Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6929

Search results for: data logging

6929 Visualization of Sediment Thickness Variation for Sea Bed Logging using Spline Interpolation

Authors: Hanita Daud, Noorhana Yahya, Vijanth Sagayan, Muizuddin Talib

Abstract:

This paper discusses on the use of Spline Interpolation and Mean Square Error (MSE) as tools to process data acquired from the developed simulator that shall replicate sea bed logging environment. Sea bed logging (SBL) is a new technique that uses marine controlled source electromagnetic (CSEM) sounding technique and is proven to be very successful in detecting and characterizing hydrocarbon reservoirs in deep water area by using resistivity contrasts. It uses very low frequency of 0.1Hz to 10 Hz to obtain greater wavelength. In this work the in house built simulator was used and was provided with predefined parameters and the transmitted frequency was varied for sediment thickness of 1000m to 4000m for environment with and without hydrocarbon. From series of simulations, synthetics data were generated. These data were interpolated using Spline interpolation technique (degree of three) and mean square error (MSE) were calculated between original data and interpolated data. Comparisons were made by studying the trends and relationship between frequency and sediment thickness based on the MSE calculated. It was found that the MSE was on increasing trends in the set up that has the presence of hydrocarbon in the setting than the one without. The MSE was also on decreasing trends as sediment thickness was increased and with higher transmitted frequency.

Keywords: Spline Interpolation, Mean Square Error, Sea Bed Logging, Controlled Source Electromagnetic

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6928 Design and Implementation of Shared Memory based Parallel File System Logging Method for High Performance Computing

Authors: Hyeyoung Cho, Sungho Kim, SangDong Lee

Abstract:

I/O workload is a critical and important factor to analyze I/O pattern and file system performance. However tracing I/O operations on the fly distributed parallel file system is non-trivial due to collection overhead and a large volume of data. In this paper, we design and implement a parallel file system logging method for high performance computing using shared memory-based multi-layer scheme. It minimizes the overhead with reduced logging operation response time and provides efficient post-processing scheme through shared memory. Separated logging server can collect sequential logs from multiple clients in a cluster through packet communication. Implementation and evaluation result shows low overhead and high scalability of this architecture for high performance parallel logging analysis.

Keywords: I/O workload, PVFS, I/O Trace.

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6927 Light Condition Change by Different Logging Systems in Lowland Dipterocarp Forest

Authors: T. Inada, M. Kanzaki, W. Ano, S. Hardiwinoto, R. Sadono

Abstract:

In a lowland dipterocarp forest, we assessed the impact of canopy openness (CO) and the resultant changes under different logging systems using hemispherical photography. CO was assessed in a primary forest and two forests logged selectively  using reduced impact logging. At one site, 3-m-wide strip cutting was conducted for line planting. From the comparison of CO among the three sites, we found significant changes caused by logging. However, no significant difference was observed between the two logged sites. Strip cutting treatment did not affect CO. One year after, significant canopy closure occurred in both of the logged sites. Canopy closure was significant regardless of the disturbance element, logging gap, skid trail, or strip cutting line. Significant establishment of seedlings within a year was observed in the strip cutting line. Seedling establishment seemed to contribute to rapid canopy closure and prospected to affect to the survival and growth of planted trees.

Keywords: Hemispherical photography, light condition, lowland dipterocarp forest, selective logging.

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6926 Modeling the Effects of Type and Intensity of Selective Logging on Forests of the Amazon

Authors: Theodore N.S. Karfakis, Anna Andrade, Carolina Volkmer-Castilho, Dennis R. Valle, Eric Arets, Paul van Gardingen

Abstract:

