Search results for: longitudinal data

Authors: C. S. Seema, P. R. Prince

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The characterization of spatio-temporal inhomogeneities occurring in the ionospheric F₂ layer is remarkable since these variations are direct consequences of electrodynamical coupling between magnetosphere and solar events. The temporal and spatial variations of the F₂ layer, which occur with a period of several days or even years, mainly owe to geomagnetic and meteorological activities. The hourly F₂ layer critical frequency (foF2) over 23rd solar cycle (1996-2008) of three ionosonde stations (Wakkanai, Kokunbunji, and Okinawa) in northern hemisphere, which falls within same longitudinal span, is analyzed using continuous wavelet techniques. Morlet wavelet is used to transform continuous time series data of foF2 to a two dimensional time-frequency space, quantifying the time evolution of the oscillatory modes. The presence of significant time patterns (periodicities) at a particular time period and the time location of each periodicity are detected from the two-dimensional representation of the wavelet power, in the plane of scale and period of the time series. The mean strength of each periodicity over the entire period of analysis is studied using global wavelet spectrum. The quasi biennial, annual, semiannual, 27 day, diurnal and 12 hour variations of foF2 are clearly evident in the wavelet power spectra in all the three stations. Critical frequency oscillations with multi-day periods (2-3 days and 9 days in the low latitude station, 6-7 days in all stations and 15 days in mid-high latitude station) are also superimposed over large time scaled variations.

Keywords: continuous wavelet analysis, critical frequency, ionosphere, solar cycle

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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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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Authors: Gali Moritz, Jacqueline H. Becker, Jyoti V. Ankam, Kimberly Arcoleo, Matthew Wysocki, Roee Holtzer, Juan Wisnivesky, Paula J. Busse, Alex D. Federman, Sunit P. Jariwala, Jonathan M. Feldman

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Objective: Cognitive impairment (CI), whose incidence is greater among ethnic/racial minorities, is a significant barrier to asthma self-management (SM) behaviors and outcomes in older adults. The aim of this study was to examine the relationships between CI, assessed using the Montreal Cognitive Assessment (MoCA), and asthma SM behaviors and outcomes in a sample of predominantly Black and Hispanic participants. Additionally, we evaluated whether using two different MoCA cutoff scores influenced the association between CI and study outcomes. Methods: Baseline cross-sectional data were extracted from a longitudinal study of older adults with asthma (N=165) age≥ 60 years and used for analysis. Cognition was assessed using the MoCA. Asthma control, asthma-related quality of life (QOL), inhaled corticosteroid (ICS) dosing, and ICS adherence were assessed using self-report. The inhaler technique was observed and rated. Results: Using established MoCA cutoff scores of 23 and 26 yielded 45% and 74% CI rates, respectively. CI, defined using the 23 cutoff score, was significantly associated with worse asthma control (p=.04) and worse ICS adherence (p=.01). With a cutoff score of 26, only asthma-related QOL was significantly associated with CI (p=.03). Race/ethnicity and education did not moderate the relationships between CI and asthma SM behaviors and outcomes. Conclusions: CI in older adults with asthma is associated with important clinical outcomes, but this relationship is influenced by the cutoff score used to define CI.

