• Journal of Korean Institute of Industrial Engineers
• /
• v.41 no.1
• /
• pp.25-33
• /
• 2015

From the viewpoint of applications to manufacturing, data mining is a useful method to find the meaningful knowledge or information about states of processes. But the data from manufacturing processes usually have two characteristics which are multicollinearity and imbalance distribution of data. Two characteristics are main causes which make bias to classification rules and select wrong variables as important variables. In the paper, we propose a new data mining procedure to solve the problem. First, to determine candidate variables, we propose the multiple hypothesis test. Second, to make unbiased classification rules, we propose the decision tree learning method with different weights for each category of quality variable. The experimental result with a real PDP (Plasma display panel) manufacturing data shows that the proposed procedure can make better information than other data mining procedures.

• Journal of Korean Society of Water and Wastewater
• /
• v.31 no.3
• /
• pp.249-256
• /
• 2017

Recently, application areas based on M2M (Machine-to-Machine communications) and IoT (Internet of Things) technologies are expanding rapidly. Accordingly, water flow and water quality management improvements are being pursued by applying this technology to water and sewage facilities. Especially, water management will collect and store accurate data based on various ICT technologies, and then will expand its service range to remote meter-reading service using smart metering system. For this, the error in flow rate data transmitting should be minimized to obtain credibility on related additional service system such as real time water flow rate analysis and billing. In this study, we have identified the structural problems in transmitting process and protocol to minimize errors in flow rate data transmission and its handling process which is essential to water supply pipeline management. The result confirmed that data acquisition via communication system is better than via analogue current values and pulse, and for communication method case, applying the industrial standard protocol is better for minimizing errors during data acquisition versus applying user assigned method.

• Proceedings of the Korea Contents Association Conference
• /
• 2005.05a
• /
• pp.329-332
• /
• 2005

The Internet advances and the documents of existing Is provided on web. An amount of data is increased through amendment and addition of information. The web is wide and is used and to follow the users of the majority which acquires information depend in web, the necessity of the data management by web is increasing. The sudden system failure frequently occurs from network environment, we must protect data from this danger. In this paper, we present data management system, which is composed of backup and restoration. This system provides systematic, efficient and stable data management on web.

• Journal of Korean Society for Quality Management
• /
• v.11 no.2
• /
• pp.25-31
• /
• 1983

Often arrangement for effective product assessment and audit have not been completely satisfactory. The underlying reasons are: (a) The lack of early evidence of new unit quality. (b) The collection and processing of data. (c) Ineffective data analysis techniques. (d) The variability of information on which decision making is based. Because of the nature of the product the essential outputs from an affective QA organization would be: (a) Confirmation of new unit quality. (b) Detection of failures which are either epidemic or slowly degradatory. (c) Identification of failure cases. (d) Provision of management information at the right time to effect the necessary corrective action. The heart of an effective QA scheme is the acquisition and processing of data. With the advent of data processing for quality monitoring becomes feasible in an automotive testing environment. This paper shows how the method enables us to use Automotive Testing data for the cost benefits of QA management.

• Journal of Korea Multimedia Society
• /
• v.12 no.9
• /
• pp.1242-1251
• /
• 2009

A DSMS(Data Stream Management System) in ubiquitous environment processes huge data that input from a number of sensor. The existed system is used with a load shedding method that is eliminated with a part of huge data stream when it doesn't process the huge data stream. The Load shedding method has to filter a part of input data. This is because, data completeness or reliability is decreased. In this paper, we proposed the overload prediction load balancing to maintain data completeness when the system has an overload. The proposed method predicts the overload time. and than it is decreased with data loss when achieves the prediction overload time. The performance evaluation shows that the proposed method performs better than the existed method.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2018.11a
• /
• pp.55-56
• /
• 2018

In order to reduce the risk of accidents, we proposed a construction safety management system combined with wearable device and LoRa (Low-Range Wireless Network) communication method to apply the usefulness of Internet (IoT) technology which means "everything connected". to construction safety management Management system. The proposed wearable safety device is a device that relays information exchange between wearable safety device and safety management server by LoRa wireless communication method. The safety management server can store workers bio-data and perform big data analysis. If a risk factor is determined from the analysis result, a warning is sent to the wearable safety device and the manager's application. The goal of this system is to prevent construction workers from entering the dangerous area that is not suitable for work, and to prevent safety accidents caused by human cause by detecting abnormal condition during work.

• The Journal of Information Systems
• /
• v.14 no.3
• /
• pp.17-22
• /
• 2005

Location management is very important in location-based services to provide services to the mobile users like banking, city guides and many more. Ubiquitous and mobile devices are the source of data in location management and its significant operations are update and search method. Some studies to improve these were presented by using optimal sequential paging, location area scheme and hierarchical database scheme. In addition, not all location services have the same access methods on data and it lead to difficulties of providing services. A proposed location management of multi-agent architecture is presented in this study. It shows the coordination of the agents on the distributed database of location-based services. The proposal focuses on the location management of the mobile object presented in a hierarchical search and update. Also, it uses a nearest neighbor technique for efficient search method of mobile objects.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.4
• /
• pp.69-79
• /
• 2015

This research proposes a modified data hiding method to hide data in a slack space of an NTFS index record. The existing data hiding method is for anti-forensics, which uses traces of file names of an index entry in an index record when files are deleted in a direcotry. The proposed method in this paper modifies the existing method to make non-admittable ASCII characters for a file name applicable. By improving the existing method, problems of a file creation error due to non-admittable characters are remedied; including the non-admittable 9 characters (i. e. slash /, colon :, greater than >, less than <, question mark ?, back slash ${\backslash}$, vertical bar |, semi-colon ;, esterisk * ), reserved file names(i. e. CON, PRN, AUX, NUL, COM1~COM9, LPT1~LPT9) and two non-admittable characters for an ending character of the file name(i. e. space and dot). Two results of the two message with non-admittable ASCII characters by keyboard inputs show the applicability of the proposed method.

• Korean Journal of Computational Design and Engineering
• /
• v.22 no.1
• /
• pp.80-88
• /
• 2017

Product data analytics (PDA) is a data-driven analysis method that uses product data management (PDM) databases as its operational data. It aims to understand and evaluate product development processes indirectly through the analysis of product data from the PDM databases. To educate and train PDA efficiently, this study proposed an approach that employs courses for both product development and PDA in a class. The participant group for product development provides a PDM database as a result of their product development activities, and the other group for PDA analyses the PDM database and provides analysis result to the product development group who can explain causes of the result. The collaboration between the two groups can enhance the efficiency of the education and training course on PDA. This study also includes an application example of the approach to a graduate class on PDA and discussion of its result.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2007.11a
• /
• pp.383-387
• /
• 2007

Traditional clustering is regarded as an unsupervised teaming to analyze unlabeled data. Semi-supervised clustering uses a small amount of labeled data to predict labels of unlabeled data as well as to improve clustering performance. Previous methods use constraints generated from available labeled data in clustering process. We propose a new constraint-based semi-supervised clustering method by reflecting initial predicted labels of unlabeled data. We evaluate and compare the performance of the proposed method in terms of classification errors through numerical experiments with blinded labeled data.