• 한국IT서비스학회지
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• 제1권1호
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• pp.119-139
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• 2002

It is noteworthy that IMT -2000 communication network based on All-HP/AIN(Advanced Intelligent Network) should accomodate current and future wire/wireless AIN service easily through integration and gearing AIN construction elements. In this paper. Intelligent Farmer model(I-Farmer Model) and methodology are suggested in order to solve the several problems including standardization on implementation of Q3 interface in Telecommunication Management Network(TMN) agents which is caused by heterogeneous platform environment and future maintenance. Also this paper proposes ITI algorithm transforming the system which is designed by I-Farmer model to Interface Specification Model(ISM) applying the I-Farmer model. In addition to ITI algorithm. we suggest NTS(Node to SIB) algorithm converting entity node and ILB/OLB component in agent system designed by the I-Farmer model to SIB of AIN GFP(Global Functional Plane) and to ASIB for application program.

• 한국IT서비스학회:학술대회논문집
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• 한국IT서비스학회 2002년도 추계학술대회
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• pp.444-450
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• 2002

실세계의 사물을 다중측면에 의하여 분석한 후 개체노드, 측면개체노드, 균일성 개체 및 다중화 추상화라는 여러 개념을 이용하여 디자인할 수 모델인 I-Farmer 모델의 구현 방안을 제시하였다. 컴포넌트는 컴포지션에 의한 소프트웨어 블록 재사용성을 제공하며 컴포넌트는 이들의 수행하는 기능에 대한 명세를 나타내는 인터페이스 명세 모델이 반드시 필요하게 된다. 본 논문에서는 I-Farmer 모델링 방법론에 의하여 디자인되어진 시스템을 컴포넌트 기반개발의 인터페이스 명세 모델로의 변형(transformation) 메카니즘인 ITI 알고리즘 및 CORBA / JAVA RMI COM IDL과의 상호관련성을 제시한다.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2000년도 추계학술발표논문집
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• pp.303-306
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• 2000

AIN CS-3를 기반으로 하는 IMT-2000 망은 지능망의 구성요소들과 통합 및 연동을 통하여 기존에 개발되었거나 앞으로 개발될 유선 지능망의 서비스들을 쉽게 수용할 수 있게 된다. 본 논문에서는 IMT-2000 및 IMT-2000과 연동되는 타 네트워크의 상이한 플랫폼 환경의 개발환경 및 향후 유지보수과정에서 발생할 것으로 예측되는 TMN 시스템 내 에이전트의 Q3 인터페이스 구현상의 표준을 이를 수 없다는 층의 문제점을 해결하기 위하여 I-Farmer 모델을 제안하였다.

• 한국멀티미디어학회:학술대회논문집
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• 한국멀티미디어학회 2001년도 추계학술발표논문집
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• pp.18-23
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• 2001

멀티미디어 통신 등 서비스 광대역화를 위하여 PSTN, PCN 및 B-lSDN 등과 같은 기존의 망과 연동되게 될 IMT-2000 통신망은 기존의 통신망들이 서로 다른 하드웨어와 운영체제 등 상이한 플랫폼 환경 하에서 개발되어 있는 관계로 망관리 시스템을 구축하는 과정에서 통합 및 유지보수 상의 여러 문제점이 대두되게 된다. 이와 같은 문제점을 해결하기 위하여 본 논문에서는 I-Farmer 모델(Intelligent-Farmer Model)에 기반한 ITS(ISM-Node to SIB) 알고리즘을 제안한다. ITS 알고리즘은 I-Farmer 모델로 설계한 에이전트 시스템 중 Entity Node 및 ILB / OLB 컴포넌트를 AIN의 GFP(Global Functional Plane)내의 SIB 및 시스템 응용프로그램 생성 컴포넌트인 지능망 ASIB로 변형(transformation)해주는 알고리즘이다.

