Search results for: geospatial data science

Authors: Deepak Singh, Rail Kuliev

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The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

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Authors: Paschal Arsein Mugabe

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This paper examines sustainable development planning in the context of environmental concerns in rural areas of the Tanzania. It challenges mainstream approaches to development, focusing instead upon transformative action for environmental justice. The goal is to help shape future sustainable development agendas in local government, international agencies and civil society organisations. Research methods: The approach of the study is geographical, but also involves various Trans-disciplinary elements, particularly from development studies, sociology and anthropology, management, geography, agriculture and environmental science. The research methods included thematic and questionnaire interviews, participatory tools such as focus group discussion, participatory research appraisal and expert interviews for primary data. Secondary data were gathered through the analysis of land use/cover data and official documents on climate, agriculture, marketing and health. Also several earlier studies that were made in the area provided an important reference base. Findings: The findings show that, agricultural sustainability in Tanzania appears likely to deteriorate as a consequence of climate change. Noteworthy differences in impacts across households are also present both by district and by income category. Also food security cannot be explained by climate as the only influencing factor. A combination of economic, political and socio-cultural context of the community are crucial. Conclusively, it is worthy knowing that people understand their relationship between climate change and their livelihood.

Keywords: agriculture, climate change, environment, sustainable development

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Authors: F. Amin, S. Feizi

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Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and next-generation network, however, are more exorbitant than improved customer relationship management. Next generation of networks are in a prime position to monetize rich supplies of customer information—while being mindful of legal and privacy issues. As data assets are transformed into new revenue streams will become integral to high performance.

Keywords: big data, next generation networks, network transformation, strategy

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Authors: Tessa Heeren

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The following proposal pertains to the complex process of successfully implementing health policies that are based on public health research. A systematic review was conducted by myself and faculty at the Cluj School of Public Health in Romania. The reviewed articles covered a wide range of topics, such as barriers and facilitators to multi-sector collaboration, differences in professional cultures, and systemic obstacles. The reviewed literature identified communication, collaboration, user-friendly dissemination, and documentation of processes in the execution of applied research as important themes for the promotion of evidence in the public health decision-making process. This proposal fits into the Academy Health National Health Policy conference because it identifies and examines differences between the worlds of research and politics. Implications and new insights for federal and/or state health policy: Recommendations made based on the findings of this research include using politically relevant levers to promote research (e.g. campaign donors, lobbies, established parties, etc.), modernizing dissemination practices, and reforms in which the involvement of external stakeholders is facilitated without relying on invitations from individual policy makers. Description of how evidence and/or data was or could be used: The reviewed articles illustrated shortcomings and areas for improvement in policy research processes and collaborative development. In general, the evidence base in the field of integrating research into policy lacks critical details of the actual process of developing evidence based policy. This shortcoming in logistical details creates a barrier for potential replication of collaborative efforts described in studies. Potential impact of the presentation for health policy: The reviewed articles focused on identifying barriers and facilitators that arise in cross sector collaboration, rather than the process and impact of integrating evidence into policy. In addition, the type of evidence used in policy was rarely specified, and widely varying interpretations of the definition of evidence complicated overall conclusions. Background: Using evidence to inform public health decision making processes has been proven effective; however, it is not clear how research is applied in practice. Aims: The objectives of the current study were to assess the extent to which evidence is used in public health decision-making process. Methods: To identify eligible studies, seven bibliographic databases, specifically, PubMed, Scopus, Cochrane Library, Science Direct, Web of Science, ClinicalKey, Health and Safety Science Abstract were screened (search dates: 1990 – September 2015); a general internet search was also conducted. Primary research and systematic reviews about the use of evidence in public health policy in Europe were included. The studies considered for inclusion were assessed by two reviewers, along with extracted data on objective, methods, population, and results. Data were synthetized as a narrative review. Results: Of 2564 articles initially identified, 2525 titles and abstracts were screened. Ultimately, 30 articles fit the research criteria by describing how or why evidence is used/not used in public health policy. The majority of included studies involved interviews and surveys (N=17). Study participants were policy makers, health care professionals, researchers, community members, service users, experts in public health.

Keywords: cross-sector, dissemination, health policy, policy implementation

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Authors: Apkar Salatian

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To relieve the burden of reasoning on a point to point basis, in many domains there is a need to reduce large and noisy data sets into trends for qualitative reasoning. In this paper we propose and describe a new architectural design pattern called REDUCER for reducing large and noisy data sets that can be tailored for particular situations. REDUCER consists of 2 consecutive processes: Filter which takes the original data and removes outliers, inconsistencies or noise; and Compression which takes the filtered data and derives trends in the data. In this seminal article, we also show how REDUCER has successfully been applied to 3 different case studies.

