Search results for: scientific data mining

Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

Procedia PDF Downloads 334

Authors: James Kinyua Gitonga, Toshio Fujimi

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

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

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Authors: Arjumand Warsy

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Among the Muslims, the Holy Quran is taught from early childhood and generally by the age of 7-8 years the reading of the entire Quran is completed by most of the children in Muslim families. During this period excellent reciter’s are selected to teach and emphasis is laid on correct reading, pronunciation and memorization. Following these years, the parents lay emphasis on the recitation of the Quran on daily basis. During the month of Ramadan the entire Quran is read one or more times and there are considerable number of Muslims who complete the entire Quran once or more each calendar month. Many Muslims do not know Arabic and for them message in the Quran is what others tell them and often they have no idea about this Guidance sent to them. This deficiency is reflected in many ways, both among people living in Muslim or non-Muslim countries. Due to the deficiency in knowledge about Islamic teachings, the foundations of Islam are being eroded by a variety of forces. In an attempt to guard against the non-Islamic influences, every Muslim must have a clear understanding of the Islamic teachings and requirements. The best guidance can be provided by the understanding of the Holy Quran. However, we are faced with the problem that often the Quran is taught in a way that fails to develop an interest and understanding of the message from Allah. Looking at the teaching of other subjects both scientific and non-scientific, at school, college or University levels, it is obvious that the advances in teaching methodologies using electronic technology have had a major impact, where both the understanding and the interest of the students are significantly elevated. We attempted to teach the meaning of the Holy Quran to children and adults using a scientific and modern approach using slide presentation and animations. The results showed almost 100% increase in the understanding of the Quran message; all attendees claimed they developed an increased interest in the study of the Holy Quran and did not lose track or develop boredom throughout the lectures. They learnt the information and remembered it more effectively. The love for Allah and Prophet Mohammad (PBUH) increased significantly. The fear of Allah and love of Heaven developed significantly. Historical facts and the stories of the past nations became clearer and the Greatness of the Creator was strongly felt. Several of attendees wanted to become better Muslims and to spread the knowledge of Islam. In this presentation, the adopted teaching method will be first presented and demonstrated to the audience using a short Surah from the Quran, followed by discussion on the results achieved during our study. We will endeavor to convey to the audience that there is a need to adopt a more scientific approach to teach the Quran so that a greater benefit is achieved by all.

Keywords: The Holy Quran, Muslims, presentations, technology

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Authors: Ryan Chalk, G. M. Shafiullah

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Climate change is a pertinent issue facing governments and societies around the world. The industrial revolution has resulted in a steady increase in the average global temperature. The mining and energy production industries have been significant contributors to this change prompting government to intervene by promoting low emission technology within these sectors. This paper initially reviews the energy problem in Australia and the mining sector with a focus on the energy requirements and production methods utilised in Western Australia (WA). Renewable energy in the form of utility-scale solar photovoltaics (PV) provides a solution to these problems by providing emission-free energy which can be used to supplement the existing natural gas turbines in operation at the proposed site. This research presents a custom renewable solution for the mining site considering the specific township network, local weather conditions, and seasonal load profiles. A summary of the required PV output is presented to supply slightly over 50% of the towns power requirements during the peak (summer) period, resulting in close to full coverage in the trench (winter) period. Dig Silent Power Factory Software has been used to simulate the characteristics of the existing infrastructure and produces results of integrating PV. Large scale PV penetration in the network introduce technical challenges, that includes; voltage deviation, increased harmonic distortion, increased available fault current and power factor. Results also show that cloud cover has a dramatic and unpredictable effect on the output of a PV system. The preliminary analyses conclude that mitigation strategies are needed to overcome voltage deviations, unacceptable levels of harmonics, excessive fault current and low power factor. Mitigation strategies are proposed to control these issues predominantly through the use of high quality, made for purpose inverters. Results show that use of inverters with harmonic filtering reduces the level of harmonic injections to an acceptable level according to Australian standards. Furthermore, the configuration of inverters to supply active and reactive power assist in mitigating low power factor problems. Use of FACTS devices; SVC and STATCOM also reduces the harmonics and improve the power factor of the network, and finally, energy storage helps to smooth the power supply.

