Search results for: Data protection

Authors: Abeba Nigussie Turi, Xiangming Samuel Li

Abstract:

Data-driven business models are more typical for established businesses than early-stage startups that strive to penetrate a market. This paper provided an extensive discussion on the principles of data analytics for early-stage digital entrepreneurial businesses. Here, we developed data-driven decision-making (DDDM) framework that applies to startups prone to multifaceted barriers in the form of poor data access, technical and financial constraints, to state some. The startup DDDM framework proposed in this paper is novel in its form encompassing startup data analytics enablers and metrics aligning with startups' business models ranging from customer-centric product development to servitization which is the future of modern digital entrepreneurship.

Keywords: Startup data analytics, data-driven decision-making, data acquisition, data generation, digital entrepreneurship.

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Authors: Minsoo Lee, Yearn Jeong Kim, Yun-mi Kim, Sujeung Cheong, Sookyung Song

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Bio-chips are used for experiments on genes and contain various information such as genes, samples and so on. The two-dimensional bio-chips, in which one axis represent genes and the other represent samples, are widely being used these days. Instead of experimenting with real genes which cost lots of money and much time to get the results, bio-chips are being used for biological experiments. And extracting data from the bio-chips with high accuracy and finding out the patterns or useful information from such data is very important. Bio-chip analysis systems extract data from various kinds of bio-chips and mine the data in order to get useful information. One of the commonly used methods to mine the data is classification. The algorithm that is used to classify the data can be various depending on the data types or number characteristics and so on. Considering that bio-chip data is extremely large, an algorithm that imitates the ecosystem such as the ant algorithm is suitable to use as an algorithm for classification. This paper focuses on finding the classification rules from the bio-chip data using the Ant Colony algorithm which imitates the ecosystem. The developed system takes in consideration the accuracy of the discovered rules when it applies it to the bio-chip data in order to predict the classes.

Keywords: Ant Colony System, DNA chip data, Classification.

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Authors: Klaus Stranacher, Vesna Krnjic, Thomas Zefferer

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The public sector holds large amounts of data of various areas such as social affairs, economy, or tourism. Various initiatives such as Open Government Data or the EU Directive on public sector information aim to make these data available for public and private service providers. Requirements for the provision of public sector data are defined by legal and organizational frameworks. Surprisingly, the defined requirements hardly cover security aspects such as integrity or authenticity. In this paper we discuss the importance of these missing requirements and present a concept to assure the integrity and authenticity of provided data based on electronic signatures. We show that our concept is perfectly suitable for the provisioning of unaltered data. We also show that our concept can also be extended to data that needs to be anonymized before provisioning by incorporating redactable signatures. Our proposed concept enhances trust and reliability of provided public sector data.

Keywords: Trusted Public Sector Data, Integrity, Authenticity, Reliability, Redactable Signatures.

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Authors: Ekachai Phaisangittisagul, Rapeepol Chongprachawat

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Obtaining labeled data in supervised learning is often difficult and expensive, and thus the trained learning algorithm tends to be overfitting due to small number of training data. As a result, some researchers have focused on using unlabeled data which may not necessary to follow the same generative distribution as the labeled data to construct a high-level feature for improving performance on supervised learning tasks. In this paper, we investigate the impact of the relationship between unlabeled and labeled data for classification performance. Specifically, we will apply difference unlabeled data which have different degrees of relation to the labeled data for handwritten digit classification task based on MNIST dataset. Our experimental results show that the higher the degree of relation between unlabeled and labeled data, the better the classification performance. Although the unlabeled data that is completely from different generative distribution to the labeled data provides the lowest classification performance, we still achieve high classification performance. This leads to expanding the applicability of the supervised learning algorithms using unsupervised learning.

Keywords: Autoencoder, high-level feature, MNIST dataset, selftaught learning, supervised learning.

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Authors: M. Klimavicius

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This paper proposes a modeling methodology for the development of data analysis solution. The Author introduce the approach to address data warehousing issues at the at enterprise level. The methodology covers the process of the requirements eliciting and analysis stage as well as initial design of data warehouse. The paper reviews extended business process model, which satisfy the needs of data warehouse development. The Author considers that the use of business process models is necessary, as it reflects both enterprise information systems and business functions, which are important for data analysis. The Described approach divides development into three steps with different detailed elaboration of models. The Described approach gives possibility to gather requirements and display them to business users in easy manner.

