Search results for: social data analysis

Authors: Anusha Vaddiraj Pallapu

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Measuring urban sustainable development is at the forefront in contributing to overall sustainability, and it refers to attaining social equity, environmental protection and minimizing the impacts of urbanization. Assessing performance of urban issues ranging from larger consumption of natural resources by humans in terms of lifestyle to creating a polluted nearby environment, social and even economic dimensions of sustainability major issues observed such as water quality, transportation, management of solid waste and traffic pollution. However, relying on the framework of the project to do the goals of sustainable development or minimization of urban impacts through management practices is not enough to deal with the present urban issues. The aim of the sustainability is to know how severely the resources are depleted because of human consumption and how issues are characterized. The paper aims to assign benchmarks for the selected sustainability indicators for research, and analysis is done through multivariate analysis in Indian context a case of Nagpur city to identify the play role of each urban issues in the overall sustainability. The main objectives of this paper are to examine the indicators over by time basis on various scenarios and how benchmarking is used, what and which categories of values should be considered as the performance of indicators function.

Keywords: environmental sustainability indicators, principal component analysis, urban sustainability, urban clusters, benchmarking

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Authors: R. Alrashedi, A. Persaud

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This study provides insights into the readiness of users to participate in e-government activities in Saudi Arabia. A user-centric model of e-participation is developed based on a review of the literature and empirically tested. The findings are based on an online survey of a sample of 200 hundred Saudi citizens and residents living in Saudi Arabia. The study found that trust of the government, attitude towards e-participation, e-participation through the use of social media, and social influence and social identity positively influence e-participation while perceived benefits of e-government is negatively related to e-participation. This study contributes to the literature by providing empirical evidence of the drivers of e-participation. The study also provides insights that could be used by policymakers to increase the level of e-participation in Saudi Arabia.

Keywords: e-government, e-participation, social media, trust, social influence and social identity

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Authors: Bartelsen-Raemy Annabelle, Gerber Andrea

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Objectives: The adoption of the UN Convention on the Rights of Persons with Disabilities has the effect that higher education institutions in Switzerland are called upon to promote inclusive university education. In this context, our School of Social Work aims to provide fair participation and the removal of barriers in our study programmes at bachelor’s and master’s levels. In 2015 we developed a concept of reasonable adjustments for students with disabilities and chronic illness as an instrument to provide equal opportunities for those students. We reviewed the implementation of this concept as part of our quality management process. Using a qualitative research design, we explored how affected students and lecturers experience the processes and measures taken and which barriers they still perceive. Methods: We captured subjective perspectives and experience of measures by conducting 15 problem-centred interviews with affected students and three experimental focus groups with lecturers. The data was processed using structured qualitative content analysis and summarised as key categories. Results: All respondents evaluated the concept of reasonable adjustment very positively and emphasised its importance for equal opportunities. Our analysis revealed differences in the usage and perception of both groups and showed that the students interviewed were a heterogeneous group with different needs. Overall, the students described the adjustments, in particular in relation to examinations and other assignments, as a great relief. The lecturers expressed high standards for their own teaching and supervision of students and, at the same time, wished for more support from the university. However, despite the positive evaluation by the lecturers, the limits of reasonable adjustment became evident. It is necessary to consider the limits of reasonable adjustments in terms of professional skills. Conclusion: Reasonable adjustments should, therefore, be seen as an element of an inclusive university culture that must be complemented by further measures. Taking this into account, we have planned further research as a basis for the development of a diversity and inclusion policy.

Keywords: opportunities and limits, reasonable adjustment, social work education, students with disabilities

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Authors: Lina Sinevičienė

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Arising problems of countries’ public finances, social and demographic changes motivate scientific and policy debates on public spending size, structure and efficiency in order to meet the changing needs of society and business. The concept of sustainable development poses new challenges for scientists and policy-makers in the field of public finance. This paper focuses on the investigation of the relationship between government expenditure and country’s economic development in the context of sustainable development. Empirical analysis focuses on the data of the European Union (except Croatia and Luxemburg) countries. The study covers 2003 – 2012 years, using annual cross-sectional data. Summarizing the research results, it can be stated that governments should pay more attention to the needs that ensure sustainable development in the long-run when formulating public expenditure policy, particularly in the field of environment protection.

