Search results for: link data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26020

Search results for: link data

25750 Social Business Process Management and Business Process Management Maturity

Authors: Dalia Suša Vugec, Vesna Bosilj Vukšić, Ljubica Milanović Glavan

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Business process management (BPM) is a well-known holistic discipline focused on managing business processes with the intention of achieving higher level of BPM maturity and better organizational performance. In recent period, traditional BPM faced some of its limitations like model-reality divide and lost innovation. Following latest trends, as an attempt to overcome the issues of traditional BPM, there has been an introduction of applying the principles of social software in managing business processes which led to the development of social BPM. However, there are not many authors or studies dealing with this topic so this study aims to contribute to that literature gap and to examine the link between the level of BPM maturity and the usage of social BPM. To meet these objectives, a survey within the companies with more than 50 employees has been conducted. The results reveal that the usage of social BPM is higher within the companies which achieved higher level of BPM maturity. This paper provides an overview, analysis and discussion of collected data regarding BPM maturity and social BPM within the observed companies and identifies the main social BPM principles.

Keywords: business process management, BPM maturity, process performance index, social BPM

Procedia PDF Downloads 325
25749 Quantifying Stability of Online Communities and Its Impact on Disinformation

Authors: Victor Chomel, Maziyar Panahi, David Chavalarias

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Misinformation has taken an increasingly worrying place in social media. Propagation patterns are closely linked to the structure of communities. This study proposes a method of community analysis based on a combination of centrality indicators for the network and its main communities. The objective is to establish a link between the stability of the communities over time, the social ascension of its members internally, and the propagation of information in the community. To this end, data from the debates about global warming and political communities on Twitter have been collected, and several tens of millions of tweets and retweets have helped us better understand the structure of these communities. The quantification of this stability allows for the study of the propagation of information of any kind, including disinformation. Our results indicate that the most stable communities over time are the ones that enable the establishment of nodes capturing a large part of the information and broadcasting its opinions. Conversely, communities with a high turnover and social ascendancy only stabilize themselves strongly in the face of adversity and external events but seem to offer a greater diversity of opinions most of the time.

Keywords: community analysis, disinformation, misinformation, Twitter

Procedia PDF Downloads 142
25748 Efficient Layout-Aware Pretraining for Multimodal Form Understanding

Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

Procedia PDF Downloads 151
25747 Imputation Technique for Feature Selection in Microarray Data Set

Authors: Younies Saeed Hassan Mahmoud, Mai Mabrouk, Elsayed Sallam

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Analysing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics

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25746 PDDA: Priority-Based, Dynamic Data Aggregation Approach for Sensor-Based Big Data Framework

Authors: Lutful Karim, Mohammed S. Al-kahtani

Abstract:

Sensors are being used in various applications such as agriculture, health monitoring, air and water pollution monitoring, traffic monitoring and control and hence, play the vital role in the growth of big data. However, sensors collect redundant data. Thus, aggregating and filtering sensors data are significantly important to design an efficient big data framework. Current researches do not focus on aggregating and filtering data at multiple layers of sensor-based big data framework. Thus, this paper introduces (i) three layers data aggregation and framework for big data and (ii) a priority-based, dynamic data aggregation scheme (PDDA) for the lowest layer at sensors. Simulation results show that the PDDA outperforms existing tree and cluster-based data aggregation scheme in terms of overall network energy consumptions and end-to-end data transmission delay.

