Search results for: data ownership

Authors: Tamanna Jethava, Rahul Joshi

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Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

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Authors: Hussaini Garba Mohammed

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Background/Significance: The lack of data gathering is affecting NGOs world-wide in general to have good data information about educational and health related issues among communities in any country and around the world. For example, HIV/AIDS smoking (Tuberculosis diseases) and COVID-19 virus carriers is becoming a serious public health problem, especially among old men and women. But there is no full details data survey assessment from communities, villages, and rural area in some countries to show the percentage of victims and patients, especial with this world COVID-19 virus among the people. These data are essential to inform programming targets, strategies, and priorities in getting good information about data gathering in any society.

Keywords: reliable information, data assessment, data mining, data communication

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Authors: Arpan Upadhyaya, Sunaina Kuknor

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The paper examines the succession management strategies and the preparation level of heirs in the context of family-owned educational institutions in Nepal. Sixteen in-depth, semi-structured interviews with the institution's leader were conducted. The study's findings show the lack of awareness about the importance of succession planning among the institution owners due to the availability of limited resources. The paper also provides some insights into how family ownership and management are done and the lack of formal processes in succession management strategies. It will aid researchers in considering the societal perspective of the successor, which is also a significant worry.

Keywords: effective plans, family business, interest, leadership, successor

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Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

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Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

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Authors: Shahnewaz Khan

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Machine learning (ML) techniques are often used in projects for creating data-driven applications. These tasks typically demand additional research and analysis. The proper technique and strategy must be chosen to ensure the success of data-driven projects. Otherwise, even exerting a lot of effort, the necessary development might not always be possible. In this post, an effort to examine the workflow of data-driven software development projects and its implementation process in order to describe how to manage a project successfully. Which will assist in minimizing the added workload.

Keywords: data, data-driven projects, data science, NLP, software project

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Authors: Carmen Cantuarias-Villessuzanne, Jeffrey Blain, Radmila Pineau

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Our research project aims at analyzing the sensitiveness of French households to urban biodiversity and urban ecosystem services (UES). Opinion surveys show that the French population is sensitive to biodiversity and ecosystem services loss, but the value given to these issues within urban fabric and real estate market lacks evidence. Using GIS data and economic evaluation, by hedonic price methods, weassess the isolated contribution of the explanatory variables of biodiversityand UES on the price of residential real estate. We analyze the variation of the valuefor three urban ecosystem services - flood control, proximity to green spaces, and refreshment - on the price of real estate whena property changes ownership. Our modeling and mapping focus on the price at theIRIS scale (statistical information unit) from 2014 to 2019. The main variables are internal characteristics of housing (area, kind of housing, heating), external characteristics(accessibility and infrastructure, economic, social, and physical environmentsuch as air pollution, noise), and biodiversity indicators and urban ecosystemservices for the Ile-de-France region. Moreover, we compare environmental values on the enhancement of greenspaces and their impact on residential choices. These studies are very useful for real estate developers because they enable them to promote green spaces, and municipalities to become more attractive.

Keywords: urban ecosystem services, sustainable real estate, urban biodiversity perception, hedonic price, environmental values

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Authors: M. Naidoo

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Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

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Authors: Tuti Haryati Jasimin, Hishamuddin Mohd Ali

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Malaysia’s green building development is gaining momentum and green buildings have become a key focus area especially within the commercial sector with the encouragement of government legislation and policy. Due to the emerging awareness among the market players’ views of the benefits associated with the ownership of green buildings in Malaysia, there is a need for valuers to incorporate consideration of sustainability into their assessments of property market value to ensure the green buildings continue to increase in the market. This paper analyses the valuers’ current perception on the valuation practices with regard to the green issues in Malaysia. The study was based on a survey of registered real estate valuers and the experts whose work related to valuation in the Klang Valley area to rate their view regarding the perception on valuation of green building. The findings present evidence that even though Malaysian valuers have limited knowledge of green buildings, they recognize the importance of incorporating the green features in the valuation process. The inclusion of incorporating the green features in valuations in practice was hindered by the inadequacy of sufficient transactional data in the market. Furthermore, valuers experienced difficulty in identifying what are the various input parameters of green building and how to adjust it in order to reflect the benefit of sustainability features correctly in the valuation process. This paper focuses on the present challenges confronted by Malaysian valuers with regards to incorporating the green features in their valuation.

