• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.39 no.2
• /
• pp.54-63
• /
• 2016

As technology has developed and cost for data processing has reduced, big data market has grown bigger. Developed countries such as the United States have constantly invested in big data industry and achieved some remarkable results like improving advertisement effects and getting patents for customer service. Every company aims to achieve long-term survival and profit maximization, but it needs to establish a good strategy, considering current industrial conditions so that it can accomplish its goal in big data industry. However, since domestic big data industry is at its initial stage, local companies lack systematic method to establish competitive strategy. Therefore, this research aims to help local companies diagnose their big data capabilities through a reference model and big data capability assessment system. Big data reference model consists of five maturity levels such as Ad hoc, Repeatable, Defined, Managed and Optimizing and five key dimensions such as Organization, Resources, Infrastructure, People, and Analytics. Big data assessment system is planned based on the reference model's key factors. In the Organization area, there are 4 key diagnosis factors, big data leadership, big data strategy, analytical culture and data governance. In Resource area, there are 3 factors, data management, data integrity and data security/privacy. In Infrastructure area, there are 2 factors, big data platform and data management technology. In People area, there are 3 factors, training, big data skills and business-IT alignment. In Analytics area, there are 2 factors, data analysis and data visualization. These reference model and assessment system would be a useful guideline for local companies.

• Journal of Computing Science and Engineering
• /
• v.2 no.4
• /
• pp.394-411
• /
• 2008

The data in automation and control systems can be achieved not only from different field devices but also from different OPC (OLE for Process Control) servers. However, current OPC clients can only read and decode the simple data from OPC servers. They will have some problems to acquire structured data and exchange the structured data. In addition to the large network control systems, the OPC clients can read, write, and subscribe to thousands of data points from/to OPC servers. Due to that, the most important factor for building a high performance and scalable industrial control system is the ability to transfer the process data between server and client in the most efficient and fastest way. In order to solve these problems, we propose a means to implement the OPC DA (Data Access) server supporting the OPC complex data, so that the OPC DA clients are able to read and decode any type of data from OPC servers. We also propose a method for caching the process data in large industrial control systems to overcome the limitation of performance of the pure OPC DA system. The performance analysis and discussion indicate that the proposed system has an acceptable performance and is feasible in order for applying to real-time industrial systems today.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.3
• /
• pp.469-476
• /
• 2016

Relational Database Management Systems have become de facto database model among most developers and users since the inception of Data Science. From IoT devices, sensors, social media and other sources, data is generated in structured, semi-structured and unstructured formats, in huge volumes, thereby the difficulty of data management greatly increases. Organizations that collect large amounts of data are increasingly turning to non relational databases - NoSQL databases. In this paper, through experiments with real field data, we demonstrate that MongoDB, a document-based NoSQL database, is a better alternative for building a Telco Subscriber Data Management System which hitherto is mainly built with Relational Database Management Systems. We compare the existing system in various phases of data flow with our proposed system powered by MongoDB. We show how various workloads at some phases of the existing system were either completely removed or significantly simplified on the new system. Based on experiment results, using MongoDB for managing telco subscriber data turned out to offer performance better than the existing system built with MSSQL Server.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.64 no.2
• /
• pp.85-91
• /
• 2015

With the increasing popularity of Smart Grid infrastructure, it is much easier to collect energy usage data using AMI (Advanced Measuring Instrument) from residential housing, buildings and factories. Several researches have been done to improve an energy efficiency by analyzing the collected energy usage data. However, it is not easy to store and analyze the energy data using a traditional relational database management system since the data size grows exponentially with an increasing popularity of Smart grid infrastructure. In this paper, we are proposing a Hadoop based Big data system to store and analyze energy usage data. Based on our limited experiments, Hadoop based energy data analysis is three times faster than that of a relational database management system based approach with the current system.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.14 no.2
• /
• pp.113-121
• /
• 2014

A subsea oil production system must be safely operated for 20-30 years after being installed. Because of the severe conditions of the subsea environment, such as extreme high pressure, low visibility, the possibility of unexpected impact by any object, and corrosion by seawater, subsea oil production systems should be monitored by subsea data logger systems and remotely operated vehicles to check for abnormal vibration and leakage to prevent a catastrophic accident. Because of the severity of subsea environmental conditions and the dominance of a few companies in the market, many people have thought that it would be difficult to develop a subsea data logger system. The primary objectives of the study described in this paper were to analyze existing subsea data logger systems to establish the requirements for a subsea data logger system, implement a prototype subsea data logger system, and conduct a test of the prototype subsea data logger system.

