Search results for: data section
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26200

Search results for: data section

25570 Investigation of the Technological Demonstrator 14x B in Different Angle of Attack in Hypersonic Velocity

Authors: Victor Alves Barros Galvão, Israel Da Silveira Rego, Antonio Carlos Oliveira, Paulo Gilberto De Paula Toro

Abstract:

The Brazilian hypersonic aerospace vehicle 14-X B, VHA 14-X B, is a vehicle integrated with the hypersonic airbreathing propulsion system based on supersonic combustion (scramjet), developing in Aerothermodynamics and hypersonic Prof. Henry T. Nagamatsu Laboratory, to conduct demonstration in atmospheric flight at the speed corresponding to Mach number 7 at an altitude of 30km. In the experimental procedure the hypersonic shock tunnel T3 was used, installed in that laboratory. This device simulates the flow over a model is fixed in the test section and can also simulate different atmospheric conditions. The scramjet technology offers substantial advantages to improve aerospace vehicle performance which flies at a hypersonic speed through the Earth's atmosphere by reducing fuel consumption on board. Basically, the scramjet is an aspirated aircraft engine fully integrated that uses oblique/conic shock waves generated during hypersonic flight, to promote the deceleration and compression of atmospheric air in scramjet inlet. During the hypersonic flight, the vehicle VHA 14-X will suffer atmospheric influences, promoting changes in the vehicle's angles of attack (angle that the mean line of vehicle makes with respect to the direction of the flow). Based on this information, a study is conducted to analyze the influences of changes in the vehicle's angle of attack during the atmospheric flight. Analytical theoretical analysis, simulation computational fluid dynamics and experimental investigation are the methodologies used to design a technological demonstrator prior to the flight in the atmosphere. This paper considers analysis of the thermodynamic properties (pressure, temperature, density, sound velocity) in lower surface of the VHA 14-X B. Also, it considers air as an ideal gas and chemical equilibrium, with and without boundary layer, considering changes in the vehicle's angle of attack (positive and negative in relation to the flow) and bi-dimensional expansion wave theory at the expansion section (Theory of Prandtl-Meyer).

Keywords: angle of attack, experimental hypersonic, hypersonic airbreathing propulsion, Scramjet

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25569 A Method of Detecting the Difference in Two States of Brain Using Statistical Analysis of EEG Raw Data

Authors: Digvijaysingh S. Bana, Kiran R. Trivedi

Abstract:

This paper introduces various methods for the alpha wave to detect the difference between two states of brain. One healthy subject participated in the experiment. EEG was measured on the forehead above the eye (FP1 Position) with reference and ground electrode are on the ear clip. The data samples are obtained in the form of EEG raw data. The time duration of reading is of one minute. Various test are being performed on the alpha band EEG raw data.The readings are performed in different time duration of the entire day. The statistical analysis is being carried out on the EEG sample data in the form of various tests.

Keywords: electroencephalogram(EEG), biometrics, authentication, EEG raw data

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25568 The Effect of Cooperative Learning on Academic Achievement of Grade Nine Students in Mathematics: The Case of Mettu Secondary and Preparatory School

Authors: Diriba Gemechu, Lamessa Abebe

Abstract:

The aim of this study was to examine the effect of cooperative learning method on student’s academic achievement and on the achievement level over a usual method in teaching different topics of mathematics. The study also examines the perceptions of students towards cooperative learning. Cooperative learning is the instructional strategy in which pairs or small groups of students with different levels of ability work together to accomplish a shared goal. The aim of this cooperation is for students to maximize their own and each other learning, with members striving for joint benefit. The teacher’s role changes from wise on the wise to guide on the side. Cooperative learning due to its influential aspects is the most prevalent teaching-learning technique in the modern world. Therefore the study was conducted in order to examine the effect of cooperative learning on the academic achievement of grade 9 students in Mathematics in case of Mettu secondary school. Two sample sections are randomly selected by which one section served randomly as an experimental and the other as a comparison group. Data gathering instruments are achievement tests and questionnaires. A treatment of STAD method of cooperative learning was provided to the experimental group while the usual method is used in the comparison group. The experiment lasted for one semester. To determine the effect of cooperative learning on the student’s academic achievement, the significance of difference between the scores of groups at 0.05 levels was tested by applying t test. The effect size was calculated to see the strength of the treatment. The student’s perceptions about the method were tested by percentiles of the questionnaires. During data analysis, each group was divided into high and low achievers on basis of their previous Mathematics result. Data analysis revealed that both the experimental and comparison groups were almost equal in Mathematics at the beginning of the experiment. The experimental group out scored significantly than comparison group on posttest. Additionally, the comparison of mean posttest scores of high achievers indicates significant difference between the two groups. The same is true for low achiever students of both groups on posttest. Hence, the result of the study indicates the effectiveness of the method for Mathematics topics as compared to usual method of teaching.