The aim of the work presented here was to either use existing forest dynamic simulation models or calibrate a new one both within the SYMFOR framework with the purpose of examining changes in stand level basal area and functional composition in response to selective logging considering trees > 10 cm d.b.h for two areas of undisturbed Amazonian non flooded tropical forest in Brazil and one in Peru. Model biological realism was evaluated for forest in the undisturbed and selectively logged state and it was concluded that forest dynamics were realistically represented. Results of the logging simulation experiments showed that in relation to undisturbed forest simulation subject to no form of harvesting intervention there was a significant amount of change over a 90 year simulation period that was positively proportional to the intensity of logging. Areas which had in the dynamic equilibrium of undisturbed forest a greater proportion of a specific ecological guild of trees known as the light hardwoods (LHW’s) seemed to respond more favorably in terms of less deviation but only within a specific range of baseline forest composition beyond which compositional diversity became more important. These finds are in line partially with practical management experience and partiality basic systematics theory respectively.

Keywords: Amazonbasin, ecological species guild, selective logging, simulation modeling.

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6925 The Southwestern Bangladesh’s Experience of Tidal River Management: An Analysis of Effectiveness and Challenges

Authors: Md. SajadulAlam, I. Ahmed, A. Naqib Jimmy, M. Haque Munna, N. Ahsan Khan

Abstract:

The construction of coastal polders to reduce salinity ingress at greater Khulna-Jashore region area was initiated in the 1960s by Bangladesh Water Development Board (BWDB). Although successful in a short run the, the Coastal Embankment Project (CEP) and its predecessors are often held accountable for the entire ecological disasters that affected many people. To overcome the water-logging crisis the first Tidal River Management (TRM) at Beel Bhaiana, Bhabodaho was implemented by the affected local people in an unplanned. TRM is an eco-engineering, low cost and participatory approach that utilizes the natural tidal characteristics and the local community’s indigenous knowledge for design and operation of watershed management. But although its outcomes were overwhelming in terms of reducing water-logging, increasing navigability etc. at Beel Bhaina the outcomes of its consequent schemes were debatable. So this study aims to examine the effectiveness and impact of the TRM schemes. Primary data were collected through questionnaire survey, Focus Group Discussion (FGD) and Key Informant Interview (KII) so as to collect mutually complementary quantitative and qualitative information along with extensive literature review. The key aspects that were examined include community participation, community perception on effectiveness and operational challenges.

Keywords: Sustainable, livelihood, salinity, water-logging, shrimp fry collectors, coastal region.

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6924 Design and Development of an Efficient and Cost-Effective Microcontroller-Based Irrigation Control System to Enhance Food Security

Authors: Robert A. Sowah, Stephen K. Armoo, Koudjo M. Koumadi, Rockson Agyeman, Seth Y. Fiawoo

Abstract:

The development of the agricultural sector in Ghana has been reliant on the use of irrigation systems to ensure food security. However, the manual operation of these systems has not facilitated their maximum efficiency due to human limitations. This paper seeks to address this problem by designing and implementing an efficient, cost effective automated system which monitors and controls the water flow of irrigation through communication with an authorized operator via text messages. The automatic control component of the system is timer based with an Atmega32 microcontroller and a real time clock from the SM5100B cellular module. For monitoring purposes, the system sends periodic notification of the system on the performance of duty via SMS to the authorized person(s). Moreover, the GSM based Irrigation Monitoring and Control System saves time and labour and reduces cost of operating irrigation systems by saving electricity usage and conserving water. Field tests conducted have proven its operational efficiency and ease of assessment of farm irrigation equipment due to its costeffectiveness and data logging capabilities.

Keywords: Agriculture, control system, data logging, food security, irrigation system, microcontroller.

