• Journal of environmental and Sanitary engineering
• /
• v.17 no.4
• /
• pp.39-46
• /
• 2002

The purpose of this research was to get an alternative idea about the situation and problems of domestic pest control company We performed a questionnaire survey of 105 companies to find the situation and problems of pest control companies with and with out lincensed sanitarians. The investigation revealed the following issues and the conclusions summarized. 1. Companies with lincensed sanitarians have shown to put forth hygenic safety(62%) as first priority as to companies without sanitarians neglect hygenic safety and rank financial benefit(40%) as their priority. 2. Companies with lincensed sanitarians have directions on its use of pesticides but the companies without inspectors rely only on field experiences. 3. Companies with lincensed sanitarians are known to use the safety equipment. To the contrary, companies without sanitarians worked without the proper safety equipment safety gear. 4. Companies with sanitarians been regularly received educational Programs on chemicals used in the pest control. And then companies without did not have my other educational programs for chemicals they used.

• Korean journal of applied entomology
• /
• v.32 no.4
• /
• pp.373-381
• /
• 1993

Resistance evolution to organophosphate-based pesticides in apple and pear inhabiting arthropods of western North America extends to many classes of pest and some beneficial species. Resistance management programs to minimize resistance in pests while exploiting it in natural enemies have met with mixed success. Among beneficials, resistances have been exploited mostly among predators of pest mites. Evolution of resistant mites, leafminers, leafhopper, aphids, leafrollers and some internal fruit feeders have led to development of new monitoring methods and means to delay or avoid resistance. But it is resistance to azinphosmethyl in codling moth (Cydia pomonella) that is changing the pest control system and moving it from chemical to biologically-based means. Newly merging IPM system will depend more on use of biological, cultural, behavior and genetic controls. But more selective pesticides also will be needed to augment pheromones, resistant host plants and genetically altered organisms. These more biologically-based tactics will be prone to resistance evolution in pests as well, if used too unilaterally and/or too extensively.

• Korean journal of applied entomology
• /
• v.21 no.3 s.52
• /
• pp.142-145
• /
• 1982

A computer mapping system MAPSYS for data management in pest management research was developed and evaluated The computer mapping program could be used in rapididly summarizing the data from pest population management and forecasting research as well as in studying the distribution of crops, relative pest species, and the other environmental factors.

• Journal of the Korean Mathematical Society
• /
• v.44 no.2
• /
• pp.327-342
• /
• 2007

In this paper, a kind of pest-predator model with impulsive effect and infinite delay is considered by the method of chain transform. By using Floquet's theorem, it is shown that there exists a globally asymptotically stable periodic pest eradication solution when the impulsive period is less than or equal to some critical value which is a directly proportional function with respect to the population of release. Furthermore, it is proved that the system is permanent if the impulsive period is larger than some critical value. Finally, the results of the corresponding systems are compared, those results obtained in this paper are confirmed by numerical simulation.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.2
• /
• pp.133-143
• /
• 2023

In this study, we propose a big data set of strawberry pests collected directly for diagnosis model learning and an automatic pest diagnosis model architecture based on deep learning. First, a big data set related to strawberry pests, which did not exist anywhere before, was directly collected from the web. A total of more than 12,000 image data was directly collected and classified, and this data was used to train a deep learning model. Second, the deep-learning-based automatic pest diagnosis module is a module that classifies what kind of pest or disease corresponds to when a user inputs a desired picture. In particular, we propose a model architecture that can optimally classify pests based on a convolutional neural network among deep learning models. Through this, farmers can easily identify diseases and pests without professional knowledge, and can respond quickly accordingly.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.25 no.2
• /
• pp.163-169
• /
• 2012

A decrease in pass ratio of Korean exporting pears causes several negative effects including an increase in pesticide dependency. In this study, we attempted to establish the pest forecasting management system, composed of weekly field forecasting by pear farmers, meteorological data obtained by automatic weather station (AWS), newly designed internet web page ($\underline{http://pearpest.jnu.ac.kr/}$) as information collecting and providing ground, and information providing service. The weekly field forecasting information on major pear diseases and pests was collected from the forecasting team composed of five team leaders from each pear exporting complex. Further, an abridged weather information for the prediction of an infestation of major disease (pear scab) and pest (pear psylla and scale species) was obtained from an AWS installed at Bonghwang in Naju City. Such information was then promptly uploaded on the web page and also publicized to the pear famers specializing in export. We hope this pest forecasting management system increases the pass ratio of Korean exporting pears throughout establishment of famer-oriented forecasting, inspiring famers' effort for the prevention and forecasting of diseases and pests occurring at pear orchards.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.39 no.2
• /
• pp.11-18
• /
• 2016

