• Journal of Life Science
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• v.28 no.11
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• pp.1369-1378
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• 2018

Prunus mume Siebold & Zucc., a member of the Rosaceae family (called Maesil in Korea), has been widely distributed in East Asia, e.g. Korea, Japan and China, and its fruit has been used as a traditional drug and health food. In this study, we evaluated physicochemical properties and physiological activities of condensed Prunus mume juice treated with pectinase (PJ). The values of total acidity, pH, sugar contents, turbidity moisture content of the PJ were 35.81%, 2.73, $54.36^{\circ}Brix$, 2.75 and 51.32%, respectively. The PJ had effective DPPH radical scavenging activity, reducing power effect, $H_2O_2$ scavenging activity and ${\beta}$-carotene bleaching effect. DPPH radical scavenging activities of PJ was 46.31%; their reducing power ($OD_{700}$) was 1.80; $H_2O_2$ scavenging activity of PJ was 91.62%; and ${\beta}$-carotene bleaching effect of PJ was 73.02%. Also, PJ showed effective levels of ${\alpha}$-glucosidase inhibition activity. The cell viability was measured by SRB assay. The PJ significantly decreased the cell viability of mouse melanoma cells (B16) and human melanoma cells (SK-MEL-2 and SK-MEL-28) in a dose-dependent manner, however, there was no effect on human keratinocyte HaCaT. In morphological study, PJ-treated SK-MEL-2 cells showed distorted and shrunken cell masses. Total polyphenol contents and total flavonoid contents of PJ were 588.31 mg% (gallic acid equivalent) and 860.45 mg% (rutin equivalent). The antiproliferative effect of PJ seems to be associated with the antioxidant activity of its flavonoid and polyphenol contents. In conclusion, PJ may be beneficial in development of a functional food material.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.117-125
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• 2019

This study compared the temperature and humidity measured by an aspirated radiation shield (ARS), the accuracy of which has been recently verified, and those measured by a system developed by the parent company (Company A) to investigate and improve the performance of the developed system. The results are as follows. Overall, the two-plate system had a lower radiation shielding effect than the one-plate system but showed better performance results when excluding the effect of strawberry vegetation on the systems. The overall maximum temperature ranges measured by company A's system and the ARS were $20.5{\sim}53.3^{\circ}C$ and $17.8{\sim}44.1^{\circ}C$, respectively. Thus, the maximum temperature measured by company A's system was $2.7{\sim}9.2^{\circ}C$ higher, and the maximum daily temperature difference was approximately $12.2^{\circ}C$. The overall average temperature measured by company A's system and the ARS was $12.4{\sim}38.6^{\circ}C$ and $11.8{\sim}32.7^{\circ}C$, respectively. Thus, the overall average temperature measured by company A's system was $0.6{\sim}5.9^{\circ}C$ higher, and the maximum daily temperature difference was approximately $6.7^{\circ}C$. The overall minimum temperature ranges measured by company A's system and the ARS were $4.2{\sim}28.6^{\circ}C$ and $2.9{\sim}26.4^{\circ}C$, respectively. Thus, the minimum temperature measured by company A's system was $1.3{\sim}2.2^{\circ}C$ higher, and the minimum daily temperature difference was approximately $2.9^{\circ}C$. In addition, the overall relative humidity ranges measured by company A's system and the ARS were 52.9~93.3% and 55.3~96.5%, respectively. Thus, company A's system showed a 2.4~3.2% lower relative humidity range than the ARS. However, there was a day when the relative humidity measured by company A's system was 18.0% lower than that measured by the ARS at maximum. In conclusion, there were differences in the relative humidity measured by the two company's devices, as in the temperature, although the differences were insignificant.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.487-499
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• 2021

Purpose:The purpose of the paper is to review the problems of performance enhancement of safety certification standards and to suggest directions for improvement in order to rationalize safety certification standards for future industrial development and environmental changes. Method: The problems and limitations of the safety certification system are summarized through literature review and interview with manager, and the status of safety certification standards is classified into design standards, performance standards, and detailed standards, and the status analysis is performed. In addition, by synthesizing the results of the investigation and analysis, improvements are suggested to improve the performance of the safety certification standards. Result: Through the survey, the problems and limitations of safety certification could be grouped into six categories: government-led certification system operation, standardized certification standards, long time required to improve certification, poor certification standards preparation system, and lack of reflection of industry opinions. And, as a result of analyzing the certification standards by dividing them into performance and design standards, in the case of machinery, equipment, and protection devices, the design standards were high at 69.7% and 64.9%, whereas in the case of protective equipment, the performance standards were high at 61.1%. In order to improve the performance of safety certification standards centered on design standards, it is necessary to determine the possibility of performance enhancement of the certification standards and determine the feasibility of the inspection test method. In order to improve performance, it was reviewed that it was necessary to establish a systemic foundation and infrastructure, such as strengthening the Product Liability Act, systematizing market monitoring, etc., distributing certification test tasks, and participating in the preparation of certification standards by the private sector. Conclusion: Through this study, the problems and limitations of Korea's safety certification system were summarized and the necessity for performance improvement was reviewed. Performance improvement of safety certification standards is a matter that requires preparatory work, such as legislative revision and infrastructure construction, and requires mid-to-long-term promotion. In addition, rather than improving the overall safety certification standards, the performance requirements for each item subject to certification should be reviewed and promoted, and details should be specified through additional research.

