Search results for: government (big) data

Authors: Nur Amalina Dayana Abd Aziz

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Assessment is an integral part of teaching and learning in any syllabus in the world. Recently, a new assessment system, School-Based Assessment (SBA) was introduced and implemented in the Malaysian education system to promote a more holistic, integrated and balanced assessment system. This effort is part of the reformation made in the Government Transformation Plan (GTP) to produce a world-class human capital as we are reaching and achieving the Vision 2020 in the near future. However, this new change has raised awareness and concerns from teachers, students, parents and non-profit organizations on how the new assessment is to be implemented and how it is affecting the students and teachers particularly. Therefore, this paper aims to investigate the issues that teachers face in implementing SBA in primary schools, the measures taken to address the issues and to propose ways of managing school-based assessment. Five national primary schools focusing in the urban areas in the Selangor state are chosen for this study to carry out. Data for the study will be gathered from interviews with teachers from each school, surveys and classrooms observation will be conducted in each school, and relevant documents are collected from the selected schools. The findings of this study will present the current issues that teachers from various types of national primary schools are facing and what actions they took to overcome the problems in carrying out SBA. Suggestions on how to better manage school-based assessment for teachers are also provided in this paper.

Keywords: community of practice, curriculum, managing change, school-based assessment

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Authors: Eusebio Odiari, Mark Birkin, Susan Grant-Muller, Nicolas Malleson

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Big data typically refers to consumer datasets revealing some detailed heterogeneity in human behavior, which if harnessed appropriately, could potentially revolutionize our understanding of the collective phenomena of the physical world. Inadvertent missing values skew these datasets and compromise the validity of the thesis. Here we discuss a conceptually consistent strategy for identifying other relevant datasets to combine with available big data, to plug the gaps and to create a rich requisite comprehensive dataset for subsequent analysis. Specifically, emphasis is on how these methodologies can for the first time enable the construction of more detailed pictures of passenger demand and drivers of mobility on the railways. These methodologies can predict the influence of changes within the network (like a change in time-table or impact of a new station), explain local phenomena outside the network (like rail-heading) and the other impacts of urban morphology. Our analysis also reveals that our new imputation data model provides for more equitable revenue sharing amongst network operators who manage different parts of the integrated UK railways.

Keywords: big-data, micro-simulation, mobility, ticketing-data, commuters, transport, synthetic, population

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Authors: C. P. Chukwuka, E. V. Chukwuka, F. Ukwadi

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This paper focuses on the advancement and societal impact of artificial intelligence (AI) systems. It explores the need for a theoretical framework in corporate governance, specifically in the context of 'hybrid' companies that have a mix of private and government ownership. The paper emphasizes the potential of AI to address challenges faced by these companies and highlights the importance of the less-explored state model in corporate governance. The aim of this research is to enhance AI systems for global impact and positive societal outcomes. It aims to explore the role of AI in refining corporate governance in hybrid companies and uncover nuanced insights into complex ownership structures. The methodology involves leveraging the capabilities of AI to address the challenges faced by hybrid companies in corporate governance. The researchers will analyze existing theoretical frameworks in corporate governance and integrate AI systems to improve problem-solving and understanding of intricate systems. The paper suggests that improved AI systems have the potential to shape a more informed and responsible corporate landscape. AI can uncover nuanced insights and navigate complex ownership structures in hybrid companies, leading to greater efficacy and positive societal outcomes. The theoretical importance of this research lies in the exploration of the role of AI in corporate governance, particularly in the context of hybrid companies. By integrating AI systems, the paper highlights the potential for improved problem-solving and understanding of intricate systems, contributing to a more informed and responsible corporate landscape. The data for this research will be collected from existing literature on corporate governance, specifically focusing on hybrid companies. Additionally, data on AI capabilities and their application in corporate governance will be collected. The collected data will be analyzed through a systematic review of existing theoretical frameworks in corporate governance. The researchers will also analyze the capabilities of AI systems and their potential application in addressing the challenges faced by hybrid companies. The findings will be synthesized and compared to identify patterns and potential improvements. The research concludes that AI systems have the potential to enhance corporate governance in hybrid companies, leading to greater efficacy and positive societal outcomes. By leveraging AI capabilities, nuanced insights can be uncovered, and complex ownership structures can be navigated, shaping a more informed and responsible corporate landscape. The findings highlight the importance of integrating AI in refining problem-solving and understanding intricate systems for global impact.