Keywords: cognition, respiratory, elderly, testing, adherence, validity

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Authors: Kaaryn M. Cater

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Students with sensory processing sensitivity (SPS), Meares-Irlen Syndrome (MIS) and dyslexia can become overwhelmed and struggle to thrive in traditional tertiary learning environments. An estimated 50% of tertiary students who disclose learning related issues are dyslexic. This study explores the relationship between SPS, MIS and dyslexia. Baseline measures will be analysed to establish any correlation between these three minority methods of information processing. SPS is an innate sensitivity trait found in 15-20% of the population and has been identified in over 100 species of animals. Humans with SPS are referred to as Highly Sensitive People (HSP) and the measure of HSP is a 27 point self-test known as the Highly Sensitive Person Scale (HSPS). A 2016 study conducted by the author established base-line data for HSP students in a tertiary institution in New Zealand. The results of the study showed that all participating HSP students believed the knowledge of SPS to be life-changing and useful in managing life and study, in addition, they believed that all tutors and in-coming students should be given information on SPS. MIS is a visual processing and perception disorder that is found in approximately 10% of the population and has a variety of symptoms including visual fatigue, headaches and nausea. One way to ease some of these symptoms is through the use of colored lenses or overlays. Dyslexia is a complex phonological based information processing variation present in approximately 10% of the population. An estimated 50% of dyslexics are thought to have MIS. The study exploring possible correlations between these minority forms of information processing is due to begin in February 2017. An invitation will be extended to all first year students enrolled in degree programmes across all faculties and schools within the institution. An estimated 900 students will be eligible to participate in the study. Participants will be asked to complete a battery of on-line questionnaires including the Highly Sensitive Person Scale, the International Dyslexia Association adult self-assessment and the adapted Irlen indicator. All three scales have been used extensively in literature and have been validated among many populations. All participants whose score on any (or some) of the three questionnaires suggest a minority method of information processing will receive an invitation to meet with a learning advisor, and given access to counselling services if they choose. Meeting with a learning advisor is not mandatory, and some participants may choose not to receive help. Data will be collected using the Question Pro platform and base-line data will be analysed using correlation and regression analysis to identify relationships and predictors between SPS, MIS and dyslexia. This study forms part of a larger three year longitudinal study and participants will be required to complete questionnaires at annual intervals in subsequent years of the study until completion of (or withdrawal from) their degree. At these data collection points, participants will be questioned on any additional support received relating to their minority method(s) of information processing. Data from this study will be available by April 2017.

Keywords: dyslexia, highly sensitive person (HSP), Meares-Irlen Syndrome (MIS), minority forms of information processing, sensory processing sensitivity (SPS)

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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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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Authors: Aleksandr I. Korobov, Natalia V. Shirgina, Aleksey I. Kokshaiskiy, Vyacheslav M. Prokhorov

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The paper presents the results of an experimental study of the effect of reverse mechanical load-unloading on the mechanical, linear, and nonlinear elastic properties of n-AMg6/C60 nanocomposite. Samples for experimental studies of n-AMg6/C60 nanocomposite were obtained by grinding AMg6 polycrystalline alloy in a planetary mill with 0.3 wt % of C60 fullerite in an argon atmosphere. The resulting product consisted of 200-500-micron agglomerates of nanoparticles. X-ray coherent scattering (CSL) method has shown that the average nanoparticle size is 40-60 nm. The resulting preform was extruded at high temperature. Modifications of C60 fullerite interferes the process of recrystallization at grain boundaries. In the samples of n-AMg6/C60 nanocomposite, the load curve is measured: the dependence of the mechanical stress σ on the strain of the sample ε under its multi-cycle load-unloading process till its destruction. The hysteresis dependence σ = σ(ε) was observed, and insignificant residual strain ε < 0.005 were recorded. At σ≈500 MPa and ε≈0.025, the sample was destroyed. The destruction of the sample was fragile. Microhardness was measured before and after destruction of the sample. It was found that the loading-unloading process led to an increase in its microhardness. The effect of the reversible mechanical stress on the linear and nonlinear elastic properties of the n-AMg6/C60 nanocomposite was studied experimentally by ultrasonic method on the automated complex Ritec RAM-5000 SNAP SYSTEM. In the n-AMg6/C60 nanocomposite, the velocities of the longitudinal and shear bulk waves were measured with the pulse method, and all the second-order elasticity coefficients and their dependence on the magnitude of the reversible mechanical stress applied to the sample were calculated. Studies of nonlinear elastic properties of the n-AMg6/C60 nanocomposite at reversible load-unloading of the sample were carried out with the spectral method. At arbitrary values of the strain of the sample (up to its breakage), the dependence of the amplitude of the second longitudinal acoustic harmonic at a frequency of 2f = 10MHz on the amplitude of the first harmonic at a frequency f = 5MHz of the acoustic wave is measured. Based on the results of these measurements, the values of the nonlinear acoustic parameter in the n-AMg6/C60 nanocomposite sample at different mechanical stress were determined. The obtained results can be used in solid-state physics, materials science, for development of new techniques for nondestructive testing of structural materials using methods of nonlinear acoustic diagnostics. This study was supported by the Russian Science Foundation (project №14-22-00042).