Keywords: Data warehouse, data analysis, business processmanagement.

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Authors: Naeem Ullah Khan, Kalsoom Khan

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No state can be progressive and prosperous in which a large number of people is deprived of their basic economic rights and freedoms. In the contemporary world of globalization, the right to development has gained a momentum force in the domain of International Development Law (IDL) and has integrated into the National Legal System (NLS) of the major developed states. The international experts on human rights argued that the right to development (RTD) is called a third-generation human right which tends to enhance the welfare and prosperity of individuals, and thus, it is a right to a process whose outcomes are human rights despite the controversy on the implications of RTD. In the Pakistan legal system, the RTD has not been expressly stated in the constitution of the Islamic Republic of Pakistan, 1973. However, there are some implied constitutional provisions which reflect the concept of RTD. The jurisprudence on RTD is still an evolving paradigm in the contextual perspective of Pakistan, and the superior court of diverse jurisdiction acts as a catalyst regarding the protection and enforcement of RTD in the interest of the public at large. However, the case law explores the positive inclination of the courts in Pakistan on RTD be incorporated as an express provision in the chapters of fundamental rights; in this scenario, the high court’s of Pakistan under Article 199 and the supreme court of Pakistan under Article 184(3) have exercised jurisdiction on the enforcement of RTD. This paper inter-alia examines the national dimensions of RTD from the standpoint of state practice in Pakistan and it analyzes the experience of judiciary in the protection and enforcement of RTD. Moreover, the paper highlights the social and cultural challenges to Pakistan in the implementation of RTD and possible solution to improve the conditions of human rights in Pakistan. This paper will also highlight the steps taken by Pakistan regarding the awareness, incorporation, and propagation of RTD at the national level.

Keywords: Globalization, Pakistan, RTD, third-generation right.

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Authors: Muslihah Wook, Zawiyah M. Yusof, Mohd Zakree Ahmad Nazri

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Data mining has been integrated into application systems to enhance the quality of the decision-making process. This study aims to focus on the integration of data mining technology and Knowledge Management System (KMS), due to the ability of data mining technology to create useful knowledge from large volumes of data. Meanwhile, KMS vitally support the creation and use of knowledge. The integration of data mining technology and KMS are popularly used in business for enhancing and sustaining organizational performance. However, there is a lack of studies that applied data mining technology and KMS in the education sector; particularly students- academic performance since this could reflect the IHL performance. Realizing its importance, this study seeks to integrate data mining technology and KMS to promote an effective management of knowledge within IHLs. Several concepts from literature are adapted, for proposing the new integrative data mining technology and KMS framework to an IHL.

Keywords: Data mining, Institutions of Higher Learning, Knowledge Management System, Students' academic performance.

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Authors: Mohamed Elkholy, Ahmed Elfatatry

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Cloud computing has emerged as a flexible computing paradigm that reshaped the Information Technology map. However, cloud computing brought about a number of security challenges as a result of the physical distribution of computational resources and the limited control that users have over the physical storage. This situation raises many security challenges for data integrity and confidentiality as well as authentication and access control. This work proposes a security mechanism for data integrity that allows a data owner to be aware of any modification that takes place to his data. The data integrity mechanism is integrated with an extended Kerberos authentication that ensures authorized access control. The proposed mechanism protects data confidentiality even if data are stored on an untrusted storage. The proposed mechanism has been evaluated against different types of attacks and proved its efficiency to protect cloud data storage from different malicious attacks.

Keywords: Access control, data integrity, data confidentiality, Kerberos authentication, cloud security.

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Authors: W. Katsarapong, W. Srisang, K. Jaroensutasinee, M. Jaroensutasinee

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National Biodiversity Database System (NBIDS) has been developed for collecting Thai biodiversity data. The goal of this project is to provide advanced tools for querying, analyzing, modeling, and visualizing patterns of species distribution for researchers and scientists. NBIDS data record two types of datasets: biodiversity data and environmental data. Biodiversity data are specie presence data and species status. The attributes of biodiversity data can be further classified into two groups: universal and projectspecific attributes. Universal attributes are attributes that are common to all of the records, e.g. X/Y coordinates, year, and collector name. Project-specific attributes are attributes that are unique to one or a few projects, e.g., flowering stage. Environmental data include atmospheric data, hydrology data, soil data, and land cover data collecting by using GLOBE protocols. We have developed webbased tools for data entry. Google Earth KML and ArcGIS were used as tools for map visualization. webMathematica was used for simple data visualization and also for advanced data analysis and visualization, e.g., spatial interpolation, and statistical analysis. NBIDS will be used by park rangers at Khao Nan National Park, and researchers.

