Search results for: satellite data
7290 Navigation and Guidance System Architectures for Small Unmanned Aircraft Applications
Authors: Roberto Sabatini, Celia Bartel, Anish Kaharkar, Tesheen Shaid, Subramanian Ramasamy
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Two multisensor system architectures for navigation and guidance of small Unmanned Aircraft (UA) are presented and compared. The main objective of our research is to design a compact, light and relatively inexpensive system capable of providing the required navigation performance in all phases of flight of small UA, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensor integrated architecture. Various existing techniques for VBN are compared and the Appearance-Based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway centreline and body rates. Additionally, we address the possible synergies of VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors, and the use of Aircraft Dynamics Model (ADM) to provide additional information suitable to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UA platform in real-time. The key mathematical models describing the two architectures i.e., VBN-IMU-GNSS (VIG) system and VIGADM (VIGA) system are introduced. The first architecture uses VBN and GNSS to augment the MEMS-IMU. The second mode also includes the ADM to provide augmentation of the attitude channel. Simulation of these two modes is carried out and the performances of the two schemes are compared in a small UA integration scheme (i.e., AEROSONDE UA platform) exploring a representative cross-section of this UA operational flight envelope, including high dynamics manoeuvres and CAT-I to CAT-III precision approach tasks. Simulation of the first system architecture (i.e., VIG system) shows that the integrated system can reach position, velocity and attitude accuracies compatible with the Required Navigation Performance (RNP) requirements. Simulation of the VIGA system also shows promising results since the achieved attitude accuracy is higher using the VBN-IMU-ADM than using VBN-IMU only. A comparison of VIG and VIGA system is also performed and it shows that the position and attitude accuracy of the proposed VIG and VIGA systems are both compatible with the RNP specified in the various UA flight phases, including precision approach down to CAT-II.
Keywords: Global Navigation Satellite System (GNSS), Lowcost Navigation Sensors, MEMS Inertial Measurement Unit (IMU), Unmanned Aerial Vehicle, Vision Based Navigation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31947289 Peakwise Smoothing of Data Models using Wavelets
Authors: D Sudheer Reddy, N Gopal Reddy, P V Radhadevi, J Saibaba, Geeta Varadan
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17417288 A New Precautionary Method for Measurement and Improvement the Data Quality
Authors: Seyed Mohammad Hossein Moossavizadeh, Mehran Mohsenzadeh, Nasrin Arshadi
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the data quality is a kind of complex and unstructured concept, which is concerned by information systems managers. The reason of this attention is the high amount of Expenses for maintenance and cleaning of the inefficient data. Such a data more than its expenses of lack of quality, cause wrong statistics, analysis and decisions in organizations. Therefor the managers intend to improve the quality of their information systems' data. One of the basic subjects of quality improvement is the evaluation of the amount of it. In this paper, we present a precautionary method, which with its application the data of information systems would have a better quality. Our method would cover different dimensions of data quality; therefor it has necessary integrity. The presented method has tested on three dimensions of accuracy, value-added and believability and the results confirm the improvement and integrity of this method.
Keywords: Data quality, precaution, information system, measurement, improvement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14567287 An Efficient Data Mining Approach on Compressed Transactions
Authors: Jia-Yu Dai, Don-Lin Yang, Jungpin Wu, Ming-Chuan Hung
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In an era of knowledge explosion, the growth of data increases rapidly day by day. Since data storage is a limited resource, how to reduce the data space in the process becomes a challenge issue. Data compression provides a good solution which can lower the required space. Data mining has many useful applications in recent years because it can help users discover interesting knowledge in large databases. However, existing compression algorithms are not appropriate for data mining. In [1, 2], two different approaches were proposed to compress databases and then perform the data mining process. However, they all lack the ability to decompress the data to their original state and improve the data mining performance. In this research a new approach called Mining Merged Transactions with the Quantification Table (M2TQT) was proposed to solve these problems. M2TQT uses the relationship of transactions to merge related transactions and builds a quantification table to prune the candidate itemsets which are impossible to become frequent in order to improve the performance of mining association rules. The experiments show that M2TQT performs better than existing approaches.Keywords: Association rule, data mining, merged transaction, quantification table.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19507286 Weigh-in-Motion Data Analysis Software for Developing Traffic Data for Mechanistic Empirical Pavement Design
Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder
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Currently, there are few user friendly Weigh-in- Motion (WIM) data analysis softwares available which can produce traffic input data for the recently developed AASHTOWare pavement Mechanistic-Empirical (ME) design software. However, these softwares have only rudimentary Quality Control (QC) processes. Therefore, they cannot properly deal with erroneous WIM data. As the pavement performance is highly sensible to the quality of WIM data, it is highly recommended to use more refined QC process on raw WIM data to get a good result. This study develops a userfriendly software, which can produce traffic input for the ME design software. This software takes the raw data (Class and Weight data) collected from the WIM station and processes it with a sophisticated QC procedure. Traffic data such as traffic volume, traffic distribution, axle load spectra, etc. can be obtained from this software; which can directly be used in the ME design software.Keywords: Weigh-in-motion, software, axle load spectra, traffic distribution, AASHTOWare.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18837285 A Novel Spectral Index for Automatic Shadow Detection in Urban Mapping Based On WorldView-2 Satellite Imagery
Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh
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In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of WorldView-2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows with accuracy of 94% effectively and automatically. Furthermore, the new shadow detection index improved road extraction from 82% to 93%.