Keywords: economic development, economic growth, government expenditure, sustainable development

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Authors: D. van der Merwe

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As the environment and associated media in which creativity is expressed transitions towards digital spaces, that same creativity undergoes a transition from individual to social forms of expression. This paper explores how the emerging social construction collectively called ‘The Metaverse’ will fundamentally alter creativity: by examining creativity as a social rather than individual process, as well as the mimetic logic underlying the platforms in which this creativity is expressed, a crisis in identity, commodification and social programming is revealed wherein the artist is more a commodity than their creations, resulting in prosthetic personalities pandering to an economic logic driven by biased algorithms. Consequently the very aura of the art and creative media produced within the digital domain must be re-assessed in terms of its cultural and exhibition value.

Keywords: aura, commodification, creativity, metaverse, mimesis, social programming

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Authors: Ebru Kaymaz, Aslı İlbay Hamamcı, Yakup Enes Garip, Samet Ay

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The use of hydrogen as a fuel is important for decreasing carbon emissions. For the steel industry, reducing carbon emissions is one of the most important agendas of recent times globally. Because of the Paris Agreement requirements, European steel industry studies on green steel production. Although many literature reviews have analyzed this topic from technological and hydrogen based ironmaking, there are very few studies focused on patents of decarbonize parts of the steel industry. Hence, this study focus on technological progress of hydrogen based ironmaking and on understanding the main trends through patent data. All available patent data were collected from Questel Orbit. The trend analysis of more than 900 patent documents has been carried out by using Questel Orbit Intellixir to analyze a large number of data for scientific intelligence.

Keywords: hydrogen based ironmaking, DRI, direct reduction, carbon emission, steelmaking, patent analysis

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Authors: O. P. Popoola, O. A. Alawode, M. O. Olayiwola, A. M. Oladele

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This research work is based on using discriminant analysis to forecast crime rate in Nigeria between 1996 and 2008. The work is interested in how gender (male and female) relates to offences committed against the government, against other properties, disturbance in public places, murder/robbery offences and other offences. The data used was collected from the National Bureau of Statistics (NBS). SPSS, the statistical package was used to analyse the data. Time plot was plotted on all the 29 offences gotten from the raw data. Eigenvalues and Multivariate tests, Wilks’ Lambda, standardized canonical discriminant function coefficients and the predicted classifications were estimated. The research shows that the distribution of the scores from each function is standardized to have a mean O and a standard deviation of 1. The magnitudes of the coefficients indicate how strongly the discriminating variable affects the score. In the predicted group membership, 172 cases that were predicted to commit crime against Government group, 66 were correctly predicted and 106 were incorrectly predicted. After going through the predicted classifications, we found out that most groups numbers that were correctly predicted were less than those that were incorrectly predicted.

Keywords: discriminant analysis, DA, multivariate analysis of variance, MANOVA, canonical correlation, and Wilks’ Lambda

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Authors: Sanda-Maria Ardeleanu, Ana Crăciunescu

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This paper is sustained by our previous research on discursive strategies, whichdemonstrated that tourismhas developed and employed apromotional languageper se. We have studied this concept within the framework of audio-visual advertising by analyzing its discursive structures at the level of three main strategies (textual, visual, and both textual and visual) and confirmed the applicability of the promotional language per se within the field. Tourism, at large, represents a largely potential interdisplinary field, which allowed us to use qualitative methods of research such as Discourse Analysis (DA). Due to further research which showed that in the third phase of qualitative research methodologies, scholars in tourism recognized semiotics and DA as potential paths to follow, but which were insufficiently explored at the time, we soon realized that the natural next step to take is to bring together common qualitative methodologies for both fields, such as the method of observation, the triangulation, Discourse Analysis, etc. Therefore and in the light of fast transformations of the medium that intermediates the message, in this paper, we are going to focus on the manifestations of the promotional language in social media texts, which advertise for the urban industry of accommodation in Romania. We shall constitute a corpus of study as the basis for our research methodology and, through the empirical method of observation and DA, we propose to recognize or discover new patterns developed at textual (mainly) and visual level or the mix of the two, known as strategies of the promotional language of tourism.