• Journal of agriculture & life science
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• v.53 no.5
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• pp.137-143
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• 2019

To manufacturing of solid fuel by reuse of the wastes, the drying unit which have 500 kg/hr of drying capacity was developed and experimentally evaluate the performance. The spinach grown in Nam-hae island were used for the experiments and investigated of the heated-air drying characteristics as the inlet amount of raw materials, raw material stirring status, conveying type and drying time. The drying air heated by the energy derived from the steam which is supplied from the incineration plant. The moisture contents of raw materials were measured 85.65%. The inlet flow rate of drying air made a difference as the depth of the raw materials loaded on the drying unit and temperature has showed 108~144℃. The drying speed of the mixed drying more than doubled as that of non mixed drying under the same drying type, inlet amount, drying time and drying air temperature. In each experiment, the drying capacity have showed over 500 kg/hr. A drying efficiency of the ratio of drying consumption energy to input energy was 33.46%, lower than the average of 57.76% for the 157 conventional dryers. Because developed dryer must have a drying time of less than one hour, it is considered that the dry efficiency has been reduced due to the loss of wind volume during drying. If waste heat from incineration plant is used as a direct heat source, the dry air temperature is expected to be at least 160℃, greatly improving the drying capacity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.15-33
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• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.

• Journal of agriculture & life science
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• v.50 no.1
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• pp.273-281
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• 2016

In this study, after carrying out a bending test that targeted the frames of plastic film greenhouse, the load-displacement relationship was analyzed to be used as basic data to develop greenhouse construction and maintenance guidelines. As a result, regardless of the shapes of the specimen, the yield and the maximum load increased as the size of the specimen increased. The displacement also showed the same pattern. A steel pipe showed lower yield and maximum load than a square pipe, and the displacement was large. In the steel pipe case, the displacement under the yield and maximum load was in the range of approximately 1.42-4.20mm and 5.80-24.13mm, respectively. In the square pipe case, the displacement under the yield and maximum load was in the range of approximately 1.62-3.00mm and 3.13-8.01mm, respectively. Further, a large difference was observed between the result of this test and the values calculated by a conventionally provided standard. In particular, not much difference was found from the result of this test in the case of a purlin member from the values provided by previous researches. However, a large difference was observed in the column or main rafter members. Furthermore, when a wide-span and venlo type, which is a glasshouse, was used as a target(h/100 and h/80), the displacement under the yield and maximum load was approximately 28.0mm and 35.0mm, respectively, which showed a large difference compared with the Netherlands standard(14.0mm) of a glasshouse. Further, in the main rafter case, a large difference was observed in the displacement limit according to the width(i.e., span) of the greenhouse where members are used. Therefore, because the displacement limit can vary depending on various factors such as type, form, and size of a greenhouse, we determined that studies or tests that consider these factors should be carried out to reflect them in the construction and maintenance of greenhouses.

• Journal of the Korean Society of Food Culture
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• v.21 no.6
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• pp.653-660
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• 2006

Some quality characteristics of tofu prepared with cuttlefish ink were investigated to study the effects of various of coagulants. Each concentration of coagulant was determined as 0.2% of GDL, 0.3# of $MgCl_2$, 1%^ of $CaCl_2$, 1.5% of $CaSO_4$ and 0.6% D-gluconic acid calcium by pre-experiment. Also, the optimum concentration of added cuttlefish ink was chosen as 3%(diluted in twenty times). The yield of inky tofu prepared with GDL as coagulant was the highest. According to prepared with $MgCl_2$ was the highest. The result of microstructure was examined by SEM, the particles of inky tofu coagulated with GDL and D-gluconic acid calcium were small and uniformity. In overall acceptability of sensory properties, inky tofu coagulated with GDL was the highest in score. In the color of inky tofu, L value and a value were the highest coagulated with GDL, but that coagulated with $CaCl_2$ had the highest b value. In the texture properties of inky tofu, hardness, gumminess and brittleness were the highest coagulated with D-gluconic acid calcium. A positive correlation was observed between the pH of tofu whey and acidity. Sensory properties of roasted nutty flavor, hardness, cohesiveness and springiness were positively correlated with the acceptability.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.521-535
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• 2023

When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.