Keywords: Spectral index, shadow detection, remote sensing images, WorldView-2.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33117284 Human Growth Curve Estimation through a Combination of Longitudinal and Cross-sectional Data
Authors: Sedigheh Mirzaei S., Debasis Sengupta
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Parametric models have been quite popular for studying human growth, particularly in relation to biological parameters such as peak size velocity and age at peak size velocity. Longitudinal data are generally considered to be vital for fittinga parametric model to individual-specific data, and for studying the distribution of these biological parameters in a human population. However, cross-sectional data are easier to obtain than longitudinal data. In this paper, we present a method of combining longitudinal and cross-sectional data for the purpose of estimating the distribution of the biological parameters. We demonstrate, through simulations in the special case ofthePreece Baines model, how estimates based on longitudinal data can be improved upon by harnessing the information contained in cross-sectional data.We study the extent of improvement for different mixes of the two types of data, and finally illustrate the use of the method through data collected by the Indian Statistical Institute.Keywords: Preece-Baines growth model, MCMC method, Mixed effect model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21257283 Semantic Support for Hypothesis-Based Research from Smart Environment Monitoring and Analysis Technologies
Authors: T. S. Myers, J. Trevathan
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Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.
Keywords: Information architecture, Semantic technologies Sensor networks, Ontologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17037282 Data Migration between Document-Oriented and Relational Databases
Authors: Bogdan Walek, Cyril Klimes
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Current tools for data migration between documentoriented and relational databases have several disadvantages. We propose a new approach for data migration between documentoriented and relational databases. During data migration the relational schema of the target (relational database) is automatically created from collection of XML documents. Proposed approach is verified on data migration between document-oriented database IBM Lotus/ Notes Domino and relational database implemented in relational database management system (RDBMS) MySQL.Keywords: data migration, database, document-oriented database, XML, relational schema
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35047281 Identity Verification Using k-NN Classifiers and Autistic Genetic Data
Authors: Fuad M. Alkoot
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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN).
Keywords: Biometrics, identity verification, genetic data, k-nearest neighbor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11047280 Power Saving System in Green Data Center
Authors: Joon-young Jung, Dong-oh Kang, Chang-seok Bae
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Power consumption is rapidly increased in data centers because the number of data center is increased and more the scale of data center become larger. Therefore, it is one of key research items to reduce power consumption in data center. The peak power of a typical server is around 250 watts. When a server is idle, it continues to use around 60% of the power consumed when in use, though vendors are putting effort into reducing this “idle" power load. Servers tend to work at only around a 5% to 20% utilization rate, partly because of response time concerns. An average of 10% of servers in their data centers was unused. In those reason, we propose dynamic power management system to reduce power consumption in green data center. Experiment result shows that about 55% power consumption is reduced at idle time.Keywords: Data Center, Green IT, Management Server, Power Saving.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16127279 Spatial Econometric Approaches for Count Data: An Overview and New Directions
Authors: Paula Simões, Isabel Natário
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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.Keywords: Spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26827278 MATLAB-Based Graphical User Interface (GUI) for Data Mining as a Tool for Environment Management
Authors: M. Awawdeh, A. Fedi
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The application of data mining to environmental monitoring has become crucial for a number of tasks related to emergency management. Over recent years, many tools have been developed for decision support system (DSS) for emergency management. In this article a graphical user interface (GUI) for environmental monitoring system is presented. This interface allows accomplishing (i) data collection and observation and (ii) extraction for data mining. This tool may be the basis for future development along the line of the open source software paradigm.