Keywords: advancement, artificial intelligence, challenges, societal impact

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Authors: Wuqi Yang, Sufeng Li, Linda Zhai, Zhizhong Yuan, Shengli Wang

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How to assess and evaluate a not-for-profit (NFP) organisation’s performance should be of concern to all stakeholders because, amongst other things, without correctly evaluating its performance might affect an NFP being not able to continue to meet its service objectives. Given the growing importance of this sector in China, more and more existing and potential donors, governments and others are starting to take an increased interest in the financial conditions and performance of NFPs. However, when these various groups look for ways (methods) to assess the performance of NFPs, they find there has been relatively little research conducted into methods for assessing the performance of NFPs in China. Furthermore, there does not appear to have been any research to date into the performance evaluation of Chinese NFPs. The focus of this paper is to investigate how the Chinese government manages and evaluates not-for-profit (NFP) organisations' performances in China. Through examining and evaluating the NFPs in China from different aspects such as business development, mission fulfillment, financial position and other status, this paper finds some institutional constraints currently facing by the NFPs in China. At the end of this paper, a new regulatory framework is proposed for regulators’ considerations. The research methods are based on a combination of a literature review; using Balanced Scorecard to assess NFPs in China; Case Study method is employed to analyse a charity foundation’s performance in Hebei Province and proposing solutions to resolve the current issues and challenges facing by the NFPs. These solutions include: formulating laws and regulations on NFPs; simplifying management procedures, introducing tax incentives, providing financial support and other incentives to support the development of non-profit organizations in China. This study provides the first step towards a greater understanding of the NFP performance evaluation in China. It is expected that the findings and solutions from this study will be useful to anyone involved with the China NFP sector; particularly CEOs, managers, bankers, independent auditors and government agencies.

Keywords: Chinese non-profit organizations, evaluation, management, supervision

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Authors: Xiaochen Mu

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Data rights confirmation, as a key legal issue in the development of the digital economy, is undergoing a transition from a traditional rights paradigm to a more complex private-economic paradigm. In this process, data rights confirmation has evolved from a simple claim of rights to a complex structure encompassing multiple dimensions of personality rights and property rights. Current data rights confirmation practices are primarily reflected in two models: holistic rights confirmation and process rights confirmation. The holistic rights confirmation model continues the traditional "one object, one right" theory, while the process rights confirmation model, through contractual relationships in the data processing process, recognizes rights that are more adaptable to the needs of data circulation and value release. In the design of the data property rights system, there is a hierarchical characteristic aimed at decoupling from raw data to data applications through horizontal stratification and vertical staging. This design not only respects the ownership rights of data originators but also, based on the usufructuary rights of enterprises, constructs a corresponding rights system for different stages of data processing activities. The subjects of data property rights include both data originators, such as users, and data producers, such as enterprises, who enjoy different rights at different stages of data processing. The intellectual property rights system, with the mission of incentivizing innovation and promoting the advancement of science, culture, and the arts, provides a complete set of mechanisms for protecting innovative results. However, unlike traditional private property rights, the granting of intellectual property rights is not an end in itself; the purpose of the intellectual property system is to balance the exclusive rights of the rights holders with the prosperity and long-term development of society's public learning and the entire field of science, culture, and the arts. Therefore, the intellectual property granting mechanism provides both protection and limitations for the rights holder. This perfectly aligns with the dual attributes of data. In terms of achieving the protection of data property rights, the granting of intellectual property rights is an important institutional choice that can enhance the effectiveness of the data property exchange mechanism. Although this is not the only path, the granting of data property rights within the framework of the intellectual property rights system helps to establish fundamental legal relationships and rights confirmation mechanisms and is more compatible with the classification and grading system of data. The modernity of the intellectual property rights system allows it to adapt to the needs of big data technology development through special clauses or industry guidelines, thus promoting the comprehensive advancement of data intellectual property rights legislation. This paper analyzes data protection under the virtual property layer theory and two-fold virtual property rights system. Based on the “bundle of right” theory, this paper establishes specific three-level data rights. This paper analyzes the cases: Google v. Vidal-Hall, Halliday v Creation Consumer Finance, Douglas v Hello Limited, Campbell v MGN and Imerman v Tchenquiz. This paper concluded that recognizing property rights over personal data and protecting data under the framework of intellectual property will be beneficial to establish the tort of misuse of personal information.