Keywords: discourse analysis, promotional language of tourism, social media, urban accommodation industry, tourism

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: Shatha Khuzaee

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The study develops multimodal stylistic approach to analyse a number of BBC online news articles reporting some key events from the so called ‘Arab Uprisings’. Critical stylistics (CS) and visual grammar (VG) provide insightful arguments to the ways ideology is projected through different verbal and visual modes, yet they are mode specific because they examine how each mode projects its meaning separately and do not attempt to clarify what happens intersemiotically when the two modes co-occur. Therefore, it is the task undertaken in this research to propose multimodal stylistic approach that addresses the issue of ideology construction when the two modes co-occur. Informed by functional grammar and social semiotics, the analysis attempts to integrate three linguistic models developed in critical stylistics, namely, transitivity choices, prioritizing and hypothesizing along with their visual equivalents adopted from visual grammar to investigate the way ideology is constructed, in multimodal text, when text/image participate and interrelate in the process of meaning making on the textual level of analysis. The analysis provides comprehensive theoretical and analytical elaborations on the different points of integration between CS linguistic models and VG equivalents which operate on the textual level of analysis to better account for ideology construction in news as non-literary multimodal texts. It is argued that the analysis well thought out a plan that would remark the first step towards the integration between the well-established linguistic models of critical stylistics and that of visual analysis to analyse multimodal texts on the textual level. Both approaches are compatible to produce multimodal stylistic approach because they intend to analyse text and image depending on whatever textual evidence is available. This supports the analysis maintain the rigor and replicability needed for a stylistic analysis like the one undertaken in this study.

Keywords: multimodality, stylistics, visual grammar, social semiotics, functional grammar

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Authors: Lok Raj Joshi, Naveen Prakash Shah, Sharad Kumar Sharma, I. Ratna Bhattarai, Rajendra Basnet, Deepak Dahal, Bahagwan Maharjan, Seraphine Kaminsa

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Context: Tuberculosis (TB) is a significant health issue in Nepal, a country with a high burden of the disease. Despite efforts to control TB, there is still a gap in the notification of TB cases, which hinders effective control and treatment. This paper aims to address this notification gap and proposes strategies to improve TB control in Nepal. Research Aim: The aim of this research is to understand and address the tuberculosis notification gap in Nepal. The focus is on enhancing the healthcare system, involving the private sector and communities, raising awareness, and addressing social determinants to achieve sustainable TB control. Methodology: The research methodology involved a review of existing epidemiological data and research studies related to TB in Nepal. Additionally, consultation with an expert group from the TB control program in Nepal provided insights into the current state of TB control and challenges in addressing the notification gap. Findings: The findings reveal that only 55% of TB cases were reported in 2022, indicating a significant notification gap. Of the reported cases, only 32% and 19% were referred by the private sector and community, respectively. Furthermore, 20% of diagnosed cases were not treated in the initial phase. The estimated number of cases of multidrug-resistant TB (MDR TB) was 2,800, suggesting a low diagnosis rate. Among the diagnosed MDR TB cases, only 60% were receiving treatment. Additionally, it was observed that 20% of diagnosed MDR TB cases were from India and not enrolling in TB treatment in Nepal, indicating a high rate of defaulters. Theoretical Importance: The study highlights the importance of adopting a holistic strategy to address the notification gap in TB cases in Nepal. It emphasizes the need to enhance healthcare infrastructure, raise awareness, involve the private sector and local communities, establish effective methods to trace initial defaulters, implement TB interventions in border regions, and mitigate the social stigma associated with the disease. Data Collection and Analysis Procedures: Data for this study was collected through a review of existing epidemiological data and research studies. The data were then analyzed to identify patterns, trends, and gaps in TB case notification in Nepal.

Keywords: TB, tuberculosis, private sector, community, migrants, nepal

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Authors: Sherine Farouk, Fauzia Jabeen

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The purpose of this study is to examine the role played by ethical climate and CSR on organizational performance in public sector organizations. In particular, the research will shed light on the link between formalized ethical procedures and employee responses including corporate social responsibility, and organizational performance among public sector employees. Data was collected from 425 employees working in public sector organizations in Abu Dhabi, the capital of United Arab Emirates. Structural Equation Modeling will be used to test the proposed hypotheses. The paper contributes to the literature by being one of the first to study CSR and ethical climate within a Middle Eastern context, and will offer important implications for theory and practice.

