

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Merchant shipping is an occupation with a high rate of fatal injuries caused by organizational accidents and maritime disasters. In most accident investigations, the leader’s actions are under scrutiny and point out the necessity to investigate the leader’s decisions in critical conditions. While several leadership studies have been carried out in the past, there is a tendency for most research to focus on holders of formal positions. The unit of analysis in most studies has been the ‘individual.’ A need is, therefore, felt to adopt a practice-based perspective of leadership, understand how leadership emerges to affect maritime safety. This paper explores the phenomenon of distributed leadership among seafarers more holistically. It further examines the role of one form of distributed leadership, that is, planfully aligned leadership in the emergency response of the team. A mixed design will be applied. In the first phase, the data gathered by way of semi-structured interviews will be used to explore the seafarer’s implicit understanding of leadership. The data will be used to develop a conceptual framework of distributed leadership, specific to the maritime context. This framework will be used to develop a simulation. Experimental design will be used to examine the relationship between planfully aligned leadership and emergency response of the team members during navigation. Findings show that planfully aligned leadership significantly and positively predicts the emergency response of team members. Planfully aligned leadership leads to a better emergency response of the team members as compared to authoritarian leadership. In the third qualitative phase, additional data will be gathered through semi-structured interviews to further validate the findings to gain a more complete understanding of distributed leadership and its relation to emergency response. Above are the predictive results; the study expects to be a cornerstone of safety leadership research and has important implications for leadership development and training within the maritime industry.

Keywords: authoritarian leadership, distributed leadership, emergency response , planfully aligned leadership

Procedia PDF Downloads 182

Authors: Haruna Shola Adeosun, Lekan M. Togunwa, Ajoke F. Adebiyi

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This paper examines the impact of social media on Nigerian Youths particularly in Nigeria. This study reviewed secondary sources data. The research adopted survey method which involves the use of questionnaire that was administered to gather primary data analysis and presentation were done with the use of tables, figures, percentages and chi-square were used to test the hypotheses formulated. The study revealed that social media consumers, especially Facebook are prone to the benefits or risks aspect of its contents. At this expense, what user derived, seeks, sought and gains from such media depend on the motive they are being used for. The study also revealed that users have the tendency to be positively influenced through heavy or over exposure to numerous contents that are damaging and harmful. This means that social media usage may be considered as good or bad. As its contents may or may not subject consumers to vulnerable use depending on what is saved from it. The study recommends that the use of Facebook should be subjected to gate keeping and monitoring in order to control the activities of users that embrace depression, bullying, sexing and sexual harassment as a way of life. Parents should close watch on their children and caution them towards cultivating the habit of over exposure to social sites so at to protect them form risks social media poses.

Keywords: evaluation, impact, soocial media, nigerian youths

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Authors: Ebenezer Kwesi Armah-Ansah, Kenneth Fosu Oteng, Esther Selasi Avinu, Eugene Budu, Edward Kwabena Ameyaw

Abstract:

Background: Maternal mortality, particularly in Benin, is a major public health concern in Sub-Saharan Africa. To provide a positive pregnancy experience and reduce maternal morbidities, all pregnant women must get appropriate and timely prenatal support. However, many pregnant women in developing countries, including Benin, begin antenatal care late. There is a paucity of empirical literature on the prevalence and predictors of early antenatal care visits in Benin. As a result, the purpose of this study is to investigate the prevalence and predictors of early antenatal care visits among women of productive age in Benin. Methods: This is a secondary analysis of the 2017/2018 Benin Demographic and Health Survey (BDHS) data. The study involved 6,919 eligible women. Data analysis was conducted using Stata version 14.2 for Mac OS. We adopted a multilevel logistic regression to examine the predictors of early ANC visits in Benin. The results were presented as odds ratios (ORs) associated with 95% confidence intervals (CIs) and p-value <0.05 to determine the significant associations. Results: The prevalence of early ANC visits among pregnant women in Benin was 57.03% [95% CI: 55.41-58.64]. In the final multilevel logistic regression, early ANC visit was higher among women aged 30-34 [aOR=1.60, 95% CI=1.17-2.18] compared to those aged 15-19, women with primary education [aOR=1.22, 95% CI=1.06-142] compared to the non-educated women, women who were covered by health insurance [aOR=3.03, 95% CI=1.35-6.76], women without a big problem in getting the money needed for treatment [aOR=1.31, 95% CI=1.16-1.49], distance to the health facility, not a big problem [aOR=1.23, 95% CI=1.08-1.41], and women whose partners had secondary/higher education [aOR=1.35, 95% CI=1.15-1.57] compared with those who were not covered by health insurance, had big problem in getting money needed for treatment, distance to health facility is a big problem and whose partners had no education respectively. However, women who had four or more births [aOR=0.60, 95% CI=0.48-0.74] and those in Atacora Region [aOR=0.50, 95% CI=0.37-0.68] had lower odds of early ANC visit. Conclusion: This study revealed a relatively high prevalence of early ANC visits among women of reproductive age in Benin. Women's age, educational status of women and their partners, parity, health insurance coverage, distance to health facilities, and region were all associated with early ANC visits among women of reproductive in Benin. These factors ought to be taken into account when developing ANC policies and strategies in order to boost early ANC visits among women in Benin. This will significantly reduce maternal and newborn mortality and help achieve the World Health Organization’s recommendation that all pregnant women should initiate early ANC visits within the first three months of pregnancy.

Keywords: antenatal care, Benin, maternal health, pregnancy, DHS, public health

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Authors: J. K. Alhassan, S. A. Lawal

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This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations.

Keywords: classification, data mining, decision tree, scholarship

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Authors: Apinya Mungaomklang, Natakamol Lookkham

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The purpose of this research is to study the characteristics of the graduates based on Thailand Qualification Framework (TQF) of the Faculty of Industrial Technology, Suan Sunandha Rajabhat University. The population of the research was employers/entrepreneurs/supervisors of students who were doing Professional Experiences course in their respective organizations during semester 1/2012. Data were collected during the month of September 2012 from the total number of 100 people. The tool used in this research was a questionnaire developed by the research team. Data were analyzed using percentage, mean and standard deviation using a computer program. The results showed that most of the surveyed organizations were private companies. The program with most students doing Professional Experiences course was Safety Technology and Occupational Health. The nature of work that most students did was associated with the document. Employers/ entrepreneurs/employers’ opinions on the characteristics of the graduates based on TQF received high scores. Cognitive skills received the highest score, followed by interpersonal relationships and responsibilities, ethics and moral, numerical analysis skills, communication and information technology skills, and knowledge, respectively.

Keywords: graduates characteristics, Thailand Qualification Framework, employers, entrepreneurs

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Authors: Charles Okon Effiong

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This paper is a sociolinguistic analysis of the semantics of students’ slang in Akwa Ibom State College of Education, Afaha Nsit, Nigeria. The descriptive survey design was deployed for the study and data were collected from one hundred and fifty (150) students through a series of instruments such as questionnaire, interviews and observations. The questionnaire was administered randomly to levels 200, 300 and Extra Time students only. Interviews and observations were also conducted on the students. These categories of students were selected because they had spent a longer time in the college and were thought to be familiar with campus slang. A total of ninety two (92) slang expressions were taken from the questionnaire and out of this number, twenty six (26) slang expressions were peculiar to the college while sixty six (66) were those slang terms also used in the society. The study proves the notion that every speaker handles a variety of registers and tends to choose among them in accordance with the social situation in which he finds himself. The study shows campus slang as a sociolect which facilitates communication among the students in a different sense. The slang expressions are fully intelligible to the students and this unique and elaborate lexicon serves to achieve group identity among other social implications.