Keywords: GLOBE protocol, Biodiversity, Database System, ArcGIS, Google Earth and webMathematica.

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Authors: A. Kourou, S. Kyriakopoulos, N. Anyfanti

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A lot of children under the age of five spend their daytime hours away from their home, in a kindergarten. Caring for children is a serious subject, and their safety in case of earthquake is the first priority. Being aware of earthquakes helps to prioritize the needs and take the appropriate actions to limit the effects. Earthquakes occurring anywhere at any time require emergency planning. Earthquake planning is a cooperative effort and childcare providers have unique roles and responsibilities. Greece has high seismicity and Ionian Islands Region has the highest seismic activity of the country. Earthquake Planning and Protection Organization (EPPO) is a national organization in Greece. The mission of EPPO is the seismic risk reduction by designing an earthquake management program of mitigation and preparedness. Among other actions EPPO has analyzed the needs and requirements of kindergartens on earthquake protection issues and has designed specific activities to familiarize the day care centers staff being prepared for earthquakes.  This research presents the results of a survey that detects the level of earthquake preparedness of kindergartens in all over the country and Ionian Islands too. A closed-form questionnaire of 20 main questions was developed for the survey in order to detect the aspects of participants concerning the earthquake preparedness actions at individual, family and day care environment level. 2668 questionnaires were gathered from March 2014 to May 2019, and analyzed by EPPO’s Department of Education. Moreover, this paper presents the EPPO’s educational activities targeted to the Ionian Islands Region that implemented in the framework of “Telemachus” Project. To provide safe environment for children to learn, and staff to work is the foremost goal of any State, community and kindergarten. This project is funded under the Priority Axis “Environmental Protection and Sustainable Development” of Operational Plan “Ionian Islands 2014-2020”. It is increasingly accepted that emergency preparedness should be thought of as an ongoing process rather than a one-time activity. Creating an earthquake safe daycare environment that facilitates learning is a challenging task. Training, drills, and update of emergency plan should take place throughout the year at kindergartens to identify any gaps and to ensure the emergency procedures. EPPO will continue to work closely with regional and local authorities to actively address the needs of children and kindergartens before, during and after earthquakes.

Keywords: Child care centers, education on earthquake issues, emergency planning, Ionian Islands Region of Greece, kindergartens, preparedness.

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Authors: Seo Young Kim, Toshimitsu Hamasaki

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Microarrays have become the effective, broadly used tools in biological and medical research to address a wide range of problems, including classification of disease subtypes and tumors. Many statistical methods are available for analyzing and systematizing these complex data into meaningful information, and one of the main goals in analyzing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we express and compare the performance of several clustering methods based on data preprocessing including strategies of normalization or noise clearness. We also evaluate each of these clustering methods with validation measures for both simulated data and real gene expression data. Consequently, clustering methods which are common used in microarray data analysis are affected by normalization and degree of noise and clearness for datasets.

Keywords: Gene expression, clustering, data preprocessing.

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Authors: C. Hipp

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The EU Regulation (EC) No 261/2004 under which air passengers can claim compensation in the event of denied boarding, cancellation or long delay of flights has to be regarded as a substantial progress for the consumer protection in the field of air transport since it went into force in February 2005. Nevertheless, different reviews of its effective functioning demonstrate that most passengers affected by service disruptions do not enforce their complaints and claims towards the airline. The main cause of this is not only the unclear legal situation due to the fact that the regulation itself suffers from many undetermined terms and loopholes it is also attributable to the strategy of the airlines which do not handle the complaints of the passengers or exclude their duty to compensate them. Economically contemplated, reasons like the long duration of a trial and the cost risk in relation to the amount of compensation make it comprehensible that passengers are deterred from enforcing their rights by filing a lawsuit. The paper focusses on the alternative dispute resolution namely the recently established conciliation bodies which deal with air passenger rights. In this paper, the Conciliation Body for Public Transport in Germany (Schlichtungsstelle für den öffentlichen Personenverkehr – SÖP) is examined as a successful example of independent consumer arbitration service. It was founded in 2009 and deals with complaints in the field of air passenger rights since November 2013. According to the current situation one has to admit that due to its structure and operation it meets on the one hand the needs of the airlines by giving them an efficient tool of their customer relation management and on the other hand that it contributes to the enforcement of air passenger rights effectively.