Keywords: green commercial office building, Malaysia, valuers’ perception, valuation, commercial sector

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Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

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In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: simulation data, data summarization, spatial histograms, exploration, visualization

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Authors: Liudmila A.Guzikova

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Being federative state Russia includes more than 80 subjects which are widely diverse by climatic conditions, demographic characteristics, cultural traditions, intensity of migration, economic development and investment attraction and other parameters. Now, in the regions of the country all forms of housing problem are present - housing mismatch to sanitary and hygienic standards, overcrowding, forced residence in financially burdensome housing, homelessness, -although the extent of these symptoms varies widely. Heterogeneity of regional conditions in combination with specifics of regional housing situation requires to concentrate the study of housing problem on the regional level. Traditionally housing market and mortgage are considered as the instruments of housing problem solving. The question arises how the housing market and mortgage market contribute to solving the housing problem in the regions of Russia. Though the purchase of dwelling in ownership should not be regarded as a universal method of the housing problem solving, the purchase of dwelling both by own funds or by use of mortgage can reduce the problem and enhance public satisfaction of living conditions. The aim of the study is to identify differences and similarities in the development of regional housing markets and mortgage lending in the regions of Russia and to evaluate their impact on the status of the housing problem. To achieve the aim of the study the methods of correlation and regression analysis are used. The data of federal statistics constitutes the information base of research. The results of the study contribute to better understanding of the interrelations in housing sphere and can be used to work out social and economic development programs in the regions.

Keywords: housing market, housing problem, mortgage, regional economy

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Authors: Vahid Bairami Rad

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Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.

Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Karolína Vozková, Matěj Kuc

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This paper deals with the impact of decrease in interest rates on the performance of commercial and cooperative banks in the Eurozone measured by net interest margin. The analysis was performed on balanced dataset of 268 commercial and 726 cooperative banks spanning the 2008-2015 period. We employed Fixed Effects estimation panel method. As expected, we found a negative relationship between market rates and net interest margin. Our results suggest that the impact of negative interest income differs across individual banking business models. More precisely, those cooperative banks were much more hit by the decrease of market interest rates which might be due to their ownership structure and more restrictive business regulation.

Keywords: cooperative banks, performance, negative interest rates, risk management

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Authors: Tosin Ige

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Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

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Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: big data, big data analytics, Hadoop, cloud

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Authors: Somya Sharma

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Ahalya, the critically acclaimed short film, is known to demolish the gender constructs of the age old myth of Ahalya. The paper tries to crack the overt meaning of the short film by reading between the dialogues and deconstructing the idea of the pseudo feminism in the short film Ahalya by Sujoy Ghosh. The film, by subverting the role of male character by making it seem submissive as compared to the female character's role seems to be just a surface level reading of the text. It seems that Sujoy Ghosh has played not just with changing the paradigm, but also trying to alter the history by doing so. The age old myth of putting Ahalya as a part of the five virgins (panchkanya) of Hindu mythology is explored in the paper. God's manoeuvre cannot be questioned and the two male characters tend to again shape the deed and the life of the female character, Ahalya. It is of importance to note that even in the 21st century, progressive actors like Radhika Apte fail to acknowledge the politics of altering history, not in a progressive way. The film blinds the viewer in the first watch to fall for the female strength and ownership of her sexuality, which is reflected in the opening scene itself where she opens the gate for the police man Indra Sen (representing God Indra who seduced her) who is charmed by her white dress. White, in Hindu mythology, stands for mourning, and this can be a hint towards the prophecy of what is about to come. Ahalya, bold, strong, and confident in this scene seems to be in total ownership of her sexual identity. Further, as the film progresses, control of Ahalya over her acts becomes even more dominant. In the myth of Ahalya, Gautama Maharishi, her husband, who wins her by Brahma's courtesy, curses her for her infidelity. She is then turned into a stone because of the curse and is redeemed when Lord Rama's foot brushes the stone. In the film, it is with the help of Ahalya that Goutam Sadhu turns Indra Sen into a stone doll. Ahalya is seen as a seductress who bewitches Indra Sen, and because the latter falls for the trap laid by the husband wife duo, he is turned into a doll. The attempt made by the paper is to read Ahalya as a character of the stand in wife who is yet again a pawn in the play of Goutama's revenge from Indra (who in the myth is able to escape from any curse or punishment for the act). The paper, therefore, reverts the idea which has till now been signified by the film and attempts to study the feminism this film appropriates. It is essential to break down the structure formed by such overt transgressing films in order to provide a real outlook of how feminism is twisted and moulded according to a man’s wishes.