• Asian-Australasian Journal of Animal Sciences
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• 제23권6호
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• pp.814-824
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• 2010

The objective of this research was to assess the effect of experience, education, record keeping, labor, and decision making on monthly milk yield per farm (MYF), monthly milk yield per cow (MYC), monthly milk revenue per farm (MRF), and monthly revenue per cow (MRC) of dairy farms supported by a private organization in Central Thailand. The dataset contained 34,082 monthly milk yield and revenue records collected from January 2004 to December 2008 on 497 farms, and information on individual farmer experience and education, record keeping, and decision making obtained with a questionnaire. Farmer experience categories were i) no experience, ii) one year, iii) two to five years, iv) six to ten years, v) eleven to fifteen years, vi) sixteen to twenty years, and vii) more than twenty years. Farmer education categories were i) no education or primary school, ii) high school, and iii) bachelor or higher degree. Record keeping categories were: i) no records and ii) kept records. Labor categories were: i) family, ii) hired people, and iii) family and hired people. Decision making categories were: i) decisions made by farmers themselves, ii) decisions made with help from government officials, and iii) decisions made with help from organization staff. The mixed linear model contained the fixed effects of year-season, farm location-farm size subclass, experience, education, record keeping, labor, and decision making on sire selection, and the random effects of farm and residual. Results showed that longer experience increased (p<0.05) monthly milk yield (MYF and MYC) and revenue (MRF and MRC). Farms that hired people produced the highest (p<0.05) monthly milk yield (MYF and MYC) and revenue (MRF and MRC), followed by farms that used family, and the lowest values were for farms that used both family and hired people. Better educated farmers produced more MYC and MRC (p<0.05) than lower educated farmers. Farms that kept records had higher MYF and MRF (p<0.05) than those without records. Although differences among farms were non-significant, farms that received help from the organization staff had higher monthly milk yield (MYF and MYC) and revenue (MRF and MRC) than those that decided by themselves or with help from government officials. These findings suggested that dairy farmers needed systematic training and continuous support to improve farm milk production and revenues in a sustainable manner.

• Journal of Biosystems Engineering
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• 제34권5호
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• pp.342-350
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• 2009

Currently TMR feed produced in commercial plant is one of the major source to feed cattle for both beef and dairy farm. However, because of lack of cutting and mixing system for utilizing domestic produced firmly baled round roughage in commercial TMR plant, these commercial TMR feed can not satisfy to farmers both in quality and price points of view. In order to solve these problems, a farm group size TMR plant model was developed in this study. The model plant was consist of round bale receiving and cutting system, pneumatic conveying system for transfer the roughage which was cut at the cutter to TMR mixer through pneumatic conveyor, TMR mixer enable to soften the stiff rice strew and to mix with other ingredients, finished feed bin which can be transfer to either packing system or individual farm, packing system by tycon bag which contains 400 kg unit and bulk unloading system to individual farmer. Also, a simulation model ARENA was applied to the model system in order to evaluate and check the production rate in each unit process and operation rate of total system and to find out if there are any clogged unit system obstructing the smooth flow of the total process flow. Processing cycle for produce one batch of the model plant was less than 30 minutes. Thus, it will take less than four hours for producing 16 tons per day equivalent to 1,000 beef cattle's daily feed.

• 한국환경교육학회지:환경교육
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• 제20권2호
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• pp.93-107
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• 2007