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6923 Influence of Instructors in Engaging Online Graduate Students in Active Learning in the United States

Authors: Ehi E. Aimiuwu

Abstract:

As of 2017, many online learning professionals, institutions, and journals are still wondering how instructors can keep student engaged in the online learning environment to facilitate active learning effectively. The purpose of this qualitative single-case and narrative research is to explore whether online professors understand their role as mentors and facilitators of students’ academic success by keeping students engaged in active learning based on personalized experience in the field. Data collection tools that were used in the study included an NVivo 12 Plus qualitative software, an interview protocol, a digital audiotape, an observation sheet, and a transcription. Seven online professors in the United States from LinkedIn and residencies were interviewed for this study. Eleven online teaching techniques from previous research were used as the study framework. Data analysis process, member checking, and key themes were used to achieve saturation. About 85.7% of professors agreed on rubric as the preferred online grading technique. About 57.1% agreed on professors logging in daily, students logging in about 2-5 times weekly, knowing students to increase accountability, email as preferred communication tool, and computer access for adequate online learning. About 42.9% agreed on syllabus for clear class expectations, participation to show what has been learned, and energizing students for creativity.

Keywords: Class facilitation, class management, online teaching, online education, pedagogy.

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6922 Satellite Data Classification Accuracy Assessment Based from Reference Dataset

Authors: Mohd Hasmadi Ismail, Kamaruzaman Jusoff

Abstract:

In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Keywords: Image Classification, Reference Data, Accuracy Assessment, Kappa Statistic, Forest Land Cover

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6921 Determination of Lithology, Porosity and Water Saturation for Mishrif Carbonate Formation

Authors: F. S. Kadhim, A. Samsuri, H. Alwan

Abstract:

Well logging records can help to answer many questions from a wide range of special interested information and basic petrophysical properties to formation evaluation of oil and gas reservoirs. The accurate calculations of porosity in carbonate reservoirs are the most challenging aspects of the well logging analysis. Many equations have been developed over the years based on known physical principles or on empirically derived relationships, which are used to calculate porosity, estimate lithology, and water saturation; however these parameters are calculated from well logs by using modern technique in a current study. Nasiriya oil field is one of the giant oilfields in the Middle East, and the formation under study is the Mishrif carbonate formation which is the shallowest hydrocarbon bearing zone in this oilfield. Neurolog software was used to digitize the scanned copies of the available logs. Environmental corrections had been made as per Schlumberger charts 2005, which supplied in the Interactive Petrophysics software. Three saturation models have been used to calculate water saturation of carbonate formations, which are simple Archie equation, Dual water model, and Indonesia model. Results indicate that the Mishrif formation consists mainly of limestone, some dolomite, and shale. The porosity interpretation shows that the logging tools have a good quality after making the environmental corrections. The average formation water saturation for Mishrif formation is around 0.4- 0.6.This study is provided accurate behavior of petrophysical properties with depth for this formation by using modern software.

Keywords: Lithology, Porosity, Water Saturation, Carbonate Formation, Mishrif Formation.

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6920 Tidal River Sediment Management–A Case Study in Southwestern Bangladesh

Authors: Md. Sharif Imam Ibne Amir, M. Shah Alam Khan, Mohammad Masud Kamal Khan, Mohammad Golam Rasul, Fatema Akram

Abstract:

The problems of severe drainage congestion and water logging in the southwestern Bangladesh have been solved by an innovative concept, Tidal River Management (TRM). TRM involves the uniform raising of the land inside a tidal basin (beel) while simultaneously maintaining the proper drainage capacity in the river. The present practice of TRM is to link the river with the selected beel by constructing a link canal at the entrance of which most of the sedimentation takes place. This localized sedimentation also creates drainage congestion and water logging making it unattractive to landowners who participate in the program. In this paper a functional sediment management plan is presented to get rid of this problem

Keywords: Beel, embankment, MIKE 21 Flow Model FM, Tidal River Management.

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6919 An Extensible Software Infrastructure for Computer Aided Custom Monitoring of Patients in Smart Homes

Authors: Ritwik Dutta, Marilyn Wolf

Abstract:

This paper describes the tradeoffs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The backend consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: Flask, Java, JavaScript, health monitoring, long term care, Mongo, Python, smart home, software engineering, webserver.