Keywords: climate change, mitigation strategies, photovoltaic (PV), power quality

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Authors: Alena Nesterenko, Svetlana Petrikova

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Research evaluation is one of the most important elements of self-regulation and development of researchers as it is impartial and independent process of assessment. The method of expert evaluations as a scientific instrument solving complicated non-formalized problems is firstly a scientifically sound way to conduct the assessment which maximum effectiveness of work at every step and secondly the usage of quantitative methods for evaluation, assessment of expert opinion and collective processing of the results. These two features distinguish the method of expert evaluations from long-known expertise widespread in many areas of knowledge. Different typical problems require different types of expert evaluations methods. Several issues which arise with these methods are experts’ selection, management of assessment procedure, proceeding of the results and remuneration for the experts. To address these issues an on-line system was created with the primary purpose of development of a versatile application for many workgroups with matching approaches to scientific work management. Online documentation assessment and statistics system allows: - To realize within one platform independent activities of different workgroups (e.g. expert officers, managers). - To establish different workspaces for corresponding workgroups where custom users database can be created according to particular needs. - To form for each workgroup required output documents. - To configure information gathering for each workgroup (forms of assessment, tests, inventories). - To create and operate personal databases of remote users. - To set up automatic notification through e-mail. The next stage is development of quantitative and qualitative criteria to form a database of experts. The inventory was made so that the experts may not only submit their personal data, place of work and scientific degree but also keywords according to their expertise, academic interests, ORCID, Researcher ID, SPIN-code RSCI, Scopus AuthorID, knowledge of languages, primary scientific publications. For each project, competition assessments are processed in accordance to ordering party demands in forms of apprised inventories, commentaries (50-250 characters) and overall review (1500 characters) in which expert states the absence of conflict of interest. Evaluation is conducted as follows: as applications are added to database expert officer selects experts, generally, two persons per application. Experts are selected according to the keywords; this method proved to be good unlike the OECD classifier. The last stage: the choice of the experts is approved by the supervisor, the e-mails are sent to the experts with invitation to assess the project. An expert supervisor is controlling experts writing reports for all formalities to be in place (time-frame, propriety, correspondence). If the difference in assessment exceeds four points, the third evaluation is appointed. As the expert finishes work on his expert opinion, system shows contract marked ‘new’, managers commence with the contract and the expert gets e-mail that the contract is formed and ready to be signed. All formalities are concluded and the expert gets remuneration for his work. The specificity of interaction of the examination officer with other experts will be presented in the report.

Keywords: expertise, management of research evaluation, method of expert evaluations, research evaluation

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Authors: Syed Ahzam Tariq, Atharva Modi

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This paper presents a probabilistic analysis of the safety of water tube boilers using fault tree analysis (FTA). A fault tree has been constructed by considering all possible areas where a malfunction could lead to a boiler accident. Boiler accidents are relatively rare, causing a scarcity of data. The fuzzy approach is employed to perform a quantitative analysis, wherein theories of fuzzy logic are employed in conjunction with expert elicitation to calculate failure probabilities. The Fuzzy Fault Tree Analysis (FFTA) provides a scientific and contingent method to forecast and prevent accidents.

Keywords: fault tree analysis water tube boiler, fuzzy probability score, failure probability

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Authors: Yuzhen Hu, Sirui Wang

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As a training base for intellectual talents, universities have a large number of students. Teaching is a primary activity in universities, and during the teaching process, a large number of people gather both inside and outside the teaching buildings, posing a strong risk of close contact. The class schedule is the fundamental basis for teaching activities in universities and plays a crucial role in the management of teaching order. Different class schedules can lead to varying degrees of indoor gatherings and trajectories of class attendees. In recent years, highly contagious diseases have frequently occurred worldwide, and how to reduce the risk of infection has always been a hot issue related to public safety. "Reducing gatherings" is one of the core measures in epidemic prevention and control, and it can be controlled through scientific scheduling in specific environments. Therefore, the scientific prevention and control goal can be achieved by considering the reduction of the risk of excessive gathering of people during the course schedule arrangement. Firstly, we address the issue of personnel gathering in various pathways on campus, with the goal of minimizing congestion and maximizing teaching effectiveness, establishing a nonlinear mathematical model. Next, we design an improved genetic algorithm, incorporating real-time evacuation operations based on tracking search and multidimensional positive gradient cross-mutation operations, considering the characteristics of outdoor crowd evacuation. Finally, we apply undergraduate course data from a university in Harbin to conduct a case study. It compares and analyzes the effects of algorithm improvement and optimization of gathering situations and explores the impact of path blocking on the degree of gathering of individuals on other pathways.

Keywords: the university timetabling problem, risk prevention, genetic algorithm, risk control

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Authors: Tammeen Siraj, Wenxing Zhou, Terry Huang, Mohammad Al-Amin