Keywords: design pattern, filtering, compression, architectural design

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Authors: Mario M. Figueroa de la Cruz, Claudia I. Solorzano, Raul Acosta, Ignacio Funes

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This technological development project seeks to create a tool that allows companies, in need of implementing a Data Center, intelligently determining factors for allocating resources support cooling and power supply (UPS) in its conception. The results should show clearly the speed, robustness and reliability of a system designed for deployment in environments where they must manage and protect large volumes of data.

Keywords: telecommunications, data center, fuzzy logic, expert systems

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Authors: Paulomi Polly Burey, Mark Lynch

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It has been shown that laboratory activities can help cement understanding of theoretical concepts, but it is difficult to deliver such an activity to an online cohort and issues such as occupational health and safety in the students’ learning environment need to be considered. Chemistry, in particular, is one of the sciences where practical experience is beneficial for learning, however typical university experiments may not be suitable for the learning environment of a distance learner. Food provides an ideal medium for demonstrating chemical concepts, and along with a few simple physical and virtual tools provided by educators, analytical chemistry can be experienced by distance learners. Food chemistry experiments were designed to be carried out in a home-based environment that 1) Had sufficient scientific rigour and skill-building to reinforce theoretical concepts; 2) Were safe for use at home by university students and 3) Had the potential to enhance student learning by linking simple hands-on laboratory activities with high-level virtual science. Two main components of the resources were developed, a home laboratory experiment component, and a virtual laboratory component. For the home laboratory component, students were provided with laboratory kits, as well as a list of supplementary inexpensive chemical items that they could purchase from hardware stores and supermarkets. The experiments used were typical proximate analyses of food, as well as experiments focused on techniques such as spectrophotometry and chromatography. Written instructions for each experiment coupled with video laboratory demonstrations were used to train students on appropriate laboratory technique. Data that students collected in their home laboratory environment was collated across the class through shared documents, so that the group could carry out statistical analysis and experience a full laboratory experience from their own home. For the virtual laboratory component, students were able to view a laboratory safety induction and advised on good characteristics of a home laboratory space prior to carrying out their experiments. Following on from this activity, students observed laboratory demonstrations of the experimental series they would carry out in their learning environment. Finally, students were embedded in a virtual laboratory environment to experience complex chemical analyses with equipment that would be too costly and sensitive to be housed in their learning environment. To investigate the impact of the intervention, students were surveyed before and after the laboratory series to evaluate engagement and satisfaction with the course. Students were also assessed on their understanding of theoretical chemical concepts before and after the laboratory series to determine the impact on their learning. At the end of the intervention, focus groups were run to determine which aspects helped and hindered learning. It was found that the physical experiments helped students to understand laboratory technique, as well as methodology interpretation, particularly if they had not been in such a laboratory environment before. The virtual learning environment aided learning as it could be utilized for longer than a typical physical laboratory class, thus allowing further time on understanding techniques.

Keywords: chemistry, food science, future pedagogy, STEM education

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Authors: Amy Gooden, Meshandren Naidoo

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Genetic research is not confined to a particular jurisdiction. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

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Authors: Karin Schoenpflug, Christine M. Klapeer

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In a large study for the Vienna City Council’s Antidiscrimination unit (WASt) an interdisciplinary team (in the fields of economics, sociology and political science) working with urban economics, critical citizenship studies, the sociology of work & inequality and urban political/human geography conducted an online survey asking LGBTIs (lesbians, gays, bisexuals, transgender and intersex people) in Vienna detailed questions on their quality-of-life, happiness and well-being. 3.161 persons responded and provided us with a rich data set concerning: 1) Labor market structures, discrimination, working conditions and employment practices (economic citizenship); 2) access to health care, welfare, education and safety in public spaces (social citizenship); 3) political participation as well as access to legal institutions (political citizenship). All those fields are important dimensions in regards to “full” citizenship and the well-being of the LGBTI population, but are also constitutive for the inclusion of sexual and gender minorities into the city population(s) of Vienna. Our data also allows us to map the sexual geography of Vienna as LGBTI communities are more likely to live in certain districts; some places are considered safe(r) and “friendlier”. In this way our work helps to fill a research gap connecting (urban) spaces and sexuality, and it produces new data and insights on the quality-of-life of this subpopulation. Our findings allow for urban (policy) planning and limiting violence and discrimination and improving the collective wellbeing and social cohesion.