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6918 New Identity Management Scheme and its Formal Analysis

Authors: Jeonghoon Han, Hanjae Jeong, Dongho Won, Seungjoo Kim

Abstract:

As the Internet technology has developed rapidly, the number of identities (IDs) managed by each individual person has increased and various ID management technologies have been developed to assist users. However, most of these technologies are vulnerable to the existing hacking methods such as phishing attacks and key-logging. If the administrator-s password is exposed, an attacker can access the entire contents of the stolen user-s data files in other devices. To solve these problems, we propose here a new ID management scheme based on a Single Password Protocol. The paper presents the details of the new scheme as well as a formal analysis of the method using BAN Logic.

Keywords: Anti-phishing, BAN Logic, ID management.

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6917 Big Data: Big Challenges to Privacy and Data Protection

Authors: Abu Bakar Munir, Siti Hajar Mohd Yasin, Firdaus Muhammad-Sukki

Abstract:

This paper seeks to analyse the benefits of big data and more importantly the challenges it pose to the subject of privacy and data protection. First, the nature of big data will be briefly deliberated before presenting the potential of big data in the present days. Afterwards, the issue of privacy and data protection is highlighted before discussing the challenges of implementing this issue in big data. In conclusion, the paper will put forward the debate on the adequacy of the existing legal framework in protecting personal data in the era of big data.

Keywords: Big data, data protection, information, privacy.

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6916 A Real Time Development Study for Automated Centralized Remote Monitoring System at Royal Belum Forest

Authors: Amri Yusoff, Shahrizuan Shafiril, Ashardi Abas, Norma Che Yusoff

Abstract:

Nowadays, illegal logging has been causing many effects including flash flood, avalanche, global warming, and etc. The purpose of this study was to maintain the earth ecosystem by keeping and regulate Malaysia’s treasurable rainforest by utilizing a new technology that will assist in real-time alert and give faster response to the authority to act on these illegal activities. The methodology of this research consisted of design stages that have been conducted as well as the system model and system architecture of the prototype in addition to the proposed hardware and software that have been mainly used such as microcontroller, sensor with the implementation of GSM, and GPS integrated system. This prototype was deployed at Royal Belum forest in December 2014 for phase 1 and April 2015 for phase 2 at 21 pinpoint locations. The findings of this research were the capture of data in real-time such as temperature, humidity, gaseous, fire, and rain detection which indicate the current natural state and habitat in the forest. Besides, this device location can be detected via GPS of its current location and then transmitted by SMS via GSM system. All of its readings were sent in real-time for further analysis. The data that were compared to meteorological department showed that the precision of this device was about 95% and these findings proved that the system is acceptable and suitable to be used in the field.

Keywords: Remote monitoring system, forest data, GSM, GPS, wireless sensor.

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6915 Numerical Analysis and Experimental Validation of a Downhole Stress/Strain Measurement Tool

Authors: Abhay Bodake, Ping Sui, Hafeez Syed, Ratish Kadam

Abstract:

Real-time measurement of applied forces, like tension, compression, torsion, and bending moment, identifies the transferred energies being applied to the bottomhole assembly (BHA). These forces are highly detrimental to measurement/logging-while-drilling tools and downhole equipment. Real-time measurement of the dynamic downhole behavior, including weight, torque, bending on bit, and vibration, establishes a real-time feedback loop between the downhole drilling system and drilling team at the surface. This paper describes the numerical analysis of the strain data acquired by the measurement tool at different locations on the strain pockets. The strain values obtained by FEA for various loading conditions (tension, compression, torque, and bending moment) are compared against experimental results obtained from an identical experimental setup. Numerical analyses results agree with experimental data within 8% and, therefore, substantiate and validate the FEA model. This FEA model can be used to analyze the combined loading conditions that reflect the actual drilling environment.

Keywords: FEA, M/LWD, Oil & Gas, Strain Measurement.