Livestock agriculture plays an essential role Hongsung's economy. Unfortunately, if manure is manage properly it can contaminate water and pollute the air. The purposes of this study were to provide awareness of environmental impact and to design educational programs with sustainable agriculture. I used the specific steps of processes. First, collecting informations through survey on environmental awareness of livestock farmers in Hongsung-gun and recognizing the tendencies. Second, analyzing on educational status of livestock farmers. Third, finding objectives of environmental educational programs. At the end of processes, establishing programs which concerning on environmental education. I used two research methods to gather and analyze the data for developing an environmental education program. The first one is a general survey among 50 livestock farmers from Hongseong-gun, Chungcheongnam-do. The second one is the in-depth interviews with specialists in environmental education and government officials from the central government - the Ministry of Agriculture and Forestry - and the local government - Hongsung-gun who are in charge of livestock farming. I found the following results from this research. First, most livestock farmers replied with 'highly likely' to the five items on the recognition of the necessity of environment preservation, whereas only 38.7% answered with 'likely' to the item on the environmental pollution caused by livestock farming. This shows the tendency that they have less recognition of the reality than necessary. Second, most of the contents among 5 areas(knowledge, recognition, function, attitude, and participation) are the knowledge areas. That results are analyzed training materials for livestock farmers made by Hongsung-gun in 2004 and in 2005 by using goal categories suggested in the Tbilisi Resolution. Third, after analyzing the survey and in-depth interviews, I found that the need for education to recognize the environmental pollution, environmental protection and recycling of the livestock waste. We can summarize conclusions from this research. First, we need on educational program improve the livestock farmers' recognition of importance in environmental protection. Second, it is necessary to develop educational program with the viewpoint that livestock waste is not one of the culprits of the environmental pollution, but a recyclable resource. Third, contents of the environmental education program, should include all the educational elements, namely, knowledge, recognition, attitude, function and participation. The education for livestock farmers requires a research on the environmental education program that can be used with crop farmers who can use the resources recycled from the livestock waste from the viewpoint of recycling resources. This research is focused on the collection and analysis of the basic data for developing an environmental education program and the composition of the program. A further research on the implementation and assessment of this program is required.

• Asian-Australasian Journal of Animal Sciences
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• 제24권8호
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• pp.1031-1040
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• 2011

The objective of this study was to characterize factors influencing genetic improvement of dairy cattle for milk production at farm level. Data were accumulated from 305-day milk yields and pedigree information from 1,921 first-lactation dairy cows that calved from 1990 to 2007 on 161 farms in Central Thailand. Variance components were estimated using average information restricted maximum likelihood procedures. Animal breeding values were predicted by an animal model that contained herd-year-season, calving age, and regression additive genetic group as fixed effects, and cow and residual as random effects. Estimated breeding values from cows that calved in a particular month were used to estimate genetic trends for each individual farm. Within-farm genetic trends (b, regression coefficient of farm milk production per month) were used to classify farms into 3 groups: i) farms with negative genetic trend (b<-0.5 kg/mo), ii) farms with no genetic trend (-0.5 kg/$mo{\leq}b{\leq}0.5$ kg/mo), and iii) farms with positive genetic trend (b>0.5 kg/mo). Questionnaires were used to gather information from individual farmers on educational background, herd characteristics, farm management, decision making practices, and opinion on dairy farming. Farmer's responses to the questionnaire were used to test the association between these factors and farm groups using Fisher's exact test. Estimated genetic trend for the complete population was $0.29{\pm}1.02$ kg/year for cows. At farm level, most farms (40%) had positive genetic trend ($0.63{\pm}4.67$ to $230.79{\pm}166.63$ kg/mo) followed by farms with negative genetic trend (35%; $-173.68{\pm}39.63$ to $-0.62{\pm}2.57$ kg/mo) and those with no genetic trend (25%; $-0.52{\pm}3.52$ to $0.55{\pm}2.68$ kg/mo). Except for educational background (p<0.05), all other factors were not significantly associated with farm group.

• Agribusiness and Information Management
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• 제8권1호
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• pp.17-26
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• 2016