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The high resolution inline inspection (ILI) tool is used extensively in the pipeline industry to identify, locate, and measure metal-loss corrosion anomalies on buried oil and gas steel pipelines. Corrosion anomalies may occur singly (i.e. individual anomalies) or as clusters (i.e. a colony of corrosion anomalies). Although the ILI technology has advanced immensely, there are measurement errors associated with the sizes of corrosion anomalies reported by ILI tools due limitations of the tools and associated sizing algorithms, and detection threshold of the tools (i.e. the minimum detectable feature dimension). Quantifying the measurement error in the ILI data is crucial for corrosion management and developing maintenance strategies that satisfy the safety and economic constraints. Studies on the measurement error associated with the length of the corrosion anomalies (in the longitudinal direction of the pipeline) has been scarcely reported in the literature and will be investigated in the present study. Limitations in the ILI tool and clustering process can sometimes cause clustering error, which is defined as the error introduced during the clustering process by including or excluding a single or group of anomalies in or from a cluster. Clustering error has been found to be one of the biggest contributory factors for relatively high uncertainties associated with ILI reported anomaly length. As such, this study focuses on developing a consistent and comprehensive framework to quantify the measurement errors in the ILI-reported anomaly length by comparing the ILI data and corresponding field measurements for individual and clustered corrosion anomalies. The analysis carried out in this study is based on the ILI and field measurement data for a set of anomalies collected from two segments of a buried natural gas pipeline currently in service in Alberta, Canada. Data analyses showed that the measurement error associated with the ILI-reported length of the anomalies without clustering error, denoted as Type I anomalies is markedly less than that for anomalies with clustering error, denoted as Type II anomalies. A methodology employing data mining techniques is further proposed to classify the Type I and Type II anomalies based on the ILI-reported corrosion anomaly information.

Keywords: clustered corrosion anomaly, corrosion anomaly assessment, corrosion anomaly length, individual corrosion anomaly, metal-loss corrosion, oil and gas steel pipeline

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Authors: Rajesh S. Mony, Vaidyaratnam Oushadhasala

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An attempt is made in this study to evolve a drug development modality based on classical Ayurvedic knowledge base as well as on modern scientific methodology. The present study involves (a) identification of a specific ailment condition, (b) the selection of a polyherbal formulation, (c) deciding suitable extraction procedure, (d) confirming the efficacy of the combination by in-vitro trials and (e) fixing up the recommended dose. The ailment segment selected is arthritic condition. The selected herbal combination is Kunturushka, Vibhitaki, Guggulu, Haridra, Maricha and Nirgundi. They were selected as per Classical Ayurvedic references, Authentified as per API (Ayurvedic Pharmacopeia of India), Extraction of each drug was done by different ratios of Hydroalcoholic menstrums, Invitro assessment of each extract after removing residual solvent for anti-Inflammatory, anti-arthritic activities (by UV-Vis. Spectrophotometer with positive control), Invitro assessment of each extract for COX enzyme inhibition (by UV-Vis. Spectrophotometer with positive control), Selection of the extracts was made having good in-vitro activity, Performed the QC testing of each selected extract including HPTLC, that is the in process QC specifications, h. Decision of the single dose with mixtures of selected extracts was made as per the level of in-vitro activity and available toxicology data, Quantification of major groups like Phenolics, Flavonoids, Alkaloids and Bitters was done with both standard Spectrophotometric and Gravimetric methods, Method for Marker assay was developed and validated by HPTLC and a good resolved HPTLC finger print was developed for the single dosage API (Active Pharmaceutical Ingredient mixture of extracts), Three batches was prepared to fix the in process and API (Active Pharmaceutical Ingredient) QC specifications.

Keywords: drug development, antiinflammatory, quality stardardisation, planar chromatography

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Authors: Yamma Rose, Kone Martine, Yonli Arsène, Wanko Ngnien Adrien

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Soil pollution and, consequently, water resources by micropollutants from gold mine tailings constitute a major threat in developing countries due to the lack of waste treatment. Phytoremediation is an alternative for extracting or trapping micropollutants from contaminated soils by mining residues. The potentialities of Chrysopogon zizanioides (acclimated plant) and Andropogon gayanus (native plant) to accumulate arsenic (As), mercury (Hg), iron (Fe) and zinc (Zn) were studied in artisanal gold mine in Ouagadougou, Burkina Faso. The phytoremediation effectiveness of two plant species was studied in 75 pots of 30 liters each, containing mining residues from the artisanal gold processing site in the rural commune of Nimbrogo. The experiments cover three modalities: Tn - planted unpolluted soils; To – unplanted mine tailings and Tp – planted mine tailings arranged in a randomized manner. The pots were amended quarterly with compost to provide nutrients to the plants. The phytoremediation assessment consists of comparing the growth, biomass and capacity of these two herbaceous plants to extract or to trap Hg, Fe, Zn and As in mining residues in a controlled environment. The analysis of plant species parameters cultivated in mine tailings shows indices of relative growth of A. gayanus very significantly high (34.38%) compared to 20.37% for C.zizanioides. While biomass analysis reveals that C. zizanioides has greater foliage and root system growth than A. gayanus. The results after a culture time of 6 months showed that C. zizanioides and A. gayanus have the potential to accumulate Hg, Fe, Zn and As. Root biomass has a more significant accumulation than aboveground biomass for both herbaceous species. Although the BCF bioaccumulation factor values for both plants together are low (<1), the removal efficiency of Hg, Fe, Zn and As is 45.13%, 42.26%, 21.5% and 2.87% respectively in 24 weeks of culture with C. zizanioides. However, pots grown with A. gayanus gives an effectiveness rate of 43.55%; 41.52%; 2.87% and 1.35% respectively for Fe, Zn, Hg and As. The results indicate that the plant species studied have a strong phytoremediation potential, although that of A. gayanus is relatively less than C. zizanioides.