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6914 Experimental and Numerical Studies of Drag Reduction on a Circular Cylinder

Authors: A.O. Ladjedel, B.T.Yahiaoui, C.L.Adjlout, D.O.Imine

Abstract:

In the present paper; an experimental and numerical investigations of drag reduction on a grooved circular cylinder have been performed. The experiments were carried out in closed circuit subsonic wind tunnel (TE44); the pressure distribution on the cylinder was conducted using a TE44DPS differential pressure scanner and the drag forces were measured using the TE81 balance. The display unit is linked to a computer, loaded with DATASLIM software for data analysis and logging of result. The numerical study was performed using the code ANSYS FLUENT solving the Reynolds Averaged Navier-Stokes (RANS) equations. The k-ε and k- ω SST models were tested. The results obtained from the experimental and numerical investigations have showed a reduction in the drag when using longitudinal grooves namely 2 and 6 on the cylinder.

Keywords: Circular cylinder, Drag, grooves, pressure distribution

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6913 Data Preprocessing for Supervised Leaning

Authors: S. B. Kotsiantis, D. Kanellopoulos, P. E. Pintelas

Abstract:

Many factors affect the success of Machine Learning (ML) on a given task. The representation and quality of the instance data is first and foremost. If there is much irrelevant and redundant information present or noisy and unreliable data, then knowledge discovery during the training phase is more difficult. It is well known that data preparation and filtering steps take considerable amount of processing time in ML problems. Data pre-processing includes data cleaning, normalization, transformation, feature extraction and selection, etc. The product of data pre-processing is the final training set. It would be nice if a single sequence of data pre-processing algorithms had the best performance for each data set but this is not happened. Thus, we present the most well know algorithms for each step of data pre-processing so that one achieves the best performance for their data set.

Keywords: Data mining, feature selection, data cleaning.

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6912 Applications of Big Data in Education

Authors: Faisal Kalota

Abstract:

Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: Analytics, Big Data in Education, Hadoop, Learning Analytics.

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6911 Research of Data Cleaning Methods Based on Dependency Rules

Authors: Yang Bao, Shi Wei Deng, Wang Qun Lin

Abstract:

This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSql), and gives 6 data cleaning methods based on these algorithms.

Keywords: Data cleaning, dependency rules, violation data discovery, data repair.

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6910 Coalescing Data Marts

Authors: N. Parimala, P. Pahwa

Abstract:

OLAP uses multidimensional structures, to provide access to data for analysis. Traditionally, OLAP operations are more focused on retrieving data from a single data mart. An exception is the drill across operator. This, however, is restricted to retrieving facts on common dimensions of the multiple data marts. Our concern is to define further operations while retrieving data from multiple data marts. Towards this, we have defined six operations which coalesce data marts. While doing so we consider the common as well as the non-common dimensions of the data marts.

Keywords: Data warehouse, Dimension, OLAP, Star Schema.

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6909 Application of Building Information Modeling in Energy Management of Individual Departments Occupying University Facilities

Authors: Kung-Jen Tu, Danny Vernatha

Abstract:

To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: Sensor, electricity sub-meters, database, energy anomaly detection.

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6908 Mining Big Data in Telecommunications Industry: Challenges, Techniques, and Revenue Opportunity

Authors: Hoda A. Abdel Hafez

Abstract:

Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: Mining Big Data, Big Data, Machine learning, Data Streams, Telecommunication.

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6907 Comparative Analysis of Diverse Collection of Big Data Analytics Tools

Authors: S. Vidhya, S. Sarumathi, N. Shanthi

Abstract:

Over the past era, there have been a lot of efforts and studies are carried out in growing proficient tools for performing various tasks in big data. Recently big data have gotten a lot of publicity for their good reasons. Due to the large and complex collection of datasets it is difficult to process on traditional data processing applications. This concern turns to be further mandatory for producing various tools in big data. Moreover, the main aim of big data analytics is to utilize the advanced analytic techniques besides very huge, different datasets which contain diverse sizes from terabytes to zettabytes and diverse types such as structured or unstructured and batch or streaming. Big data is useful for data sets where their size or type is away from the capability of traditional relational databases for capturing, managing and processing the data with low-latency. Thus the out coming challenges tend to the occurrence of powerful big data tools. In this survey, a various collection of big data tools are illustrated and also compared with the salient features.