Keywords: Air passenger rights, alternative dispute resolution (ADR), consumer protection, EU law regulation (EC) No 261/2004.

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Authors: Marinela Mircea

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The development of information and communication technology, the increased use of the internet, as well as the effects of the recession within the last years, have lead to the increased use of cloud computing based solutions, also called on-demand solutions. These solutions offer a large number of benefits to organizations as well as challenges and risks, mainly determined by data visualization in different geographic locations on the internet. As far as the specific risks of cloud environment are concerned, data security is still considered a peak barrier in adopting cloud computing. The present study offers an approach upon ensuring the security of cloud data, oriented towards the whole data life cycle. The final part of the study focuses on the assessment of data security in the cloud, this representing the bases in determining the potential losses and the premise for subsequent improvements and continuous learning.

Keywords: cloud computing, data life cycle, data security, security assessment.

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Authors: Ana Lambelho

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In an economic crisis such as the one that shook (and still shake) Europe, one does not question the importance of the measures that encourage the hiring and integration of young people into the labour market. In the mentioned context, enterprises tend to reduce the cost of labour and to seek flexible contracting instruments. The professional internships allow innovation and creativity at low cost, because, as they are not labour contracts, the enterprises do not have to respect the minimum standards related to wages, working time duration and so on. In Portugal, we observe a widespread existence of training contracts in which the trainee worked several hours without salary or was paid below the legally prescribed for the function and the work period. For this reason, under the tripartite agreement for a new system of regulation of labour relations, employment policies and social protection, between the Government and the social partners, in June 2008, foresaw a prohibition of professional internships unpaid and the legal regulation of the mandatory internships for access to an activity. The first Act about private internship contracts, i.e., internships without public funding was embodied in the Decree-Law N. 66/2011, of 1^st June. This work is dedicated to the study of the legal regime of the internship contract in Portugal, by analysing the problems brought by the new set of rules and especially those which remains unresolved. In fact, we can conclude that the number of situations covered by the Act is much lower than what was expected, because of the exclusion of the mandatory internship for access to a profession when the activity is developed autonomously. Since the majority of the activities can be developed both autonomously or subordinated, it is quite easy to out of the Act requirements and, so, out of the protection that it confers to the intern. In order to complete this study, we considered not only the mentioned legal Act, but also the few doctrine and jurisprudence about the theme.

Keywords: Intern, internship contact, labour law, Portugal.

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Authors: D. Prangchumpol

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This paper is a description approach to predict incoming and outgoing data rate in network system by using association rule discover, which is one of the data mining techniques. Information of incoming and outgoing data in each times and network bandwidth are network performance parameters, which needed to solve in the traffic problem. Since congestion and data loss are important network problems. The result of this technique can predicted future network traffic. In addition, this research is useful for network routing selection and network performance improvement.

Keywords: Traffic prediction, association rule, data mining.

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Authors: Petr Morávek, Miloš Šeda

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In practice, we often come across situations where it is necessary to make decisions based on incomplete or uncertain data. In control systems it may be due to the unknown exact mathematical model, or its excessive complexity (e.g. nonlinearity) when it is necessary to simplify it, respectively, to solve it using a rule base. In the case of databases, searching data we compare a similarity measure with of the requirements of the selection with stored data, where both the select query and the data itself may contain vague terms, for example in the form of linguistic qualifiers. In this paper, we focus on the processing of uncertain data in databases and demonstrate it on the example multi-criteria decision making in the selection of variants, specified by higher number of technical parameters.

Keywords: fuzzy logic, linguistic variable, multicriteria decision

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Authors: A. Gutiérrez, A. Castillo, J.M. Gómez, J.M. Gutiérrez, A. García-Cabot

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Lighting is not only important for the safety of traffic, but also it is very important for the protection of pedestrians. Improvement on visibility in a long distance, lighting, signing, reduces considerably the risk of accidents in crosswalks. This paper evaluates different aspects of crosswalks including signing and lighting to improve road safety.

