• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.63-83
• /
• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Journal of Information Management
• /
• v.9 no.1
• /
• pp.21-25
• /
• 1976

1975년(年) 3월(月), 4년반(年半) 동안의 Chemical Abstracts 색인(索引)과 온-라인이 가능(可能)한 CA Condensates를 비교(比較)하였다. 두가지 데이터 베이스를 함께 이용(利用)하여 검색(檢索)하는 방법(方法)이 가장 효율적(效率的)이지만 실예(實例)에서 보는 바와 같이 CA Condensates를 검색(檢索)하는 것이 보다 실용적(實用的)이다. System Development Corp 사(社) (SDC)에 설치(設置)되어 있는 온-라인 형태(形態)인 CHEMCON과 CHEM7071을 Chemical Abstracts 색인(索引)과 비교(比較)하였다. 대부분(大部分)의 Chemical Abstracts 이용자(理容者)들은 Chemical Abstracts 책자나 우가색인(累加索引)에는 친숙(親熟)하지만 CA Condensates는 아마도 그리 친숙(親熟)하지 못할 것이다. CA Condensates는 서지적 사항을 기계(機械)로 읽을 수 있는 형태(形態)로 되어 있고 Chemical Abstracts에 따라서 색인(索引)되므로 매주 발행되는 Chemical Abstracts 책자의 뒷 부분이 있는 색인(索引)과 같이 우리에게 가장 친숙(親熟)한 형태(形態)로 되어 있다. Chemical Abstracts가 현재(現在) 사용(使用)하고 있는 데이터 데이스이지만 본고(本稿)에서는 Index와 Condensates를 둘 다 데이터 베이스로 정의(定義)한다. Condensates가 미국(美國)의 Chemical Abstracts Service 기관으로부터 상업적(商業的)으로 이용(利用)할 수 있게 되자 여러 정보(情報)센터에서는 이용자(利用者)들의 프로 파일을 뱃취방식(方式)으로 처리(處理)하여 매주 나오는 자기(磁氣)테이프에서 최신정보(最新情報)를 검색(檢索)하여 제공(提供)하는 서어비스 (SDI)를 시작하였다. 어떤 정보(情報)센터들은 지나간 자기(磁氣)테이프들을 모아서 역시 뱃취방식(方式)으로 소급(遡及) 문헌검색(文獻檢索) 서어비스를 한다. 자기(磁氣)테이프를 직접 취급(取扱)하는 사람들을 제외(除外)하고는 대부분(大部分) Condensates를 아직 잘 모르고 있다. 소급(遡及) 문헌검색(文獻檢索)은 비용이 다소 비싸고 두서없이 이것 저것 문헌(文獻)을 검색(檢索)하는 방법(方法)은 실용적(實用的)이 못된다. 매주 나오는 색인(索引)에 대해서 두 개나 그 이상의 개념(槪念)이나 물질(物質)을 조합(組合)하여 검색(檢索)하는 방법(方法)은 어렵고 실용적(實用的)이 못된다. 오히려 주어진 용어(用語) 아래에 있는 모든 인용어(引用語)들을 보고 초록(抄錄)과의 관련성(關連性)을 결정(決定)하는 것이 때때로 더 쉽다. 상호(相互) 작용(作用)하는 온-라인 검색(檢索)을 위한 Condensates의 유용성(有用性)은 많은 변화를 가져 왔다. 필요(必要)한 문헌(文獻)만을 검색(檢索)해 보는 것이 이제 가능(可能)하고 어떤 항목(項目)에 대해서도 완전(完全)히 색인(索引)할 수 있게 되었다. 뱃취 시스팀으로는 검색(檢索)을 시작해서 그 결과(結果)를 받아 볼 때 까지 수시간(數時間)에서 며칠까지 걸리는 번거로운 시간차(時間差)를 이제는 보통 단 몇 분으로 줄일 수 있다. 그리고 뱃취 시스팀과는 달리 부정확하거나 불충분한 검색방법(檢索方法)은 즉시 고칠 수가 있다. 연속적인 뱃취 형태의 검색방법(檢索方法)에 비해서 순서(順序)없이 온-라인으로 검색(檢索)하는 방법(方法)이 분명(分明)하고 정확(正確)한 장점(長點)이 있다. CA Condensates를 자주 이용(移用)하게 되자 그의 진정한 가치(價値)에, 대해 논의(論義)가 있었다. CA Condensates의 색인방법(索引方法)은 CA Abstract 책자나 우가색인(累加索引)의 방법(方法)보다 확실히 덜 체계적(體系的)이고 철저(徹底)하지 못하다. 더우기 두 데이터 베이스는 중복(重複)것이 많으므로, 중복(重複)해서 검색(檢索)할 가치(價値)가 없는지를 결정(決定)해야 한다. 다른 몇 개의 데이터 베이스와 CA Condensates를 비교(比較)한 논문(論文)들이 여러 번 발표(發表)되어 왔는데 일반적(一般的)으로 CA Condensates는 하위(下位)의 데이터 베이스로 나타났다. Buckley는 Chemical Abstracts의 색인(索引)이 CA Condensates 보다 더 좋은 문헌 (데라마이신의 제법에 관해서)을 제공(提供)한 실례(實例)를 인용(引用)하였다. 죠오지대학(大學)의 Search Center는 CA Condensates가 CA Integrated Subject File 보다 기능(機能)이 못하다는 것을 알았다. CA Condensates의 다른 여러 가지 형태(形態)들을 또한 비교(比較)하였다. Michaels은 CA Condensates를 온-라인으로 검색(檢索)한 것과 매주 나오는 Chemical Abstracts 책자의 색인(索引)은 수작업(手作業)으로 검색(檢索)한 것을 비교(比較)한 논문(論文)을 발표(發表)하였다. 그리고 Prewitt는 온-라인으로 축적(蓄積)한 두 개의 상업용(商業用) CA Condensates를 비교(比較)하였다. Amoco Research Center에서도 CA Condensates와 Chemical Abstracts 색인(索引)의 검색결과(檢索結果)를 비교(比較)하고 CA Condensates의 장점(長點)과 색인(索引)의 장점(長點), 그리고 사실상(事實上) 서로 동등(同等)하다는 실례(實例)를 발견(發見)하였다. 1975년(年) 3월(月), 적어도 4년분(年分)의 CA Condensates와 색인(索引)(Vols 72-79, 1970-1973)을 비교(比較)하였다. 저자(著者)와 일반(一般) 주제(主題) 대한 검색(檢索)은 Vol 80 (Jan-June, 1974)을 사용(使用)하여 비교(比較)하였다. CA Condensates는 보통 세분화(細分化)된 복합물(複合物)을 검색(檢索)하는 데 불편(不便)하다. Buckly가 제시(提示)한 실례(實例)가 그 대표적(代表的)인 예(例)이다. 그러나, 다른 형태(形態)의 검색실예(檢索實例)(단체저자(團?著者), 특허수탁저(特許受託著), 개인저자(個人著者), 일반적(一般的)인/세분화(細分化)된 화합물(化合物) 그리고 반응종류(反應種類)로 실제적(實際的)인 검색(檢索)을 위한 CA Condensates의 이점(利點)을 예시(例示)하였다. 다음 실례(實例)에서 CHEMCON과 CHEM7071은 CA Condensates를 온-라인으로 입력(入力)시킨 것이다.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.187-204
• /
• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Horticultural Science & Technology
• /
• v.33 no.6
• /
• pp.883-890
• /
• 2015