Keywords: data protection, property rights, intellectual property, Big data

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Authors: Randy D. Colon

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Through a freedom of information request, data pertaining to Housing Choice Voucher (HCV) households has been obtained from the Chicago Housing Authority, including rent price and number of bedrooms per HCV household, community area, and zip code from 2013 to the first quarter of 2018. Similar data pertaining to the private rental market will be obtained through public records found through the United States Department of Housing and Urban Development. The datasets will be analyzed through statistical and mapping software to investigate the potential link between HCV households and distorted rent prices. Quantitative data will be supplemented by qualitative data to investigate the lived experience of Chicago residents. Qualitative data will be collected at community meetings in the Chicago Englewood neighborhood through participation in neighborhood meetings and informal interviews with residents and community leaders. The qualitative data will be used to gain insight on the lived experience of community leaders and residents of the Englewood neighborhood in relation to housing, the rental market, and HCV. While there is an abundance of quantitative data on this subject, this qualitative data is necessary to capture the lived experience of local residents effected by a changing rental market. This topic reflects concerns voiced by members of the Englewood community, and this study aims to keep the community relevant in its findings.

Keywords: Chicago, housing, housing choice voucher program, housing subsidies, rental market

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Authors: Amir Tosson, Mohammad Reza, Christian Gutt

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Metadata stands at the forefront of advancing data management practices within research communities, with particular significance in the realms of neutron and photon scattering. This paper introduces a groundbreaking approach—dynamic metadata schema—within the context of X-ray Photon Correlation Spectroscopy (XPCS). XPCS, a potent technique unravelling nanoscale dynamic processes, serves as an illustrative use case to demonstrate how dynamic metadata can revolutionize data acquisition, sharing, and analysis workflows. This paper explores the challenges encountered by the neutron and photon communities in navigating intricate data landscapes and highlights the prowess of dynamic metadata in addressing these hurdles. Our proposed approach empowers researchers to tailor metadata definitions to the evolving demands of experiments, thereby facilitating streamlined data integration, traceability, and collaborative exploration. Through tangible examples from the XPCS domain, we showcase how embracing dynamic metadata standards bestows advantages, enhancing data reproducibility, interoperability, and the diffusion of knowledge. Ultimately, this paper underscores the transformative potential of dynamic metadata, heralding a paradigm shift in data management within the neutron and photon research communities.

Keywords: metadata, FAIR, data analysis, XPCS, IoT

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Authors: Lukman Abiodun Nafiu

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

Keywords: Diseases, Mortality, Children, Vaccination

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Authors: Jae Young Park, Hwansu Jung, Jong Tae Kim

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Whether the data has been well parallelized is an important factor in the Solid-State-Drive (SSD) performance. SSD parallelization is affected by allocation scheme and it is directly connected to SSD performance. There are dynamic allocation and static allocation in representative allocation schemes. Dynamic allocation is more adaptive in exploiting write operation parallelism, while static allocation is better in read operation parallelism. Therefore, it is hard to select the appropriate allocation scheme when the workload is mixed read and write operations. We simulated conditions on a few mixed data patterns and analyzed the results to help the right choice for better performance. As the results, if data arrival interval is long enough prior operations to be finished and continuous read intensive data environment static allocation is more suitable. Dynamic allocation performs the best on write performance and random data patterns.

Keywords: dynamic allocation, NAND flash based SSD, SSD parallelism, static allocation

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Authors: Rashmi Raghunandan, Sanjana Shankar, Rakshitha K. Bhat

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Social media contributes a vast amount of data and information about individuals to the internet. This project will greatly reduce the need for unnecessary manual analysis of large and diverse social media profiles by filtering out and combining the useful information from various social media profiles, eliminating irrelevant data. It differs from the existing social media aggregators in that it does not provide a consolidated view of various profiles. Instead, it provides consolidated INFORMATION derived from the subject’s posts and other activities. It also allows analysis over multiple profiles and analytics based on several profiles. We strive to provide a query system to provide a natural language answer to questions when a user does not wish to go through the entire profile. The information provided can be filtered according to the different use cases it is used for.

