• Journal of Mechanical Science and Technology
• /
• v.14 no.10
• /
• pp.1089-1103
• /
• 2000

A Problem of relevant interest to some industries is that of obtaining optimum two-dimensional layout. To solve this provlem, one is given a number of rectangular sheets and an order for a specified number of each of certain types of two-dimensional regular and irregular shapes. The aim is to cut the the shapes out of the sheets in such a way as to minimize the amount of waste produced. A DCS (Distributed Control System) is an integrated system which applies the decentralization concept to a control system handling both sequential and analog control. A DCS performs many operations such as data gathering, data processing, data storing and monitoring the operatin conditions for the operator. IN this paper, we propose a genetic algorithm based on rotation parameters from which the best pattern of layout is found as well as a layout method for better performance time. A DCS for the plate cutting process system, which is performed by a virtual system, is also identified.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.51
• /
• pp.139-149
• /
• 1999

Developed in this paper is a prototype extranet using mobile device such as Personal Digital Assistance(PDA) or Handheld PC(HPC). Especially an adjustment transaction system for auto insurance using wireless data communications is described. Using infrastructures such as PCS, Cellular, Private Radio, wireless communications offers tremendous applications in Korea. A survey of such applications is presented in this paper. Also an analysis of currently available infrastructures of wireless communications is described in this paper. The scheme of an adjustment transaction consists of seven steps: (1) get list of adjustment, (2) obtain insurance information, (3) check police record, (4) get an accident record, (5) get bluebook value, (6) examine the car, (7) file report. Comparing with the previous on-line method that spends much time on gathering data, the proposed system guarantees more rapid transaction using wireless communications.

• Korean Journal of Computational Design and Engineering
• /
• v.8 no.3
• /
• pp.133-140
• /
• 2003

This paper describes a Multi-step Digitizing Method and Reverse Model generation algorithm for improvement of reverse engineering accuracy. Reverse engineering is the process of reproducing computational model by directly extracting geometric information on the physical objects. For the improvement of measuring data accuracy, we propose a multi-step digitizing method. First, measuring cloud-of-point by use of a laser scanning system. Second, gathering digitizing data by a scanning touch probe. Fine digitizing plan generated from coarse surface model directly from the cloud-of-point and it allows CMM more accurate scanning data. Finally in this paper we propose the algorithm of generating NURB surface from more accurate measuring points.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.649-651
• /
• 2016

Wireless Sensor Network(WSN) consists of spatially distributed sensors to monitor physical conditions, such as temperature, light and motion, and to pass their data through the network to a base station. Each battery equipped node is consumed to pass their data to their neighbors. We are gathering the amount of energy that was consumed to gather data and to pass it This paper describes processes of energy consumption of WSN in Matlab.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2831-2833
• /
• 2000

Since the access to Station Control Computers(DCCs) is restricted to the main control room(MCR). the operating data of power plants can't be easily analyzed and effectively managed. It is possible to reduce waste of time and human energy by means of building the Remote Monitoring Network of DCCs connected to Local Area Network. automatizing collection and analysis of DCC data. gathering the operating state of power plants. and managing systematically. Furthermore. this system help preventing trip by means of analyzing the data promptly and watching main system continuously.

• Journal of the Semiconductor & Display Technology
• /
• v.7 no.1
• /
• pp.23-27
• /
• 2008

Wireless sensor networks are emerging as a solution for a wide range of data gathering applications. The most difficult challenge for the design of sensor nodes is the need for significant reductions in energy consumption. The threshold methods which filter redundant and similar data can be used to save energy. In this paper, we propose the adaptive threshold method to effectively manage the energy in wireless sensor nodes. In the adaptive threshold method, wireless sensor nodes can change the thresholds dynamically as the sensing environments vary. The simulation results show that the adaptive threshold method works very effectively even when we experience the significant volatility in the data. This scheme can be used in order to monitor the malfunction in the equipment of semiconductor manufacturing line.

• Journal of Community Nutrition
• /
• v.8 no.1
• /
• pp.16-23
• /
• 2006

This paper describes a methodology for conducting Community Nutrition research with rather than on people in a community to generate grounded theory. This collaborative grounded theory methodology incorporates local knowledge and wisdom and builds community leadership capacity through engaging community-based professionals and para-professionals in the research process. In addition to building capacity for participation and leadership in research, education and action, this approach can increase the validity and value of the research and facilitate its application in community led programs. The methodology has five components: background, study design, data gathering, data analysis and interpretation, and application of findings in community programming. Three stages of the data analysis component focus sequentially on each interview independently, comparing across interviews, and systematically testing theory developed in the first two.

• International conference on construction engineering and project management
• /
• 2011.02a
• /
• pp.556-560
• /
• 2011

Players of construction projects proceed with each work process by information gathering, modification and communication. Due to the complex and long-span lifecycle projects increased, it became more important to grasp this mechanism for the successful project performance in construction project. Hence, most project information management systems or knowledge management systems equip information retrieval system. There are two logic to infer the meaning of retrieval target; inductive reasoning and deductive reasoning. The former is based on metadata explaining the target and the later is based on relation between data. To infer the information flow, it is necessary to define the correlation between players and work processes. However, most established information retrieval systems are based on index search system and it is not focused on correlation between data but data itself. Thus, this research aims to research on process of information flow retrieval system for large-scale construction projects.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.11
• /
• pp.984-990
• /
• 2016

In wireless mesh sensor networks (WMSNs), sensor nodes are connected in the form of a mesh topology and transfer sensor data by multi-hop routing. A data aggregation method for WMSNs is required to minimize the number of routing hops and the energy consumption of each node with limited battery power. This paper presents a shortest path data aggregation method for WMSNs. The proposed method utilizes a simple hash function based on shuffled row major indexing for addressing sensor nodes. This allows sensor data to be aggregated without complex routing tables and calculation for deciding the next hop. The proposed data aggregation algorithms work in a fractal fashion with different mesh sizes. The method repeatedly performs gathering and moves sensor data to sink nodes in higher-level clusters. The proposed method was implemented and simulations were performed to confirm the accuracy of the proposed algorithms.

• Journal of the Korea society of information convergence
• /
• v.7 no.2
• /
• pp.49-57
• /
• 2014

Recently, opinion mining is introduced to extract useful information from SNS data and to evaluate the true intention of users. Opinion mining are required several efficient techniques to collect and analyze a large amount of SNS data and extract meaningful data from them. Therefore in this paper, we propose a parallel HDFS(Hadoop Distributed File System) and emotion functions based on Mapreduce to extract some emotional information of users from various unstructured big data on social networks. The experiment results have verified that the proposed system and functions perform faster than O(n) for data gathering time and loading time, and maintain stable load balancing for memory and CPU resources.