Keywords: academic achievement, comparison group, cooperative learning, experimental group

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25567 A Study on Big Data Analytics, Applications and Challenges

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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25566 A Study on Big Data Analytics, Applications, and Challenges

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

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25565 Improved K-Means Clustering Algorithm Using RHadoop with Combiner

Authors: Ji Eun Shin, Dong Hoon Lim

Abstract:

Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

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25564 Hydrocarbon Source Rocks of the Maragh Low

Authors: Elhadi Nasr, Ibrahim Ramadan

Abstract:

Biostratigraphical analyses of well sections from the Maragh Low in the Eastern Sirt Basin has allowed high resolution correlations to be undertaken. Full integration of this data with available palaeoenvironmental, lithological, gravity, seismic, aeromagnetic, igneous, radiometric and wireline log information and a geochemical analysis of source rock quality and distribution has led to a more detailed understanding of the geological and the structural history of this area. Pre Sirt Unconformity two superimposed rifting cycles have been identified. The oldest is represented by the Amal Group of sediments and is of Late Carboniferous, Kasimovian / Gzelian to Middle Triassic, Anisian age. Unconformably overlying is a younger rift cycle which is represented the Sarir Group of sediments and is of Early Cretaceous, late Neocomian to Aptian in age. Overlying the Sirt Unconformity is the marine Late Cretaceous section. An assessment of pyrolysis results and a palynofacies analysis has allowed hydrocarbon source facies and quality to be determined. There are a number of hydrocarbon source rock horizons in the Maragh Low, these are sometimes vertically stacked and they are of fair to excellent quality. The oldest identified source rock is the Triassic Shale, this unit is unconformably overlain by sandstones belonging to the Sarir Group and conformably overlies a Triassic Siltstone unit. Palynological dating of the Triassic Shale unit indicates a Middle Triassic, Anisian age. The Triassic Shale is interpreted to have been deposited in a lacustrine palaeoenvironment. This particularly is evidenced by the dark, fine grained, organic rich nature of the sediment and is supported by palynofacies analysis and by the recovery of fish fossils. Geochemical analysis of the Triassic Shale indicates total organic carbon varying between 1.37 and 3.53. S2 pyrolysate yields vary between 2.15 mg/g and 6.61 mg/g and hydrogen indices vary between 156.91 and 278.91. The source quality of the Triassic Shale varies from being of fair to very good / rich. Linked to thermal maturity it is now a very good source for light oil and gas. It was once a very good to rich oil source. The Early Barremian Shale was also deposited in a lacustrine palaeoenvironment. Recovered palynomorphs indicate an Early Cretaceous, late Neocomian to early Barremian age. The Early Barremian Shale is conformably underlain and overlain by sandstone units belonging to the Sarir Group of sediments which are also of Early Cretaceous age. Geochemical analysis of the Early Barremian Shale indicates that it is a good oil source and was originally very good. Total organic carbon varies between 3.59% and 7%. S2 varies between 6.30 mg/g and 10.39 mg/g and the hydrogen indices vary between 148.4 and 175.5. A Late Barremian Shale unit of this age has also been identified in the central Maragh Low. Geochemical analyses indicate that total organic carbon varies between 1.05 and 2.38%, S2 