Keywords: social network, analysis, Facebook, Linkedin, git, big data

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Authors: Sufrin Hannan, Budi Suharjo, Rita Nurmalina, Kirbrandoko

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The challenge for independent surveyor service companies now is growing with increasing uncertainty in business. Protection from the government for domestic independent surveyor industry from competitor attack, such as entering the global surveyors to Indonesia also no longer exists. Therefore, building customer loyalty becomes very important to create a long-term relationship between an independent surveyor with its customers. This study aims to develop a model that can be used to build customer loyalty by looking at various factors that determine customer loyalty, especially on independent surveyors for coal inspection in Indonesia. The development of this model uses the relationship marketing approach. Testing of the hypothesis is done by testing the variables that determine customer loyalty, either directly or indirectly, which amounted to 10 variables. The data were collected from 200 questionnaires filled by independent surveyor company decision makers from 51 exporting companies and coal trading companies in Indonesia and analyzed using Structural Equation Model (SEM). The results show that customer loyalty of independent surveyors is influenced by customer satisfaction, trust, switching-barrier, and relationship-bond. Research on customer satisfaction shows that customer satisfaction is influenced by the perceived quality and perceived value, while perceived quality is influenced by reliability, assurance, responsiveness, and empathy.

Keywords: relationship marketing, customer loyalty, customer satisfaction, switching barriers, relationship bonds

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Authors: Rima Shishakly, Mervyn Misajon

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Education is similar to other businesses and industries. Achieving data integrity is essential in order to attain a significant supporting for all the stakeholders in the educational sector. Efficient data collect, flow, processing, storing and retrieving are vital in order to deliver successful solutions to the different stakeholders. Ministry of Education (MOE) in United Arab Emirates (UAE) has adopted ‘Education 2020’ a series of five-year plans designed to introduce advanced education management information systems. As part of this program, in 2010 MOE implemented Student Information Systems (SIS) to manage and monitor the students’ data and information flow between MOE and international private schools in UAE. This paper is going to discuss data integrity concerns between MOE, and private schools. The paper will clarify the data integrity issues and will indicate the challenges that face private schools in UAE.

Keywords: education management information systems (EMIS), student information system (SIS), United Arab Emirates (UAE), ministry of education (MOE), (KHDA) the knowledge and human development authority, Abu Dhabi educational counsel (ADEC)

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Authors: Zahidul Islam

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This study investigates the effectiveness of resourcing in post-disaster housing reconstruction with reference to Cyclones Sidr and Aila in Bangladesh. Through evaluating three key theories- Build Back Better approach, Balance Scorecard approach and Dynamic Competency theories, the synthesis of literature, and empirical fieldwork, this research develops a dynamic theoretical framework that moves the trajectory of post-disaster housing reconstruction towards the reconstruction of more resilient houses. The ultimate goal of any post-disaster housing reconstruction project is to provide quality houses and to achieve high levels of satisfaction for beneficiaries. However, post-disaster reconstruction projects often fail in their stated objectives; only 10-20% housing needs are met, with most houses constructed on a temporary rather than permanent basis. A number of scholars have argued that access to resources can significantly increase the capacity and capability of disaster victims to rebuild their lives, including the construction of new homes. This study draws on structured interviews of 285 villagers affected by cyclones to investigate the effectiveness of resourcing in rebuilding houses after Cyclone Sidr in 2007 and Cyclone Aila in 2009. Furthermore, semi-structured interviews were conducted with 20 key stakeholders in UNDP, Oxfam, government officials, and national and international NGOs. The results of this study show that recovery rate of cyclone resilient houses that can withstand cyclone is very low and majority of the population are still vulnerable. Furthermore, hierarchical regression of survey data and thematic analyses of qualitative data indicate that access to resources, level of education, quality of building materials and income generating activities of the respondents are critical for effective post-disaster recovery. Conversely, resource availability, lack of coordination among participant organisations, corruption and lack of access to appropriate land constituted significant obstacles to livelihood recovery. Finally, this study makes significant theoretical contributions to theories of post-disaster recovery by introducing new variables and measures for evaluating the quality and effectiveness of post-disaster housing.