Keywords: Data Mining, Environmental data, Mathematical Models, Matlab Graphical User Interface.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47267277 An Approach for the Integration of the Existing Wireless Networks
Authors: Rajkumar Samanta, Abhishek Pal
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The demand of high quality services has fueled dimensional research and development in wireless communications and networking. As a result, different wireless technologies like Wireless LAN, CDMA, GSM, UMTS, MANET, Bluetooth and satellite networks etc. have emerged in the last two decades. Future networks capable of carrying multimedia traffic need IP convergence, portability, seamless roaming and scalability among the existing networking technologies without changing the core part of the existing communications networks. To fulfill these goals, the present networking systems are required to work in cooperation to ensure technological independence, seamless roaming, high security and authentication, guaranteed Quality of Services (QoS). In this paper, a conceptual framework for a cooperative network (CN) is proposed for integration of heterogeneous existing networks to meet out the requirements of the next generation wireless networks.
Keywords: Cooperative Network, Wireless Network, Integration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23477276 Principal Component Analysis using Singular Value Decomposition of Microarray Data
Authors: Dong Hoon Lim
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A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented via a singular value decomposition(SVD), is useful for analysis of microarray data. For application of PCA using SVD we use the DNA microarray data for the small round blue cell tumors(SRBCT) of childhood by Khan et al.(2001). To decide the number of components which account for sufficient amount of information we draw scree plot. Biplot, a graphic display associated with PCA, reveals important features that exhibit relationship between variables and also the relationship of variables with observations.
Keywords: Principal component analysis, singular value decomposition, microarray data, SRBCT
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32377275 Roof Material Detection Based on Object-Based Approach Using WorldView-2 Satellite Imagery
Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi
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One of the most important tasks in urban remote sensing is the detection of impervious surfaces (IS), such as roofs and roads. However, detection of IS in heterogeneous areas still remains one of the most challenging tasks. In this study, detection of concrete roof using an object-based approach was proposed. A new rule-based classification was developed to detect concrete roof tile. This proposed rule-based classification was applied to WorldView-2 image and results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images, with 85% accuracy.
Keywords: Urban remote sensing, impervious surface, Object- Based, Roof Material, Concrete tile, WorldView-2.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37837274 Clustering Mixed Data Using Non-normal Regression Tree for Process Monitoring
Authors: Youngji Yoo, Cheong-Sool Park, Jun Seok Kim, Young-Hak Lee, Sung-Shick Kim, Jun-Geol Baek
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In the semiconductor manufacturing process, large amounts of data are collected from various sensors of multiple facilities. The collected data from sensors have several different characteristics due to variables such as types of products, former processes and recipes. In general, Statistical Quality Control (SQC) methods assume the normality of the data to detect out-of-control states of processes. Although the collected data have different characteristics, using the data as inputs of SQC will increase variations of data, require wide control limits, and decrease performance to detect outof- control. Therefore, it is necessary to separate similar data groups from mixed data for more accurate process control. In the paper, we propose a regression tree using split algorithm based on Pearson distribution to handle non-normal distribution in parametric method. The regression tree finds similar properties of data from different variables. The experiments using real semiconductor manufacturing process data show improved performance in fault detecting ability.Keywords: Semiconductor, non-normal mixed process data, clustering, Statistical Quality Control (SQC), regression tree, Pearson distribution system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17667273 Speech Data Compression using Vector Quantization
Authors: H. B. Kekre, Tanuja K. Sarode
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Mostly transforms are used for speech data compressions which are lossy algorithms. Such algorithms are tolerable for speech data compression since the loss in quality is not perceived by the human ear. However the vector quantization (VQ) has a potential to give more data compression maintaining the same quality. In this paper we propose speech data compression algorithm using vector quantization technique. We have used VQ algorithms LBG, KPE and FCG. The results table shows computational complexity of these three algorithms. Here we have introduced a new performance parameter Average Fractional Change in Speech Sample (AFCSS). Our FCG algorithm gives far better performance considering mean absolute error, AFCSS and complexity as compared to others.Keywords: Vector Quantization, Data Compression, Encoding, , Speech coding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23887272 Ontology and CDSS Based Intelligent Health Data Management in Health Care Server
Authors: Eun-Jung Ko, Hyung-Jik Lee, Jeun-Woo Lee
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In ubiqutious healthcare environment, user's health data are transfered to the remote healthcare server by the user's wearable system or mobile phone. These collected user's health data should be managed and analyzed in the healthcare server, so that care giver or user can monitor user's physiological state. In this paper, we designed and developed the intelligent Healthcare Server to manage the user's health data using CDSS and ontology. Our system can analyze user's health data semantically using CDSS and ontology, and report the result of user's physiological raw data to the user and care giver.