The soilborne fungus Fusarium oxysporum f. sp. lilii (Fol) is a serious threat to all lily cultivars, especially infecting bulbs and flowers. It has become increasingly important to develop varieties resistant against the bulb rot disease. Genetic diversity of cultivars and reliable screening methods are required for this purpose. Here, an efficient in vitro screening system for evaluating resistance to Fol in 38 in vitro-grown lily plants was investigated. Various factors including culture conditions of Fol, inoculum density, appropriate plant materials, inoculation method and duration, and incubation period of plant materials after inoculation were combined to optimize the screening method. As a result, we suggest optimal conditions for an in vitro screening system for the selection of Fol-resistant lily cultivars as follows. Fol was grown on potato dextrose agar (PDA) medium for 6 days at $25^{\circ}C$ in darkness and used as working inoculation. Spore suspensions were prepared (inoculum density: $1.0{\times}10^4$ $spores{\cdot}mL^{-1}$), and then leaf segments $1.5{\times}2.0cm^2$ were inoculated by dipping for 22 hours at $25^{\circ}C$ in dark. Later, leaves were cultured on 0.6% agar plates at $25^{\circ}C$ and 50% humidity with a photoperiod of 16 hours light/8 hours dark (fluence rate of $40{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$) to examine the progress of bulb rot. After 7 days, disease levels were classified into indices 1 (no symptom) to 6 (serious bulb rot). Soil inoculation of Fol carried out with resistant or susceptible lily cultivars that had been selected through in vitro screening confirmed the reproducibility of results. Therefore, the in vitro screening method established in this study is efficient and reliable for selection of lily cultivars resistant against bulb rot disease.