Keywords: artisanal gold mine tailings, andropogon gayanus, chrysopogon zizanioides, phytoremediation

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Authors: Nino Damenia

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E-commerce opens a new horizon for business development, which is why the presence of e-commerce is a necessary condition for the formation, growth, and development of the country's economy. Worldwide, e-commerce turnover is growing at a high rate every year, as the electronic environment provides great opportunities for product promotion. E-commerce in Georgia is developing at a fast pace, but it is still a relatively young direction in the country's economy. Movement restrictions and other public health measures caused by the COVID-19 pandemic have reduced economic activity in most economic sectors and countries, significantly affecting production, distribution, and consumption. The pandemic has accelerated digital transformation. Digital solutions enable people and businesses to continue part of their economic and social activities remotely. This has also led to the growth of e-commerce. According to the data of the National Statistics Service of Georgia, the share of online trade is higher in cities (27.4%) than in rural areas (9.1%). The COVID-19 pandemic has forced local businesses to expand their digital offerings. The size of the local market increased 3.2 times in 2020 to 138 million GEL. And in 2018-2020, the share of local e-commerce increased from 11% to 23%. In Georgia, the state is actively engaged in the promotion of activities based on information technologies. Many measures have been taken for this purpose, but compared to other countries, this process is slow in Georgia. The purpose of the study is to determine development prospects for the economy of Georgia based on the analysis of electronic commerce. Research was conducted around the issues using Georgian and foreign scientists' articles, works, reports of international organizations, collections of scientific conferences, and scientific electronic databases. The empirical base of the research is the data and annual reports of the National Statistical Service of Georgia, internet resources of world statistical materials, and others. While working on the article, a questionnaire was developed, based on which an electronic survey of certain types of respondents was conducted. The conducted research was related to determining how intensively Georgian citizens use online shopping, including which age category uses electronic commerce, for what purposes, and how satisfied they are. Various theoretical and methodological research tools, as well as analysis, synthesis, comparison, and other types of methods, are used to achieve the set goal in the research process. The research results and recommendations will contribute to the development of e-commerce in Georgia and economic growth based on it.

Keywords: e-commerce, information technology, pandemic, digital transformation

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Authors: Mohiuddin Sakib, Fatin Nihal, Anisul Haque, Munsur Rahman, Mansur Ali

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Sundarban, the largest mangrove forest in the world, is known to act as a buffer against the cyclone and storm surge. Theoretically, Sundarban absorbs the initial thrust of the wind and acts to ‘resist’ the storm surge flooding. The role of Sundarban was evident during the cyclone Sidr when the Sundarban solely defended the initial thrust of the cyclonic wind and the resulting storm surge inundation. In doing this, Sundarban sacrificed 30% of its plant habitats. Although no scientific study has yet been conducted, it is generally believed that Sundarban will continuously play its role as a buffer against the cyclone when landfall of the cyclone is at or close to the Sundarban. Considering these facts, the present study mainly focused on a scientific insight into the role of Sundarban as a buffer against the present-day cyclone and storm surge and also its probable role on the impacts of future storms of similar nature but with different landfall locations. The Delft 3D dashboard and flow model are applied to compute the resulting inundation due to cyclone induced storm surge. The results show that Sundarban indeed acts as a buffer against the storm surge inundation when cyclone landfall is at or close to Sundarban.

Keywords: buffer, Mangrove forest, Sidr, landfall, roughness

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Authors: Temidayo O. Omotehinwa, David O. Oyewola, Friday J. Agbo

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This study aims to gather a proper perspective of the development landscape of Computer Science research in Nigeria. Therefore, a bibliometric analysis of 4,333 bibliographic records of Computer Science research in Nigeria in the last 31 years (1991-2021) was carried out. The bibliographic data were extracted from the Scopus database and analyzed using VOSviewer and the bibliometrix R package through the biblioshiny web interface. The findings of this study revealed that Computer Science research in Nigeria has a growth rate of 24.19%. The most developed and well-studied research areas in the Computer Science field in Nigeria are machine learning, data mining, and deep learning. The social structure analysis result revealed that there is a need for improved international collaborations. Sparsely established collaborations are largely influenced by geographic proximity. The funding analysis result showed that Computer Science research in Nigeria is under-funded. The findings of this study will be useful for researchers conducting Computer Science related research. Experts can gain insights into how to develop a strategic framework that will advance the field in a more impactful manner. Government agencies and policymakers can also utilize the outcome of this research to develop strategies for improved funding for Computer Science research.