Keywords: disaster, resourcing, housing, resilience

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Authors: Kamel Belammi, Houria Fatrim

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imbalanced data set, a problem often found in real world application, can cause seriously negative effect on classification performance of machine learning algorithms. There have been many attempts at dealing with classification of imbalanced data sets. In medical diagnosis classification, we often face the imbalanced number of data samples between the classes in which there are not enough samples in rare classes. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weight and some rules of thumb to determine those weights. After the balancing phase, we applythe different classifiers (support vector machine (SVM), k- nearest neighbor (KNN) and multilayer neuronal networks (MNN)) for balanced data set. We have also compared the obtained results before and after balancing method.

Keywords: multilayer neural networks, k- nearest neighbor, support vector machine, imbalanced medical data, least mean square algorithm, diabetes

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Authors: A. E. Obayelu, S. O. Olubiyo

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Food is different from other commodities because everybody needs food for survival. This has led to a shift in focus to food security in the global policy arena. However, there is paucity of studies on the interactions between food security, migration, urbanization and population rise. This paper therefore look at the linkages between migration and food security in the context of rapid urbanization and population rise of Nigeria. The study obtained data and information from both secondary sources and primary method through the voice of some selected Nigerians through telephone interview. The findings revealed that, the primary factor for the rapid urbanization in Nigeria is migration; most foods are still produced by peasant farmers who are scattered all over the rural areas and not multinational companies who produce on large scale. The country is still characterized with inadequate infrastructural facilities and services to cater for growing population. There are no protective policies enforced by the Nigeria government. In most cases, the migrants are left entirely on mercy of what they can find to due for survival. The most common coping mechanisms by migrants from rural to urban areas are changing food intake in terms of quantity, quality, diversity and frequency and prioritizing children. Policies that address urban food security need to consider the complex relationship between rapid population rise and migration and appropriate transformations that will be able to manage urbanization. With increasing rate of urbanization, the focus of food security should no longer be that of rural only

Keywords: agricultural commercialization, agricultural transformation, food security, urban, urbanization

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Authors: Eugenio Ferrer Santiago

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The growing complexities of the modern world on high-end gadgets, software applications, scams, identity theft, and Artificial Intelligence (AI) make the “uninformed” the weak and vulnerable to be victims of cybercrimes. Artificial Intelligence is not a new thing in our daily lives; the principles of database management, logical programming, and garbage in and garbage out are all connected to AI. The Philippines had in place legal safeguards against the abuse of cyberspace, but self-regulation of key industry players and self-protection by individuals are primordial to attain the success of these initiatives. Data protection, Data Privacy, and Research Ethics must work hand in hand during the policy process in the course of urban planning practice in different environments. This paper focuses on the interconnection of data protection, data privacy, and research ethics in coming up with clear-cut policies against perpetrators in the urban planning professional practice relevant in sustainable communities and smart cities. This paper shall use expository methodology under qualitative research using secondary data from related literature, interviews/blogs, and the World Wide Web resources. The claims and recommendations of this paper will help policymakers and implementers in the policy cycle. This paper shall contribute to the body of knowledge as a simple treatise and communication channel to the reading community and future researchers to validate the claims and start an intellectual discourse for better knowledge generation for the good of all in the near future.

Keywords: data privacy, data protection, urban planning, research ethics

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Authors: Abeer K. Jameel, Harry Evdorides

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Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: road safety, Iraq, crash data, road risk assessment, The International Road Assessment Program (iRAP)

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Authors: Charles P. Mukumba, Kahilu K. Shakantu

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Achieving the Sustainable Development Goals [SDGs] is a key to achieving transformational results that support Zambia’s development. Public procurement is an integral to the government’s mission to deliver goods and services, in a timely and economic manner beyond the value of money spent. This study explores the link between sustainable public procurement and the SDG targets in Zambia. And to validate the established links with the public sector procurement in Zambia. The study employed qualitative research using semi-structured interviews with 18 public procurement officials. The collected data was analysed using thematic analysis. The findings indicate that public procurement plays a fundamental role in achieving the sustainable development goals [SDGs] by helping to deliver core public services that support SDGs and also by systematising and co-delivering added value along the way. The study further established the importance of sustainable public procurement within the context of development. The interviews were limited to mainstream public sector procurement entities in Lusaka, Zambia. Sustainable public procurement actions have the potential to impact SDG goals. Promoting sustainable public procurement will enhance sustainable development and significantly improve supply chain that would benefit the economy, society and environment. Findings will inform policy-makers how to strategically design sustainable public procurement policy by attuning it to procuring entities objectives and priorities in order to contribute to the attainment of SDGs.