Keywords: corporate social responsibility, ethical climate, organizational performance, United Arab Emirates

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Authors: Stephen Bahooshy

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Our understanding of gender inequality has advanced in recent years. Differences in pay and societal gendered behaviour expectations have been emphasized. It is acknowledged globally that gender shapes everyone’s experiences of health and social care, including access to care, use of services and products, and the interaction with care providers. NHS Digital in England collects data from local authorities on the number of carers and people with support needs and the services they access. This data does not provide a gender breakdown. Caring can have many positive and negative impacts on carers’ health and wellbeing. For example, caring can improve physical health, provide a sense of pride and purpose, and reduced stress levels for those who undertake a caring role by choice. Negatives of caring include financial concerns, social isolation, a reduction in earnings, and not being recognized as a carer or involved and consulted by health and social care professionals. Treating male and female carers differently is by definition unequitable and precludes one gender from receiving the benefits of caring whilst potentially overburdening the other with the negatives of caring. In order to explore the issue on a preliminary basis, five local authorities who provide statutory adult social care services in England were sent Freedom of Information requests in 2019. The authorities were selected to include county councils and London boroughs. The authorities were asked to provide data on the amount of money spent on care at home packages to people over 65 years, broken down by gender and carer gender for each financial year between 2013 and 2019. Results indicated that in each financial year, female carers supporting someone over 65 years received less financial support for care at home support packages than male carers. Over the six-year period, this difference equated to a £9.5k deficit in financial support received on average per female carer when compared to male carers. An example of a London borough with the highest disparity presented an average weekly spend on care at home for people over 65 with a carer of £261.35 for male carers and £165.46 for female carers. Consequently, female carers in this borough received on average £95.89 less per week in care at home support than male carers. This highlights a real and potentially detrimental disparity in the care support received to female carers in order to support them to continue to care in parts of England. More research should be undertaken in this area to better explore this issue and to understand if these findings are unique to these social care providers or part of a wider phenomenon. NHS Digital should request local authorities collect data on gender in the same way that large employers in the United Kingdom are required by law to provide data on staff salaries by gender. People who allocate social care packages of support should consider the impact of gender when allocating support packages to people with support needs and who have carers to reduce any potential impact of gender bias on their decision-making.

Keywords: caregivers, carers, gender equality, social care

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Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Priya Nambisan, Lien B. Nguyen

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Women participate extensively in the healthcare field, professionally (as physicians, nurses, dietitians, etc.) as well as informally (as caregivers at home). This provides them with a better understanding of the health needs of people. Women are also in the forefront of using social media and other mobile health related apps. Further, many health mobile apps are specifically designed for women users. All of these indicate the potential for women to be successful entrepreneurs in healthcare, especially, in the area of mobile health app development. However, extant research in entrepreneurship has paid limited attention to women entrepreneurship in healthcare. The objective of this study is to determine the key factors that shape the intentions and actions of women entrepreneurs with regard to their entrepreneurial pursuits in the healthcare field. Specifically, the study advances several hypotheses that relate key variables such as personal skills and capabilities, experience, support from institutions and family, and perceptions regarding entrepreneurship to individual intentions and actions regarding entrepreneurship (specifically, in the area of mobile apps). The study research model will be validated using survey data collected from potential women entrepreneurs in the healthcare field – students in the area of health informatics and engineering. The questionnaire-based survey relates to woman respondents’ intention to become entrepreneurs in healthcare and the key factors (independent variables) that may facilitate or inhibit their entrepreneurial intentions and pursuits. The survey data collection is currently ongoing. We also plan to conduct semi-structured interviews with around 10-15 women entrepreneurs who are currently developing mobile apps to understand the key issues and challenges that they face in this area. This is an exploratory study and as such our goal is to combine the findings from the regression analysis of the survey data and that from the content analysis of the interview data to inform on future research on women entrepreneurship in healthcare. The study findings will hold important policy implications, specifically for the development of new programs and initiatives to promote women entrepreneurship, particularly in healthcare and technology areas.