Keywords: bibliometric analysis, biblioshiny, computer science, Nigeria, science mapping

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Authors: Jacky Liu

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This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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Authors: Tambe Daniel Atem

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Background: Clinical Research is an organized research on human beings intended to provide adequate information on the drug use as a therapeutic agent on its safety and efficacy. The significance of the study is to educate the global health and life science graduates in Clinical Research in depth to perform better as it involves testing drugs on human beings. Objectives: to provide an overall understanding of the scientific approach to the evaluation of new and existing medical interventions and to apply ethical and regulatory principles appropriate to any individual research. Methodology: It is based on – Primary data analysis and Secondary data analysis. Primary data analysis: means the collection of data from journals, the internet, and other online sources. Secondary data analysis: a survey was conducted with a questionnaire to interview the Clinical Research Professionals to understand the need of training to perform clinical trials globally. The questionnaire consisted details of the professionals working with the expertise. It also included the areas of clinical research which needed intense training before entering into hardcore clinical research domain. Results: The Clinical Trials market worldwide worth over USD 26 billion and the industry has employed an estimated 2,10,000 people in the US and over 70,000 in the U.K, and they form one-third of the total research and development staff. There are more than 2,50,000 vacant positions globally with salary variations in the regions for a Clinical Research Coordinator. R&D cost on new drug development is estimated at US$ 70-85 billion. The cost of doing clinical trials for a new drug is US$ 200-250 million. Due to an increase trained Clinical Research Professionals India has emerged as a global hub for clinical research. The Global Clinical Trial outsourcing opportunity in India in the pharmaceutical industry increased to more than $2 billion in 2014 due to increased outsourcing from U.S and Europe to India. Conclusion: Assessment of training need is recommended for newer Clinical Research Professionals and trial sites, especially prior the conduct of larger confirmatory clinical trials.

Keywords: clinical research, clinical trials, clinical research professionals

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Authors: N. Songumpai, W. Sumranwanich, S. Chatmaneerungcharoen

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This research aims to study the understanding of 8 aspects of nature of science (NOS). The research participants were 39 General Science student teachers who were selected by purposive sampling. In 2015 academic year, they enrolled in the course of Science Education Learning Management. Qualitative research was used as research methodology to understand how the student teachers propose on NOS. The research instruments consisted of open-ended questionnaires and semi-structure interviews that were used to assess students’ understanding of NOS. Research data was collected by 8 items- questionnaire and was categorized into students’ understanding of NOS, which consisted of complete understanding (CU), partial understanding (PU), misunderstanding (MU) and no understanding (NU). The findings reveal the majority of students’ misunderstanding of NOS regarding the aspects of theory and law(89.7%), scientific method(61.5%) and empirical evidence(15.4%) respectively. From the interview data, the student teachers present their misconceptions of NOS that indicate about theory and law cannot change; science knowledge is gained through experiment only (step by step); science is the things that are around humans. These results suggest that for effective science teacher education, the composition of design of NOS course needs to be considered. Therefore, teachers’ understanding of NOS is necessary to integrate into professional development program/course for empowering student teachers to begin their careers as strong science teachers in schools.

Keywords: nature of science, student teacher, no understanding, misunderstanding, partial understanding, complete understanding

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Authors: Nur Aziza Luxfiati

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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

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Authors: Soheil Roumi, Fan Zhang, Rodney Stewart

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Indoor environmental quality (IEQ) indexes represented the suitability of a place to study, work, and live. Many indexes have been introduced based on the physical measurement or occupant surveys in commercial buildings. The earlier studies did not elaborate on the relationship between energy consumption and IEQ in office buildings. Such a relationship can provide a comprehensive overview of the building's performance. Also, it would find the potential of already constructed buildings under the upcoming climate change. A commercial building in southeast Queensland, Australia, was evaluated in this study. Physical measurements of IEQ and Energy areconducted, and their relationship will be determined using statistical analysis. The case study building is modelled in TRNSys software, and it will be validatedusingthe actual building's BMS data. Then, the modelled buildingwill be simulated by predicted weather data developed by the commonwealth scientific and industrial research organisation of Australia to investigate the occupant resilience and energy consumption. Finally, recommendations will be presented to consume less energy while providinga proper indoor environment for office occupants.

Keywords: IEQ, office buildings, thermal comfort, occupant resilience

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Authors: Indhumathi Gopal

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Undergraduate research is well documented in Science, Technology, Engineering, and Mathematics (STEM), neurosciences, and microbiology disciplines, though it is hardly part of a physical fitness & wellness discipline. However, students need experiential learning opportunities, like internships and research assistantships, to get ahead with graduate schools and be gainfully employed. The first step towards this goal is to have students do a simple research project in a semester-long course. The value of research experiences and how to integrate research activity in a physical fitness & wellness course are discussed. The investigator looks into a mini research project, “Awareness of Obesity among College Students” and explains how to guide students through the research process, including journal search, data collection, and basic statistics. Besides, students will be introduced to the statistical package program SPSS 22.0 to assist with data evaluation. The lab component of the combined lecture-physical activity course could include the measurement of student’s weight with respect to their height to obtain body mass index (BMI). Students could categorize themselves in accordance with the World Health Organization’s guidelines. Results obtained after completing the data analysis help students be aware of their own potential health risks associated with overweight and obesity. Overweight and obesity are risk factors for hypertension, hypercholesterolemia, heart disease, stroke, diabetes, and certain types of cancer. It is hoped that this experience will get students interested in scientific studies, gain confidence, think critically, and develop problem-solving and good communication skills.