Keywords: sustainable public procurement, sustainable development goals, target, Zambia

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Authors: Sinead Impey, Damon Berry, Selma Furtado, Miriam Galvin, Loretto Grogan, Orla Hardiman, Lucy Hederman, Mark Heverin, Vincent Wade, Linda Douris, Declan O'Sullivan, Gaye Stephens

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Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: healthcare, knowledge acquisition, maximal data sets, action design science

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Authors: Payal Abichandani, Rishi Prakash, Paras Nath Barwal, B. K. Murthy

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Information generated from various computerization processes is a potential rich source of knowledge for its designated community. To pass this information from generation to generation without modifying the meaning is a challenging activity. To preserve and archive the data for future generations it’s very essential to prove the authenticity of the data. It can be achieved by extracting the metadata from the data which can prove the authenticity and create trust on the archived data. Subsequent challenge is the technology obsolescence. Metadata extraction and standardization can be effectively used to resolve and tackle this problem. Metadata can be categorized at two levels i.e. Technical and Domain level broadly. Technical metadata will provide the information that can be used to understand and interpret the data record, but only this level of metadata isn’t sufficient to create trustworthiness. We have developed a tool which will extract and standardize the technical as well as domain level metadata. This paper is about the different features of the tool and how we have developed this.

Keywords: digital preservation, metadata, OAIS, PDI, XML

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Authors: Cuiyang Feng, Xu Tang, Yi Jin

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Coal is the most important primary energy source in China, which exerts a significant influence on the rapid economic growth. However, it makes the water resources to be a constraint on coal industry development, on account of the reverse geographical distribution between coal and water. To ease the pressure on water shortage, the ‘3 Red Lines’ water policies were announced by the Chinese government, and then ‘water for coal’ plan was added to that policies in 2013. This study utilized a structural path analysis (SPA) based on the multi-regional input-output table to quantify the virtual water flows caused by coal consumption in different stages. Results showed that the direct water input (the first stage) was the highest amount in all stages of coal consumption, accounting for approximately 30% of total virtual water content. Regional analysis demonstrated that virtual water trade alleviated the pressure on water use for coal consumption in water shortage areas, but the import of virtual water was not from the areas which are rich in water. Sectoral analysis indicated that the direct inputs from the sectors of ‘production and distribution of electric power and heat power’ and ‘Smelting and pressing of metals’ took up the major virtual water flows, while the sectors of ‘chemical industry’ and ‘manufacture of non-metallic mineral products’ importantly but indirectly consumed the water. With the population and economic growth in China, the water demand-and-supply gap in coal consumption would be more remarkable. In additional to water efficiency improvement measures, the central government should adjust the strategies of the virtual water trade to address local water scarcity issues. Water resource as the main constraints should be highly considered in coal policy to promote the sustainable development of the coal industry.

Keywords: coal consumption, multi-regional input-output model, structural path analysis, virtual water

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Authors: Antonio Gioiosa, Simone Doanti, Eric Flumerfelt, Luca Morescalchi, Elena Pedreschi, Gianantonio Pezzullo, Ryan A. Rivera, Franco Spinella

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The Mu2e experiment at Fermilab aims to measure the charged-lepton flavour violating neutrino-less conversion of a negative muon into an electron in the field of an aluminum nucleus. With the expected experimental sensitivity, Mu2e will improve the previous limit of four orders of magnitude. The Mu2e data acquisition (DAQ) system provides hardware and software to collect digitized data from the tracker, calorimeter, cosmic ray veto, and beam monitoring systems. Mu2e’s trigger and data acquisition system (TDAQ) uses otsdaq as its solution. developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under-the-hood, for event transfer, filtering, and processing. Otsdaq is an online DAQ software suite with a focus on flexibility and scalability while providing a multi-user, web-based interface accessible through the Chrome or Firefox web browser. The detector read out controller (ROC) from the tracker and calorimeter stream out zero-suppressed data continuously to the data transfer controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes from a cosmic ray veto system (CRV).