Keywords: u-healthcare, CDSS, healthcare server, health data, ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22247271 Performance Analysis of Artificial Neural Network Based Land Cover Classification
Authors: Najam Aziz, Nasru Minallah, Ahmad Junaid, Kashaf Gul
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Landcover classification using automated classification techniques, while employing remotely sensed multi-spectral imagery, is one of the promising areas of research. Different land conditions at different time are captured through satellite and monitored by applying different classification algorithms in specific environment. In this paper, a SPOT-5 image provided by SUPARCO has been studied and classified in Environment for Visual Interpretation (ENVI), a tool widely used in remote sensing. Then, Artificial Neural Network (ANN) classification technique is used to detect the land cover changes in Abbottabad district. Obtained results are compared with a pixel based Distance classifier. The results show that ANN gives the better overall accuracy of 99.20% and Kappa coefficient value of 0.98 over the Mahalanobis Distance Classifier.Keywords: Landcover classification, artificial neural network, remote sensing, SPOT-5.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15837270 A Genetic Algorithm for Clustering on Image Data
Authors: Qin Ding, Jim Gasvoda
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Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.
Keywords: Clustering, data mining, genetic algorithm, image data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20307269 A Holistic Framework for Unifying Data Security and Management in Modern Enterprises
Authors: Ashly Joseph
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Modern businesses struggle significantly to secure and manage their data properly as the volume and complexity of their data both expand exponentially. Through the use of a multi-layered defense strategy, a centralized management platform, and cutting-edge technologies like AI, this research paper presents a comprehensive framework to integrate data security and management. The constraints of current data protection and management strategies, technological advancements, and the evolving threat landscape are all examined in this article. It suggests best practices for putting into practice integrated data security and governance models, placing an emphasis on ongoing adaptation. The advantages mentioned include a strengthened security posture, simpler procedures, lower costs, and reduced complexity. Additionally, issues including skill shortages, antiquated systems, and cultural obstacles are examined. Security executives and Chief Information Security Officers are given practical advice on how to evaluate, plan, and put into place strong data-centric security and management capabilities. The goal of the paper is to provide a thorough study of the data security and management landscape and to arm contemporary businesses with the knowledge they need to be proactive in protecting their data assets.
Keywords: Data security, security management, cloud computing, cybersecurity, data governance, security architecture, data management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2237268 Post Mining- Discovering Valid Rules from Different Sized Data Sources
Authors: R. Nedunchezhian, K. Anbumani
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A big organization may have multiple branches spread across different locations. Processing of data from these branches becomes a huge task when innumerable transactions take place. Also, branches may be reluctant to forward their data for centralized processing but are ready to pass their association rules. Local mining may also generate a large amount of rules. Further, it is not practically possible for all local data sources to be of the same size. A model is proposed for discovering valid rules from different sized data sources where the valid rules are high weighted rules. These rules can be obtained from the high frequency rules generated from each of the data sources. A data source selection procedure is considered in order to efficiently synthesize rules. Support Equalization is another method proposed which focuses on eliminating low frequency rules at the local sites itself thus reducing the rules by a significant amount.