pyrolysate between 1.6 and 5.34 mg/g and the hydrogen index between 152.4 and 224.4. It is a good oil source rock which is now mature. In addition to the non marine hydrocarbon source rocks pre Sirt Unconformity, three formations in the overlying Late Cretaceous section also provide hydrocarbon quality source rocks. Interbedded shales within the Rachmat Formation of Late Cretaceous, early Campanian age have total organic carbon ranging between, 0.7 and 1.47%, S2 pyrolysate varying between 1.37 and 4.00 mg/g and hydrogen indices varying between 195.7 and 272.1. The indication is that this unit would provide a fair gas source to a good oil source. Geochemical analyses of the overlying Tagrifet Limestone indicate that total organic carbon varies between 0.26% and 1.01%. S2 pyrolysate varies between 1.21 and 2.16 mg/g and hydrogen indices vary between 195.7 and 465.4. For the overlying Sirt Shale Formation of Late Cretaceous, late Campanian age, total organic carbon varies between 1.04% and 1.51%, S2 pyrolysate varies between 4.65 mg/g and 6.99 mg/g and the hydrogen indices vary between 151 and 462.9. The study has proven that both the Sirt Shale Formation and the Tagrifet Limestone are good to very good and rich sources for oil in the Maragh Low. High resolution biostratigraphical interpretations have been integrated and calibrated with thermal maturity determinations (Vitrinite Reflectance (%Ro), Spore Colour Index (SCI) and Tmax (ºC) and the determined present day geothermal gradient of 25ºC / Km for the Maragh Low. Interpretation of generated basin modelling profiles allows a detailed prediction of timing of maturation development of these source horizons and leads to a determination of amounts of missing section at major unconformities. From the results the top of the oil window (0.72% Ro) is picked as high as 10,700’ and the base of the oil window (1.35% Ro) assuming a linear trend and by projection is picked as low as 18,000’ in the Maragh Low. For the Triassic Shale the early phase of oil generation was in the Late Palaeocene / Early to Middle Eocene and the main phase of oil generation was in the Middle to Late Eocene. The Early Barremian Shale reached the main phase of oil generation in the Early Oligocene with late generation being reached in the Middle Miocene. For the Rakb Group section (Rachmat Formation, Tagrifet Limestone and Sirt Shale Formation) the early phase of oil generation started in the Late Eocene with the main phase of generation being between the Early Oligocene and the Early Miocene. From studying maturity profiles and from regional considerations it can be predicted that up to 500’ of sediment may have been deposited and eroded by the Sirt Unconformity in the central Maragh Low while up to 2000’ of sediment may have been deposited and then eroded to the south of the trough.

Keywords: Geochemical analysis of the source rocks from wells in Eastern Sirt Basin.

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25563 Improving the Gain of a Multiband Antenna by Adding an Artificial Magnetic Conductor Metasurface

Authors: Amira Bousselmi

Abstract:

This article presents a PIFA antenna designed for geolocation applications (GNSS) operating on 1.278 GHz, 2.8 GHz, 5.7 GHz and 10 GHz. To improve the performance of the antenna, an artificial magnetic conductor structure (AMC) was used. Adding the antenna with AMC resulted in a measured gain of 4.78 dBi. The results of simulations and measurements are presented. CST Microwave Studio is used to design and compare antenna performance. An antenna design methodology, design and characterization of the AMC surface are described as well as the simulated and measured performances of the AMC antenna are then discussed. Finally, in Section V, there is a conclusion.