Keywords: physical fitness, undergraduate research experience, obesity, BMI

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Authors: Le Chen

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This paper presents an efficient tool platform scheme to ensure quality protection throughout the software development process. The main principle is to manage the information of requirements, design, development, testing, operation and maintenance process with proper tools, and to set up the quality standards of each process. Through the tools’ display and summary of quality standards, the quality standards can be visualizad and ready for policy decision, which is called Quality Gate in this paper. In addition, the tools are also integrated to achieve the exchange and relation of information which highly improving operational efficiency. In this paper, the feasibility of the scheme is verified by practical application of development projects, and the overall information display and data mining are proposed to be further improved.

Keywords: efficiency, quality gate, software process, tools

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Authors: Rachel P. Vasconcellos

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The Russian constructivism is usually enshrined in history as another ''modernist ism'', that is, as an artistic phenomenon related to the early twentieth century‘s zeitgeist. What we aim in this essay is to analyze the constructivist movement not over the Art History field neither through the aesthetic debate, but through a geographical critical theory, taking the main idea of construction in the concrete sense of production of space. Seen from the perspective of the critique of space, the constructivist production is presented as a plan of totality, designed as socialist society‘s spatiality, contemplating and articulating all its scalar levels: the objects of everyday life, the building, the city and the territory. The constructivist avant-garde manifests a geographical ideology, launching the foundation‘s basis of modern planning ideology. Taken in its political sense, the artistic avant-garde of the Russian Revolution intended to anticipate the forms of a social future already put in progress: their plastic research pointed to new formal expressions to revolutionary contents. With the foundation of new institutions under a new State, it was given to the specialized labor of artists, architects, and planners the task of designing the socialist society, based on the thesis of scientific socialism. Their projects were developed under the politico-economics imperatives to the Soviet modernization – that is: the structural needs of industrialization and inclusion of all people in the productive work universe. This context shapes the creative atmosphere of the constructivist avant-garde, which uses the methods of engineering to the transform everyday life. Architecture, urban planning, and state planning integrated must then operate as spatial arrangement morphologically able to produce socialist life. But due to the intrinsic contradictions of the process, the rational and geometric aesthetic of the City-Machine appears, finally, as an image of a scientific socialist utopia.

Keywords: city-machine, critique of space, production of space, soviet territorialization

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Authors: Mohsen Mohammadi, Toshio Fujimi

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High population and irregular urban development in Kabul city, Afghanistan's capital, are among factors that increase its vulnerability to earthquake disasters (on top of its location in a high seismic region); this can lead to widespread economic loss and casualties. This study aims to evaluate earthquake risks in Kabul's 13th district based on scientific data. The research data, which include hazard curves of Kabul, vulnerability curves, and a questionnaire survey through sampling in district 13, have been incorporated to develop risk curves. To estimate potential casualties, we used a set of M parameters in a model developed by Coburn and Spence. The results indicate that in the worst case scenario, more than 90% of district 13, which comprises mostly residential buildings, is exposed to high risk; this may lead to nearly 1000 million USD economic loss and 120 thousand casualties (equal to 25.88% of the 13th district's population) for a nighttime earthquake. To reduce risks, we present the reconstruction of the most vulnerable buildings, which are primarily adobe and masonry buildings. A comparison of risk reduction between reconstructing adobe and masonry buildings indicates that rebuilding adobe buildings would be more effective.