Keywords: nanocomposite, generation of acoustic harmonics, nonlinear acoustic parameter, hysteresis

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Authors: Sami Kabir, Sadek Hossain Khoka

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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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Authors: Jamil Lane, Jason Freeman

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Background: The role of interpersonal relationships is vital predictors of adolescents’ eating habits, exercise activity, and health problems including obesity. The effect of interpersonal relationships (i.e. family, friends, and intimate partners) on individual health behaviors and development have gained considerable attention during the past 10 years. Teenagers eating habits and exercise activities are established through a dynamic course involving internal and external factors such as food preferences, body weight perception, and parental and peer influence. When conceptualizing one’s interpersonal relationships, it is important to understand that how one relates to others is shaped by their culture. East-Asian culture has been characterized as collectivistic, which describes the significant role intergroup relationships play in their construction of the self. Cultures found in North America, on the other hand, can be characterized as individualistic, meaning that these cultures encourage individuals to prioritize their interest over the needs and want of their compatriots. Individuals from collectivistic cultures typically have stronger boundaries between in-group and out-group membership, whereas those from individualistic cultures see themselves as distinct and separate from strangers as well as family or friends. Objective: The purpose of this study is to examine the effect of collectivism and individualism on interpersonal relationships that shapes eating patterns and physical activity among Asian-American and European-American adolescents. Design/Methods: Analyses were based on data from the National Longitudinal Study of Adolescent Health, a nationally representative sample of adolescents in the United States who were surveyed from 1994 through 2008. This data will be used to examine interpersonal relationship factors that shape dietary intake and physical activity patterns within the Asian-American and European-American population in the United States. Factors relating to relationship strength, eating, and exercise behaviors were reported by participants in this first wave of data collection (1995). We plan to analyze our data using intragroup comparisons among those who identified as 'Asian-American' (n = 270) and 'White or European American' (n = 4,294) among the domains of positivity of peer influence and level of physical activity / healthy eating. Further, intergroup comparisons of these relationships will be made to extricate how the role positive peer influence in maintaining healthy eating and exercise habits differs with cultural variation. Results: We hypothesize that East-Asian participants with a higher degree of positivity in their peer and family relationships will experience a significantly greater rise in healthy eating and exercise behaviors than European-American participants with similar degrees of relationship positivity.

Keywords: interpersonal relationships, eating patterns, physical activity, adolescent health

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Authors: C. B. Abhilash, Kavi Mahesh

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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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Authors: Dina Ahmad Alkhodary

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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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Authors: Lukman Abiodun Nafiu

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This study examines the impact evaluation of vaccination against eight-child-killer diseases on under-five children mortality at Mbale District. It was driven by three specific objectives which are to determine the proportion of under-five children mortality due to the eight-child-killer diseases to the total under-five children mortality; establish the cause-effect relationship between the eight-child-killer diseases and under-five children mortality; as well as establish the dependence of under-five children mortality in the location at Mbale District. A community based cross-sectional and longitudinal (panel) study design involving both quantitative and qualitative (focus group discussion and in-depth interview) approaches was employed over a period of 36 months. Multi-stage cluster design involving Health Sub-District (HSD), Forms of Ownership (FOO) and Health Facilities Centres (HFC) as the first, second and third stages respectively was used. Data was collected regarding the eight-child-killer diseases namely: measles, pneumonia, pertussis (whooping cough), diphtheria, poliomyelitis (polio), tetanus, haemophilus influenza, rotavirus gastroenteritis and mortality regarding immunized and non-immunized children aged 0-59 months. We monitored the children over a period of 24 months. The study used a sample of 384 children out of all the registered children for each year at Mbale Referral Hospital and other Primary Health Care Centres (HCIV, HCIII and HCII) at Mbale District between 2015 and 2019. These children were followed from birth to their current state (living or dead). The data collected in this study was analysed using cross tabulation and the chi-square test. The study concluded that majority of mothers at Mbale district took their children for immunization and thus reducing the occurrence of under-five children mortality. Overall, 2.3%, 4.6%, 3.1%, 5.4%, 1.5%, 3.8%, 0.0% and 0.0% of under-five children had polio, tetanus, diphtheria, measles, pertussis, pneumonia, haemophilus influenzae and rotavirus gastroenteritis respectively across all the sub counties at Mbale district during the period considered. Also, different locations (sub counties) do not have significant influence on the occurrence of these eight-child-killer diseases among the under-five children at Mbale district. Therefore, the study recommended that government and agencies should continue to work together to implement measures of vaccination programs and increasing access to basic health care with a continuous improvement on the social interventions to progress child survival.