Keywords: antenna multiband, global navigation system, AMC, Galeleo

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25562 Health Policies towards Refugees: A Comparison of Policy Implementations from the EU and Turkey

Authors: Pelin Sonmez

Abstract:

Health services provided to refugees and asylum seekers are very important and of priority due to their physical damages during the war and conflict situation, possible diseases in migration journey and negative psychological mood. However, there are very poor international standards in regards to providing health services to these people, which in return cause each country to differ their regulations. United Nations Sustainable Development Goals that are in effect as of 2016 assure that attention should be provided to non-citizen vulnerable groups in terms of health policies and they should be included in the global development, thereby aims to decrease the problems arising from providing health services to refugees. Though, we should not forget that these are the recent and yet uncertain attempts, mostly, as a result of Syrian War's forced migration wave. As an attempt to reveal different attitudes of international actors, this study compares/analyzes health services provided to refugees and asylum seekers on the basis of Turkey-EU policy implementations. While doing so, two research data will be focused upon. In this globe, results of the focus group interviews and a field study in a specific work (from its health related section) which was done in 2017 to 5000 Syrian women living in Turkey and presented to Republic of Turkey Disaster and Emergency Management Presidency will be utilized.

Keywords: European Union, health policies, refugee, Syrian women, Turkey

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25561 Framework for Integrating Big Data and Thick Data: Understanding Customers Better

Authors: Nikita Valluri, Vatcharaporn Esichaikul

Abstract:

With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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25560 Reproductive Health of Women After Taking Chemotherapy for Gestational Trophoblastic Disease

Authors: Ezeh Chukwunonso Peter Excel, Akruti Vg

Abstract:

Aim/Background: To show that even after undergoing 1-5 courses of chemotherapy for Gestational Trophoblastic Disease (GTD) reproductive health of women is intact and they conceive successfully after it. Method: Retrospective cohort analysis using data from the Lugansk regional maternity hospital database of years 1993-2013, which shows n=18 females had GTD and underwent 1-5 courses of chemotherapy. Results and Discussion: Frequency of GTD was rare. All 18 patients (pts) belong to age group of 17-39 years, covering wide range of reproductive age. Out of 18 pts, 15 had hydatidiform mole (HM) while other 3 had choriocarcinoma (CC). In anamnesis, among CC pts, 1 had early pre-eclampsia at 24 weeks and 1 had 4th week of late postpartum (PP) bleeding, while all HM pts had genital inflammatory diseases, 1 pt of HM during follow-up had High hCG and 3 times curettage in 5 months. 18 women became pregnant for 25 times after chemotherapy. Chemotherapy was given under indication of either high level of HCG, luteal cyst >6cm or path-morphological results of curettage. CC 3 pts had (2 spontaneous abortions (SA), 2 term cesarean section (CS), 1 preterm CS). HM 15 pts had (3 artificial abortion, 2 SA, 7CS (5 term and 2 preterm), 8 vaginal deliveries (7 term and 1 preterm)). Conclusion: During our research we got 22.2% preterm deliveries and 55.6% CS which is higher than the normal cases, but still all the 18 women were able to have kids successfully after chemotherapy. So we can conclude that chemotherapy for GTD was successful in keeping the reproductive health of women intact.

Keywords: reproductive health, chemotherapy, gestational trophoblastic disease, women

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25559 Incremental Learning of Independent Topic Analysis

Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

Abstract:

In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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25558 Open Data for e-Governance: Case Study of Bangladesh

Authors: Sami Kabir, Sadek Hossain Khoka

Abstract:

Open Government Data (OGD) refers to all data produced by government which are accessible in reusable way by common people with access to Internet and at free of cost. In line with “Digital Bangladesh” vision of Bangladesh government, the concept of open data has been gaining momentum in the country. Opening all government data in digital and customizable format from single platform can enhance e-governance which will make government more transparent to the people. This paper presents a well-in-progress case study on OGD portal by Bangladesh Government in order to link decentralized data. The initiative is intended to facilitate e-service towards citizens through this one-stop web portal. The paper further discusses ways of collecting data in digital format from relevant agencies with a view to making it publicly available through this single point of access. Further, possible layout of this web portal is presented.

