• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.470-472
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• 2006

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as environment and health, industry scene system monitoring, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modem learning techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes having the capability of simple processing and wireless communication. The proposed system is able to perform context classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to intelligent dust collecting system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.97-99
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• 2011

스마트폰에 대한 관심이 높아지면서 스마트폰 사용자가 증가하고 있다. 스마트폰 중에서도 안드로이드 스마트폰의 증가세가 가장 두드러지며 현재 국내 스마트폰 시장에서 가장 많은 점유율을 차지하고 있다. 스마트폰은 전화기능 외에도 다양한 기능을 가지고 있고 다양한 애플리케이션을 실행할 수 있으며 이러한 특징은 사용자들로 하여금 많은 일을 스마트폰으로 처리하게 하였으며 많은 데이터들이 스마트폰에 저장되게 되었다. 본 논문에서는 이러한 데이터들을 수집하는 방법을 제안한다. 이러한 수집방법은 모바일 포렌식 분야에도 도움이 될 수 있으며 복잡해지는 정보들을 사용자가 관리하기 편하게 하는데도 도움이 될 수 있다. 본 논문에서는 논리적인 정보획득 방법에 기반을 두어 안드로이드 프레임워크의 컴포넌트중 하나인 컨텐트 프로바이더를 통해서 안드로이드 스마트폰의 기본 애플리케이션이 제공하는 정보들을 수집하는 방법으로 정보를 수집한다.

• Agricultural and Biosystems Engineering
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• v.6 no.2
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• pp.54-58
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• 2005

In this study, tele-robotics was researched to actualize robots in agriculture. The robot system consisted of a data collecting robot, several robots that performed their own agricultural operations, a server, client computers and networks between robots and computers. In this paper, as a first step, harvesting experiments were carried out. From the results, it was observed that the tele-robotics had feasibility to propel the robotization in agriculture. The tele-robotics has advantages not only that human workers are released from the severe working environment but also that the greenhouse can be monitored and controlled anytime and anywhere.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.528-533
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• 2010

This research is part of the development of Data Acquisition embedded system that specifically use in ship. The purpose of this data acquisition system mainly is to acquire data from multiple sensors or others related external devices and it will further discuss in this paper. The data collecting, hardware design, software design and the final project outcome of this data acquisition system will be discussed in this paper.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.43-55
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• 2020

Recently, as the importance of experience data increases, there are many attempts to deal with experience data from a data science perspective. In the case of approaching as a collection method of a quantitative survey method that seeks to quantify numerically such as big data, it is difficult to interpret the value of experience in a wide range, and it is relatively expensive and time consuming, and personal information infringement There is a limit to the analysis due to the risk of However, since ethnography, a procedure for collecting experience data based on qualitative research, is mainly carried out in the natural real environment of future customers from the perspective of users, it is possible to confirm the nature that customers face with a small sample. In addition, it is also easy to interpret the relational dimension of the empirical data. Although the ethnography method of collecting experiential data is economical and efficient, it is important to reduce errors in the collection process because the lack of scientific procedures for the data collection process can be a problem. It is important to secure the validity of whether the correct measurement tool is used for ethnography-based experiential data collection and to secure the reliability of the use of a valid measurement tool and method by accurately selecting the measurement target. From this point of view, it is necessary to verify the reliability of the research method that clearly selects the measurement target and secures the validity for the development of the correct measurement method and tool for the collection of ethnography experience data. Therefore, in this study, a verification study was conducted on the data and methodology cases of the'I know you_AI' service that analyzes the customer experience of self-employed based on the ethnography method of collecting experience data..

