• Journal of Bio-Environment Control
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• v.7 no.3
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• pp.226-236
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• 1998

If the lowest leaves of the cucumber were removed or training cultivable method was changed, a computer vision system could divide well the cucumber fruit from the others, and also an end-effector could reach and grip cucumber fruit and cut well its fruit stalk. Therefore, this study investigated whether removal leaves and training cultivable method of a cucumber could affect its growth and yield. They can help to be designed the vision system and the end-effector. A cucumber fruit grew by 6-l5cm long for 2 days regardless of removing leaves. Removal leaves didn't affect growth of cucumber fruit. Number of cucumber fruit was produced within 10% different values by three methods (A, B, C) of removal leaves. The first grade rate (best quality) of 4 B and C was 56.7%, 53.1%, 56.3% respectively. Consequently, proper removal leaves were better than traditional way, which does not remove a leaf, because they make cucumber plant ventilate more freely and absorb more light.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.11
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• pp.1435-1442
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• 2008

The purpose of this study was to identify the influence of consumption value on healthy functional food choice. Also, this study explored the role of health motivation, health concern, and food involvement as a moderating variable in the relationship between consumption value and healthy functional food choice. A total of 281 responses were collected using on-site survey (response rate 96.0%) from college students in Daegu, Gyeoungbuk Province. The questionnaire contained questions on consumption value, health motivation, health concern, food involvement, and purchasing intention of healthy functional food. The respondents rated the items using a 5-point scale from 1 (strongly disagree) to 5 (strongly agree). According to the confirmatory factor analysis, item evaluating using factor loading resulted in the retention of 25 consumption value items loading on seven factors, four health motivation items loading one factor, six health concern items loading on one factor, and four food involvement items loading on one factor with an internal consistency. Results of stepwise regression found that social value-I, emotional, functional, epistemic, and conditional values among consumption value determined the purchasing intention of healthy functional food. Results of hierarchical regression showed that health concern had a positive effect on the relationship between social value-I and purchasing intention of healthy functional food.

• Progress in Medical Physics
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• v.17 no.3
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• pp.136-143
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• 2006

The respiratory gating radiation therapy which Irradiates only in the stable respiratory period with analyzing the periodic motion of a reflective marker on the patient's abdomen has been applied to the precise radiation treatment in order to minimize the effect of organ motion induced by the respiration. This respiratory gating system establishes irradiation region using the amplitude-based or phase-based method. Although phase-based method Is preferred because of the stability in the real treatment conditions, it has some limits to explain the exact correlation between the marker motion and organ motion. Even when the variation of amplitude which can introduce target motion considered as an error is produced, the phase-based method has the possibility to irradiate including the error positions. In this study, the error analysis program was developed for the verification of the tumor position's variation correlated with the variation of marker's amplitude which can be occurred during a phase-based respiratory sating treatment. The analysis program was tested with a virtual treatment record file and with a record file using moving phantom which were modified considering the irregular amplitude's variation simulating the real clinical situations. In both cases, accurate discrimination of error points and error calculation were produced. When the treatment record files of a real patient were analyzed with the program, the accurate recognition and calculation of the error points were also verified. The analysis program developed in this study will be applied as a useful tool for the analysis of errors due to the irregular variation of patients' respiration during the phase-base respiratory gating radiation treatment.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.23-33
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• 2016

The current smart lighting is shaped to offer the lighting environment suitable for current context, after identifying user's action and location through a sensor. The sensor-based context awareness technology just considers a single user, and the studies to interpret many users' various context occurrences and conflicts lack. In existing studies, a fuzzy theory and algorithm including ReBa have been used as the methodology to solve context conflict. The fuzzy theory and algorithm including ReBa just avoid an opportunity of context conflict that may occur by providing services by each area, after the spaces where users are located are classified into many areas. Therefore, they actually cannot be regarded as customized service type that can offer personal preference-based context conflict. This paper proposes a priority-based LED lighting control system interpreting multiple context conflicts, which decides services, based on the granted priority according to context type, when service conflict is faced with, due to simultaneous occurrence of various contexts to many users. This study classifies the residential environment into such five areas as living room, 'bed room, study room, kitchen and bath room, and the contexts that may occur within each area are defined as 20 contexts such as exercising, doing makeup, reading, dining and entering, targeting several users. The proposed system defines various contexts of users using an ontology-based model and gives service of user oriented lighting environment through rule based on standard and context reasoning engine. To solve the issue of various context conflicts among users in the same space and at the same time point, the context in which user concentration is required is set in the highest priority. Also, visual comfort is offered as the best alternative priority in the case of the same priority. In this manner, they are utilized as the criteria for service selection upon conflict occurrence.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.153-169
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• 2020