Keywords: Diseases, Mortality, Children, Vaccination

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Authors: Amal M. Alrayes

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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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Authors: Yung-Feng Yen, Yun-Ju Lai

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Background: Metabolic syndrome (MetS) is reversible; however, the effect of changes in MetS status on the risk of incident cancer has not been extensively studied. We aimed to investigate the effects of changes in MetS status on incident cancer risk. Methods: This prospective, longitudinal study used data from Taiwan’s MJ cohort of 157,915 adults recruited from 2002–2016 who had repeated MetS measurements 5.2 (±3.5) years apart and were followed up for the new onset of cancer over 8.2 (±4.5) years. A new diagnosis of incident cancer in study individuals was confirmed by their pathohistological reports. The participants’ MetS status included MetS-free (n=119,331), MetS-developed (n=14,272), MetS-recovered (n=7,914), and MetS-persistent (n=16,398). We used the Fine-Gray sub-distribution method, with death as the competing risk, to determine the association between MetS changes and the risk of incident cancer. Results: During the follow-up period, 7,486 individuals had new development of cancer. Compared with the MetS-free group, MetS-persistent individuals had a significantly higher risk of incident cancer (adjusted hazard ratio [aHR], 1.10; 95% confidence interval [CI], 1.03-1.18). Considering the effect of dynamic changes in MetS status on the risk of specific cancer types, MetS persistence was significantly associated with a higher risk of incident colon and rectum, kidney, pancreas, uterus, and thyroid cancer. The risk of kidney, uterus, and thyroid cancer in MetS-recovered individuals was higher than in those who remained MetS but lower than MetS-persistent individuals. Conclusions: Persistent MetS is associated with a higher risk of incident cancer, and recovery from MetS may reduce the risk. The findings of our study suggest that it is imperative for individuals with pre-existing MetS to seek treatment for this condition to reduce the cancer risk.

Keywords: metabolic syndrome change, cancer, risk factor, cohort study

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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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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Authors: Amy Gooden, Meshandren Naidoo

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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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Authors: Tejinder Singh

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

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

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

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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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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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Authors: Milica Lazic, Jovana Jestrovic

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The aim of this research is to examine moderating role of positive and negative affect, defined as traits, in relationship between a number of stressful life events to which an individual is exposed and life satisfaction. The tendency to experience positive and negative emotions is considered as relatively independent, and life satisfaction depends on presence and intensity of emotions of different valence. However, the role of positive and negative affect can be much more complex. It can change the direction and/or intensity of correlation between a number of stressful life events and life satisfaction. Thus, this question is important for two reasons, (I) better comprehension of inconsistent result of correlation intensity between stressful events and life satisfaction (II) verification on what conditions positive and negative affect have a protective role, and on what conditions the positive and/or negative affect is vulnerability factor. Longitudinal data were collected in two waves from 660 adolescents. Firstly, participants completed the Positive and Negative Affect Schedule. A year later, Life events questionnaire, which measures the number of stressful events in the past six months and Satisfaction with Life Scale were administered. The data were analyzed using hierarchical regression analyses: three-way interaction. The results show that number of life events, positive and negative effect contribute to the level of life satisfaction. The check of moderation role shows the significant three-way interaction of number of life event, and both, positive and negative affect. Individuals who report high level of positive affect, estimate to be moderate to highly satisfied with their lives, regardless of number of stressors to which they are exposed and also how often they experience negative emotions. Individuals, who often experience negative emotions and rarely positive, report the lowest level of life satisfaction. It doesn't change despite the number of stressors they were exposed to. Individuals who report that rarely experience not only positive than also negative emotions estimate different level of life satisfaction depending on number of stressors they were exposed to. Under the influence of numerous stressors, their level of life satisfaction is low, and it's equal to life satisfaction level of individuals who often experience negative and rarely positive emotions. The result of this research shows that tendency to often experience positive emotions is the protective factor in situation when individuals are exposed to high number of stressors. On the other hand, tendency to rarely experience positive emotions present vulnerability factor. Conclusions and practical implications are further discussed.