Keywords: urban sexual geographies, LGBTI, socio-economic status, Vienna, sitizenship status

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Authors: Baris Can Yalcin

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Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

Keywords: design, mechatronics, motion sensor, data acquisition

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Authors: Ephraim Daka, Maxim Kotsemir

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The National system Innovation (NSI) have recently proliferated as a vehicle for addressing poverty and national competitiveness in the developing countries. While several governments in Sub-Saharan Africa have adopted the developed countries’ models of innovation to local conditions, the Zambian case is rather unique. This study highlights conceptual and socioeconomic challenges directed to the performances of the NSI. The paper analyses science and technology strategies with the inclusion of “innovation” and its effect towards improving socioeconomic elements. The authors reviewed STI policy and national strategy documents, followed by interviews compared to economical regional and national data sets. The NSI and its related to inter-linkages and support mechanism to socioeconomic development were explored.

Keywords: national system of innovation, socioeconomics, development, Zambia

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Authors: T. Santiboon, S. Tongbu, P. S. Saihong

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This study focuses on investigating students' perceptions of their physics classroom learning environments of their individualizations and their interactions with the instructional practicum in teaching physics of the master science trainee educational students for improving and creating attitude skills’ sustainable development toward physics for upper secondary educational students in Thailand. Associations between these perceptions and students' attitudes toward physics were also determined. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI) modified from the original Science Laboratory Environment Inventory. The 25-item Individualized Classroom Environment Questionnaire (ICEQ) was assessed those dimensions which distinguish individualized physics classrooms from convention on individualized open and inquiry-based education Teacher-student interactions were assessed with the 48-item Questionnaires on Teacher Interaction (QTI). Both these questionnaires have an Actual Form (assesses the class as it actually is) and a Preferred Form (asks the students what they would prefer their class to be like - the ideal situation). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) modified from the original Test Of Science-Related Attitude (TOSRA) The questionnaires were administered in three phases with the Custer Random Sampling technique to a sample consisted of 989 students in 28 physics classes from 10 schools at the grade 10, 11, and 12 levels in the Secondary Educational Service Area 26 (Maha Sarakham Province) and Area 27 (Roi-Et). Statistically significant differences were found between the students' perceptions of actual-1, actual-2 and preferred environments of their physics laboratory and distinguish individualized classrooms, and teacher interpersonal behaviors with their improving and creating attitudes skills’ sustainable development to their physics classes also were found. Predictions of the monitoring and evaluation of master science trainee educational students of their practicum in teaching physics; students’ skills developments of their physics achievements’ sustainable for the set of actual and preferred environments as a whole and physics related attitudes also were correlated. The R2 values indicate that 58%, 67%, and 84% of the variances in students’ attitudes to their actuale-1, actual-2 and preferred for the PLEI; 42%,science trainee educational students of their practicum in teaching physics; students’ skill developments of their physics achievements’ sustainable for the set of actual and preferred environments as a whole and physics related attitudes also were correlated. The R2 values indicate that 58%, 67%, and 84% of the variances in students’ attitudes to their actuale-1, actual-2 and preferred for the PLEI; 42%, 63%, and 72% for the ICEQ, and 38%, 59%, and 68% for the QTI in physics environment classes were attributable to their perceptions of their actual and preferred physics environments and their developing creative science skills’ sustainable toward physics, consequently. Based on all the findings, suggestions for improving the physics laboratory and individualized classes and teacher interpersonal behaviors with students' perceptions are provided of their improving and creating attitude skills’ sustainable development by the master science trainee educational students ’ instructional administrations.

Keywords: promotion, instructional model, qualitative method, reflective thinking, trainee teacher student

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Authors: Ashish Dhamaniya, Satish Chandra

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Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: normal distribution, percentile speed, speed spread ratio, traffic volume

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Authors: Ming Wei

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Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

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Authors: Elaine Wong Yee-Sing, Liaw Wee Tong

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Rapid transformations in demographic and socioeconomic shifts are leading to a growing global demand for health and beauty products and services that demands holistic concepts of well-being. In addition, technological breakthroughs such as internet of things make it convenient and offer innovative solutions for well-being and engage consumers to track their own health conditions and fitness goals. This 'new health economy' encompasses three key concepts: well-being, well-conditioned and well-shaped; which are shaped by wellness segments and goals that influence purchasing decisions of consumers. The research protocol aims to examine the feasibility, challenges, and capabilities in provision for each customer with an ecosystem, or platform, that organizes data and insights to create an individual health and fitness, nutrition, and beauty profile. Convenience sampling of 100 consumers residing in private housing within five major districts in Singapore will be selected to participate in the study. Statistical Package for Social Science 25 will be used to conduct descriptive statistics for quantitative data while qualitative data results using focus interviews, will be translated and transcribed to identify improvements in provision of these services. Rising income in emerging global markets is fuelling the demand for these general wellbeing products and services. Combined with technological advances, it is imperative to understand how these highly personalized services with integrated technology can be designed better to support consumer preferences; provide greater flexibility and high-quality service, and generate better health awareness among consumers.