Keywords: women entrepreneurship, healthcare, mobile apps, health apps

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Dawit Thomas Lambamo

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Conduct disorder has become a major health and social problem; it is the most common psychiatric problem diagnosed among students which affect the academic and social interaction of students. This intervention was conducted in Dil Betigil primary school. After identifying six students with conduct disorder in Dil Betigil primary school, the intervention was conducted using a true experimental research design specifically pretest and posttest control group design. Data from teachers and parents of the students with conduct disorder were collected using adapted conduct disorder scale and semi-structured interview. The independent sample t-test of Pretest results of both experimental and control group indicated that there is no statistically significant difference between experimental and control groups. Intervention is carried out to enhance their social interaction and to decrees aggressive, a serious violation of rules and theft behavior of students in collaboration with teachers and parents. After six intervention weeks the post-test result showed that there was statistically significant difference in aggression and serious violation between the experimental and control groups, but there was no statistically significant mean difference regarding deceitful or theft between the experimental and control group.

Keywords: conduct, disorder, social interaction, interaction

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Authors: Dana R. Thomson, Catherine Linard, Sabine Vanhuysse, Jessica E. Steele, Michal Shimoni, Jose Siri, Waleska Caiaffa, Megumi Rosenberg, Eleonore Wolff, Tais Grippa, Stefanos Georganos, Helen Elsey

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The Sustainable Development Goals (SDGs) and Urban Health Equity Assessment and Response Tool (Urban HEART) identify dozens of key indicators to help local decision-makers prioritize and track inequalities in health outcomes. However, presentations and discussions at the International Conference on Urban Health (ICUH) 2017 suggested that additional indicators are needed to make decisions and policies. A local decision-maker may realize that malaria or road accidents are a top priority. However, s/he needs additional health determinant indicators, for example about standing water or traffic, to address the priority and reduce inequalities. Health determinants reflect the physical and social environments that influence health outcomes often at community- and societal-levels and include such indicators as access to quality health facilities, access to safe parks, traffic density, location of slum areas, air pollution, social exclusion, and social networks. Indicator identification and disaggregation are necessarily constrained by available datasets – typically collected about households and individuals in surveys, censuses, and administrative records. Continued advancements in earth observation, data storage, computing and mobile technologies mean that new sources of health determinants indicators derived from 'big data' are becoming available at fine geographic scale. Big data includes high-resolution satellite imagery and aggregated, anonymized mobile phone data. While big data are themselves not representative of the population (e.g., satellite images depict the physical environment), they can provide information about population density, wealth, mobility, and social environments with tremendous detail and accuracy when combined with population-representative survey, census, administrative and health system data. The aim of this paper is to (1) flag to data scientists important indicators needed by health decision-makers at the city and sub-city scale - ideally free and publicly available, and (2) summarize for local decision-makers new datasets that can be generated from big data, with layperson descriptions of difficulties in generating them. We include SDGs and Urban HEART indicators, as well as indicators mentioned by decision-makers attending ICUH 2017.

Keywords: health determinant, health outcome, mobile phone, remote sensing, satellite imagery, SDG, urban HEART

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Authors: Utkrash Sarkar, Vineet Tiwari, Shailendra Singh

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The development of social media has brought about a tremendous change in the marketing scenario for every industry. It has become a new hybrid element of the promotional mix in the marketing segment. This paper tries to show some light on the fact that in today’s scenario social media is a platform that everyone should take in consideration for any type of marketing campaign. In this paper, we have formulated a questionnaire, and through it, we have tried to gather information from the respondents that how social media is influencing their decision when they choose their travel destinations for tourism purpose, does it help in creating any awareness about places which they don’t have an idea? As a result, guiding the state government and providing them with a marketing strategy that how they can use social media in a better manner so that they could help increase their revenue and can make people aware about the places of the state which the target audience can plan to go for their next vacation.

