• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.31-37
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• 1999

The frequency of gall formation by pine needle gall midges ranged from 35% to 40% in both P. densiflora and P. thunbergii species. However, there was no indication of gall development from larva on both P. virgiana and P. rigida species suggesting that some specific compounds might play role in preventing gall formation of larva. The susceptible species to pine needle gall midges including P. densiflora and P. thunbergii contained a little salicylic acid under the free phenolic compound conditions while the resistant species against such insects including P. virginiana and P. rigida species contained about 37ppm to 50ppm of salicylic acid. Thus, this compound might have important roles in insect resistance. The contents of internal salicylic acid in the needles of susceptible pines increased from 9.5ppm to 20.6ppm after direct external irrigation of salicylic acid solution and flour treatment on roots. As a result, the frequency of gall formation decreased dramatically 17~19 times lower when compared with that of control. According to our results, the application of salicylic acid for effective prevention against insect damages should be performed before hatching eggs. The frequency of gall formation in the hybrid pines of P. thunbergii(susceptible) and P. virginiana(resistant) showed approximately 24% as average value of those in both species. In the case of specific individuals, it ranged from 2.8% to 11.5% in hybrids of both species. Therefore, effective production of insect resistant pines can be obtained through hybrids by crossing between susceptible and resistant species including P. thunbergii and P. virginiana by increasing internal salicylic acid contents of the needles.

• Journal of Home Health Care Nursing
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• v.11 no.1
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• pp.5-13
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• 2004

The home health care industry has grown rapidly and can be expected to continue to grow in the foreseeable future. Home health care refers to the practice of nursing applied to clients with a health condition in the clients place of residence. clients and their designated care givers are the focus at home health nursing practice. The goal of care is to initiate. manage and evaluate the resources needed to promote the clients optimal level of well-being and function. Nursing activities necessary to achieve this goal may warrant preventive maintenance and restorative emphases to prevent potential problems from developing. Many project program were suggested home health care model for Korea's health care system and policy direction for expansion and establishment of home health care .But the aim of this paper is to provide on overview for theoretical frame work in home health care. Theories and conceptual frameworks or models are important nursing because they define and guide the boundaries of professional practice and identify key nurse-patient-caregiver relationships that emerge with caring. Following is the research with an investigation of the literature review in the University of Arizona international medline database, In conclusion, are as followers: First, many nursing theorists have had a tremendous impact on nursing practice. the following highlights those nursing theorists that are particularly helpful in understanding home health care. 1. Florence Nightingale : Our earliest theoretical legacy. Nightingale's believes are reflected in basic infection control practice such as hand washing and infectious waste disposal and are key nursing interventions in home care. 2. Martha Roger's :Science of unitary human beings theory. Rorger's believed that the focus of shared. non invasive healing modelities is the human environmental field rather than direct physical care. These modelities continue to evolve as our awareness (reflecting greater diversity, faster rhythms, motions, and ways of knowing) transcends time and space, allowing individuals to get in touch with their integral nature of unbroken wholeness. On people as ever changing energy fields have special relevance in home care especially with hospice and palliative care applications. 3. Madeline Leininger's; Transcultural nursing theory. Home care nurses move through a variety of communities and often care for patients from different cultural back grounds. Therefore Leininger's work has a good that with home care because home care nursing practice is very culturally focused. 4. Dorothea Orem's : Self care deficit theory. Orem's theory views care as something to be performed by both nurses and patients. The role of the nurse is to provide education and support that help patients acquire the necessary activities to perform self-care. Orem's theory is foundational to have care because it begins to truly acknowledge the role of the patient in managing his or her own health. which is referred to as self-care. 5. Margaret Neuman's; Health as expending consciousness theory. Neuman believes that health compasses disease and reflects an underlying pattern of person-environment interaction. A key application of 'Neuman's work to home care is for nurses to understand that health and illness do not necessarily exist at opposite ends of a continuum. 6. Jean Watson's: Theory of human caring. Watson's theory of human caring in nursing proposes human caring as the moral ideal of nursing. Nurses participate human caring to protect, enhance and preserve humanity by assisting individuals to fing meaning in illness. pain and existence and to help others gain self knowledge. self control. and self healing such thinking lends richness to theory development. as well as clinical practice in home care. Second, Robin Rice : Dynamic self determination for self care. (A theoretical framework for home care) Dynamical self determination for self care can be useful to home care nurses in a variety of ways. As research tool it can be reflected in the interview process when the home visit. The home care nurse's role is that of facilitator of patient self-determination for self care through numerous strategies. including patient education and case management.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.3
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• pp.23-32
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• 2010