Keywords: Association rules, multiple data stores, synthesizing, valid rules.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13927267 RFID-ready Master Data Management for Reverse Logistics
Authors: Jincheol Han, Hyunsun Ju, Jonghoon Chun
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Sharing consistent and correct master data among disparate applications in a reverse-logistics chain has long been recognized as an intricate problem. Although a master data management (MDM) system can surely assume that responsibility, applications that need to co-operate with it must comply with proprietary query interfaces provided by the specific MDM system. In this paper, we present a RFID-ready MDM system which makes master data readily available for any participating applications in a reverse-logistics chain. We propose a RFID-wrapper as a part of our MDM. It acts as a gateway between any data retrieval request and query interfaces that process it. With the RFID-wrapper, any participating applications in a reverse-logistics chain can easily retrieve master data in a way that is analogous to retrieval of any other RFID-based logistics transactional data.Keywords: Reverse Logistics, Master Data Management, RFID.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19577266 Dynamic Models versus Frailty Models for Recurrent Event Data
Authors: Entisar A. Elgmati
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Recurrent event data is a special type of multivariate survival data. Dynamic and frailty models are one of the approaches that dealt with this kind of data. A comparison between these two models is studied using the empirical standard deviation of the standardized martingale residual processes as a way of assessing the fit of the two models based on the Aalen additive regression model. Here we found both approaches took heterogeneity into account and produce residual standard deviations close to each other both in the simulation study and in the real data set.Keywords: Dynamic, frailty, misspecification, recurrent events.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23427265 Issues and Architecture for Supporting Data Warehouse Queries in Web Portals
Authors: Minsoo Lee, Yoon-kyung Lee, Hyejung Yoon, Soo-kyung Song, Sujeong Cheong
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Data Warehousing tools have become very popular and currently many of them have moved to Web-based user interfaces to make it easier to access and use the tools. The next step is to enable these tools to be used within a portal framework. The portal framework consists of pages having several small windows that contain individual data warehouse query results. There are several issues that need to be considered when designing the architecture for a portal enabled data warehouse query tool. Some issues need special techniques that can overcome the limitations that are imposed by the nature of data warehouse queries. Issues such as single sign-on, query result caching and sharing, customization, scheduling and authorization need to be considered. This paper discusses such issues and suggests an architecture to support data warehouse queries within Web portal frameworks.
Keywords: Data Warehousing tools, data warehousing queries, web portal frameworks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21097264 Design of the Large Dimension Cold Shield Cooled by G-M Cryocooler
Authors: Gong Jie, Yu Qianxu, Liu Min, Shan Weiwei
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The design of methods of the 20 K large dimension cold shield used for infrared radiation demarcating in space environment simulation test were introduced in this paper. The cold shield were cooled by five G-M cryocoolers , and the dimension of the cold shield is the largest in our country.Cold shield installation and distribution and compensator for contraction on cooling were introduced detailedly. The temperature distribution and cool-down time of cold shield surface were also calculated and analysed in this paper. The design of cold shield resolves the difficulty of compensator for contraction on cooling successfully. Test results show that the actual technical performance indicators of cold shield met and exceeded the design requirements.
Keywords: cold shield, G-M cryocooler,infrared radiometer demarcating, satellite, space environment simulation equipments
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16737263 Data Mining Using Learning Automata
Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri
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In this paper a data miner based on the learning automata is proposed and is called LA-miner. The LA-miner extracts classification rules from data sets automatically. The proposed algorithm is established based on the function optimization using learning automata. The experimental results on three benchmarks indicate that the performance of the proposed LA-miner is comparable with (sometimes better than) the Ant-miner (a data miner algorithm based on the Ant Colony optimization algorithm) and CNZ (a well-known data mining algorithm for classification).Keywords: Data mining, Learning automata, Classification rules, Knowledge discovery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19217262 Secure and Efficient Transmission of Aggregated Data for Mobile Wireless Sensor Networks
Authors: A. Krishna Veni, R.Geetha
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Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.
Keywords: Aggregation, lifetime, network security, wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12097261 Development of Greenhouse Analysis Tools for Home Agriculture Project
Authors: M. Amir Abas, M. Dahlui
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This paper presents the development of analysis tools for Home Agriculture project. The tools are required for monitoring the condition of greenhouse which involves two components: measurement hardware and data analysis engine. Measurement hardware is functioned to measure environment parameters such as temperature, humidity, air quality, dust and etc while analysis tool is used to analyse and interpret the integrated data against the condition of weather, quality of health, irradiance, quality of soil and etc. The current development of the tools is completed for off-line data recorded technique. The data is saved in MMC and transferred via ZigBee to Environment Data Manager (EDM) for data analysis. EDM converts the raw data and plot three combination graphs. It has been applied in monitoring three months data measurement for irradiance, temperature and humidity of the greenhouse..Keywords: Monitoring, Environment, Greenhouse, Analysis tools
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2004