• 제목/요약/키워드: Data Paper

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Simple Routing Control System for 10 Gb/s Data Transmission Using a Frequency Modulation Technique

  • Omoto, Daichi;Kishine, Keiji;Inaba, Hiromi;Tanaka, Tomoki
    • IEIE Transactions on Smart Processing and Computing
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    • 제5권3호
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    • pp.199-206
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    • 2016
  • This paper describes a simple routing control system. We propose achieving high-speed data transmission without modifying the data frame configuration. To add a routing control signal, called the "labeling signal" in this paper, to the data frame, we use a frequency modulation technique on the transmitted frame. This means you need not change the data frame when you transmit additional signals. Using a prototype system comprising a field-programmable gate array and discrete elements, we investigate the system performance and devise a method to achieve high resolution. A three-channel routing control for a 10 Gb/s data frame was achieved, which confirms the advantages of the proposed system.

A Bus Data Compression Method on a Phase-Based On-Chip Bus

  • Lee, Jae-Sung
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제12권2호
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    • pp.117-126
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    • 2012
  • This paper provides a method for compression transmission of on-chip bus data. As the data traffic on on-chip buses is rapidly increasing with enlarged video resolutions, many video processor chips suffer from a lack of bus bandwidth and their IP cores have to wait for a longer time to get a bus grant. In multimedia data such as images and video, the adjacent data signals very often have little or no difference between them. Taking advantage of this point, this paper develops a simple bus data compression method to improve the chip performance and presents its hardware implementation. The method is applied to a Video Codec - 1 (VC-1) decoder chip and reduces the processing time of one macro-block by 13.6% and 10.3% for SD and HD videos, respectively

병렬 웹 서비스를 이용한 조립체 모델 데이터의 획득 (Retrieval of Assembly Model Data Using Parallel Web Services)

  • 김병철;한순흥
    • 한국CDE학회논문집
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    • 제13권3호
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    • pp.217-226
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    • 2008
  • Web Services for CAD (WSC) aims at interoperation with CAD systems based on Web Services. This paper introduces one part of WSC which enables remote users to retrieve assembly model data using Web Services. However, retrieving assembly model data takes long time. To resolve this problem, this paper proposes using parallel Web Services. As assembly models comprise a set of part models, it is easy to separate the problem domain into smaller problems. In addition, Web Services inherently supports distributed computing. This characteristic makes the parallel processing of Web Services easy. Firstly, the implementation of WSC which retrieves assembly model data based parallel Web Services is shown. And then, for the comparison, the experiments on the retrieval of assembly model data based on single Web Services and parallel Web Services are shown.

Big Data Analysis and Prediction of Traffic in Los Angeles

  • Dauletbak, Dalyapraz;Woo, Jongwook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권2호
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    • pp.841-854
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    • 2020
  • The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

Enabling Efficient Verification of Dynamic Data Possession and Batch Updating in Cloud Storage

  • Qi, Yining;Tang, Xin;Huang, Yongfeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권6호
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    • pp.2429-2449
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    • 2018
  • Dynamic data possession verification is a common requirement in cloud storage systems. After the client outsources its data to the cloud, it needs to not only check the integrity of its data but also verify whether the update is executed correctly. Previous researches have proposed various schemes based on Merkle Hash Tree (MHT) and implemented some initial improvements to prevent the tree imbalance. This paper tries to take one step further: Is there still any problems remained for optimization? In this paper, we study how to raise the efficiency of data dynamics by improving the parts of query and rebalancing, using a new data structure called Rank-Based Merkle AVL Tree (RB-MAT). Furthermore, we fill the gap of verifying multiple update operations at the same time, which is the novel batch updating scheme. The experimental results show that our efficient scheme has better efficiency than those of existing methods.

전자해도 기반의 위치식별 ID 연계 모델 (ePosition Identification linked Model Based on ENC)

  • 서기열;이상지;오세웅;서상현;박계각
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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    • pp.201-205
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    • 2007
  • This paper proposes a link model that can provide the spacial position along the surface of the earth as an information or data using ePosition ID through the Internet. Moreover, to support the information service of maritime position, it needs the ENC linked technique based on S-57 that is an IHO transfer standard for digital hydrographic data. Therefore, it designs the linked model for applying and utilizing the ePosition technology with ENC data, as well as supplementing the base technology in applying them to marine related fields. As a study method, this paper first analyses ENC data model and structure, and converses for processing of ENC file to ePosition data. Finally, it derives the interconnection method with ePosition database and shows the ePosition service application based on the linked ENC data and its validity.

