• IE interfaces
• /
• v.12 no.1
• /
• pp.79-93
• /
• 1999

As most of information systems developed are data-centric rather than process-centric, it is difficult for users to understand and manage the system from the viewpoint of work processes. To resolve the problem of the data-centric design, we propose a new method to design WFMSs(Workflow Management Systems), which are focused on processes and modified from current information engineering methods. In this research, the drawing approval and engineering change approval process of a K manufacturing company has been analyzed as a sample process. This method takes two steps, i.e., process analysis and system design. In the prosess analysis, data and processes are analyzed, and functions and tasks are derived from the processes. In the system design, a data model for the operation of WFMS is designed, and based on this data model, build-time and run-time functions of WFMS are designed.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.3 s.96
• /
• pp.9-17
• /
• 1999

This paper presents a method of grinding and polishing automation of precision die after CNC machining. The method employs a robot system equipped with a pneumatic spindle and a special abrasive film pad. The robot program is automatically generated off-line program form a PC and downloaded to robot controller. Position and orientation data for the program is supplied form cutter contact (CC) data of NC machining process. This eliminates separate robot teaching process. This paper aims at practical automation of die finishing process which is very time consuming and suffering from shortage of workpeople. Time loss due to changeover from one product to another is eliminated by PC off-line programming exploiting appropriate NC machining data. Dextrous 6-axis robot with rigid wrist and simple tooling enables the process applicable to larger, rather complex 3 dimensional free surfaces.

• Journal of Korean Library and Information Science Society
• /
• v.54 no.3
• /
• pp.321-346
• /
• 2023

A data paper describing research data helps credit researchers producing the data while helping other researchers verify previous research and start new research by reusing the data. Publishing a data paper and depositing data to a public data repository are increasing with these benefits. A domestic academic society that plans to publish data papers faces challenges, including timely acquiring tremendous knowledge concerning data paper structures and templates, peer review policy and process, and trustworthy data repositories, as a data paper has different characteristics, unlike a research paper. However, the need for more research and information concerning the critical elements of data paper and the peer-review process makes it difficult to operate for data paper review and publication. To address these issues, we propose essential concepts of the data paper and the data paper peer-review, including the process model of the peer-review with in-depth analysis of five data journals' data paper templates, articles, and other guides worldwide. Academic societies intending to publish or add data papers as a new type of paper may establish policies and define a peer-review process by adopting the proposed conceptual models, effectively streamlining the preparation of data paper publication.

• Journal of the Korea Safety Management & Science
• /
• v.6 no.3
• /
• pp.237-247
• /
• 2004

The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.

• Journal of Powder Materials
• /
• v.31 no.2
• /
• pp.137-145
• /
• 2024

In order to predict the process window of laser powder bed fusion (LPBF) for printing metallic components, the calculation of volumetric energy density (VED) has been widely calculated for controlling process parameters. However, because it is assumed that the process parameters contribute equally to heat input, the VED still has limitation for predicting the process window of LPBF-processed materials. In this study, an explainable machine learning (xML) approach was adopted to predict and understand the contribution of each process parameter to defect evolution in Ti alloys in the LPBF process. Various ML models were trained, and the Shapley additive explanation method was adopted to quantify the importance of each process parameter. This study can offer effective guidelines for fine-tuning process parameters to fabricate high-quality products using LPBF.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.1
• /
• pp.79-86
• /
• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• Journal of Korea Multimedia Society
• /
• v.24 no.6
• /
• pp.768-788
• /
• 2021

The reversible data hiding technique safely transmits secret data to the recipient from malicious attacks by third parties. In addition, this technique can completely restore the image used as a transmission medium for secret data. The reversible data hiding schemes have been proposed in various forms, and recently, the reversible data hiding schemes based on interpolation are actively researching. The reversible data hiding scheme based on the interpolation method expands the original image into the cover image and embed secret data. However, the existing interpolation-based reversible data hiding schemes did not embed secret data during the interpolation process. To improve this problem, this paper proposes embedding the first secret data during the image interpolation process and embedding the second secret data into the interpolated cover image. In the embedding process, the original image is divided into blocks without duplicates, and the maximum and minimum values are determined within each block. Three way searching based on the maximum value and two way searching based on the minimum value are performed. And, image interpolation is performed while embedding the first secret data using the PVD scheme. A stego image is created by embedding the second secret data using the maximum difference value and log function in the interpolated cover image. As a result, the proposed scheme embeds secret data twice. In particular, it is possible to embed secret data even during the interpolation process of an image that did not previously embed secret data. Experimental results show that the proposed scheme can transmit more secret data to the receiver while maintaining the image quality similar to other interpolation-based reversible data hiding schemes.

• Journal of the Korean Data and Information Science Society
• /
• v.18 no.4
• /
• pp.1157-1170
• /
• 2007

LBS must manage various context data and make the best use of this data for application service in ubiquitous environment. Conventional mobile object data management architecture did not consider process of context data. Therefore a new mobile data management framework is needed to process location context data. In this paper, we design a new context management framework for a location based application service. A suggestion framework is consisted of context collector, context manager, rule base, inference engine, and mobile object context database. It describes a form of rule base and a movement process of inference engine that are based on location based application scenario. It also presents an embodiment instance of interface which suggested framework is applied to location context interference of mobile object.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2010.04a
• /
• pp.226-234
• /
• 2010

In this thesis, we present process that remove mistake of data before statistical analysis. If field data which is not simple examination about validity of data, we cannot believe analyzed statistics information. As statistical analysis information is produced based on data to be input in statistical analysis process, the data to be input should be free of error. In this paper, we study the application of statistical analysis road map that can enhance application on site by organizing basic theory and approaching on initial data exploratory phase, essential step before conducting statistical analysis. Therefore, access to statistical analysis can be enhanced and reliability on result of analysis can be secured by conducting correct statistical analysis.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.9
• /
• pp.1-10
• /
• 2015

In this paper, we propose a new variable latency L1 data cache architecture for multi-core processors. Our proposed architecture extends the traditional variable latency cache to be geared toward the multi-core processors. We added a specialized data structure for recording the latency of the L1 data cache. Depending on the added latency to the L1 data cache, the value stored to the data structure is determined. It also tracks the remaining cycles of the L1 data cache which notifies data arrival to the reservation station in the core. As in the variable latency cache of the single-core architecture, our proposed architecture flexibly extends the cache access cycles considering process variation. The proposed cache architecture can reduce yield losses incurred by L1 cache access time failures to nearly 0%. Moreover, we quantitatively evaluate performance, power, energy consumption, power-delay product, and energy-delay product when increasing the number of cache access cycles.