Keywords: In pavement flashing warning lights, street lighting, signing, visibility.

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Authors: Stuart Henry, Philip Morrow, John Winder, Bryan Scotney

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The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.

Keywords: Data cleansing, stereophotogrammetry.

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Authors: Yi Chao Huang, Yu Ling Liao, Chiu Shuang Lin

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A data cutting and sorting method (DCSM) is proposed to optimize the performance of data mining. DCSM reduces the calculation time by getting rid of redundant data during the data mining process. In addition, DCSM minimizes the computational units by splitting the database and by sorting data with support counts. In the process of searching for the relationship between metabolic syndrome and lifestyles with the health examination database of an electronics manufacturing company, DCSM demonstrates higher search efficiency than the traditional Apriori algorithm in tests with different support counts.

Keywords: Data mining, Data cutting and sorting method, Apriori algorithm, Metabolic syndrome

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Authors: Feng Yue, Fei Dai

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With the rapid development of urbanization process in China, its environmental protection pressure is severely tested. So, analyzing and optimizing the landscape pattern is an important measure to ease the pressure on the ecological environment. This paper takes Wuhan Urban Development Zone as the research object, and studies its landscape pattern evolution and quantitative optimization strategy. First, remote sensing image data from 1990 to 2015 were interpreted by using Erdas software. Next, the landscape pattern index of landscape level, class level, and patch level was studied based on Fragstats. Then five indicators of ecological environment based on National Environmental Protection Standard of China were selected to evaluate the impact of landscape pattern evolution on the ecological environment. Besides, the cost distance analysis of ArcGIS was applied to simulate wildlife migration thus indirectly measuring the improvement of ecological environment quality. The result shows that the area of land for construction increased 491%. But the bare land, sparse grassland, forest, farmland, water decreased 82%, 47%, 36%, 25% and 11% respectively. They were mainly converted into construction land. On landscape level, the change of landscape index all showed a downward trend. Number of patches (NP), Landscape shape index (LSI), Connection index (CONNECT), Shannon's diversity index (SHDI), Aggregation index (AI) separately decreased by 2778, 25.7, 0.042, 0.6, 29.2%, all of which indicated that the NP, the degree of aggregation and the landscape connectivity declined. On class level, the construction land and forest, CPLAND, TCA, AI and LSI ascended, but the Distribution Statistics Core Area (CORE_AM) decreased. As for farmland, water, sparse grassland, bare land, CPLAND, TCA and DIVISION, the Patch Density (PD) and LSI descended, yet the patch fragmentation and CORE_AM increased. On patch level, patch area, Patch perimeter, Shape index of water, farmland and bare land continued to decline. The three indexes of forest patches increased overall, sparse grassland decreased as a whole, and construction land increased. It is obvious that the urbanization greatly influenced the landscape evolution. Ecological diversity and landscape heterogeneity of ecological patches clearly dropped. The Habitat Quality Index continuously declined by 14%. Therefore, optimization strategy based on greenway network planning is raised for discussion. This paper contributes to the study of landscape pattern evolution in planning and design and to the research on spatial layout of urbanization.

Keywords: Landscape pattern, optimization strategy, ArcGIS, Erdas, landscape metrics, landscape architecture.

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: Data mining, hybrid storage system, recurrent neural network, support vector machine.

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, data mining, Hadoop, Map Reduce, MongoDB, NoSQL.

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Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: Critical success factors, data quality, data quality management, Delphi, Q-Sort.

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Authors: Sher Muhammad, Mirza Muhammad Waqar

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It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79⁰ to 24.85⁰ in latitude and 66.91⁰ to 66.97⁰ in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image pre processing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end member extraction. Well distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (White Mangroves) and Avicennia germinans (Black Mangroves) have been observed throughout the study area.

Keywords: Mangrove, Hyperspectral, SAM, SFF, SID.

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Authors: M. Abbasi Dezfouli, S. Mazraeh, M. H. Yektaie

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Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.

Keywords: Wireless Sensor Networks, Security, Concealed Data Aggregation.

