Search results for: data privacy

Authors: Abdelrhman Elagez, Rolla Monib

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This empirical study investigates the observed risks associated with adopting Artificial Intelligence (AI) technologies in the construction industry and proposes potential mitigation strategies. While AI has transformed several industries, the construction industry is slowly adopting advanced technologies like AI, introducing new risks that lack critical analysis in the current literature. A comprehensive literature review identified a research gap, highlighting the lack of critical analysis of risks and the need for a framework to measure and mitigate the risks of AI implementation in the construction industry. Consequently, an online survey was conducted with 24 project managers and construction professionals, possessing experience ranging from 1 to 30 years (with an average of 6.38 years), to gather industry perspectives and concerns relating to AI integration. The survey results yielded several significant findings. Firstly, respondents exhibited a moderate level of familiarity (66.67%) with AI technologies, while the industry's readiness for AI deployment and current usage rates remained low at 2.72 out of 5. Secondly, the top-ranked barriers to AI adoption were identified as lack of awareness, insufficient knowledge and skills, data quality concerns, high implementation costs, absence of prior case studies, and the uncertainty of outcomes. Thirdly, the most significant risks associated with AI use in construction were perceived to be a lack of human control (decision-making), accountability, algorithm bias, data security/privacy, and lack of legislation and regulations. Additionally, the participants acknowledged the value of factors such as education, training, organizational support, and communication in facilitating AI integration within the industry. These findings emphasize the necessity for tailored risk assessment frameworks, guidelines, and governance principles to address the identified risks and promote the responsible adoption of AI technologies in the construction sector.

Keywords: risk management, construction, artificial intelligence, technology

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Authors: Branci Sarra, Branci Saadia

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

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

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Authors: Prashant Shrivastava

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

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

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Authors: Jaouadi Ikram, Machhout Mohsen

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The development of a quantum key distribution (QKD) system on a field-programmable gate array (FPGA) platform is the subject of this paper. A quantum cryptographic protocol is designed based on the properties of quantum information and the characteristics of FPGAs. The proposed protocol performs key extraction, reconciliation, error correction, and privacy amplification tasks to generate a perfectly secret final key. We modeled the presence of the spy in our system with a strategy to reveal some of the exchanged information without being noticed. Using an FPGA card with a 100 MHz clock frequency, we have demonstrated the evolution of the error rate as well as the amounts of mutual information (between the two interlocutors and that of the spy) passing from one step to another in the key generation process.

Keywords: QKD, BB84, protocol, cryptography, FPGA, key, security, communication

Procedia PDF Downloads 180

Authors: Ilgin Gökaşar, Saman Ghaffarian

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

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

Procedia PDF Downloads 458

Authors: Ali Asheibi

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

Keywords: data mining, harmonic data, clustering, classification

Procedia PDF Downloads 241

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

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

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

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

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

Keywords: communication, computer network, data collection, probe

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Authors: Kristine Joy Y. Sumanga, Clarissa Mae D. Derecho

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Telemedicine is providing health care services using electronic means at a distance, including the diagnosis, treatment, and prevention of diseases as well as the research and evaluation and education of health care providers. The role of telemedicine in this time of the COVID-19 pandemic is vital, especially in the practice of medicine. General Objective: To determine the extent of knowledge, preparedness and perception of telemedicine among Family Medicine Resident Physicians in different training institutions in Cebu City during the Coronavirus Disease 19 pandemic. Methods: A descriptive, cross-sectional survey research study was conducted in four hospital training institutions in Cebu City. A total of 41 respondents gave their consent and were given the online survey questionnaire pertaining to the extent of knowledge, preparedness and perceptions on telemedicine, including respondents’ demographic data and problems encountered in Telemedicine. Results: Out of the 41 respondents, 56.10% were young adults (26 to 30 years old), mostly females (70.73%), single (68.29%), first-year residents (43.90%), employed at a government hospital (70.73%) and are in the traditional residency pathway (82.93%). On relevant experience, 82.93% experienced telemedicine during residency, with 100% on follow-up consultations, and 95% were consulted due to infections. Respondents’ extent of knowledge was average, while the extent of preparedness and perception were great. Problems with low connectivity (80.48%) were noted by most of the respondents. Conclusion: Resident physicians moderately understood the information about telemedicine but with a great extent of preparedness and perception. They are always prepared for telemedicine modality because they are fully aware of its existence and need in the delivery of health care services among their patients at the time of the pandemic. Challenges to low connectivity and handling patients’ data privacy were the major concerns met by the resident physicians in the use of telemedicine.