Keywords: deconstructing, Hindu mythology, Panchkanya, predominant feminism, seductress, stone doll

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Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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Authors: Winfred Okoe Addy, Jean Jacques Dominique Beraud

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Access control systems (ACs) are some of the most important components in safety areas. Inaccuracies of regulatory frameworks make personal policies and remedies more appropriate than standard models or protocols. This problem is exacerbated by the increasing complexity of software, such as integrated Big Data (BD) software for controlling large volumes of encrypted data and resources embedded in a dedicated BD production system. This paper proposes a general access control strategy system for the diffusion of Big Data domains since it is crucial to secure the data provided to data consumers (DC). We presented a general access control circulation strategy for the Big Data domain by describing the benefit of using designated access control for BD units and performance and taking into consideration the need for BD and AC system. We then presented a generic of Big Data access control system to improve the dissemination of Big Data.

Keywords: access control, security, Big Data, domain

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Authors: Babak Pourghahramani

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One of the modern crimes against property and ownership in the cyber-space is the computer fraud. Despite being modern, the aforementioned crime has its roots in the principles of religious jurisprudence. In some cases, this crime is compatible with the traditional regulations and that is when the computer is considered as a crime commitment device and also some computer frauds that take place in the context of electronic exchanges are considered as crime based on the E-commerce Law (approved in 2003) but the aforementioned regulations are flawed and until recent years there was no comprehensive law in this regard; yet after some years the Computer Crime Act was approved in 2009/26/5 and partly solved the problem of legal vacuum. The present study intends to investigate the computer fraud according to Iran's Computer Crime Act and by taking into consideration the international documents.

Keywords: fraud, cyber fraud, computer fraud, classic fraud, computer crime

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Authors: Michael Gidey Gebru

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Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

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Authors: Grace Anweh, Patience Achakpa-ikyo

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The issue of women unfavourable representation in the mass media is long standing. While it is a worldwide problem, developing countries in Africa especially Nigeria are considered peculiar. This paper, ‘mass media representation and the status of women in the 2015, general elections in Nigeria’ therefore aimed to assess the current trend of role playing in the mass media and how this has affected general status of women in Nigeria politics with particular reference to the 2015 general elections. The study employed a review of secondary literature and data regarding previous performances of Nigeria women in politics from 1999 to 2015 and the picture that has been paid by Nigerian mass media about women. Anchoring the paper on the agenda setting theory of the mass media, the paper analysed secondary literature and discovered that from 1999 to date, women have been participating in politics but rather than improve their status in elective offices, the percentage of women for such offices is rather declining. This trend the paper concluded is attributed to the way and manner women are represented in the mass media - as not good for policy making offices except as kitchen and home managers. The paper therefore recommends that, the country should adopt the quota allocation for all the political parties in order to give women a chance to compete with their male counterparts. While women should strive towards the managerial and ownership of media houses in order to represent the interest of women in politics thus offering the opportunity for the favourable representation of women and role models for those who may want to tour a similar part.

Keywords: mass media, media representation, Nigeria elections, women

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Authors: Dan Li, Hao Tang

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The idea of “public bonds” was foreign to Qing China because it went against the traditional political ideology that supported that the emperor had absolute ownership over the nation. When a new fiscal crisis emerged out of the First Sino-Japanese War in 1894, the Qing rulers had no better option than to issue domestic bonds. This article documents the processes of issuance, distribution, and reimbursement for a total of three bonds issued by the Qing. These processes reveal how a well-established Western fiscal instrument could be extremely awkward and difficult to implant in China—a culturally, politically, and institutionally different society. Our paper sheds light on why Qing China failed to rise as a modern fiscal state.

Keywords: public bond, Qing China, fiscal crisis, fiscal state, the first Sino-Japanese war

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Authors: Bita Mashayekhi, Farzaneh Jalali, Alemeh Yazdanian

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This study contributes to identifying the corporate governance indices in previous researches by using content analysis on relevant papers published in 20 top accounting journals according to Google Scholar ranking, dated from 1990 to 2016. For this purpose, 65 papers are scrutinized deeply, and the concepts of corporate governance are coded and categorized. Then extracted indices are clustered into 10 and 51 categories and subcategories, respectively; and their frequencies are determined. Results show that the board of directors’ characteristics is employed more frequently in reviewed papers, and the board of directors’ independency is the most frequent index within the 97 percent of our sample. Duality, board size, and ownership structure have more frequencies in comparison with other extracted corporate governance indices.