Product liability (PL), which began enforcement in 2002, refers to the legal responsibility of the manufacturers or sellers (wholesales or retailers) for the property damage or bodily harm caused by their product. With a strong enforcement of the Product Liability (PL) Act, companies are required to structure and operate a response system to defend or prevent product accidents efficiently, but small and medium enterprises (SMEs) are unable to respond more aggressively due to limitation of management resources. In this manner, it is important to develop response strategies for SMEs to efficiently cope with the PL Act. In this paper, the PEST (Political, Economic, Social, and Technological) analysis is performed to reveal the impact of the PL Act on SMEs in macro-economic point of view. To formulate SME's PL response strategy, SWOT analysis is performed to categorize each factors from PEST analysis and AHP is applied to identify the intensities of SWOT factors. The prioritized SWOT factor, results of PEST-SWOT-AHP analysis, are used to formulate SME's PL response strategies. The study results are briefly summarized as follows. To reduce product defects, it is necessary for SMEs to formulate PL response strategies for each phase of the product life cycle by continuously collecting and analyzing PL cases in the same industry or for similar products. In addition, SMEs should invest more technological effort to ensure product safety. Further, SMEs should spread PL awareness to all staff members by training internal PL experts. Moreover, a SME should enroll in PL insurance and spread this information to its customers so that they become aware that the company is proactively conforming to the PL law.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.186-186
• /
• 2018

본 연구에서는 매개변수 자동 보정기법인 PEST(Model-Independent Parameter Estimation and Uncertainty Analysis)를 CAT 모형에 연계하여 유출특성 분석을 실시하였다. CAT-PEST 연계모형은 CAT 모형의 모의유출량을 이용하며 PEST의 반복계산을 통하여 최적 매개변수를 추정한다. 침투방법은 CAT에서 제공하는 Rainfall Excess 방법, Green and Ampt 방법 및 Horton 방법을 이용하였으며 각 침투방법에 따른 유출 특성을 비교 및 분석하였다. 연구대상유역은 보령 댐 유역으로 유역면적은 $163.7km^2$이며 전체면적의 약 80%가 산지로 구성되어 있고, 유로연장은 22.3km, 유역평균경사는 40.19%이다. 또한 보령댐 유역의 월평년값 평균기온은 -0.8에서 $25.5^{\circ}C$로 계절변동이 매우 큰 것을 알 수 있다. 최근 몇 년간 심각한 가뭄 피해를 입은 보령댐 유역은 2016년에 도수관로를 완공하여 이를 통해 금강으로부터 물을 끌어다 쓰고 있는 실정이며, CAT 모형에서는 금강도수유입량을 외부유입 처리하여 유출량을 산정하였다. 모의기간은 1999년부터 2017년까지이며 전체기간에 대한 보정 후 연도별 보정을 실시하였다. 통계적 평가수단은 $R^2$, RMSE 및 NSE를 사용하여 유역 최종출구점에서의 유출량과 비교하였으며 전체기간에 대한 보정결과 NSE와 $R^2$가 0.75 이상으로 나타나 대체적으로 모의 유출수문곡선이 관측 수문곡선과 유사한 양상을 보였다.

• The Plant Pathology Journal
• /
• v.37 no.2
• /
• pp.200-203
• /
• 2021

Rice blast caused by the filamentous fungus Magnaporthe oryzae, is arguably the most devastating rice disease worldwide. Development of a high-throughput and reliable field blast resistance evaluation system is essential for resistant germplasm screening, resistance genes identification and resistant varieties breeding. However, the occurrence of rice blast in paddy field is easily affected by various factors, particularly lack of sufficient inoculum, which always leads to the non-uniform occurrence and reduced disease severity. Here, we described a procedure for adequately inducing the occurrence of rice seedling blast in paddy field, which involves pretreatment of diseased straw, initiation of seedling blast for the first batch of spreader population, inducing the occurrence of the second batch of spreader population and test materials. This procedure enables uniform and consistent infection, which facilitates efficient and accurate assessment of seedling blast resistance for diverse rice materials.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.1
• /
• pp.133-152
• /
• 2022

Rice is a fundamental staple food commodity all around the world. Globally, it is grown over 167 million hectares and occupies almost 1/5^th of total cultivated land under cereals. With a total production of 782 million metric tons in 2018. In Pakistan, it is the 2^nd largest crop being produced and 3^rd largest food commodity after sugarcane and rice. The stem borers a type of pest in rice and other crops, Scirpophaga incertulas or the yellow stem borer is very serious pest and a major cause of yield loss, more than 90% damage is recorded in Pakistan on rice crop. Yellow stem borer population of rice could be stimulated with various environmental factors which includes relative humidity, light, and environmental temperature. Focus of this study is to find the environmental factors changes i.e., temperature, relative humidity and rainfall that can lead to cause outbreaks of yellow stem borers. this study helps to find out the hot spots of insect pest in rice field with a control of farmer's palm. Proposed system uses temperature, relative humidity, and rain sensor along with artificial neural network to predict yellow stem borer attack and generate warning to take necessary precautions. result shows 85.6% accuracy and accuracy gradually increased after repeating several training rounds. This system can be good IoT based solution for pest attack prediction which is cost effective and accurate.