• Journal of Intelligence and Information Systems
• /
• v.16 no.3
• /
• pp.181-199
• /
• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.4
• /
• pp.175-190
• /
• 2018

Recently, policy of the marine advanced countries were switched from the preemption using ocean to post-project development. In this study, we suggest improvement and the pending issues when are deducted to the database of the marine spatial information is constructed over the GIS system for the Korean Marine Spatial Planning (KMSP). More than 250 spatial information in the seas of Korea were processed in order of data collection, GIS transformation, data analysis and processing, data grouping, and space mapping. It's process had some problem occurred to error of coordinate system, digitizing process for lack of the spatial information, performed by overlapping for the original marine spatial information, and so on. Moreover, solution is needed to data processing methods excluding personal information which is necessary when produce the spatial data for analysis of the used marine status and minimized method for different between the spatial information based GIS system and the based real information. Therefore, collection and securing system of lacking marine spatial information is enhanced for marine spatial planning. it is necessary to link and expand marine fisheries survey system. It is needed to the marine spatial planning. The marine spatial planning is required to the evaluation index of marine spatial and detailed marine spatial map. In addition, Marine spatial planning is needed to standard guideline and system of quality management. This standard guideline generate to phase for production, processing, analysis, and utilization. Also, the quality management system improve for the information quality of marine spatial information. Finally, we suggest necessity need for the depths study which is considered as opening extension of the marine spatial information and deduction on application model.

• Journal of Bio-Environment Control
• /
• v.31 no.4
• /
• pp.384-392
• /
• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Journal of Intelligence and Information Systems
• /
• v.20 no.1
• /
• pp.149-161
• /
• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.

• Korean Journal of Agricultural Science
• /
• v.7 no.2
• /
• pp.87-102
• /
• 1980

In order to investigate the utilization probability of two years old laying hen for W.L. and R.I.R. breeds, carcass weight and percentage were examined and dried old chicken meat products were manufactured for experiments. The results obtained are as follows. 1. Average living body weight were 1,635.40g for the W.L. breeds and 2,289.29g for the R.I.R. breeds and percentage carcass and lean meat for the W.L. were 58.73% and 43.95%, for the R.I.R. 60.34%, 41.98%, respectively. 2. In constitution percentage of carcass on different parts for W.L. and R.I.R. breeds, head were 4.13% and 3.94%, wing 9.97% and 8.62%, breast 32.54% and 20.94%, back 11.35% and 9.75%, thigh 30.75% and 31.34%, hypordermic fat 11.37% and 17.34%, respectively. 3. In constitution percentage of lean meat on different parts for W.L. and R.I.R. breeds, head were 4.03% and 3.95%, wing 9.47% and 9.79%, breast 39.37% and 38.14%, back 11.24% and 9.40%, thigh 36.16% and 38.74%, respectively. 4. In chemical composition of old chicken meat for W.L. breed, moisture was 68.18%, crude protein 22.80%, crude fat 2.70%, extract 5.15% and crude ash 1.18% and for R.I.R. breed, moisture was 68.04%, crude protein 22.18%, crude fat 3.13%, extract 5.45% and crude ash 1.21%. 5. Weight loss in steaming for W.L. at $121^{\circ}C$ for 30min., 60min., and 90min. were 54.91, 56.43 and 58.42%, respectively, and for R.I.R. were 45.23, 47.68 and 49.68%, respectively. 6. The yield of old chicken meat product per a hen were 253.01g for W.L. and 368.64g for R.I.R., the ratio for fresh meat weight and for carcass weight were 35.47% and 26.34% for W.L. breed and 38.25 and 26.83% for R.I.R. breed. 7. In chemical composition of old chicken meat product for W.L., moisture was 16.69%, crude protein 66.16%, crude fat 12.81%, crude ash 4.35%, and R.I.R., moisture 16.11%, crude protein 65.95%, crude fat 13.78% and crude ash 4.57%. 8. To investigate the physical properties which was main factor affecting the product quality, tensile strength, tear strength and elongation rate were measured. The adhesive force of the product made under pressure of $70kg/cm^2$ was similar to those of chipo which was the control product. 9. When measured the color of each protein product, lightness of the product pressed at $70kg/cm^2$ was better than that at $35kg/cm^2$, and the lightness of breast muscle product at $70kg/cm^2$ and chipo was not significant as 16.7% and 16.4%, respectively. Dominant wavelength of product pressed at $70kg/cm^2$ was very similar to chipo which was yellowish orange. 10. In the results of sensory evaluation test containing taste, color, chewing texture and oder of the meat product, when index of chipo as control product was 100, index of breast meat product was higher than that as 118.4, but miscellaneous product was 99.7 and thigh product was 96.2. 11. Summing up the results written above, the meat product utilizing two years old laying hen was compared favorably with its similar food such as chipo on the point of nutrition and physical properties as high protein food, therefore, it was thought that industrialization must be highly appropriate.