Keywords: beauty, consumers, health, technology, wellness

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Authors: Omar Romero-Hernandez, Federico Castillo, Armando Sanchez, Sergio Romero, Andrea Romero, Michael Mitchell

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Environmental policies for resource conservation in rural areas include subsidies on services and social programs to cover living expenses. Government's expectation is that rural communities who benefit from social programs, such as payment for ecosystem services, are provided with an incentive to conserve natural resources and preserve natural sinks for greenhouse gases. At the same time, global climate change has affected the lives of people worldwide. The capability to adapt to global warming depends on the available resources and the standard of living, putting rural communities at a disadvantage. This paper explores whether rural entrepreneurship can represent a solution to resource conservation and global warming adaptation in rural communities. The research focuses on a sample of two coffee communities in Oaxaca, Mexico. Researchers used geospatial information contained in aerial photographs of the geographical areas of interest. Households were identified in the photos via the roofs of households and georeferenced via coordinates. From the household population, a random selection of roofs was performed and received a visit. A total of 112 surveys were completed, including questions of socio-demographics, perception to climate change and adaptation activities. The population includes two groups of study: entrepreneurs and non-entrepreneurs. Data was sorted, filtered, and validated. Analysis includes descriptive statistics for exploratory purposes and a multi-regression analysis. Outcomes from the surveys indicate that coffee farmers, who demonstrate entrepreneurship skills and hire employees, are more eager to adapt to climate change despite the extreme adverse socioeconomic conditions of the region. We show that farmers with entrepreneurial tendencies are more creative in using innovative farm practices such as the planting of shade trees, the use of live fencing, instead of wires, and watershed protection techniques, among others. This result counters the notion that small farmers are at the mercy of climate change and have no possibility of being able to adapt to a changing climate. The study also points to roadblocks that farmers face when coping with climate change. Among those roadblocks are a lack of extension services, access to credit, and reliable internet, all of which reduces access to vital information needed in today’s constantly changing world. Results indicate that, under some circumstances, funding and supporting entrepreneurship programs may provide more benefit than traditional social programs.

Keywords: entrepreneurship, global warming, rural communities, climate change adaptation

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

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Authors: L. Vujičić, Ž. Ivković, Ž. Boneta

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There is a widespread belief in everyday discourse that science subjects (physics, chemistry and biology) are, along with math, the most difficult school subjects in the education of an individual. This assumption is usually justified by the following facts: low GPA in these subjects, the number of pupils who fail these subjects is high in comparison to other subjects, and the number of pupils interested in continuing their studies in the fields with a focus on science subjects is lower compared to non-science-oriented fields. From that perspective, the project: “Could it be different? How do children explore it?” becomes extremely interesting because it is focused on young children and on the introduction of new methods, with aim of arousing interest in scientific literacy development in 10 kindergartens by applying the methodology of an action research, with an ethnographic approach. We define scientific literacy as a process of encouraging and nurturing the research and explorative spirit in children, as well as their natural potential and abilities that represent an object of scientific research: to learn about exploration by conducting exploration. Upon project completion, an evaluation questionnaire was created for the parents of the children who had participated in the project, as well as for those whose children had not been involved in the project. The purpose of the first questionnaire was to examine the level of satisfaction with the project implementation and its outcomes among those parents whose children had been involved in the project (N=142), while the aim of the second questionnaire was to find out how much the parents of the children not involved (N=154) in this activity were interested in this topic.

Keywords: documenting, early childhood education, evaluation questionnaire for parents, scientific literacy development

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Authors: Lola Rosalia Saavedra Guzman, Plamen Neytchev Netchev

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In general, agnosticism is perceived as an uncertainty between a well-structured (religious) belief (in some Christian or pagan deity) and its absolute and total absence, often causing the suspicion that an agnostic is an atheist, which is "reinsured" in case if their personal belief is wrong. All of this, along with the prevailing view among the naturalists that science has already demonstrated the inexistence of God, has compelled us to seek the foundation of agnosticism and faith in the contemporary formal human logic, advanced mathematics, and the natural sciences. Along the way, we will find that no natural science can demonstrate the existence of God, nor could it discard it for rational considerations, which show that there is something beyond. After all, it seems that the human intellect is insufficient to respond surely with yes or no to the existence of higher intelligences leaving unconditional faith as the only path to God for Christians and transcendent techniques, for pagan religious beliefs.