Keywords: telemedicine, knowledge, preparedness, perception, family medicine, residents, COVID 19

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Authors: Asim Majeed, Rehan Bhana, Mak Sharma, Rebecca Goode, Nizam Bolia, Mike Lloyd-Williams

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This study aims to investigate and explore the underlying causes of security concerns of customers emerged when WHSmith transformed its physical system to virtualized business model through NetSuite. NetSuite is essentially fully integrated software which helps transforming the physical system to virtualized business model. Modern organisations are moving away from traditional business models to cloud based models and consequently it is expected to have a better, secure and innovative environment for customers. The vital issue of the modern age race is the security when transforming virtualized through cloud based models and designers of interactive systems often misunderstand privacy and even often ignore it, thus causing concerns for users. The content analysis approach is being used to collect the qualitative data from 120 online bloggers including TRUSTPILOT. The results and finding provide useful new insights into the nature and form of security concerns of online users after they have used the WHSmith services offered online through their website. Findings have theoretical as well as practical implications for the successful adoption of cloud computing Business-to-Business model and similar systems.

Keywords: innovation, virtualization, cloud computing, organizational flexibility

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Authors: Nay Myo Sandar

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

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

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Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

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

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

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Authors: Chiao-Chen Chang, Yang-Chieh Chin

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Social media has created a change in the way the network community is clustered, especially from the location of the community, from the original virtual space to the intertwined network, and thus the communication between people will change from face to face communication to social media-based communication model. However, social media users who have had a fixed engagement may have an intention to switch to another service provider because of the emergence of new forms of social media. For example, some of Facebook or Twitter users switched to Instagram in 2014 because of social media messages or image overloads, and users may seek simpler and instant social media to become their main social networking tool. This study explores the impact of system features overload, information overload, social monitoring concerns, problematic use and privacy concerns as the antecedents on social media fatigue, dissatisfaction, and alternative attractiveness; further influence social media switching. This study also uses the online questionnaire survey method to recover the sample data, and then confirm the factor analysis, path analysis, model fit analysis and mediating analysis with the structural equation model (SEM). Research findings demonstrated that there were significant effects on multiple paths. Based on the research findings, this study puts forward the implications of theory and practice.

Keywords: social media, switching, social media fatigue, alternative attractiveness

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Authors: V. Vishu, R. Manimegalai

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A combination of Intelligence and Radio frequency identification to bring an enhanced authentication method for the improvement of visually challenged people. The main goal is to provide an improved authentication by combining Advanced Encryption Standard algorithm and Intelligence. Here the encryption key will be generated as a combination of intelligent information from sensors and tag values. The main challenges are security, privacy and cost. Besides, the method was created to evaluate the amount of interaction between sensors and significant influence on the level of visually challenged people’s mental and physical states. The proposal is to apply various ideas on independent living or to assist them for a good life.

Keywords: AES, encryption, intelligence, smart key

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Authors: A. Alssbaiheen, S. Love

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Mobile government (m-government) is one of the promising technologies for developing the governance of developing countries. While developing countries often have less advanced internet infrastructure compared to the developed world, mobile phone penetration is very high in the Gulf Cooperation Council (GCC) countries and mobile internet use offers a means to transcend traditional logistical barriers to accessing government services. The study explores the challenges and opportunities of the mobile government in Saudi Arabia. Semi-structured interviews were conducted with a diverse cohort of Saudi mobile users. A total of 77 semi-structured interviews were collected and subsequently analysed using open, axial, and selective coding. The participants’ responses revealed that many opportunities exist for the development of m-government in Saudi Arabia, including high popular awareness of government initiatives in e-government, and willingness to use such services, largely due to the time-saving and convenience aspects it offers compared with traditional bureaucratic services. However, numerous barriers were identified, including the low quality and speed of the internet, service customization, and concerns about privacy data security. It was also felt that in addition to infrastructure challenges, the traditional bureaucratic attitude of government department would itself hinder the effective deployment and utilization of m-government services.