Keywords: big data, clustering, tree topology, data aggregation, sensor networks

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25745 Research on Spatial Distribution of Service Facilities Based on Innovation Function: A Case Study of Zhejiang University Zijin Co-Maker Town

Authors: Zhang Yuqi

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Service facilities are the boosters for the cultivation and development of innovative functions in innovative cluster areas. At the same time, reasonable service facilities planning can better link the internal functional blocks. This paper takes Zhejiang University Zijin Co-Maker Town as the research object, based on the combination of network data mining and field research and verification, combined with the needs of its internal innovative groups. It studies the distribution characteristics and existing problems of service facilities and then proposes a targeted planning suggestion. The main conclusions are as follows: (1) From the perspective of view, the town is rich in general life-supporting services, but lacking of provision targeted and distinctive service facilities for innovative groups; (2) From the perspective of scale structure, small-scale street shops are the main business form, lack of large-scale service center; (3) From the perspective of spatial structure, service facilities layout of each functional block is too fragile to fit the characteristics of 2aggregation- distribution' of innovation and entrepreneurial activities; (4) The goal of optimizing service facilities planning should be guided for fostering function of innovation and entrepreneurship and meet the actual needs of the innovation and entrepreneurial groups.

Keywords: the cultivation of innovative function, Zhejiang University Zijin Co-Maker Town, service facilities, network data mining, space optimization advice

Procedia PDF Downloads 117
25744 The Effect of Evil Eye in the Individuals' Journey for Personhood within a Christian Orthodox Society

Authors: Nikolaos Souvlakis

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The present paper negotiates the effect of 'the evil eye' on individuals' mental health while at the same time poses the problem of how the evil eye fits into the anthropological arena as a key question that forges a fundamental link between religion, anthropology and mental health professions. It is the argument of the paper that the evil eye is an essential and fundamental human phenomenon and therefore any scholarly field involved in its study must consider the insight it provides into the development of personhood. The study was an anthropological study in the geographical area of Corfu, a Greek Orthodox society uninfluenced by the Ottoman Islamic Culture. The paper aims to deepen our understanding of the evil eye as it analyses the interaction between the evil eye and gaze and how they affect the development of personhood; based on the empirical data collected from the fieldwork. Therefore, the paper adopts a psychoanalytic anthropology approach to facilitate a better understanding of the evil eye through the accounts of individuals’ journeys in the process of their development of personhood. Finally, the paper aims to offer a detailed analysis of the particular element of eye (‘I’) and, more specifically, of ‘the others’, as they relate to the phenomenon of the evil eye.

Keywords: gaze, evil eye, mental health, personhood

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25743 The Interactive Effects among Supervisor Support, Academic Emotion, and Positive Mental Health: An Evidence Based on Longitudinal Cross-Lagged Panel Data Analysis on Postgraduates in China

Authors: Jianzhou Ni, Hua Fan

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It has been determined that supervisor support has a major influence on postgraduate students' academic emotions and is considered a method of successfully anticipating postgraduates' good psychological well-being levels. As a result, by assessing the mediating influence upon academic emotions for contemporary postgraduates in China, this study investigated the tight reciprocal relationship between psychological empowerment and positive mental well-being among postgraduates. To that end, a help enables a theoretical analysis of role clarity, academic emotion, and positive psychological health was developed, and its validity and reliability were demonstrated for the first time using the normalized postgrad relationship with supervisor scale, academic emotion scale, and positive mental scale, as well as questionnaire data from Chinese postgraduate students. This study used the cross-lagged (ARCL) panel model data to longitudinally measure 798 valid data from two survey questions polls taken in 2019 (T1) and 2021 (T2) to investigate the link between supervisor support and positive graduate student mental well-being in a bidirectional relationship of influence. The study discovered that mentor assistance could have a considerable beneficial impact on graduate students' academic emotions and, as a result, indirectly help learners attain positive mental health development. This verifies the theoretical premise that academic emotions partially mediate the effect of mentor support on positive mental health development and argues for the coexistence of the two. The outcomes of this study can help researchers gain a better knowledge of the dynamic interplay among three different research variables: supervisor support, academic emotions, and positive mental health, as well as fill gaps in previous research. In this regard, the study indicated that mentor assistance directly stimulates students' academic drive and assists graduate students in developing good academic emotions, which contributes to the development of positive mental health. However, given the restricted measurement time in this study's cross-lagged panel data and the potential effect of moderating effects other than academic mood on graduate students' good mental health, the results of this study need to be more fully understood and validated.