Keywords: social media, marketing, information, decision making

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Authors: Pailin Klinkesorn

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The research aimed to study the use of learning strategies for Japanese language among college students with different learning achievements who study Japanese as a foreign language in the Higher Education’s level. The survey was conducted by using a questionnaire adapted from Strategy Inventory for language Learning or SILL (Oxford, 1990), consisting of two parts: questions about personal data and questions about the use of learning strategies for Japanese language. The samples of college students in the Japanese language program were purposively selected from Suansunandha Rajabhat University. The data from the questionnaire was statistically analyzed by using mean scores and one-way ANOVA. The results showed that Social Strategies was used by the greatest number of college students, whereas Memory Strategies was used by the least number of students. The students in different levels used various strategies, including Memory Strategies, Cognitive Strategies, Metacognitive Strategies and Social Strategies, at the significance level of 0.05. In addition, the students with different learning achievements also used different strategies at the significance level of 0.05. Further studies can explore learning strategies of other groups of Japanese learners, such as university students or company employees. Moreover, learning strategies for language skills, including listening, speaking, reading and writing, can be analyzed for better understanding of learners’ characteristics and for teaching applications.

Keywords: language learning strategies, achievement, Japanese, college students

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Authors: Justyna Żywiołek, Marek Matulewski

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Data, is information processed by enterprises for primary and secondary purposes as processes. Thanks to processing, the sales process takes place; in the case of the surveyed companies, sales take place online. However, this indirect form of contact with the customer causes many problems for both customers and furniture manufacturers. The article presents solutions that would solve problems related to the analysis of data and information in the order fulfillment process sent to post-warranty service. The article also presents an analysis of threats to the security of this information, both for customers and the enterprise.

Keywords: ordering furniture online, information security, furniture industry, enterprise security, risk analysis

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Authors: R. A. Harun, N. M. Ishak, N. Yusoff, S. Amat

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This quantitative research is aimed to identify the level of leadership quality and emotional intelligence for members of Students' Representatives Council (SRC) of Malaysian Public Universities (MPU). The variables include the leadership quality and emotional quotient (EQ). 238 SRC members in MPU were selected as subjects of the study. Data were collected using two instruments i.e. Malaysian Emotional Quotient Inventory (MEQI) and Ayu-Noriah Leadership Audit Trail Inventory (Ayu-Noriah, LATI). Data were analyzed using descriptive (mean and percentage). Research findings showed that the subjects scored highly in four out of five EQ domains (Self-Regulations, Self-Motivation, Empathy and Social Skills). However, the subjects scored medium to low in Self-Awareness. Analysis on the sub domains (a total of 28 sub domains) showed that the subjects scored high in 17 sub domains for EQ, whilst another 11 were at medium level. The overall analysis indicates that the subjects have high level of EQ. Findings on their leadership qualities showed that they obtained high scores in all seven factors that were measured i.e. Strategy and Leadership Model, Recruit, Review Performance and Honor, Deploy Strategically, Developing, Engage and Retain and Built HR Capabilities/Line Ownership. The overall score for leadership qualities was found to be high.

Keywords: emotional intelligence, leadership, students representative council, Malaysian public universities

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Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

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The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

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Authors: Sulmaz Mozaffari, Zahra Mozaffari, Saman Mozaffari

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Man has always tried to find the Ideal place for life and he has experienced a lot of problems. So many internal and external limits has been on his way. Today man is threatened by so many crisis because of his specific look to the world. Literature as a universal science has not ignored this problem either. Children's literature has tried to present the social, cultural, religious and economical problems in tales and novels. This research tries to analyse social and cultural problems related to 10th century children from social point of criticism.

Keywords: social criticism, crisis, children's literature, tale

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Authors: Grace Omowunmi Soyebi

Abstract:

Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

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Authors: Kamal Kasmaoui, Farid Makhlouf

Abstract:

This article seeks to assess the role of the level of interpersonal trust in a country in the remittance landscape. Using historical data from the 2010-2014 wave of the World Value Survey (WVS) for interpersonal trust, our findings underline the substitution role played by the interpersonal trust with remittances. More accurately, remittances tend to drop when the rate of interpersonal trust in the country of origin is high. Overall, a rise in trust is likely to underpin social cohesion, limiting, therefore, the need for remittances. These results are still fairly solid and unambiguous after controlling for confounding factors and possible reverse causality.