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Authors: Faruq A. Al-Omari, Nabeel I. Al-Fayoumi

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In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthesized image is then processed utilizing efficient image processing techniques to cluster the data in the dataset. Henceforth, the algorithm avoids exhaustive search to identify clusters. The algorithm considers only a small set of the data that contains critical boundary information sufficient to identify contained clusters. Compared to available data clustering techniques, the proposed algorithm produces similar quality results and outperforms them in execution time and storage requirements.

Keywords: Data clustering, Data mining, Image-mapping, Pattern discovery, Predictive analysis.

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Authors: Khaireyah Kh. Al-Hamad, V. Nassehi, A. R. Khan

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Air pollution is a major environmental health problem, affecting developed and developing countries around the world. Increasing amounts of potentially harmful gases and particulate matter are being emitted into the atmosphere on a global scale, resulting in damage to human health and the environment. Petroleum-related air pollutants can have a wide variety of adverse environmental impacts. In the crude oil production sectors, there is a strong need for a thorough knowledge of gaseous emissions resulting from the flaring of associated gas of known composition on daily basis through combustion activities under several operating conditions. This can help in the control of gaseous emission from flares and thus in the protection of their immediate and distant surrounding against environmental degradation. The impacts of methane and non-methane hydrocarbons emissions from flaring activities at oil production facilities at Kuwait Oilfields have been assessed through a screening study using records of flaring operations taken at the gas and oil production sites, and by analyzing available meteorological and air quality data measured at stations located near anthropogenic sources. In the present study the Industrial Source Complex (ISCST3) Dispersion Model is used to calculate the ground level concentrations of methane and nonmethane hydrocarbons emitted due to flaring in all over Kuwait Oilfields. The simulation of real hourly air quality in and around oil production facilities in the State of Kuwait for the year 2006, inserting the respective source emission data into the ISCST3 software indicates that the levels of non-methane hydrocarbons from the flaring activities exceed the allowable ambient air standard set by Kuwait EPA. So, there is a strong need to address this acute problem to minimize the impact of methane and non-methane hydrocarbons released from flaring activities over the urban area of Kuwait.

Keywords: Kuwait Oilfields, ISCST3 model, flaring, Airpollution, Methane and Non-methane.

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Authors: M. Abbasi Dezfouli, S. Mazraeh, M. H. Yektaie

Abstract:

Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.

Keywords: Wireless Sensor Networks, Security, Concealed Data Aggregation.

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Authors: H. P. Kerry

Abstract:

Drone technology has become a significant discourse in a nation’s national security, while this technology could constitute a danger to national security on the one hand, on the other hand, it is used in developed and developing countries for border security, and in some cases, for protection of security agents and migrants. In the case of Nigeria, drones are used by the military to monitor and tighten security around the borders. However, terrorist groups have devised a means to utilize the technology to their advantage. Therefore, the potential danger in the widespread proliferation of this technology has become a myriad of risks. The research on the effects of cross-border use of drones in Nigerian national security looks at the negative and positive consequences of using drone technology. The study employs the use of interviews and relevant documents to obtain data while the study applied the Just War theory to justify the reason why countries use force; it further buttresses the points with what the realist theory thinks about the use of force. In conclusion, the paper recommends that the Nigerian government through the National Assembly should pass a bill for the establishment of a law that will guide the use of armed and unarmed drones in Nigeria enforced by the Nigeria Civil Aviation Authority and the office of the National Security Adviser.

Keywords: Armed drones, cross-border, drones, national security.

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Authors: D Sudheer Reddy, N Gopal Reddy, P V Radhadevi, J Saibaba, Geeta Varadan

Abstract:

Smoothing or filtering of data is first preprocessing step for noise suppression in many applications involving data analysis. Moving average is the most popular method of smoothing the data, generalization of this led to the development of Savitzky-Golay filter. Many window smoothing methods were developed by convolving the data with different window functions for different applications; most widely used window functions are Gaussian or Kaiser. Function approximation of the data by polynomial regression or Fourier expansion or wavelet expansion also gives a smoothed data. Wavelets also smooth the data to great extent by thresholding the wavelet coefficients. Almost all smoothing methods destroys the peaks and flatten them when the support of the window is increased. In certain applications it is desirable to retain peaks while smoothing the data as much as possible. In this paper we present a methodology called as peak-wise smoothing that will smooth the data to any desired level without losing the major peak features.

Keywords: smoothing, moving average, peakwise smoothing, spatialdensity models, planar shape models, wavelets.

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