Keywords: trigger, daq, mu2e, Fermilab

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Charuvan Kasemsap

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This research was studied in Bangnampriao District, Chachernsao Province, Thailand. The primary data relating to flooding, drought, and saline intrusion problem on agriculture were collected by surveying, focus group, and in-depth interview with agricultural officers, technical officers of irrigation department, and local government leader of Bangnampriao District. The likelihood and consequence of risk were determined the risk index by risk assessment matrix. In addition, the risk index and the total coping capacity scores were investigated the vulnerability index by vulnerability matrix. It was found that the high-risk drought and saline intrusion was dramatically along Bang Pakong River owing to the end destination of Chao Phraya Irrigation system of Central Thailand. This leads yearly the damage of rice paddy, mango tree, orchard, and fish pond. Therefore, some agriculture avoids rice growing during January to May, and also pumps fresh water from a canal into individual storage pond. However, Bangnampriao District will be strongly affected by the impacts of climate change. Monthly precipitations are expected to decrease in number; dry seasons are expected to be more in number and longer in duration. Thus, the risk and vulnerability of agriculture are also increasing. Adaptation strategies need to be put in place in order to enhance the resilience of the agriculture.

Keywords: agriculture, bangnampriao, climate change, risk assessment

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Authors: Mohamed Elmeshad

Abstract:

During the mid-1990's Egypt had become obliged to implement the Economic Reform and Structural Adjustment Program that included broad economic liberalization, expansion of the private sector and a contraction the size of government spending. This coincided as well with attempts to appear more democratic and open to liberalizing public space and discourse. At the same time, economic pressures and the proliferation of social media access and activism had led to increased pressure to open a mediascape and remove it from the clutches of the government, which had monopolized print and broadcast mass media for over 4 decades by that point. However, the mechanisms that governed the privatization of mass media allowed for sustained government control, even through the prism of ostensibly privately owned newspapers and television stations. These mechanisms involve barriers to entry from a financial and security perspective, as well as operational capacities of distribution and access to means of production. The power dynamics between mass media establishments and the state were moulded during this period in a novel way. Power dynamics within media establishments had also formed under such circumstances. The changes in the country's political economy itself somehow mirrored these developments. This paper will examine these dynamics and shed light on the political economy of Egypt's newly privatized mass media in the early 2000's especially. Methodology: This study will rely on semi-structured interviews from individuals involved with these changes from the perspective of the media organizations. It also will map out the process of media privatization by looking at the administrative, operative and legislative institutions and contexts in order to attempt to draw conclusions on methods of control and the role of the state during the process of privatization. Finally, a brief discourse analysis will be necessary in order to aptly convey how these factors ultimately reflected on media output. Findings and conclusion: The development of Egyptian private, “independent” mirrored the trajectory of transitions in the country’s political economy. Liberalization of the economy meant that a growing class of business owners would explore opportunities that such new markets would offer. However the regime’s attempts to control access to certain forms of capital, especially in sectors such as the media affected the structure of print and broadcast media, as well as the institutions that would govern them. Like the process of liberalisation, much of the regime’s manoeuvring with regards to privatization of media had been haphazardly used to indirectly expand the regime and its ruling party’s ability to retain influence, while creating a believable façade of openness. In this paper, we will attempt to uncover these mechanisms and analyse our findings in ways that explain how the manifestations prevalent in the context of a privatizing media space in a transitional Egypt provide evidence of both the intentions of this transition, and the ways in which it was being held back.