Keywords: Big data, Big data analytics, Business analytics, Data analysis, Data visualization, Data discovery.

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6906 Multi-labeled Data Expressed by a Set of Labels

Authors: Tetsuya Furukawa, Masahiro Kuzunishi

Abstract:

Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.

Keywords: Classification Hierarchies, Multi-labeled Data, Multiple Classificaiton, Orders of Sets of Labels

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6905 The Comparison of Data Replication in Distributed Systems

Authors: Iman Zangeneh, Mostafa Moradi, Ali Mokhtarbaf

Abstract:

The necessity of ever-increasing use of distributed data in computer networks is obvious for all. One technique that is performed on the distributed data for increasing of efficiency and reliablity is data rplication. In this paper, after introducing this technique and its advantages, we will examine some dynamic data replication. We will examine their characteristies for some overus scenario and the we will propose some suggestion for their improvement.

Keywords: data replication, data hiding, consistency, dynamicdata replication strategy

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6904 Implementation of an IoT Sensor Data Collection and Analysis Library

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: Clustering, data mining, DBSCAN, k-means, k-medoids, sensor data.

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6903 Government (Big) Data Ecosystem: Definition, Classification of Actors, and Their Roles

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: Big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review.

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6902 A Secure Auditing Framework for Load Balancing in Cloud Environment

Authors: R. Geetha, T. Padmavathy

Abstract:

Security audit is an important aspect or feature to be considered in cloud service customer. It is basically a certification process to audit the controls that deliver the security requirements. Security audits are conducted by trained and qualified staffs that belong to an independent auditing organization. Security audits must be carried as a standard of security controls. Proper check to be made that the cloud user has a proper reporting and logging facilities with the customer's system and hence ensuring appropriate business and operational flow of data through cloud service. We propose a cloud-based secure auditing framework, which enables confided in power to safely store their mystery information on the semi-believed cloud specialist co-ops, and specifically share their mystery information with a wide scope of information recipient, to diminish the key administration intricacy for power proprietors and information collectors. Unique in relation to past cloud-based information framework, data proprietors transfer their mystery information into cloud utilizing static and dynamic evaluating plan. Another propelled determination is, if any information beneficiary needs individual record to download, the information collector will send the solicitation to the expert. The specialist proprietor has the Access Control. At the off probability, the businessman must impart the primary record to the knowledge collector, acknowledge statistics beneficiary solicitation. Once the acknowledgement for the records is over, the recipient downloads the first record and this record shifting time with date and downloading time with date are monitored by the inspector. In addition to deduplication concept, diminished cloud memory area using dynamic document distribution has been proposed.

Keywords: Cloud computing, cloud storage auditing, data integrity, key exposure.

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6901 Imputation Technique for Feature Selection in Microarray Data Set

Authors: Younies Mahmoud, Mai Mabrouk, Elsayed Sallam

Abstract:

Analyzing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics.

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6900 Automatic Real-Patient Medical Data De-Identification for Research Purposes

Authors: Petr Vcelak, Jana Kleckova

Abstract:

Our Medicine-oriented research is based on a medical data set of real patients. It is a security problem to share patient private data with peoples other than clinician or hospital staff. We have to remove person identification information from medical data. The medical data without private data are available after a de-identification process for any research purposes. In this paper, we introduce an universal automatic rule-based de-identification application to do all this stuff on an heterogeneous medical data. A patient private identification is replaced by an unique identification number, even in burnedin annotation in pixel data. The identical identification is used for all patient medical data, so it keeps relationships in a data. Hospital can take an advantage of a research feedback based on results.

Keywords: DASTA, De-identification, DICOM, Health Level Seven, Medical data, OCR, Personal data

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