India is largest producer of banana in the world producing 29.72 million tonnes from an area of 0.803 million ha with a productivity of 35.7 MT ha-1 and accounted for 15.48 and 27.01 per cent of the world's area and production respectively (www.nhb.gov.in). In India, Tamil Nadu leads other states both in terms of area and production followed by Maharashtra, Gujarat and Andhra Pradesh. In Rayalaseema region of Andhra Pradesh, Kurnool district had special reputation in the cultivation of banana in an area of 5765 hectares with an annual production of 2.01 lakh tonnes in the year 2012-13 and hence, it was purposively chosen for the study. On $23^{rd}$ November 2003, the Government of Andhra Pradesh has commenced a comprehensive project called 'Andhra Pradesh Micro Irrigation Project (APMIP)', first of its kind in the world so as to promote water use efficiency. APMIP is offering 100 per cent of subsidy in case of SC, ST and 90 per cent in case of other categories of farmers up to 5.0 acres of land. In case of acreage between 5-10 acres, 70 per cent subsidy and acreage above 10, 50 per cent of subsidy is given to the farmer beneficiaries. The sampling frame consists of Kurnool district, two mandals, four villages and 180 sample farmers comprising of 60 farmers each from Marginal (<1ha), Small (1-2ha) and Other (>2ha) categories. A well structured pre-tested schedule was employed to collect the requisite information pertaining to the performance of drip irrigation among the sample farmers and Data Envelopment Analysis (DEA) model was employed to analyze the performance of drip irrigation in banana farms. The performance of drip irrigation was assessed based on the parameters like: Land Development Works (LDW), Fertigation costs (FC), Volume of water supplied (VWS), Annual maintenance costs of drip irrigation (AMC), Economic Status of the farmer (ES), Crop Productivity (CP) etc. The first four parameters are considered as inputs and last two as outputs for DEA modelling purposes. The findings revealed that, the number of farms operating at CRS are more in number in other farms (46.66%) followed by marginal (45%) and small farms (28.33%). Similarly, regarding the number of farmers operating at VRS, the other farms are again more in number with 61.66 per cent followed by marginal (53.33%) and small farms (35%). With reference to scale efficiency, marginal farms dominate the scenario with 57 per cent followed by others (55%) and small farms (50%). At pooled level, 26.11 per cent of the farms are being operated at CRS with an average technical efficiency score of 0.6138 i.e., 47 out of 180 farms. Nearly 40 per cent of the farmers at pooled level are being operated at VRS with an average technical efficiency score of 0.7241. As regards to scale efficiency, nearly 52 per cent of the farmers (94 out of 180 farmers) at pooled level, either performed at the optimum scale or were close to the optimum scale (farms having scale efficiency values equal to or more than 0.90). Majority of the farms (39.44%) are operating at IRS and only 29 per cent of the farmers are operating at DRS. This signifies that, more resources should be provided to these farms operating at IRS and the same should be decreased towards the farms operating at DRS. Nearly 32 per cent of the farms are operating at CRS indicating efficient utilization of resources. Log linear regression model was used to analyze the major determinants of input use efficiency in banana farms. The input variables considered under DEA model were again considered as influential factors for the CRS obtained for the three categories of farmers. Volume of water supplied ($X_1$) and fertigation cost ($X_2$) are the major determinants of banana farms across all the farmer categories and even at pooled level. In view of their positive influence on the CRS, it is essential to strengthen modern irrigation infrastructure like drip irrigation and offer more fertilizer subsidies to the farmer to enhance the crop production on cost-effective basis in Kurnool district of Andhra Pradesh, India. This study further suggests that, the present era of Information Technology will help the irrigation management in the context of generating new techniques, extension, adoption and information. It will also guide the farmers in irrigation scheduling and quantifying the irrigation water requirements in accordance with the water availability in a particular season. So, it is high time for the Government of India to pay adequate attention towards the applications of 'Information and Communication Technology (ICT) and its applications in irrigation water management' for facilitating the deployment of Decision Supports Systems (DSSs) at various levels of planning and management of water resources in the country.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.257-261
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• 2022

Diseases of agricultural plants in recent years have spread greatly across the regions of the Kyrgyz Republic and pose a serious threat to the yield of many crops. The consequences of it can greatly affect the food security for an entire country. Due to force majeure, abnormal cases in climatic conditions, the annual incomes of many farmers and agricultural producers can be destroyed locally. Along with this, the rapid detection of plant diseases also remains difficult in many parts of the regions due to the lack of necessary infrastructure. In this case, it is possible to pave the way for the diagnosis of diseases with the help of the latest achievements due to the possibilities of feedback from the farmer - developer in the formation and updating of the database of sick and healthy plants with the help of advances in computer vision, developing on the basis of machine and deep learning. Currently, model training is increasingly used already on publicly available datasets, i.e. it has become popular to build new models already on trained models. The latter is called as transfer training and is developing very quickly. Using a publicly available data set from PlantVillage, which consists of 54,306 or NewPlantVillage with a data volumed with 87,356 images of sick and healthy plant leaves collected under controlled conditions, it is possible to build a deep convolutional neural network to identify 14 types of crops and 26 diseases. At the same time, the trained model can achieve an accuracy of more than 99% on a specially selected test set.