Keywords: corporate governance, content analysis, corporate governance index, top accounting journals

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Authors: Abdullah Alsaeed

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Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Tristance Kee

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With the unprecedented increase in elderly population globally, it is critical to search for new sustainable housing and urban development alternatives to traditional housing options. This research examines concepts of elderly migration pattern in the context of a high density city in Hong Kong to Mainland China. The research objectives are to: 1) explore the relationships between soon-to-be-old elderly and their intentions to move to Mainland upon retirement and their demographic characteristics; and 2) What are the desired amenities, locational factors and activities that are expected in the soon-to-be-old generation’s retirement housing environment? Primary data was collected through questionnaire survey conducted using random sampling method with respondents aged between 45-64 years old. The face-to-face survey was completed by 500 respondents. The survey was divided into four sections. The first section focused on respondent’s demographic information such as gender, age, education attainment, monthly income, housing tenure type and their visits to Mainland China. The second section focused on their retirement plans in terms of intended retirement age, prospective retirement funding and retirement housing options. The third section focused on the respondent’s attitudes toward retiring in Mainland for housing. It asked about their intentions to migrate retire into Mainland and incentives to retire in Hong Kong. The fourth section focused on respondent’s ideal housing environment including preferred housing amenities, desired living environment and retirement activities. The dependent variable in this study was ‘respondent’s consideration to move to Mainland China upon retirement’. Eight primary independent variables were integrated into the study to identify the correlations between them and retirement migration plan. The independent variables include: gender, age, marital status, monthly income, present housing tenure type, property ownership in Hong Kong, relationship with Mainland and the frequency of visiting Mainland China. In addition to the above independent variables, respondents were asked to indicate their retirement plans (retirement age, funding sources and retirement housing options), incentives to migrate to retire (choices included: property ownership, family relations, cost of living, living environment, medical facilities, government welfare benefits, etc.), perceived ideal retirement life qualities including desired amenities (sports, medical and leisure facilities etc.), desired locational qualities (green open space, convenient transport options and accessibility to urban settings etc.) and desired retirement activities (home-based leisure, elderly friendly sports, cultural activities, child care, social activities, etc.). The finding shows correlations between the used independent variables and consideration to migrate for housing options. The two independent variables indicated a possible correlation were gender and the frequency of visiting Mainland at present. When considering the increasing property prices across the border and strong social relationships, potential retirement migration is a very subjective decision that could vary from person to person. This research adds knowledge to housing research and migration study. Although the research is based in Mainland, most of the characteristics identified including better medical services, government welfare and sound urban amenities are shared qualities for all sustainable urban development and housing strategies.

Keywords: elderly migration, housing alternative, soon-to-be-old, sustainable environment

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

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Authors: Mohamed Fairooz Abdul Khir

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The linkage between liability for risk and legitimacy of reward is a governing principle that must be fully observed in financial transactions. It is the cornerstone of any Islamic business or financial deal. The absence of risk taking principle may give rise to numerous prohibited elements such as ribā, gharar and gambling that violate the objectives of financial transactions. However, fiqhī domains from which it emanates have not been clearly spelled out by the scholars. In addition, the concept of risk taking in relation to contemporary risks associated with financial contracts, such as credit risk, liquidity risk, reputational risk and market risk, needs further scrutiny as regard their Sharīʿah bases. Hence, this study is imperatively significant to prove that absence of risk taking concept in Islamic financial instruments give rise to prohibited elements particularly ribā. This study is primarily intended to clarify the concept of risk in Islamic financial transactions from the fiqhī perspective and evaluate analytically the selected issues involving risk taking based on the established concept of risk taking from fiqhī viewpoint. The selected issues are amongst others charging cost of fund on defaulting customers, holding the lessee liable for total loss of leased asset under ijārah thumma al-bayʿ and capital guarantee under mushārakah based instruments. This is a library research in which data has been collected from various materials such as classical fiqh books, regulators’ policy guidelines and journal articles. This study employed deductive and inductive methods to analyze the data critically in search for conclusive findings. It suggests that business risks have to be evaluated based on their subjects namely (i) property (māl) and (ii) work (ʿamal) to ensure that Islamic financial instruments structured based on certain Sharīʿah principles are not diverted from the risk taking concept embedded in them. Analysis of the above selected cases substantiates that when risk taking principle is breached, the prohibited elements such as ribā, gharar and maysir do arise and that they impede the realization of the maqāṣid al-Sharīʿah intended from Islamic financial contracts.

Keywords: Islamic finance, ownership risk, ribā, risk taking

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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