Keywords: communication, slang, social relationship, sociolinguistics

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Authors: Heba Abdelmotaal

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This paper explores the impact of the extent of a company's environmental, social, and governance (ESG) disclosure on credit rating and capital structure. The analysis is based on a sample of 202 firms from the 350 FTSE firms over the period of 2008-2013. ESG disclosure score is measured using Proprietary Bloomberg score based on the extent of a company's Environmental, Social, and Governance (ESG) disclosure. The credit rating is measured by The QuiScore, which is a measure of the likelihood that a company will become bankrupt in the twelve months following the date of calculation. The Capital Structure is measured by long term debt ratio. Two hypotheses are test using panel data regression. The results suggested that the higher degree of ESG disclosure leads to better credit rating. There is significant negative relationship between ESG disclosure and the long term debit percentage. The paper includes implications for the transparency which is resulting of the ESG disclosure could support the Monitoring Function. The monitoring role of disclosure is the increasing in the transparency of the credit rating agencies, also it could affect on managers’ actions. This study provides empirical evidence on the material of ESG disclosure on credit ratings changes and the firms’ capital decision making.

Keywords: capital structure, credit rating agencies, ESG disclosure, panel data regression

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Authors: K. Azadeh, M. Ghasemi, S. Fazelifar

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Aim: Changes in stress hormones can be modify response of immune system. Cortisol as the most important body corticosteroid is anti-inflammatory and immunosuppressive hormone. Normal levels of cortisol in humans has fluctuated during the day, In other words, cortisol is released periodically, and regulate through the release of ACTH circadian rhythm in every day. Therefore, the aim of this study was to determine the effects of Chamomile on serum levels of inflammatory indexes to a bout of eccentric exercise in young women. Methodology: 32 women were randomly divided into 4 groups: high dose of Chamomile, low dose of Chamomile, ibuprofen and placebo group. Eccentric exercise included 5 set and rest period between sets was 1 minute. For this purpose, subjects warm up 10 min and then done eccentric exercise. Each participant completed 15 repetitions with optional 20 kg weight or until can’t continue moving. When the subject was no longer able to continue to move, immediately decreased 5 kg from the weight and the protocol continued until cause exhaustion or complete 15 repetitions. Also, subjects received specified amount of ibuprofen and Chamomile capsules in target groups. Blood samples in 6 stages (pre of starting pill, pre of exercise protocol, 4, 24, 48 and 72 hours after eccentric exercise) was obtained. The levels of cortisol and adrenocorticotropic hormone levels were measured by ELISA way. K-S test to determine the normality of the data and analysis of variance for repeated measures was used to analyze the data. A significant difference in the p < 0/05 accepted. Results: The results showed that Individual characteristics including height, weight, age and body mass index were not significantly different among the four groups. Analyze of data showed that cortisol and ACTH basic levels significantly decreased after supplementation consumption, but then gradually significantly increased in all stages of post exercise. In High dose of Chamomile group, increasing tendency of post exercise somewhat less than other groups, but not to a significant level. The inter-group analysis results indicate that time effect had a significant impact in different stages of the groups. Conclusion: The results of this study, one session of eccentric exercise increased cortisol and ACTH hormone. The results represent the effect of high dose of Chamomile in the prevention and reduction of increased stress hormone levels. As regards use of medicinal plants and ibuprofen as a pain medication and inflammation has spread among athletes and non-athletes, the results of this research can provide information about the advantages and disadvantages of using medicinal plants and ibuprofen.

Keywords: chamomile, inflammatory indexes, eccentric exercise, young girls

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Authors: María Del Mar Ramos-Lorente, Rafael Martínez-Martín

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More than 40 years have passed since the Spanish Constitution in force today was approved in 1978. The period prior to that Constitution, which marked the transition to democracy, was marked by National Catholicism, which actively limited the existence of religions other than Catholicism in the national territory. The approval of this norm allowed the opening in many aspects, including the religious one. This work will profusely describe the evolution of the appearance of religious minorities in Spain from the moment of the transition, in which the space for religious freedom appears up to the present. The methodology is twofold. On the one hand, qualitative analysis of the legislation has allowed the religious opening. On the other, the quantitative analysis of the NMRs implemented in Spain. The entire analysis establishes the increase in religious organizations as a result, with notable variations across the territory.

Keywords: new religious movements, religious minorities, sociological analysis, Spain

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

Procedia PDF Downloads 359