Keywords: awareness, barriers, challenges, government services, mobile government, m-government, opportunities

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Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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Authors: Mengdi Zhang, Zhenji Gao, Ning Kang, Rongmei Liu

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Management and application of geological big data is an important part of China's national big data strategy. With the implementation of a national big data strategy, geological big data management becomes more and more critical. At present, there are still a lot of technology barriers as well as cognition chaos in many aspects of geological big data management and application, such as data sharing, intellectual property protection, and application technology. Therefore, it’s a key task to make better use of new technologies for deeper delving and wider application of geological big data. In this paper, we briefly introduce the basic principle of blockchain technology at the beginning and then make an analysis of the application dilemma of geological data. Based on the current analysis, we bring forward some feasible patterns and scenarios for the blockchain application in geological big data and put forward serval suggestions for future work in geological big data management.

Keywords: blockchain, intellectual property protection, geological data, big data management

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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: Nael Hirzalla

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The legality of some countries or agencies’ acts to spy on personal phone calls of the public became a hot topic to many social groups’ talks. It is believed that this act is considered an invasion to someone’s privacy. Such act may be justified if it is singling out specific cases but to spy without limits is very unacceptable. This paper discusses the needs for not only a simple and light weight technique to secure mobile voice calls but also a technique that is independent from any encryption standard or library. It then presents and tests one encrypting algorithm that is based of frequency scrambling technique to show fair and delay-free process that can be used to protect phone calls from such spying acts.

Keywords: frequency scrambling, mobile applications, real-time voice encryption, spying on calls

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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: Zheng Miao, Dennis Fernandez

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CRISPR research has the potential to completely transform life science, agriculture, live-stock and the health care industry. The Intellectual Property derived from its research has raised significant attention in the academic as well as the biopharmaceutical industry culminating an urgent need for strategic IP protection. We review the rudimentary concepts and key competitors of CRISPR technologies as well as the paramount strategies for intellectual property protection. Further, we elaborate on prosecution issues related to CRISPR patents as well as possible solutions to various patent laws, interferences and litigation. Finally, we address how the bioinformatics of the CRISPR technology begs an inquiry into issues of privacy and a host of ethical concerns.

Keywords: bioinformatics, CRISPR, biotechnology, intellectual property

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Authors: Malik Takreem Ahmad, Pablo Lamata, Rasi Mizori

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Background: In recent years, mobile health apps have grown in popularity as a means for people to track and manage their health. While there is increasing worry that these applications may potentially contribute to the emergence of health anxiety, they can also help to encourage healthy behaviours and provide access to health information. Objective: The objective of this literature review is to look at available mhealth apps and critically evaluate the compromise between reassurance and anxiety. Methodology: A literature review was carried out to analyse the effects of mhealth apps on the creation of health anxiety within the general population. PubMed and SCOPUS were used to search for relevant articles, and abstracts were screened using inclusion criteria of the terms: mhealth apps; e-Health; healthcare apps; cyberchondria; Health anxiety; illness anxiety disorder. A total of 27 studies were included in the review. Results and discussion: The findings suggest a direct relationship between mobile health app use and health anxiety. The impact of mobile health apps on health anxiety may depend on how they are used - individuals receiving a constant stream of health-related information may trigger unnecessary concern about one's health. The need for more regulation and oversight is identified, which can lead to app quality and safety consistency. There are also concerns about data security and privacy and the resulting "digital gap" for individuals without mobiles or internet access. Conclusion: While health apps can be valuable tools for managing and tracking health, individuals need to use them in a balanced and informed way to avoid increased anxiety.

Keywords: mobile health, mhealth apps, cyberchondria, health anxiety

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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: 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: Pei-Shan Wei, Szu-Ying Lee, Hsi-Peng Lu, Jen-Chuen Tzou, Chien-I Weng

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Mobile social games recently become extremely popular, spawning a whole new entertainment culture. However, mobile game players are fickle, quickly and easily picking up and abandoning games. This pilot study seeks to identify factors that influence users to discontinue playing mobile social games. We identified three sacrifices which can prompt users to abandon games: monetary sacrifice, time sacrifice and privacy sacrifice. The results showed that monetary sacrifice has a greater impact than the other two factors in causing players to discontinue usage intention.

Keywords: abandon, mobile devices, mobile social games, perceived sacrifice

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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: Wafa' Slaibi Alsharafat

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Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

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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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