Keywords: e-governance, one-stop web portal, open government data, reusable data, web of data

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25557 The Lived Experiences of Fathers with Children Who Have Cerebral Palsy: An Interpretative Phenomenological Analysis

Authors: Krizette Ladera

Abstract:

Fathers are there not only to provide the financial stability of a family but a father is also there to provide the love and support that usually people would see as the mother’s responsibility. To describe the lived experiences and how fathers make sense of their lived experiences with their children who have cerebral palsy is the main objective of the study. A qualitative research using a thematic analysis was used for the study. The qualitative research focused on the personal narratives, self-report and expression of the participant’s memory in terms of how they tell their stories. The interpretative phenomenological analysis was used to focus on the experience of the participants on how they will describe their experiences, and to also add on that the IPA will also attempt to describe and explain the meaning of human experiences using interview, specifically on the father who have a child that suffers from cerebral palsy. For the sampling technique, the snowball technique was used to gather participants from the referral of other participants. The five non-randomly selected fathers will be served as the participants for the research. A self-made interview with an open-ended question was used as the research instrument; it includes profiling of the respondent as well as their experiences in taking care of their child that suffers from cerebral palsy. In analyzing a data, the researcher used the thematic analysis where in the interview was made into a transcript, then it was organized and divided themes. After that, the relations of each themes, was identified and it was later documented and translated into written text format using thematic grouping. Finally, the researcher analyzed each data according to its themes and put it in a table to be presented in the result section of the study And as for the result of the study, the researcher was able to come up with the four (4) main themes that most of the participants experienced and those are: The experiences in finding out about the condition of the Child, disclosing the condition of the child to the family and its emotional effect, The experiences of living the day of day realities in providing the physical, financial, emotional and a well balanced environment to the child, and the religious perspectives of the fathers. Along with those four (4) themes comes the subtheme which explains the themes in a more detailed explanation.

Keywords: cerebral palsy, children, fathers, lived experiences

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25556 Resource Framework Descriptors for Interestingness in Data

Authors: C. B. Abhilash, Kavi Mahesh

Abstract:

Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

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25555 Data Mining Practices: Practical Studies on the Telecommunication Companies in Jordan

Authors: Dina Ahmad Alkhodary

Abstract:

This study aimed to investigate the practices of Data Mining on the telecommunication companies in Jordan, from the viewpoint of the respondents. In order to achieve the goal of the study, and test the validity of hypotheses, the researcher has designed a questionnaire to collect data from managers and staff members from main department in the researched companies. The results shows improvements stages of the telecommunications companies towered Data Mining.

Keywords: data, mining, development, business

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25554 The Impact of System and Data Quality on Organizational Success in the Kingdom of Bahrain

Authors: Amal M. Alrayes

Abstract:

Data and system quality play a central role in organizational success, and the quality of any existing information system has a major influence on the effectiveness of overall system performance.Given the importance of system and data quality to an organization, it is relevant to highlight their importance on organizational performance in the Kingdom of Bahrain. This research aims to discover whether system quality and data quality are related, and to study the impact of system and data quality on organizational success. A theoretical model based on previous research is used to show the relationship between data and system quality, and organizational impact. We hypothesize, first, that system quality is positively associated with organizational impact, secondly that system quality is positively associated with data quality, and finally that data quality is positively associated with organizational impact. A questionnaire was conducted among public and private organizations in the Kingdom of Bahrain. The results show that there is a strong association between data and system quality, that affects organizational success.

Keywords: data quality, performance, system quality, Kingdom of Bahrain

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25553 Cloud Computing in Data Mining: A Technical Survey

Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

Abstract:

Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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25552 Cross-border Data Transfers to and from South Africa

Authors: Amy Gooden, Meshandren Naidoo

Abstract:

Genetic research and transfers of big data are not confined to a particular jurisdiction, but there is a lack of clarity regarding the legal requirements for importing and exporting such data. 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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25551 The Study of Security Techniques on Information System for Decision Making

Authors: Tejinder Singh

Abstract:

Information system is the flow of data from different levels to different directions for decision making and data operations in information system (IS). Data can be violated by different manner like manual or technical errors, data tampering or loss of integrity. Security system called firewall of IS is effected by such type of violations. The flow of data among various levels of Information System is done by networking system. The flow of data on network is in form of packets or frames. To protect these packets from unauthorized access, virus attacks, and to maintain the integrity level, network security is an important factor. To protect the data to get pirated, various security techniques are used. This paper represents the various security techniques and signifies different harmful attacks with the help of detailed data analysis. This paper will be beneficial for the organizations to make the system more secure, effective, and beneficial for future decisions making.