Keywords: agnosticism, formal logic, axioms and postulates, Gödel theorems, and logical faults

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Authors: M. Mohammed Raoof, A. Enkhtaivan, H. Aljuaid

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This study follows the design science research methodology to design and implement a smartphone application artifact. The developed artifact was evaluated through three phases. The System Usability Scale (SUS) metric was used for the evaluation. The designed artifact aims to spread awareness about reducing air pollution, decreasing lung cancer development, and checking the air quality status in Southern California Counties. Participants have been drawn for a pilot study to facilitate awareness of air pollution. The study found that smartphone applications have a beneficial effect on the study’s aims.

Keywords: air pollution, design science research, indoor air pollution, lung cancer, outdoor air pollution, smartphone application

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

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Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

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Authors: Dariusz Jacek Jakóbczak

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Mathematics and computer science are interested in methods of 2D curve interpolation and extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR) is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm, exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to build the orthogonal matrix operator and how to use it in a process of curve reconstruction.

Keywords: 2D data interpolation, hurwitz-radon matrices, MHR method, probabilistic modeling, curve extrapolation

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Authors: Kyle De Freitas, Margaret Bernard

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Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

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Authors: Z. Dedovets, M. Rodionov

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The goal of the modern education system is to prepare students to be able to adapt to ever-changing life situations. They must be able to acquire required knowledge independently; apply such knowledge in practice to solve various problems by using modern technologies; think critically and creatively; competently use information; be communicative, work in a team; and develop their own moral values, intellect and cultural awareness. As a result, the status of education significantly increases; new requirements to its quality have been formed. In recent years, the competency-based approach in education has become of significant interest. This approach is a strengthening of applied and practical characteristics of a school education and leads to the forming of the key students’ competencies which define their success in future life. In this article, the authors’ attention focuses on a range of key competencies, educational, informational and communicative and on the possibility to develop such competencies via STEM education. This research shows the change in students’ attitude towards scientific disciplines such as mathematics, general science, technology and engineering as a result of STEM education. Two-staged analyzes questionnaires completed by students of forms II to IV in the republic of Trinidad and Tobago allowed the authors to categorize students between two levels that represent students’ attitude to various disciplines. The significance of differences between selected levels was confirmed with the use of Pearsons’ chi-squared test. In summary, the analysis of obtained data makes it possible to conclude that STEM education has a great potential for development of core students’ competencies and encourages the development of positive student attitude towards the above mentioned above scientific disciplines.

Keywords: STEM, science, technology, engineering, mathematics, students’ competency, Pearson's chi-squared test

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Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

Abstract:

Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

Procedia PDF Downloads 88

Authors: Shivam Dubey, Vinit Srivastava, Abhay Singh Thakur, Rahul Vaish

Abstract:

The presence of organic dyes in water is a critical issue that poses a significant threat to the environment and human health. We have investigated the use of corona discharge as a potential method for degrading organic dyes in water. Methylene Blue dye was exposed to corona discharge, and its photo-absorbance was measured over time to determine the extent of degradation. The results depicted a decreased absorbance for the dye and the loss of the characteristic colour of methylene blue. The effects of various parameters, including current, voltage, gas phase, salinity, and electrode spacing, on the reaction rates, were investigated. The highest reaction rates were observed at the highest current and voltage (up to 10kV), lowest salinity, smallest electrode spacing, and an environment containing enhanced levels of oxygen. These findings have possible applications for science education curriculum. By investigating the use of corona discharge for destroying organic dyes, we can provide students with a practical application of scientific principles that they can apply to real-world problems. This research can demonstrate the importance of understanding the chemical and physical properties of organic dyes and the effects of corona discharge on their degradation and provide a holistic understanding of the applications of scientific research. Moreover, our study also emphasizes the importance of considering the various parameters that can affect reaction rates. By investigating the effects of current, voltage, matter phase, salinity, and electrode spacing, we can provide students with an opportunity to learn about the importance of experimental design and how to evade constraints that can limit meaningful results. In conclusion, this study has the potential to provide valuable insights into the use of corona discharge for destroying organic dyes in water and has significant implications for science education. By highlighting the practical applications of scientific principles, experimental design, and the importance of considering various parameters, this research can help students develop critical thinking skills and prepare them for future careers in science and engineering.

Keywords: dye degradation, corona discharge, science education, hands-on learning, chemical education

Procedia PDF Downloads 56

Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

Abstract:

Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

Procedia PDF Downloads 609

Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

Abstract:

In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

Procedia PDF Downloads 483