Keywords: supervisor support, academic emotions, positive mental health, interaction effects, longitudinal cross-lagged measurements

Procedia PDF Downloads 88
25742 Local Tax Map Software System Development

Authors: Smithinun Thairoongrojana

Abstract:

This research is a qualitative research with three main purposes: (1) to develop the local tax map software system to be linked to the main Local Tax Map System (LTAX3000) system; (2) to design and develop a program for tax data fieldwork on wireless devices and link it to LTAX3000 database of Surat Thani Municipality; (3) to develop the human resource responsible for the fieldwork to be able to use the program and maintain the system and also to be able to work with the dynamic of technologies. In-depth interviews with the two groups of samples, the board of Surat Thani Municipality and operation staff responsible for observing and taxing fieldworks were conducted. The result of this study demonstrates the new developed fieldworks system that can be used both stand-alone usage and networking usage. The fieldworks system to collect and store the variety of taxing information within Surat Thani Municipality will be explained. Then the fieldwork operation process development and the replacement of transferring and storing the information via the network communication.

Keywords: Local tax map, software system development, wireless devices, human resource

Procedia PDF Downloads 192
25741 Rt-Pcr Negative COVID-19 Infection in a Bodybuilding Competitor Using Anabolic Steroids: A Case Report

Authors: Mariana Branco, Nahida Sobrino, Cristina Neves, Márcia Santos, Afonso Granja, João Rosa Oliveira, Joana Costa, Luísa Castro Leite

Abstract:

This case reports a COVID-19 infection in an unvaccinated adult man with no history of COVID-19 and no relevant clinical history besides anabolic steroid use, undergoing weaning with tamoxifen after a bodybuilding competition. The patient presented a 4cm cervical mass 3 weeks after COVID-19 infection in his cohabitants. He was otherwise asymptomatic and tested negative to multiple RT-PCR tests. Nevertheless, the IgG COVID-19 antibody was positive, suggesting the previous infection. This report raises a potential link between anabolic steroid use and atypical COVID-19 onset. Objectives: The goals of this paper are to raise a potential link between anabolic steroid use and atypical COVID-19 onset but also to report an uncommon case of COVID-19 infection with consecutive negative gold standard tests. Methodology: The authors used CARE guidelines for case report writing. Introduction: This case reports a COVID-19 infection case in an unvaccinated adult man, with multiple serial negative reverse transcription polymerase chain reaction (RT-PCR) test results, presenting with single cervical lymphadenopathy. Although the association between COVID-19 and lymphadenopathy is well established, there are no cases with this presentation, and consistently negative RT-PCR tests have been reported. Methodologies: The authors used CARE guidelines for case report writing. Case presentation: This case reports a 28-year-old Caucasian man with no previous history of COVID-19 infection or vaccination and no relevant clinical history besides anabolic steroid use undergoing weaning with tamoxifendue to participation in a bodybuilding competition. He visits his primary care physician because of a large (4 cm) cervical lump, present for 3 days prior to the consultation. There was a positive family history for COVID-19 infection 3 weeks prior to the visit, during which the patient cohabited with the infected family members. The patient never had any previous clinical manifestation of COVID-19 infection and, despite multiple consecutive RT-PCR testing, never tested positive. The patient was treated with an NSAID and a broad-spectrum antibiotic, with little to no effect. Imagiological testing was performed via a cervical ultrasound, followed by a needle biopsy for histologic analysis. Serologic testing for COVID-19 immunity was conducted, revealing a positive Anti-SARS-CoV-2 IgG (Spike S1) antibody, suggesting the previous infection, given the unvaccinated status of our patient Conclusion: In patients with a positive epidemiologic context and cervical lymphadenopathy, physicians should still consider COVID-19 infection as a differential diagnosis, despite negative PCR testing. This case also raises a potential link between anabolic steroid use and atypical COVID-19 onset, never before reported in scientific literature.