Keywords: information systems, data integrity, TCP/IP network, vulnerability, decision, data

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25550 Data Integration with Geographic Information System Tools for Rural Environmental Monitoring

Authors: Tamas Jancso, Andrea Podor, Eva Nagyne Hajnal, Peter Udvardy, Gabor Nagy, Attila Varga, Meng Qingyan

Abstract:

The paper deals with the conditions and circumstances of integration of remotely sensed data for rural environmental monitoring purposes. The main task is to make decisions during the integration process when we have data sources with different resolution, location, spectral channels, and dimension. In order to have exact knowledge about the integration and data fusion possibilities, it is necessary to know the properties (metadata) that characterize the data. The paper explains the joining of these data sources using their attribute data through a sample project. The resulted product will be used for rural environmental analysis.

Keywords: remote sensing, GIS, metadata, integration, environmental analysis

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25549 Placenta A Classical Caesarean Section with Peripartum Hysterectomy at 27+3 Weeks Gestation For Placnta Accreta

Authors: Huda Abdelrhman Osman Ahmed, Paul Feyi Waboso

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Introduction: Placenta accreta spectrum (PAS) disorders present a significant challenge in obstetric management due to the high risk of hemorrhage and potential complications at delivery. This case describes a 27+3 weeks gestation in a patient with placenta accreta managed with classical cesarean section and peripartum hysterectomy. Case Description: AGravida 4P3 patient presented at 27+3 weeks gestation with painless, unprovoked vaginal bleeding and an estimated blood loss (EBL) of 300 mL. At the 20+5 week anomaly scan, a placenta previa was identified anterior, covering the os anterior uterus and containing lacunae with signs of myometrial thinning. At a 24+1 week scan conducted at a tertiary center, further imaging indicated placenta increta with invasion into the myometrium and potential areas of placenta percreta. The patient’s past obstetric history included three previous cesarean sections, with no significant medical or surgical history. Social history revealed heavy smoking but no alcohol use. No drug allergies were reported. Given the risks associated with PAS, a management plan was formulated, including an MRI at a later stage and cesarean delivery with a possible hysterectomy between 34-36 weeks. However, at 27+3 weeks, the patient experienced another episode of vaginal bleeding EBL 500 ml, necessitating immediate intervention. Management: As the patient was unstable, she was not transferred to the tertiary center. Completed and informed consent was obtained. MDT planning-group and cross-matching 4 units, uterotonics. Tranexamic acid blood products, cryo, cell salvage, 2 obstetric consultants and an anesthetic consultant, blood bank aware and hematologist. HDU bed and ITU availability. This study assisted in performing a classical Caesarean section, Where the urologist inserted JJ ureteric stents. Following this, we also assisted in a total abdominal hysterectomy with the conservation of ovaries. 4 units RBC and 1 unit FFP were transfused. The total blood loss was 2.3 L. Outcome: The procedure successfully achieved hemostasis, and the neonate was delivered with subsequent transfer to a neonatal intensive care unit for management. The patient’s postoperative course was monitored closely with no immediate complications. Discussion: This case highlights the complexity and urgency in managing placenta accreta spectrum disorders, particularly with the added challenges posed by remote location and limited tertiary support. The need for rapid decision-making and interdisciplinary coordination is emphasized in such high-risk obstetric cases. The case also underscores the potential for surgical intervention and the importance of family involvement in emergent care decisions. Conclusion: Placenta accreta spectrum disorders demand meticulous planning and timely intervention. This case contributes to understanding PAS management at earlier gestational ages and provides insights into the challenges posed by access to tertiary care, especially in urgent situations.