The purpose of this study is to quantify human energy budgets for different structures of outdoor spatial surfaces affecting thermal comfort, to analyze the impacts of tree shading on building energy savings, and to suggest desirable strategies of urban greenspace planning concerned. Concrete paving and grass spaces without tree shading and compacted-sand spaces with tree shading were selected to reflect archetypal compositional types for outdoor spatial materials. The study then estimated human energy budgets in static activity for the 3 space types. Major determinants of energy budgets were the presence of shading and also the albedo and temperature of base surfaces. The energy budgets for concrete paving and grass spaces without tree shading were $284\;W/m^2$ and $226\;W/m^2$, respectively, and these space types were considerably poor in thermal comfort. Therefore, it is desirable to construct outdoor resting spaces with evapotranspirational shade trees and natural materials for the base plane. Building energy savings from tree shading for the case of Daegu in the southern region were quantified using computer modeling programs and compared with a previous study for Chuncheon in the middle region. Shade trees planted to the west of a building were most effective for annual savings of heating and cooling energy. Plantings of shade trees in the south should be avoided, because they increased heating energy use with cooling energy savings low in both climate regions. A large shade tree in the west and east saved cooling energy by 1~2% across building types and regions. Based on previous studies and these results, some strategies including indicators for urban greenspace planning were suggested to improve thermal comfort of outdoor spaces and to save energy use in indoor spaces. These included thermal comfort in construction materials for outdoor spaces, building energy savings through shading, evapotranspiration and windspeed mitigation by greenspaces, and greenspace areas and volume for air-temperature reductions. In addition, this study explored the application of the strategies to greenspace-related regulations to ensure their effectiveness.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.19-26
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• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.9
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• pp.590-596
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• 2012

Enhanced coagulation is best available technologies to treat NOM in water to produce clean drinking water. In this research, the comparison experiments between conventional coagulation (CC) and enhanced coagulation (EC) using 4 type coagulants i.e., ferric chloride, aluminium sulphate (alum), poly aluminium sulphate organic magnesium (PSOM) and poly aluminium chloride (PACl) were performed in terms of surrogate parameters such as dissolved organic carbon (DOC), trihalomethane formation potential (THMFP), haloacetic acid formation potential (HAAFP) and zeta potential variation in order to find out the most effective coagulant and conditions to fit Nakdong River water. When applied to EC process, the turbidity removal efficiency did not increased gradually compared to the CC process when adding coagulants. Furthermore, the removal efficiency of turbidity became decreased much more as coagulants were added increasingly whereas the removal efficiency of DOC, THMFP and HAAFP became increased by 13~18%, 9~18% and 9~18% respectively compared to the CC process. The characteristics of turbidity removal showed relatively high removal efficiency considering the pH variation in entire pH range when using $FeCl_3$ and PACl. Additionally, in case of alum and PSOM steady removal efficiency was shown between pH 5 and pH 8. In terms of DOC surrogate the coagulants including 4 type coagulants indicated high removal efficiency between pH 5 and pH 7. The removal efficiency of dissolved organic matter (DOM) in EC between less than 1 kDa and more than 10 kDa augmented by 11~21% and 16% respectively compared to the CC process. The removal efficiency of hydrophobic and hydrophilic organic matter proved to be increased by 27~38% and 11~15% respectively. In conclusion, the most effective coagulant relating to EC for Nakdong River water was proved to be $FeCl_3$ followed by PSOM, PAC and alum in order.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.3
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• pp.203-207
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• 2009

The concern of seriousness and harmful effects of environmental pollution is rising by the various water pollutions, appearances of new micro-noxious substances and increase of sustainable pollutants. The method is suggested that can effectively increase the removal of organic substances and several pollutants using a coagulation process. The experiment for characteristics of $ZrSiO_4$ (zirconium silicate) as a coagulation-aid was carried out for application to coagulation process with domestic wastewater and lake water, and the removal rate of the organic substances depending on a dosage was evaluated by PDA (Photometric Dispersion Analyzer) in this study. Zeta-potential of zirconium silicate solution was -32.22 mv at pH 7 and the lower negative(-) charge was detected in the more acidic conditions. Absorbance on $UV_{254}$ presented higher when zirconium silicate was added than in a domestic wastewater itself. Besides, the results by PDA experiment represented that injection of zirconium silicate could promote growing of floc. Tests for coagulation process were conducted by three ways which are pre-injection, co-injection and post-injection of zirconium silicate with alum. Accordingly, removal efficiency of organic substances increased over 15% in co-injection than in using of alum as a sole reagent. When a 20 mg/L of alum was used with a 10 mg/L of zirconium silicate, the removal efficiency was high up to 90%. Removal efficiency of $COD_{Cr}$ was improved more than 15% in case of dosage of coagulant either PAC (Poly aluminium chloride) or PACS (Poly aluminium chloride Silicate) together with zirconium silicate. As a result, the removal efficiency of $COD_{Cr}$ were 5~10% higher in a co-injection of zirconium silicate with a coagulant than a pre-injection and a post-injection but it of soluble substances was lower in a co-injection.

• Archives of design research
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• v.18 no.3 s.61
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• pp.85-94
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• 2005

Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.