Keywords: business, mass media, political economy, power, privatisation

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Authors: Amenaghawon Clement Osemwinyen

Abstract:

The Activity, Student-centred, Experiment, Improvisation - Plan, Do, See, Improve (ASEI-PDSI) method championed by the Strengthening Mathematics And Science Education (SMASE) - Nigeria Project is an attempt to improve the quality of mathematics, which has consistently declined over the years in both public primary and secondary schools across the country. The study thus assessed the ASEI-PDSI method on students’ attitudes and achievement in junior secondary schools (JSS) mathematics in FCT-Abuja. A survey research design was adopted, and 100 mathematics teachers using a stratified random sampling method were used for the study. The data were collected using structured questionnaires and analyzed using descriptive statistics. The findings showed that the ASEI-PDSI method had significantly improved the attitudes of students toward mathematics. The study also revealed that the ASEI-PDSI method significantly influenced junior secondary school (JSS) students’ mathematics achievement. Amongst the recommendations were that teachers should be encouraged to adopt the ASEI-PDSI method in teaching and learning mathematics in order to create a mathematically stimulating classroom environment which could advertently influence junior secondary school (JSS) students’ attitude and academic performance in mathematics. Also, regular in-service training programs should be organized by stakeholders (government and other interest groups) so as to improve the teaching strategies of teachers, mostly as they affect the ASEI-PDSI method.

Keywords: achievement, ASEI-PDSI method, attitude, mathematics, SMASE

Procedia PDF Downloads 87

Authors: Anna Fowler

Abstract:

When considering assets that may need protection, the mind begins to contemplate homes, cars, and investment funds. In most cases, the protection of those assets can be covered through security systems and insurance. Data is not the first thought that comes to mind that would need protection, even though data is at the core of most supply chain operations. It includes trade secrets, management of personal identifiable information (PII), and consumer data that can be used to enhance the overall experience. Data is considered a critical element of success for supply chains and should be one of the most critical areas to protect. In the supply chain industry, there are two major misconceptions about protecting data: (i) We do not manage or store confidential/personally identifiable information (PII). (ii) Reliance on Third-Party vendor security. These misconceptions can significantly derail organizational efforts to adequately protect data across environments. These statistics can be exciting yet overwhelming at the same time. The first misconception, “We do not manage or store confidential/personally identifiable information (PII)” is dangerous as it implies the organization does not have proper data literacy. Enterprise employees will zero in on the aspect of PII while neglecting trade secret theft and the complete breakdown of information sharing. To circumvent the first bullet point, the second bullet point forges an ideology that “Reliance on Third-Party vendor security” will absolve the company from security risk. Instead, third-party risk has grown over the last two years and is one of the major causes of data security breaches. It is important to understand that a holistic approach should be considered when protecting data which should not involve purchasing a Data Loss Prevention (DLP) tool. A tool is not a solution. To protect supply chain data, start by providing data literacy training to all employees and negotiating the security component of contracts with vendors to highlight data literacy training for individuals/teams that may access company data. It is also important to understand the origin of the data and its movement to include risk identification. Ensure processes effectively incorporate data security principles. Evaluate and select DLP solutions to address specific concerns/use cases in conjunction with data visibility. These approaches are part of a broader solutions framework called Data Security Assurance (DSA). The DSA Framework looks at all of the processes across the supply chain, including their corresponding architecture and workflows, employee data literacy, governance and controls, integration between third and fourth-party vendors, DLP as a solution concept, and policies related to data residency. Within cloud environments, this framework is crucial for the supply chain industry to avoid regulatory implications and third/fourth party risk.

Keywords: security by design, data security architecture, cybersecurity framework, data security assurance

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Authors: Lindelwa Mngomezulu, Tonderai Muchenje

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Over the decades, E-mails provide easy, fast and timely communication enabling businesses and state owned agencies to communicate with their stakeholders and with their own employees in real-time. Moreover, since the launch of Microsoft office 365 and many other clouds based E-mail services, many businesses have been migrating from the on premises E-mail services to the cloud and more precisely since the beginning of the Covid-19 pandemic, there has been a significant increase of E-mails utilization, which then leads to the increase of cyber-attacks. In that regard, E-mail security has become very important in the E-mail transportation to ensure that the E-mail gets to the recipient without the data integrity being compromised. The classification of the features to enhance E-mail security for further from the enhanced cyber-attacks as we are aware that since the technology is advancing so at the cyber-attacks. Therefore, in order to maximize the data integrity we need to also maximize security of the E-mails such as enhanced E-mail authentication. The successful enhancement of E-mail security in the future may lessen the frequency of information thefts via E-mails, resulting in the data of South African State-owned agencies not being compromised.

Keywords: e-mail security, cyber-attacks, data integrity, authentication

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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Authors: Malay Bhattacharyya, Saparya Suresh

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The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

Procedia PDF Downloads 109