Keywords: Accreta, Hysterectomy, 3MDT, prematurity

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25548 Analysis of Genomics Big Data in Cloud Computing Using Fuzzy Logic

Authors: Mohammad Vahed, Ana Sadeghitohidi, Majid Vahed, Hiroki Takahashi

Abstract:

In the genomics field, the huge amounts of data have produced by the next-generation sequencers (NGS). Data volumes are very rapidly growing, as it is postulated that more than one billion bases will be produced per year in 2020. The growth rate of produced data is much faster than Moore's law in computer technology. This makes it more difficult to deal with genomics data, such as storing data, searching information, and finding the hidden information. It is required to develop the analysis platform for genomics big data. Cloud computing newly developed enables us to deal with big data more efficiently. Hadoop is one of the frameworks distributed computing and relies upon the core of a Big Data as a Service (BDaaS). Although many services have adopted this technology, e.g. amazon, there are a few applications in the biology field. Here, we propose a new algorithm to more efficiently deal with the genomics big data, e.g. sequencing data. Our algorithm consists of two parts: First is that BDaaS is applied for handling the data more efficiently. Second is that the hybrid method of MapReduce and Fuzzy logic is applied for data processing. This step can be parallelized in implementation. Our algorithm has great potential in computational analysis of genomics big data, e.g. de novo genome assembly and sequence similarity search. We will discuss our algorithm and its feasibility.

Keywords: big data, fuzzy logic, MapReduce, Hadoop, cloud computing

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25547 Forthcoming Big Data on Smart Buildings and Cities: An Experimental Study on Correlations among Urban Data

Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

Abstract:

Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: big data, machine learning, ontology model, urban data model

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25546 Effect of Climate Change on Rainfall Induced Failures for Embankment Slopes in Timor-Leste

Authors: Kuo Chieh Chao, Thishani Amarathunga, Sangam Shrestha

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Rainfall induced slope failures are one of the most damaging and disastrous natural hazards which occur frequently in the world. This type of sliding mainly occurs in the zone above the groundwater level in silty/sandy soils. When the rainwater begins to infiltrate into the vadose zone of the soil, the negative pore-water pressure tends to decrease and reduce the shear strength of soil material. Climate change has resulted in excessive and unpredictable rainfall in all around the world, resulting in landslides with dire consequences to human lives and infrastructure. Such problems could be overcome by examining in detail the causes for such slope failures and recommending effective repair plans for vulnerable locations by considering future climatic change. The selected area for this study is located in the road rehabilitation section from Maubara to Mota Ain road in Timor-Leste. Slope failures and cracks have occurred in 2013 and after repairs reoccurred again in 2017 subsequent to heavy rains. Both observed and future predicted climate data analyses were conducted to understand the severe precipitation conditions in past and future. Observed climate data were collected from NOAA global climate data portal. CORDEX data portal was used to collect Regional Climate Model (RCM) future predicted climate data. Both observed and RCM data were extracted to location-based data using ArcGIS Software. Linear scaling method was used for the bias correction of future data and bias corrected climate data were assigned to GeoStudio Software. Precipitations of wet seasons (December to March ) in 2007 to 2013 is higher than 2001-2006 period and it is more than nearly 40% higher precipitation than usual monthly average precipitation of 160mm.The results of seepage analyses which were carried out using SEEP/W model with observed climate, clearly demonstrated that the pore water pressure within the fill slope was significantly increased due to the increase of the infiltration during the wet season of 2013.One main Regional Climate Models (RCM) was analyzed in order to predict future climate variation under two Representative Concentration Pathways (RCPs).In the projected period of 76 years ahead from 2014, shows that the amount of precipitation is considerably getting higher in the future in both RCP 4.5 and RCP 8.5 emission scenarios. Critical pore water pressure conditions during 2014-2090 were used in order to recommend appropriate remediation methods. Results of slope stability analyses indicated that the factor of safety of the fill slopes was reduced from 1.226 to 0.793 during the dry season to wet season in 2013.Results of future slope stability which were obtained using SLOPE/W model for the RCP emissions scenarios depict that, the use of tieback anchors and geogrids in slope protection could be effective in increasing the stability of slopes to an acceptable level during the wet seasons. Moreover, methods and procedures like monitoring of slopes showing signs or susceptible for movement and installing surface protections could be used to increase the stability of slopes.