• Journal of Information Technology Services
• /
• v.14 no.2
• /
• pp.143-158
• /
• 2015

Companies and governments in an era of big data have been tried to create new values with their data resources. Among many data resources, many companies especially pay attention to data which is obtained from Social Network Service (SNS) because it reveals precise opinion of customers and can be used to estimate profiles of them from their social relationships. However, it is not only hard to collect, store, and analyze the data, but system applications are also insufficient. Therefore, this study proposes a S-POS (Social POS) system which consists of three parts; Twitter Side, POS Side and TPAS (Twitter&POS Analysis System). In this system, SNS data and POS data which are collected from Twitter Side and POS Side are stored in Mongo D/B. And it provides several services with POS terminal based on analysis and matching results which are generated from TPAS. Through S-POS system, we expect to efficient and effective store and sales managements of system users. Moreover, they can provide some differentiated services such as cross-selling and personalized recommendation services.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.16 no.6
• /
• pp.789-796
• /
• 2013

Next Generation Weapon system from the center of the platform to share information in real-time Network Centric Warfare(NCW: Network Centric Warfare) has been changed. Data link system is defined as a network. That is, all in real-time battlefield information is to enable sharing. Data link system is classified as a precision strike, Monitoring/control, control of a Patriot missile battery systems. These systems are most effective in a Joint warfare and precision strike. Data Link Systems(Data Communications) implementation is accomplished by using the KDLM(Korean Data Link Modem) and Radio Transceiver. KDLM is operated in conjunction with the legacy Radios(re-using fielded HF/VHF/UHF radio systems). In this paper, we describe in terms of KDLM system design. In this paper, the proposed design structure is how to effectively interact with legacy various radio. First, The results provide an analysis of that Dynamic TDMA system and apply modem structure. Radio characteristics data are necessary for an effective TDMA system design. This article analyzes the test results and describes the structure to improve the receive performance.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.121-128
• /
• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• The KIPS Transactions:PartA
• /
• v.11A no.1
• /
• pp.75-80
• /
• 2004

To interact database data with GRID system, implementation and installation of data manipulation module which manipulates database data and its index is required. Developing a search system searching data on web-based database, and integrating it with grid system, it is possible that searching data on web and use it directly on GRID system without independent data module. So, we can build easy and effective grid system, and the system could have more flexible architecture adapting data change. In this paper, we propose a searching system which interacting web-based database with GRID systems. We integrated the searching system with a bio god system which runs virtual screening jobs. As a result, UB Grid (Universal Bio Grid) is constructed. Developer could reduce time and effort required to integrate web data to GRID system, and user could use UB Grid system easily and effectively.

• Journal of the Korean Society for information Management
• /
• v.4 no.1
• /
• pp.154-169
• /
• 1987

The Computerizing Record Management System(RMS) has been developed for ULJIN Nuclear Power Plant in Korea on the basis of the Manual System. By means of review and analysis of processing flow & project requirements, system logics such as Receiving system, Logging system, Distribution system, Filing system, Indexing & Retrieval system and Output system of statistic and various reports, have been established for computerizing. Structure of Masterfile has been designed so as to include Bibliographic data, Transmittal data, Distribution data, Area data, RMS data for operation of Plant. The RMS data have been designed for construction and operation of the plant by adding index parameters for operation such as System code, KEPCO No., Component link code and Retention period on the point of receiving. The RMS has turned out an easy access to cross-reference between RMS and Material Control System.