Keywords: earthquake risk evaluation, Kabul, mitigation, vulnerability

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Authors: Fani Sakellariadou

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The Blue Economy includes all marine-based and marine-related activities. They correspond to established, emerging as well as unborn ocean-based industries. Seabed mining is an emerging marine-based activity; its operations depend particularly on cutting-edge science and technology. The 21st century will face a crisis in resources as a consequence of the world’s population growth and the rising standard of living. The natural capital stored in the global ocean is decisive for it to provide a wide range of sustainable ecosystem services. Seabed mineral deposits were identified as having a high potential for critical elements and base metals. They have a crucial role in the fast evolution of green technologies. The major categories of marine mineral deposits are deep-sea deposits, including cobalt-rich ferromanganese crusts, polymetallic nodules, phosphorites, and deep-sea muds, as well as shallow-water deposits including marine placers. Seabed mining operations may take place within continental shelf areas of nation-states. In international waters, the International Seabed Authority (ISA) has entered into 15-year contracts for deep-seabed exploration with 21 contractors. These contracts are for polymetallic nodules (18 contracts), polymetallic sulfides (7 contracts), and cobalt-rich ferromanganese crusts (5 contracts). Exploration areas are located in the Clarion-Clipperton Zone, the Indian Ocean, the Mid Atlantic Ridge, the South Atlantic Ocean, and the Pacific Ocean. Potential environmental impacts of deep-sea mining include habitat alteration, sediment disturbance, plume discharge, toxic compounds release, light and noise generation, and air emissions. They could cause burial and smothering of benthic species, health problems for marine species, biodiversity loss, reduced photosynthetic mechanism, behavior change and masking acoustic communication for mammals and fish, heavy metals bioaccumulation up the food web, decrease of the content of dissolved oxygen, and climate change. An important concern related to deep-sea mining is our knowledge gap regarding deep-sea bio-communities. The ecological consequences that will be caused in the remote, unique, fragile, and little-understood deep-sea ecosystems and inhabitants are still largely unknown. The blue economy conceptualizes oceans as developing spaces supplying socio-economic benefits for current and future generations but also protecting, supporting, and restoring biodiversity and ecological productivity. In that sense, people should apply holistic management and make an assessment of marine mining impacts on ecosystem services, including the categories of provisioning, regulating, supporting, and cultural services. The variety in environmental parameters, the range in sea depth, the diversity in the characteristics of marine species, and the possible proximity to other existing maritime industries cause a span of marine mining impact the ability of ecosystems to support people and nature. In conclusion, the use of the untapped potential of the global ocean demands a liable and sustainable attitude. Moreover, there is a need to change our lifestyle and move beyond the philosophy of single-use. Living in a throw-away society based on a linear approach to resource consumption, humans are putting too much pressure on the natural environment. Applying modern, sustainable and eco-friendly approaches according to the principle of circular economy, a substantial amount of natural resource savings will be achieved. Acknowledgement: This work is part of the MAREE project, financially supported by the Division VI of IUPAC. This work has been partly supported by the University of Piraeus Research Center.

Keywords: blue economy, deep-sea mining, ecosystem services, environmental impacts

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Authors: Dongseok Cho, Mitchell Driedger, Sera Han, Noman Khan, Mohammed Elmorsy, Mohamad El-Hajj

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Since the approval of the COVID-19 vaccine in late 2020, vaccination rates have varied around the globe. Access to a vaccine supply, mandated vaccination policy, and vaccine hesitancy contribute to these rates. This study used COVID-19 vaccination data from Our World in Data and the Multilateral Leaders Task Force on COVID-19 to create two COVID-19 vaccination indices. The first index is the Vaccine Utilization Index (VUI), which measures how effectively each country has utilized its vaccine supply to doubly vaccinate its population. The second index is the Vaccination Acceleration Index (VAI), which evaluates how efficiently each country vaccinated its population within its first 150 days. Pearson correlations were created between these indices and country indicators obtained from the World Bank. The results of these correlations identify countries with stronger health indicators, such as lower mortality rates, lower age dependency ratios, and higher rates of immunization to other diseases, displaying higher VUI and VAI scores than countries with lesser values. VAI scores are also positively correlated to Governance and Economic indicators, such as regulatory quality, control of corruption, and GDP per capita. As represented by the VUI, proper utilization of the COVID-19 vaccine supply by country is observed in countries that display excellence in health practices. A country’s motivation to accelerate its vaccination rates within the first 150 days of vaccinating, as represented by the VAI, was largely a product of the governing body’s effectiveness and economic status, as well as overall excellence in health practises.

Keywords: data mining, Pearson correlation, COVID-19, vaccination rates and hesitancy

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Authors: Mustafa Elfituri, Jonathan Cook

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Recently, graph-based computations have become more important in large-scale scientific computing as they can provide a methodology to model many types of relations between independent objects. They are being actively used in fields as varied as biology, social networks, cybersecurity, and computer networks. At the same time, graph problems have some properties such as irregularity and poor locality that make their performance different than regular applications performance. Therefore, parallelizing graph algorithms is a hard and challenging task. Initial evidence is that standard computer architectures do not perform very well on graph algorithms. Little is known exactly what causes this. The Graph500 benchmark is a representative application for parallel graph-based computations, which have highly irregular data access and are driven more by traversing connected data than by computation. In this paper, we present results from analyzing the performance of various example implementations of Graph500, including a shared memory (OpenMP) version, a distributed (MPI) version, and a hybrid version. We measured and analyzed all the factors that affect its performance in order to identify possible changes that would improve its performance. Results are discussed in relation to what factors contribute to performance degradation.

Keywords: graph computation, graph500 benchmark, parallel architectures, parallel programming, workload characterization.