Keywords: life events, life satisfaction, subjective well-being, positive and negative affect

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Authors: Carolina Senabre, Sergio Valero, Emilio Velasco

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This research objective is to compare the differences of brake measurements obtained with the same vehicle when braking on VTEQ Ministry of Transport (MOT) brake testers versus others such as Maha, Ryme and a dynamometric platform. These different types of brake testers have been used and analyzed by the mechanical engineering staffs at the mechanical laboratory at the Miguel Hernández University. Parameters of the vehicle have been controlled to be the same in all tests. Therefore, brake measurements variability will be due to the tester used. Advances and disadvantages of each brake tester have been analyzed.

Keywords: brake tester, Ministry of transport, longitudinal braking, Bank of Rollers

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Authors: Rideci Farias, Haroldo Paranhos

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The present work deals with the use of drainage geo-composite as a deep drainage and geogrid element to reinforce the base of the body of the landfill destined to the road pavement on geological faults in the stretch of the TO-342 Highway, between the cities of Miracema and Miranorte, in the State of Tocantins / TO, Brazil, which for many years was the main link between TO-010 and BR-153, after the city of Palmas, also in the state of Tocantins / TO, Brazil. For this application, geotechnical and geological studies were carried out by means of SPT percussion drilling, drilling and rotary drilling, to understand the problem, identifying the type of faults, filling material and the definition of the water table. According to the geological and geotechnical studies carried out, the area where the route was defined, passes through a zone of longitudinal fault to the runway, with strong breaking / fracturing, with presence of voids, intense alteration and with advanced argilization of the rock and with the filling up parts of the faults by organic and compressible soils leachate from other horizons. This geology presents as a geotechnical aggravating agent a medium of high hydraulic load and very low resistance to penetration. For more than 20 years, the region presented constant excessive deformations in the upper layers of the pavement, which after routine services of regularization, reconformation, re-compaction of the layers and application of the asphalt coating. The faults were quickly propagated to the surface of the asphalt pavement, generating a longitudinal shear, forming steps (unevenness), close to 40 cm, causing numerous accidents and discomfort to the drivers, since the geometric positioning was in a horizontal curve. Several projects were presented to the region's highway department to solve the problem. Due to the need for partial closure of the runway, the short time for execution, the use of geosynthetics was proposed and the most adequate solution for the problem was taken into account the movement of existing geological faults and the position of the water level in relation to several Layers of pavement and failure. In order to avoid any flow of water in the body of the landfill and in the filling material of the faults, a drainage curtain solution was used, carried out at 4.0 meters depth, with drainage geo-composite and as reinforcement element and inhibitor of the possible A geogrid of 200 kN / m of resistance was inserted at the base of the reconstituted landfill. Recent evaluations, after 13 years of application of the solution, show the efficiency of the technique used, supported by the geotechnical studies carried out in the area.