Keywords: COVID-19, cervical lymphadenopathy, anabolic steroids, primary care

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25740 Teacher's Gender and Primary School Pupils Achievement in Social Studies and Its Educational Implications on Pupils

Authors: Elizabeth Oyenike Abegunrin

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This study is borne out of the dire need to improve the academic achievement of pupils in social studies. The paper attempted to reconcile the lacuna in teacher’s gender and primary school pupils’ achievement. With specific reference to Social Studies classroom, the aim of this study was to detail how pupils’ achievement is a function of the teacher’s gender as well as to establish the link (if any) between teacher’s gender and pupils’ educational achievement. The significance of this was to create gender-template standard for teachers, school owners, administrators and policy makers to follow in the course of engendering pupils’ achievement in Social Studies. By adopting a quasi-experimental research design, a sample of two hundred pupils was selected across five primary schools in Education District I, Lagos State and assigned to experimental and control groups. A 40-item Gender and Social Studies Achievement Test (GSSAT) was used to obtain data from the pupils. Having analyzed the data collected using Pearson Product Moment Correlation (PPMC), a reliability of 0.78 was obtained. Result revealed that teacher’s gender (male/female) had no significant effect on pupils’ achievement in Social Studies and that there was significant interaction effect of teacher’s commitment devoid of gender on the general education output of pupils in Social Studies. Taken together, the results revealed that there is a high degree correlation between teacher’s commitment and pupils academic achievement in social studies, and not gender-based. The study recommended that social studies teachers should re-assess their classroom instructional strategies and use more innovative instructional methods and techniques that will give the pupils equal opportunities to excel in social studies, rather than their gender differences.

Keywords: gender, academic achievement, social studies, primary school

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25739 Control the Flow of Big Data

Authors: Shizra Waris, Saleem Akhtar

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

Keywords: computer, it community, industry, big data

Procedia PDF Downloads 194
25738 Management as a Proxy for Firm Quality

Authors: Petar Dobrev

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There is no agreed-upon definition of firm quality. While profitability and stock performance often qualify as popular proxies of quality, in this project, we aim to identify quality without relying on a firm’s financial statements or stock returns as selection criteria. Instead, we use firm-level data on management practices across small to medium-sized U.S. manufacturing firms from the World Management Survey (WMS) to measure firm quality. Each firm in the WMS dataset is assigned a mean management score from 0 to 5, with higher scores identifying better-managed firms. This management score serves as our proxy for firm quality and is the sole criteria we use to separate firms into portfolios comprised of high-quality and low-quality firms. We define high-quality (low-quality) firms as those firms with a management score of one standard deviation above (below) the mean. To study whether this proxy for firm quality can identify better-performing firms, we link this data to Compustat and The Center for Research in Security Prices (CRSP) to obtain firm-level data on financial performance and monthly stock returns, respectively. We find that from 1999 to 2019 (our sample data period), firms in the high-quality portfolio are consistently more profitable — higher operating profitability and return on equity compared to low-quality firms. In addition, high-quality firms also exhibit a lower risk of bankruptcy — a higher Altman Z-score. Next, we test whether the stocks of the firms in the high-quality portfolio earn superior risk-adjusted excess returns. We regress the monthly excess returns on each portfolio on the Fama-French 3-factor, 4-factor, and 5-factor models, the betting-against-beta factor, and the quality-minus-junk factor. We find no statistically significant differences in excess returns between both portfolios, suggesting that stocks of high-quality (well managed) firms do not earn superior risk-adjusted returns compared to low-quality (poorly managed) firms. In short, our proxy for firm quality, the WMS management score, can identify firms with superior financial performance (higher profitability and reduced risk of bankruptcy). However, our management proxy cannot identify stocks that earn superior risk-adjusted returns, suggesting no statistically significant relationship between managerial quality and stock performance.