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Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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Authors: Kristina Rosengren, Petra Brannefors, Eric Carlstrom

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Background: Implementation and use of person-centered care (PCC) is increasing worldwide, and why the current study intends to increase knowledge regarding how PCC is used in different European countries. Purpose: To describe the extent of person-centred care in 23 European countries in relation to use specific countries healthcare system (Beveridge, Bismarck, Mixed/OOP). Methods: The study was conducted by literature review inspired by Spice, both scientific empirical studies (Cinahl, Medline, Scopus) as well as grey literature (Google) were used. Totally 1194 documents were included divided into Cinahl n=139, Medline n=245, Scopus n=493 and Google n=317. Data were analysed with descriptive (percentage, range) regarding content and scope of PCC/country according to content and scope of PCC in each country, grouped into the healthcare system (Beveridge, Bismarck, Mixed/OOP) and geographic placement. Results: PCC were most common in UK (England, Scotland, Wales, North Ireland), n=481, 40.3%, Sweden (n=231, 19.3%), The Netherlands (n=80, 6.7%), Ireland (n=79, 6.6%) and Norway (n=61, 5.1%); and less common in Poland (0.6%), Hungary (0.5%), Greece (0.4%), Latvia (0.4%) and Serbia (0%). Beveridge healthcare system (12/23=0.5217, 52.2%) show 85 percent of documents with advantage of scientific literature valued 2.92 (n=999, 0.55-4.07), compare to advantage of grey literature in Bismarck (10/23=0.4347, 43.5%) with 15 percentage valued 2.35 (n=190, 0-3.27) followed by Mixed/OOP (1/23=4%) with 0.4 valued 2.25. Conclusions: Seven out of 10 countries with Beveridge health system used PCC compare to less-used PCC in countries with the Bismarck system. Research, as well as national regulations regarding PCC, are important tools to motivate the advantage of PCC in clinical practice. Moreover, implementation of PCC needs a systematic approach, from national (politicians), regional (guideline) and local (specific healthcare settings) levels visualized by decision-making as law, mission, policies, and routines in clinical practice to establish a well-integrated phenomenon in Europe.

Keywords: Beveridge, Bismarck, Europe, evidence-based, literature review, person-centered care

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Authors: Shizra Waris, Saleem Akhtar

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Big data is a research area receiving attention from academia and IT communities. In the digital world, the amounts of data produced and stored have within a short period of time. Consequently this fast increasing rate of data has created many challenges. In this paper, we use functionalism and structuralism paradigms to analyze the genesis of big data applications and its current trends. This paper presents a complete discussion on state-of-the-art big data technologies based on group and stream data processing. Moreover, strengths and weaknesses of these technologies are analyzed. This study also covers big data analytics techniques, processing methods, some reported case studies from different vendor, several open research challenges and the chances brought about by big data. The similarities and differences of these techniques and technologies based on important limitations are also investigated. Emerging technologies are suggested as a solution for big data problems.

Keywords: computer, it community, industry, big data

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Authors: Sylvia Szabo, Thilini Navaratne, Indrajit Pal, Seree Park

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Deltaic and coastal regions are often strategically important both from local and regional perspectives. While deltas are known to be bread baskets of the world, delta inhabitants often face the risk of food and nutritional insecurity. These risks are highly exacerbated by the impacts of climate and environmental change. While numerous regional studies examined the prevalence and the determinants of food security in specific delta and coastal regions, there is still a lack of a systematic analysis of the most widely used scientific food security indicators. In order to fill this gap, a systematic review was carried out using Covidence, a Cochrane-adopted systematic review processing software. Papers included in the review were selected from the SCOPUS, Thomson Reuters Web of Science, Science Direct, ProQuest, and Google Scholar databases. Both scientific papers and grey literature (e.g., reports by international organizations) were considered. The results were analyzed by food security components (access, availability, quality, and strategy) and by world regions. Suggestions for further food security, nutrition, and health research, as well as policy-related implications, are also discussed.

Keywords: delta regions, coastal, food security, indicators, systematic review

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Authors: Rajkamal Ajmeri, Leena Mehta

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Growing magnitude of human trafficking is the indicatory symptom of ill society. Despite of many treaties, legislation and protocols control over human trafficking require additional attention. However, many Anti Human Trafficking Units (AHTU) are working throughout India but it is a fact that incidence pertaining to illegal human trade is not fully under control. Social work as discipline and practice base profession has a lot of concern about situation and the trafficked victims. United state put Indian in tier II watch list because they are not fully complying with the minimum standard of Trafficking Victims Protection laws but they are making a significant effort to bring themselves into compliance with those standards. In order to solve the issue, scientific research of experiences and opinions of government / non government machineries can play an effective role in raising the standard legislation for trafficked victims. Proper study can enhance understanding on various problems faced by government machineries. The study can help in developing the scientific model, which can effectively solve the problem in human trafficking field.

Keywords: human trafficking, legislations, victims, social work, government machinery

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