A new way of shopping based on virtual assistant, so called voice shopping, is drawing attention. The voice shopping market is growing around the world, and Korea is on the verge of full-scale commercialization of this new shopping. For the development of voice shopping-related industries, it is necessary to research on specific issues related to this new shopping methods, such as the quality of services, efficient processes tailored to new ways, and ways to build customer relationships. As part of such an attempt, the study seeks to determine the factors that affect consumers' perception and attitudes toward voice shopping. The study conducted the analysis based on survey response data of 171 online shopping users. In addition to the typical factors of the technology acceptability model(TAM) such as perceived usefulness and ease of use, the impact of perceived playfulness was included for analyzing the intention on the acceptance of voice shopping. In particular, this study focuses on the impact of user attributes. For the spread of voice shopping, it is necessary to set up a valid target customer and understand users for establishing an effective customer relationship. Therefore, this study tries to analyze how the perceptions on the voice shopping(perceived usefulness, ease of use, and perceived playfulness) are affected by users' attributes, such as user innovativeness and user knowledge level. The result of analysis shows that user innovativeness have a positive relationship with all of perceived usefulness, ease of use, and perceived playfulness. The user knowledge base, however, was not significant to all these three variables. The user knowledge base is shown to have a positive effect on user innovativeness which is the source of positively significant factor for the variable of the perceptions on the voice shopping. Meanwhile, among the variables of extended technology acceptance model, perceived usefulness and perceived playfulness have positive effects on the acceptance of voice shopping, while ease of use has no significant impact on the voice shopping acceptance. Ease of use has a positive relationship with perceived usefulness and playfulness. This study is meaningful in providing implications on the development of voice shopping platforms and related services, and establishment of customer relationship.

• Korean Journal of Food Science and Technology
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• v.34 no.5
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• pp.762-769
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• 2002

As a preliminary test for defining intact yellow croaker pigment, the pigment was analyzed by column chromatography and UV-vis spectrophotometry. All maximum absorbance wavelengths commonly showed three maximum absorbance ranges, similar to those of carotenoid, suggesting that the tested pigment may be carotenoid. We detected total six peak RT values in the chromatogram through PDA-HPLC under gradient mode (behavior A at 10% for initial 2 min and changed to behavior B for 60 min). Most pigments were detected at the peak with 3.27 RT value. Because seven peaks were detected under gradient mode and three under isocratic mode [methanol : methylene chloride (90 : 10, v/v)], gradient mode was determined to be more appropriate for quantitative analysis. By the comparison test of RT values among yellow pigment in croakers and reference pigments, such as zeaxanthine, ${\beta}-cryptoxanthine$, ${\beta}-carotene$, and astaxanthin, only ${\beta}-cryptoxanthine$ was detected in the white croaker, whereas such pigment of yellow croaker having RT value of 31.02 was not detected. Therefore, RT value was found to be applicable for detecting adulterated croaker.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• The Korean Journal of Archival Studies
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• no.14
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• pp.3-51
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• 2006

In this paper, I applied known theories of appraisal and re-appraisal to the Japanese Colonial Archives and the Colonial City Planing Archives in Korea. The purpose of this application to some of sample archives was to develop a useful and effective approach to appraise the archives which were not appraised before they were determined to be "permanent" archives by the Japanese colonial officials. The colonial archives have lost their context and "chain of custody." A large portion of their volume also disappeared. Only thirty thousands volumes survived. The appraisal theories and related issues applied to and tested on these archives are; "original natures" of archives defined by Sir. Hillary Jenkinson, Schellenburg's information value appraisal theory, the re-appraisal theory based on economy of preservation and prospect for use of the archives, function-based appraisal theory and documentation theory, the special nature of the archives as unique, old and rare colonial archives, the intrinsic value of the archives, especially the city planing maps and drawings, and finally, the determination of the city planing archives as permanent archives according to the contemporary and modern disposal authority. The colonial archives tested were not naturally self-proven authentic and trustworthy records as many other archives are. They lost their chain of custody and they do not guarantee the authenticity and sincerity of the producers. They need to be examined and reviewed critically before they are used as historical evidence or any material which documented the contemporary society. Rapport's re-appraisal theory simply does not fit into these rare historical archives. The colonial archives have intrinsic values. Though these archives represent some aspects of the colonial society, they can not document the colonial society since they are just survived remains or a little part of the whole archives created. The functions and the structure of the Government General of Korea(朝鮮總督府) were not fully studied yet and hardly can be used to determine the archival values of the archives created in some parts of the colonial apparatus. The actual appraisal methods proved to be effective in the case of colonial archives was Schellenburg's information value appraisal theory. The contextual and content information of the colonial archives were analysed and reconstructed. The appraisal works also resulted in full descriptions of the colonial archives which were never described before in terms of archival principles.

• Korean Journal of Breeding Science
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• v.50 no.4
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• pp.396-405
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• 2018

The areas of soybean (Glycine max (L.) Merrill) cultivation in Gangwon-do have increased due to the growing demand for well-being foods. The soybean barcode system is a useful tool for cultivar identification and diversity analysis, which could be used in the seed production system for soybean cultivars. We genotyped cultivars using 202 insertion and deletion (InDel) markers specific to dense variation blocks (dVBs), and examined their ability to identify cultivars and analyze diversity by comparison to the database in the soybean barcode system. The genetic homology of "Cheonga," "Gichan," "Daewang," "Haesal," and "Gangil" to the 147 accessions was lower than 81.2%, demonstrating that these barcodes have potentiality in cultivar identification. Diversity analysis of one hundred and fifty-three soybean cultivars revealed four subgroups and one admixture (major allele frequency <0.6). Among the accessions, "Heugcheong," "Hoban," and "Cheonga" were included in subgroup 1 and "Gichan," "Daewang," "Haesal," and "Gangil" in the admixture. The genetic regions of subgroups 3 and 4 in the admixture were reshuffled for early maturity and environmental tolerance, respectively, suggesting that soybean accessions with new dVB types should be developed to improve the value of soybean products to the end user. These results indicated that the two-dimensional barcodes of soybean cultivars enable not only genetic identification, but also management of genetic resources through diversity analysis.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.