Keywords: excess stock returns, management, profitability, quality

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25737 Women’s Leadership for Sustainable Outcomes: On the Road to Gender Equality for a Better Tomorrow

Authors: Deepika Faugoo

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Gender equality stands as the cornerstone of societal progress, intricately woven into the very essence of the 2030 Sustainable Development Goals (SDGs). Yet, the gender leadership gap remains a formidable obstacle hindering global equality. Despite women's educational advancements, their underrepresentation in senior roles persists as a baffling anomaly. Drawing from contemporary research, empirical evidence, and secondary data, this paper underscores the imperative of advancing women in leadership to drive SDGs related to empowerment and gender equality by 2030. It highlights the undeniable link between women leaders and sustainable outcomes, citing case studies and examples of their contributions to financial performance, prosperity, economic growth, and societal well-being. Exploring persistent barriers and emerging challenges, it offers actionable strategies to enhance women's representation in leadership, promising transformative benefits for organizations and societies. Amidst societal upheavals, gender equality emerges as a potent solution, catalyzing change toward a future where every voice resonates, ensuring no one is left behind.

Keywords: senior leadership, empowerment, SDGs, gender equality

Procedia PDF Downloads 69
25736 Training During Emergency Response to Build Resiliency in Water, Sanitation, and Hygiene

Authors: Lee Boudreau, Ash Kumar Khaitu, Laura A. S. MacDonald

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In April 2015, a magnitude 7.8 earthquake struck Nepal, killing, injuring, and displacing thousands of people. The earthquake also damaged water and sanitation service networks, leading to a high risk of diarrheal disease and the associated negative health impacts. In response to the disaster, the Environment and Public Health Organization (ENPHO), a Kathmandu-based non-governmental organization, worked with the Centre for Affordable Water and Sanitation Technology (CAWST), a Canadian education, training and consulting organization, to develop two training programs to educate volunteers on water, sanitation, and hygiene (WASH) needs. The first training program was intended for acute response, with the second focusing on longer term recovery. A key focus was to equip the volunteers with the knowledge and skills to formulate useful WASH advice in the unanticipated circumstances they would encounter when working in affected areas. Within the first two weeks of the disaster, a two-day acute response training was developed, which focused on enabling volunteers to educate those affected by the disaster about local WASH issues, their link to health, and their increased importance immediately following emergency situations. Between March and October 2015, a total of 19 training events took place, with over 470 volunteers trained. The trained volunteers distributed hygiene kits and liquid chlorine for household water treatment. They also facilitated health messaging and WASH awareness activities in affected communities. A three-day recovery phase training was also developed and has been delivered to volunteers in Nepal since October 2015. This training focused on WASH issues during the recovery and reconstruction phases. The interventions and recommendations in the recovery phase training focus on long-term WASH solutions, and so form a link between emergency relief strategies and long-term development goals. ENPHO has trained 226 volunteers during the recovery phase, with training ongoing as of April 2016. In the aftermath of the earthquake, ENPHO found that its existing pool of volunteers were more than willing to help those in their communities who were more in need. By training these and new volunteers, ENPHO was able to reach many more communities in the immediate aftermath of the disaster; together they reached 11 of the 14 earthquake-affected districts. The collaboration between ENPHO and CAWST in developing the training materials was a highly collaborative and iterative process, which enabled the training materials to be developed within a short response time. By training volunteers on basic WASH topics during both the immediate response and the recovery phase, ENPHO and CAWST have been able to link immediate emergency relief to long-term developmental goals. While the recovery phase training continues in Nepal, CAWST is planning to decontextualize the training used in both phases so that it can be applied to other emergency situations in the future. The training materials will become part of the open content materials available on CAWST’s WASH Resources website.