• Journal of Sasang Constitutional Medicine
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• v.28 no.1
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• pp.57-66
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• 2016

Objectives The purpose of this study is to report on the collecting status of the prospective clinical data, that is designed to find clinical factors for determining the constitutional prescription.Methods We collected the prospective clinical data of 1208 subjects in the 10 oriental hospitals and 2 oriental clinic, from September 2012 to July 2015. Subjects were diagnosed and prescribed by the Sasang Constitution specialist. We counted the usage frequency of each constitutional herbal formula. Besides we check the main chief complaints on each constitutional herbal formula.Results & Conclusions In TE type, Yeoldahanso-tang, Cheongsimnyeonja-tang were used in high frequency. In SE type, Palmulgunja-tang, Gwakhyangjunggi-san were used in high frequency. In SY type, Hyeongbangjihwang-tang, Yanggyeoksanhwa-tang were used in high frequency. The both of high frequency-prescriptions in TE types were for the Interiorheat disease, expecially liver-heat lung-dry symptomatology. The main chief complaint of high frequency-prescriptions was fatigue in every constitution. We hope that the process of constitutional prescription would be standardized through the subsequent researches.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.78-83
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• 2007

Robot collects surrounding information to recognize tile unknown environment by using various sensors such as visual, infrared ray and ultra sonic sensors. Although visual sensor is the most popular one, it has some difficulties in collecting data in dark or too bright environment due to sensitivity of the light. It also requests significant amount of calculation on collecting data from certain images with marked, straight and curved ones. As an alternative, ultra sonic sensor can simply overcome this visual sensing system's flaw and easily be used. It is easier than visual system, especially in case of collecting data on object and distance in dark environment. Ultra sonic sensor can replace the expensive visual sensing system not only in avoiding obstacles but also in reaching to the target area smoothly. The purpose of this paper is to develop the algorithm to optimize the environmental recognition, path planning and free-ranging by minimizing errors caused by inaccurate information and by considering characteristics of the ultra sonic rays such as refraction and diffusion. This paper also realizes the system that can recognize the environment and make the appropriate path planning by applying the algorithm on this moving robot.

• The Journal of Bigdata
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• v.4 no.2
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• pp.93-103
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• 2019

In this paper, we introduce a big data platform and a metadata management technique for fishery science R & D information. The big data platform collects and integrates various types of fisheries science R & D information and suggests how to build it in the form of a data lake. In addition to existing data collected and accumulated in the field of fisheries science, we also propose to build a big data platform that supports diverse analysis by collecting unstructured big data such as satellite image data, research reports, and research data. Next, by collecting and managing metadata during data extraction, preprocessing and storage, systematic management of fisheries science big data is possible. By establishing metadata in a standard form along with the construction of a big data platform, it is meaningful to suggest a systematic and continuous big data management method throughout the data lifecycle such as data collection, storage, utilization and distribution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.13-19
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• 2019

The accuracy of machine learning is greatly affected by amount of learning data and quality of data. Collecting existing Web-based learning data has danger that data unrelated to actual learning can be collected, and it is impossible to secure data transparency. In this paper, we propose a method for collecting data directly in parallel by blocks in a block - chain structure, and comparing the data collected by each block with data in other blocks to select only good data. In the proposed system, each block shares data with each other through a chain of blocks, utilizes the All-reduce structure of Parallel-SGD to select only good quality data through comparison with other block data to construct a learning data set. Also, in order to verify the performance of the proposed architecture, we verify that the original image is only good data among the modulated images using the existing benchmark data set.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.111-119
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• 2024

In this paper, we propose a big data platform that can collect information from various sources collected at ocean. Currently operating ocean-related big data platforms are focused on storing and sharing created data, and each data provider is responsible for data collection and preprocessing. There are high costs and inefficiencies in collecting and integrating data in a marine environment using communication networks that are poor compared to those on land, making it difficult to implement related infrastructure. In particular, in fields that require real-time data collection and analysis, such as weather information, radar and sensor data, a number of issues must be considered compared to land-based systems, such as data security, characteristics of organizations and ships, and data collection costs, in addition to communication network issues. First, this paper defines these problems and presents solutions. In order to design a big data platform that reflects this, we first propose a data source, hierarchical MEC, and data flow structure, and then present an overall platform structure that integrates them all.