Keywords: climate change, precipitation, SEEP/W, SLOPE/W, unsaturated soil

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25545 Data-driven Decision-Making in Digital Entrepreneurship

Authors: Abeba Nigussie Turi, Xiangming Samuel Li

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Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship

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25544 Corporate Social Responsibility and Corporate Reputation: A Bibliometric Analysis

Authors: Songdi Li, Louise Spry, Tony Woodall

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Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.

Keywords: corporate social responsibility, corporate reputation, bibliometric analysis, software program

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25543 Furnishing Ancillary Alternatives for High Speed Corridors and Pedestrian Crossing: Elevated Cycle Track, an Expedient to Urban Space Prototype in New Delhi

Authors: Suneet Jagdev, Hrishabh Amrodia, Siddharth Menon, Abhishek Singh, Mansi Shivhare

Abstract:

Delhi, the National Capital, has undergone a surge in development rate, consequently engendering an unprecedented increase in population. Over the years the city has transformed into a car-centric infrastructure with high-speed corridors, flyovers and fast lanes. A considerable section of the population is hankering to rehabilitate to the good old cycling days, in order to contribute towards a green environment as well as to maintain their physical well-being. Furthermore, an extant section of Delhi’s population relies on cycles as their primary means of commuting in the city. Delhi has the highest number of cyclists and second highest number of pedestrians in the country. However, the tumultuous problems of unregulated traffic, inadequate space on roads, adverse weather conditions stifle them to opt for cycling. Lately, the city has been facing a conglomeration of problems such as haphazard traffic movement, clogged roads, congestion, pollution, accidents, safety issues, etc. In 1957, Delhi’s cyclists accounted for 36 per cent of trips which dropped down to a mere 4 per cent in 2008. The declining rate is due to unsafe roads and lack of proper cycle lanes. Now as the 10 percent of the city has cycle tracks. There is also a lack of public recreational activities in the city. These conundrums incite the need of a covered elevated cycling bridge track to facilitate the safe and smooth cycle commutation in the city which would also serve the purpose of an alternate urban public space over the cycle bridge reducing the cost as well as the space requirement for the same, developing a user–friendly transportation and public interaction system for urban areas in the city. Based on the archival research methodologies, the following research draws information and extracts records from the data accounts of the Delhi Metro Rail Corporation Ltd. as well as the Centre for Science and Environment, India. This research will predominantly focus on developing a prototype design for high speed elevated bicycle lanes based on different road typologies, which can be replicated with minor variations in similar situations, all across the major cities of our country including the proposed smart cities. Furthermore, how these cycling lanes could be utilized for the place making process accommodating cycle parking and renting spaces, public recreational spaces, food courts as well as convenient shopping facilities with appropriate optimization. How to preserve and increase the share of smooth and safe cycling commute cycling for the routine transportation of the urban community of the polluted capital which has been on a steady decline over the past few decades.

Keywords: bicycle track, prototype, road safety, urban spaces

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25542 Cryptographic Protocol for Secure Cloud Storage

Authors: Luvisa Kusuma, Panji Yudha Prakasa

Abstract:

Cloud storage, as a subservice of infrastructure as a service (IaaS) in Cloud Computing, is the model of nerworked storage where data can be stored in server. In this paper, we propose a secure cloud storage system consisting of two main components; client as a user who uses the cloud storage service and server who provides the cloud storage service. In this system, we propose the protocol schemes to guarantee against security attacks in the data transmission. The protocols are login protocol, upload data protocol, download protocol, and push data protocol, which implement hybrid cryptographic mechanism based on data encryption before it is sent to the cloud, so cloud storage provider does not know the user's data and cannot analysis user’s data, because there is no correspondence between data and user.

Keywords: cloud storage, security, cryptographic protocol, artificial intelligence

Procedia PDF Downloads 357
25541 Decentralized Data Marketplace Framework Using Blockchain-Based Smart Contract

Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

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Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

Procedia PDF Downloads 158