Keywords: water and sanitation, emergency response, education and training, building resilience

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25735 Understanding Racial Disparate Treatment of Juvenile Interpersonal Violent Offenders in the Juvenile Justice System Using Focal Concerns Theory

Authors: Suzanne Overstreet-Juenke

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Disproportionate minority contact (DMC) is a salient issue that has been found at every stage of the decision-making process in the juvenile justice system. Existing research indicates that DMC influences adjudication for drug, property, and personal crimes. Because intimate partner violence (IPV) is a major public health problem and global concern, the current study examines DMC at adjudication among youth charged for crimes of interpersonal violence. This research uses administrative, Court Designated Worker (CDW) data collected from 2014 to 2016. The results are contextualized using Steffensmeier’s version of focal concerns theory of judicial decision-making. This study assesses race and two seriousness of offense measures to establish whether a link exists between race and adjudication. The results of the study is similar to prior research on the topic. These results are discussed in terms of policy implications, limitations, and future research.

Keywords: race, disproportionate minority contact, focal concerns theory, juvenile

Procedia PDF Downloads 78
25734 High Performance Computing and Big Data Analytics

Authors: Branci Sarra, Branci Saadia

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Because of the multiplied data growth, many computer science tools have been developed to process and analyze these Big Data. High-performance computing architectures have been designed to meet the treatment needs of Big Data (view transaction processing standpoint, strategic, and tactical analytics). The purpose of this article is to provide a historical and global perspective on the recent trend of high-performance computing architectures especially what has a relation with Analytics and Data Mining.

Keywords: high performance computing, HPC, big data, data analysis

Procedia PDF Downloads 520
25733 A Landscape of Research Data Repositories in Re3data.org Registry: A Case Study of Indian Repositories

Authors: Prashant Shrivastava

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The purpose of this study is to explore re3dat.org registry to identify research data repositories registration workflow process. Further objective is to depict a graph for present development of research data repositories in India. Preliminarily with an approach to understand re3data.org registry framework and schema design then further proceed to explore the status of research data repositories of India in re3data.org registry. Research data repositories are getting wider relevance due to e-research concepts. Now available registry re3data.org is a good tool for users and researchers to identify appropriate research data repositories as per their research requirements. In Indian environment, a compatible National Research Data Policy is the need of the time to boost the management of research data. Registry for Research Data Repositories is a crucial tool to discover specific information in specific domain. Also, Research Data Repositories in India have not been studied. Re3data.org registry and status of Indian research data repositories both discussed in this study.

Keywords: research data, research data repositories, research data registry, re3data.org

Procedia PDF Downloads 326
25732 A Study of Cloud Computing Solution for Transportation Big Data Processing

Authors: Ilgin Gökaşar, Saman Ghaffarian

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The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features.

Keywords: big data, cloud computing, Intelligent Transportation Systems, ITS, traffic data processing

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25731 Harmonic Data Preparation for Clustering and Classification

Authors: Ali Asheibi

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The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

Procedia PDF Downloads 250
25730 Linguistic Summarization of Structured Patent Data

Authors: E. Y. Igde, S. Aydogan, F. E. Boran, D. Akay

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Patent data have an increasingly important role in economic growth, innovation, technical advantages and business strategies and even in countries competitions. Analyzing of patent data is crucial since patents cover large part of all technological information of the world. In this paper, we have used the linguistic summarization technique to prove the validity of the hypotheses related to patent data stated in the literature.

Keywords: data mining, fuzzy sets, linguistic summarization, patent data

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25729 Proposal of Data Collection from Probes

Authors: M. Kebisek, L. Spendla, M. Kopcek, T. Skulavik

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In our paper we describe the security capabilities of data collection. Data are collected with probes located in the near and distant surroundings of the company. Considering the numerous obstacles e.g. forests, hills, urban areas, the data collection is realized in several ways. The collection of data uses connection via wireless communication, LAN network, GSM network and in certain areas data are collected by using vehicles. In order to ensure the connection to the server most of the probes have ability to communicate in several ways. Collected data are archived and subsequently used in supervisory applications. To ensure the collection of the required data, it is necessary to propose algorithms that will allow the probes to select suitable communication channel.

Keywords: communication, computer network, data collection, probe

Procedia PDF Downloads 362
25728 DNA Methylation Score Development for In utero Exposure to Paternal Smoking Using a Supervised Machine Learning Approach

Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic

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The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.

Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning

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25727 Optimization of Traffic Agent Allocation for Minimizing Bus Rapid Transit Cost on Simplified Jakarta Network

Authors: Gloria Patricia Manurung

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Jakarta Bus Rapid Transit (BRT) system which was established in 2009 to reduce private vehicle usage and ease the rush hour gridlock throughout the Jakarta Greater area, has failed to achieve its purpose. With gradually increasing the number of private vehicles ownership and reduced road space by the BRT lane construction, private vehicle users intuitively invade the exclusive lane of BRT, creating local traffic along the BRT network. Invaded BRT lanes costs become the same with the road network, making BRT which is supposed to be the main public transportation in the city becoming unreliable. Efforts to guard critical lanes with preventing the invasion by allocating traffic agents at several intersections have been expended, lead to the improving congestion level along the lane. Given a set of number of traffic agents, this study uses an analytical approach to finding the best deployment strategy of traffic agent on a simplified Jakarta road network in minimizing the BRT link cost which is expected to lead to the improvement of BRT system time reliability. User-equilibrium model of traffic assignment is used to reproduce the origin-destination demand flow on the network and the optimum solution conventionally can be obtained with brute force algorithm. This method’s main constraint is that traffic assignment simulation time escalates exponentially with the increase of set of agent’s number and network size. Our proposed metaheuristic and heuristic algorithms perform linear simulation time increase and result in minimized BRT cost approaching to brute force algorithm optimization. Further analysis of the overall network link cost should be performed to see the impact of traffic agent deployment to the network system.

Keywords: traffic assignment, user equilibrium, greedy algorithm, optimization

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25726 Performance Analysis of a Hybrid Channel for Foglet Assisted Smart Asset Reporting

Authors: Hasan Farahneh

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Smart asset management along roadsides and in deserted areas is a topic of deprived attention. We find most of the work in emergency reporting services in intelligent transportation systems (ITS) and rural areas but not much in asset reporting. Currently, available asset management mechanisms are based on scheduled maintenance and do not effectively report any emergency situation in a timely manner. This paper is the continuation of our previous work, in which we proposed the usage of Foglets and VLC link between smart vehicles and road side assets. In this paper, we propose a hybrid communication system for asset management and emergency reporting architecture for smart transportation. We incorporate Foglets along with visible light communication (VLC) and radio frequency (RF) communication. We present the channel model and parameters of a hybrid model to support an intelligent transportation system (ITS) system. Simulations show high improvement in the system performance in terms of communication range and received data. We present a comparative analysis of a hybrid ITS system.

Keywords: Internet of Things, Foglets, VLC, RF, smart vehicle, roadside asset management

Procedia PDF Downloads 135
25725 A Review on Big Data Movement with Different Approaches

Authors: Nay Myo Sandar

Abstract:

With the growth of technologies and applications, a large amount of data has been producing at increasing rate from various resources such as social media networks, sensor devices, and other information serving devices. This large collection of massive, complex and exponential growth of dataset is called big data. The traditional database systems cannot store and process such data due to large and complexity. Consequently, cloud computing is a potential solution for data storage and processing since it can provide a pool of resources for servers and storage. However, moving large amount of data to and from is a challenging issue since it can encounter a high latency due to large data size. With respect to big data movement problem, this paper reviews the literature of previous works, discusses about research issues, finds out approaches for dealing with big data movement problem.