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Multivariable Bayesian curve-fitting under functional measurement error model

  • Hwang, Jinseub;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • 제27권6호
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    • pp.1645-1651
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    • 2016
  • A lot of data, particularly in the medical field, contain variables that have a measurement error such as blood pressure and body mass index. On the other hand, recently smoothing methods are often used to solve a complex scientific problem. In this paper, we study a Bayesian curve-fitting under functional measurement error model. Especially, we extend our previous model by incorporating covariates free of measurement error. In this paper, we consider penalized splines for non-linear pattern. We employ a hierarchical Bayesian framework based on Markov Chain Monte Carlo methodology for fitting the model and estimating parameters. For application we use the data from the fifth wave (2012) of the Korea National Health and Nutrition Examination Survey data, a national population-based data. To examine the convergence of MCMC sampling, potential scale reduction factors are used and we also confirm a model selection criteria to check the performance.

웹 데이터베이스 응용을 위한 액티브데이터마이닝 컴포넌트 개발 (Development of Active Data Mining Component for Web Database Applications)

  • 최용구
    • Journal of Information Technology Applications and Management
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    • 제15권2호
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    • pp.1-14
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    • 2008
  • The distinguished prosperity of information technologies from great progress of e-business during the last decade has unavoidably made software development for active data mining to discovery hidden predictive information regarding business trends and behavior from vary large databases. Therefore this paper develops an active mining object(ADMO) component, which provides real-time predictive information from web databases. The ADMO component is to extended ADO(ActiveX Data Object) component to active data mining component based on COM(Component Object Model) for application program interface(API). ADMO component development made use of window script component(WSC) based on XML(eXtensible Markup Language). For the purpose of investigating the application environments and the practical schemes of the ADMO component, experiments for diverse practical applications were performed in this paper. As a result, ADMO component confirmed that it could effectively extract the analytic information of classification and aggregation from vary large databases for Web services.

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Rating and Comments Mining Using TF-IDF and SO-PMI for Improved Priority Ratings

  • Kim, Jinah;Moon, Nammee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권11호
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    • pp.5321-5334
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    • 2019
  • Data mining technology is frequently used in identifying the intention of users over a variety of information contexts. Since relevant terms are mainly hidden in text data, it is necessary to extract them. Quantification is required in order to interpret user preference in association with other structured data. This paper proposes rating and comments mining to identify user priority and obtain improved ratings. Structured data (location and rating) and unstructured data (comments) are collected and priority is derived by analyzing statistics and employing TF-IDF. In addition, the improved ratings are generated by applying priority categories based on materialized ratings through Sentiment-Oriented Point-wise Mutual Information (SO-PMI)-based emotion analysis. In this paper, an experiment was carried out by collecting ratings and comments on "place" and by applying them. We confirmed that the proposed mining method is 1.2 times better than the conventional methods that do not reflect priorities and that the performance is improved to almost 2 times when the number to be predicted is small.

Data Security in Unattended Wireless Sensor Networks through Aggregate Signcryption

  • Babamir, Faezeh Sadat;Eslami, Ziba
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권11호
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    • pp.2940-2955
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    • 2012
  • In this paper, we propose aggregate signcryption for achieving data security in UWSNs. The main challenge of these networks established in sensitive environments is offline sink visiting. Moreover, the sensors must retain collected data for long enough time to offload them onto the itinerant sink. Thus, the unattended nature of data collection intervals might offer the adversary the opportunity to apply various attacks without detection. In this paper, employing low order operations (in time and space), we propose a new secure scheme in which various security goals such as confidentiality (through encrypting), authentication and integrity (through signing) are achieved. In addition, the aggregation process of our scheme reduces the space and communication overheads both for sensors and sink, i.e. the proposed technique efficiently enables the sensors and sink to protect, verify and recover all the related data. We further compare our scheme with the best alternative work in the literature.