Keywords: interpersonal trust, social capital, remittances, 2SLS

Procedia PDF Downloads 174

Authors: Wenhsuan Lee, Yachi Chang, Yingyih Shih

Abstract:

In clinical practices, it is common that while facing the unknown progress of their disease, palliative care patients may easily feel anxious and depressed. These types of reactions are a cause of psychosomatic diseases and may also influence treatment results. However, the purpose of palliative care is to provide relief from all kinds of pains. Therefore, how to make patients more comfortable is an issue worth studying. This study adopted the “bio-psycho-social model” proposed by Engel and applied spontaneous breathing training, in the hope of seeing patients’ psychological state changes caused by their physiological state changes, improvements in their anxious conditions, corresponding adjustments of their cognitive functions, and further enhancement of their social functions and the social support system. This study will be a one-year study. Palliative care outpatients will be recruited and assigned to the experimental group or the control group for six outpatient visits (once a month), with 80 patients in each group. The patients of both groups agreed that this study can collect their physiological quantitative data using an HRV device before the first outpatient visit. They also agreed to answer the “Beck Anxiety Inventory (BAI)”, the “Taiwanese version of the WHOQOL-BREF questionnaire” before the first outpatient visit, to fill a self-report questionnaire after each outpatient visit, and to answer the “Beck Anxiety Inventory (BAI)”, the “Taiwanese version of the WHOQOL-BREF questionnaire” after the last outpatient visit. The patients of the experimental group agreed to receive the breathing training under HRV monitoring during the first outpatient visit of this study. Before each of the following three outpatient visits, they were required to fill a self-report questionnaire regarding their breathing practices after going home. After the outpatient visits, they were taught how to practice breathing through an HRV device and asked to practice it after going home. Later, based on the results from the HRV data analyses and the pre-tests and post-tests of the “Beck Anxiety Inventory (BAI)”, the “Taiwanese version of the WHOQOL-BREF questionnaire”, the influence of the breathing training in the bio, psycho, and social aspects were evaluated. The data collected through the self-report questionnaires of the patients of both groups were used to explore the possible interfering factors among the bio, psycho, and social changes. It is expected that this study will support the “bio-psycho-social model” proposed by Engel, meaning that bio, psycho, and social supports are closely related, and that breathing training helps to transform palliative care patients’ psychological feelings of anxiety and depression, to facilitate their positive interactions with others, and to improve the quality medical care for them.

Keywords: palliative care, breathing training, bio-psycho-social model, heart rate variability

Procedia PDF Downloads 259

Authors: Theertha Chandroth

Abstract:

This paper presents a comparative study on how to check JSON (JavaScript Object Notation) data against XML (eXtensible Markup Language) data from a software testing point of view. JSON and XML are widely used data interchange formats, each with its unique syntax and structure. The objective is to explore various techniques and methodologies for validating comparison and integration between JSON data to XML and vice versa. By understanding the process of checking JSON data against XML data, testers, developers and data practitioners can ensure accurate data representation, seamless data interchange, and effective data validation.

Keywords: XML, JSON, data comparison, integration testing, Python, SQL

Procedia PDF Downloads 140

Authors: Saghir Ahmad, Abid Hussain Ch, Misbah Malik, Ayesha Batool

Abstract:

Terrorism is the marvel in which dreadful circumstance is made by a gathering of individuals who view themselves as abused by society. Terrorism is the unlawful utilization of power or viciousness by a man or a sorted out gathering by the general population or property with the aim of intimidation or compulsion of social orders or governments frequently for ideological or political reasons. Terrorism is as old as people. The main aim of the study was to find out the causes of terrorism through the perceptions of the universities students of teacher training institutions. This study was quantitative in nature. Survey method was used to collect data. A sample of two hundred and sixty seven students was selected from public universities. A five point Likert scale was used to collect data. Mean, Standard deviation, independent sample t-test, and One Way ANOVA were applied to analyze the data. The major findings of the study indicated that students perceived the main causes of terrorism are poverty, foreign interference, wrong concept of Islamization, and social injustice. It is also concluded that mostly, students think that drone attacks are promoting the terrorist activities. The education is key to eliminate the terrorism. There is need to educate the people and specially youngsters to bring the peace in the world.

Keywords: dreadful circumstance, governments, power, students, terrorism

Procedia PDF Downloads 548