Keywords: geosynthetics, geocomposite, geogrid, road, recovery, geological failure

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Authors: Luvisa Kusuma, Panji Yudha Prakasa

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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 343

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 145

Authors: Geraldine Mc Loughlin, Mary Horgan, Rosaleen Murphy

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Childbirth is a life-changing event, a psychological transition for the mother that must be viewed in a social context. Much has been written and documented regarding the preparation for birth and the immediate postnatal period, but the full psychological impact on the mother is not clear. One aspect of the transition process is Identity. Depending on a person’s worldview, the concept of identity is viewed differently; the nature of reality and how they construct knowledge influence these perspectives. Becoming a mother is not just an event but a process that time and experience will help to shape the understanding of the woman. To explore the emotional and psychological aspects of first-time mother’s experience during the transition to new motherhood. To identify factors affecting women’s identities in the period of 36 weeks gestation to 12 weeks postpartum. Interpretative Phenomenological Analysis (IPA) was used. It explores how these women make sense of and give meaning to their experiences. IPA is underpinned by 3 key principles: phenomenology, hermeneutics and idiographics. A purposeful sample of 10 women was recruited for this longitudinal study, to enable data to be collected during the transition to motherhood. Individual identity was interpreted and viewed as developing in response to changing contexts, such as the birth event becoming a parent, enabling one to construct one’s own sense of a meaningful life. Women effectively differentiated themselves from their personal and social identities and took responsibility for their actions. Identity is culturally and socially shaped and experienced, though not experienced similarly by all women. The individualized perspective on identity recognizes that (a) social influences are seen as external to the individual and (b) the view that social influences are, in fact, internalized by the individual.

Keywords: motherhood, transition, identity, IPA

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Authors: Alaa Badawi, Suzan Sayegh, Mohamed Sallam, Eman Sadoun, Mohamed Al-Thani, Muhammad W. Alam, Paul Arora

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Background: The dual burden of tuberculosis (TB) and diabetes mellitus (DM) has increased over the past decade with DM prevalence increasing in countries already afflicted with a high burden of TB. The coexistence of the two conditions presents a serious threat to global public health. Objective: The present study examines the global relationship between the prevalence of DM and the incidence of TB to evaluate their coexistence worldwide and their contribution to one another. Methods: This is an ecological longitudinal study covering the period between years 2000 to 2012. We utilized data from the WHO and World Bank sources and International Diabetes Federation to estimate prevalence of DM (%) and the incidence of TB (per 100,000). Measures of central tendency and dispersion as well as the harmonic mean and linear regression were used for different WHO regions. The association between DM prevalence and TB incidence was examined by quartile of DM prevalence. Results: The worldwide average (±S.D.) prevalence of DM within the study period was 6.6±3.8% whereas TB incidence was 135.0±190.5 per 100,000. DM prevalence was highest in the Eastern Mediterranean (8.3±4.1) and West Pacific (8.2±5.6) regions and lowest in the Africa (3.5±2.6). TB incidence was highest in Africa (313.1±275.9 per 100,000) and South-East Asia (216.7±124.9) and lowest in the European (46.5±68.6) and American (47.2±52.9) regions. Only countries with high DM prevalence (>7.6%) showed a significant positive association with TB incidence (r=0.17, p=0.013). Conclusion: A positive association between DM and TB may exist in some – but not all – world regions, a dual burden that necessitates identifying the nature of this coexistence to assist in developing public health approaches that curb their rising burden.

Keywords: diabetes mellitus, tuberculosis, disease burden, global association

Procedia PDF Downloads 447

Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

Procedia PDF Downloads 295

Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

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This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

Procedia PDF Downloads 346

Authors: Mohamed Elkholy, Ahmed Elfatatry

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Cloud computing has emerged as a flexible computing paradigm that reshaped the Information Technology map. However, cloud computing brought about a number of security challenges as a result of the physical distribution of computational resources and the limited control that users have over the physical storage. This situation raises many security challenges for data integrity and confidentiality as well as authentication and access control. This work proposes a security mechanism for data integrity that allows a data owner to be aware of any modification that takes place to his data. The data integrity mechanism is integrated with an extended Kerberos authentication that ensures authorized access control. The proposed mechanism protects data confidentiality even if data are stored on an untrusted storage. The proposed mechanism has been evaluated against different types of attacks and proved its efficiency to protect cloud data storage from different malicious attacks.

Keywords: access control, data integrity, data confidentiality, Kerberos authentication, cloud security

Procedia PDF Downloads 320