Keywords: Big Data, Cloud Computing, Big Data Movement, Network Techniques

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25724 Optimized Approach for Secure Data Sharing in Distributed Database

Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

Abstract:

In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation

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25723 The Four Elements of Zoroastrianism and Sustainable Ecosystems with an Ecological Approach

Authors: Esmat Momeni, Shabnam Basari, Mohammad Beheshtinia

Abstract:

The purpose of this study is to provide a symbolic explanation of the four elements in Zoroastrianism and sustainable ecosystems with an ecological approach. The research method is fundamental and deductive content analysis. Data collection has been done through library and documentary methods and through reading books and related articles. The population and sample of the present study are Yazd city and Iran country after discovering symbolic concepts derived from the theoretical foundations of Zoroastrianism in four elements of water, air, soil, fire and conformity with Iranian architecture with the ecological approach in Yazd city, the sustainable ecosystem it is explained by the system of nature. The validity and reliability of the results are based on the trust and confidence of the research literature. Research findings show that Yazd was one of the bases of Zoroastrianism in Iran. Many believe that the first person to discuss the elements of nature and respect Zoroastrians is the Prophet of this religion. Keeping the environment clean and pure by paying attention to and respecting these four elements. The water element is a symbol of existence in Zoroastrianism, so the people of Yazd used the aqueduct and designed a pool in front of the building. The soil element is a symbol of the raw material of human creation in the Zoroastrian religion, the most readily available material in the desert areas of Yazd, used as bricks and adobes, creating one of the most magnificent roof coverings is the dome. The wind element represents the invisible force of the soul in Creation in Zoroastrianism, the most important application of wind in the windy, which is a highly efficient cooling system. The element of fire, which is always a symbol of purity in Zoroastrianism, is located in a special place in Yazd's Ataskadeh (altar/ temple), where the most important religious prayers are held in and against the fire. Consequently, indigenous knowledge and attention to indigenous architecture is a part of the national capital of each nation that encompasses their beliefs, values, methods, and knowledge. According to studies on the four elements of Zoroastrianism, the link between these four elements are that due to the hot and dry fire at the beginning, it is the fire that begins to follow the nature of the movement in the stillness of the earth, and arises from the heat of the fire and because of vigor and its decreases, cold (wind) emerges, and from cold, humidity and wetness. And by examining books and resources on Yazd's architectural design with an ecological approach to the values of the four elements Zoroastrianism has been inspired, it can be concluded that in order to have environmentally friendly architecture, it is essential to use sustainable architectural principles, to link religious and sacrament culture and ecology through architecture.

Keywords: ecology, architecture, quadruple elements of air, soil, water, fire, Zoroastrian religion, sustainable ecosystem, Iran, Yazd city

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25722 Exploring the Spatial Characteristics of Mortality Map: A Statistical Area Perspective

Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou

Abstract:

The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1st, 2008 and December 31st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.

Keywords: mortality map, spatial patterns, statistical area, variation

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25721 Polarisation in Latin America: Examining the Role of Social Media in Ideological Positioning Based on 2018 Census Data

Authors: Sarah Ledoux

Abstract:

This paper analyses the quantitative effects of political content consumption in social media platforms on self-reported ideological preference across the Latin American region. Initially praising the democratic potential of the internet and its social networking websites, digital politics scholars have transitioned their discourse to warning against the undemocratic side-effects it cultivates, such as hate speech, filter bubbles, and ideological polarisation. Holding technology solely responsible for political trends worldwide is an oversimplification of the factors influencing social change. Nonetheless, widespread use of social media in new democracies raises questions on the reproduction of recent trends that have been observed in the US and Western Europe. Through the analysis of ordered logistic regressions on data from the 2018 AmericasBarometer survey, this study examines the extent to which the relationship between the consumption of political content on social media is related to ideological polarisation in Latin America. The findings indicate that there is a close link between consumption of political information on social media, specifically on Facebook and WhatsApp, and ideological positioning on the extremes of the political left- and right-wings. This relation holds when controlling for individual-level demographic and attitudinal factors, as well as country-level effects. These results demonstrate with empirical evidence that viewing political content on social media has a significant positive effect on the likelihood that citizens position themselves on the extreme ends of the left-right ideological spectrum and implies that political polarisation is a phenomenon that accompanies politically driven social media use.

Keywords: Latin America, polarisation, political consumption, political ideology, social media, survey

Procedia PDF Downloads 147