• Journal of Wetlands Research
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• v.15 no.3
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• pp.301-315
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• 2013

The purpose of this study is to investigate characteristics of hydromorpological structures that affect landscape preference and visual characteristics on the sections of the designated streams where have dynamic ecological characteristics. We evaluated the ecological status of the streams utilizing LAWA to assess hydromorpological structures of streams. We also investigated preference and visual characteristics of stream landscapes through Semantic Differential Scale(SD scale). The differences of visual images according to the characteristics of hydromorpological structures in the sites were analyzed by descriptive statistics, One-way ANOVA, and t-test. As a result, this study showed that sections represented as "good" ecological status are shown to be harmonious, beautiful, natural, and clean comparing to sections represented as "poor" ecological status. The hydromorpological structures that have significant impacts on the visual characteristics are considered as riparian vegetation, cross-sectional shape, and the artificial structures. Results of this study can help guide the stream restoration of the damaged stream to improving ecological function and positive landscape.

• Knowledge Management Research
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• v.20 no.2
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• pp.25-42
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• 2019

AI speakers which are wireless speakers with smart features have released from many manufacturers and adopted by many customers. Though smart features including voice recognition, controlling connected devices and providing information are embedded in many mobile phones, AI speakers are sitting in home and has a role of the central en-tertainment and information provider. Many surveys have investigated the important factors to adopt AI speakers and influ-encing factors on satisfaction. Though most surveys on AI speakers are cross sectional, we can track customer attitude toward AI speakers longitudinally by analyzing customer reviews on AI speakers. However, there is not much research on the change of customer attitude toward AI speaker. Therefore, in this study, we try to grasp how the attitude of AI speaker changes with time by applying text mining-based analysis. We collected the customer reviews on Amazon Echo which has the highest share of AI speakers in the global market from Amazon.com. Since Amazon Echo already have two generations, we can analyze the characteristics of reviews and compare the attitude ac-cording to the adoption time. We identified all sub topics of customer reviews and specified the topics for smart features. And we analyzed how the share of topics varied with time and analyzed diverse meta data for comparisons. The proportions of the topics for general satisfaction and satisfaction on music were increasing while the proportions of the topics for music quality, speakers and wireless speakers were decreasing over time. Though the proportions of topics for smart fea-tures were similar according to time, the share of the topics in positive reviews and importance metrics were reduced in the 2nd generation of Amazon Echo. Even though smart features were mentioned similarly in the reviews, the influential effect on satisfac-tion were reduced over time and especially in the 2nd generation of Amazon Echo.

• Tunnel and Underground Space
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• v.31 no.4
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• pp.211-220
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• 2021

Tunnel collapse often occurs during deep underground tunneling (> 40 m depth) in South Korea. Natural cavities as well as water supply pipes, sewer pipes, electric power cables, artificial cavities created by subway construction are complexly distributed in the artificial ground in the shallow depths of the urban area. For deep tunnel excavation, it is necessary to understand the properties of the ground which is characterized by porous elements and various geological structures, and their influence on the stability of the ground. This study analyzed geological factors for risk assessment in deep excavation in South Korea based on domestic and overseas case study. As a result, a total of 7 categories and 38 factors were derived. Factors with high weights were fault and fault clay, differential stress, rock type, groundwater and mud inrush, uniaxial compressive strength, cross-sectional area of tunnel, overburden thickness, karst and valley terrain, fold, limestone alternation, fluctuation of groundwater table, tunnel depth, dyke, RQD, joint characteristics, anisotropy, rockburst and so forth.

• Smart Media Journal
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• v.10 no.4
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• pp.45-54
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• 2021

The skin is the body's first line of defense against external infection. When a skin disease strikes, the skin's protective role is compromised, necessitating quick diagnosis and treatment. Recently, as artificial intelligence has advanced, research for technical applications has been done in a variety of sectors, including dermatology, to reduce the rate of misdiagnosis and obtain quick treatment using artificial intelligence. Although previous studies have diagnosed skin diseases with low incidence, this paper proposes a method to classify common illnesses such as warts and corns using a convolutional neural network. The data set used consists of 3 classes and 2,515 images, but there is a problem of lack of training data and class imbalance. We analyzed the performance using a deep metric loss function and a cross-entropy loss function to train the model. When comparing that in terms of accuracy, recall, F1 score, and accuracy, the former performed better.

• Journal of Nutrition and Health
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• v.55 no.6
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• pp.601-616
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• 2022

In the era of the fourth industrial revolution technology, the inclusion of personalized nutrition for healthcare (PNH), when establishing a healthcare platform to prevent chronic diseases such as obesity, diabetes, cerebrovascular and cardiovascular disease, pulmonary disease, and inflammatory diseases, enhances the national competitiveness of global healthcare markets. Furthermore, since the government experienced COVID-19 and the population dead cross in 2020, as well as numerous health problems due to an increasing super-aged Korean society, there is an urgent need to secure, develop, and utilize PNH-related technologies. Three conditions are essential for the development of PNH technologies. These include the establishment of causality between obesity genome (genotype) and prevalence (phenotype) in Koreans, validation of clinical intervention research, and securing PNH-utilization technology (i.e., algorithm development, artificial intelligence-based platform, direct-to-customer [DTC]-based PNH, etc.). Therefore, a national control tower is required to establish appropriate PNH infrastructure (basic and clinical research, cultivation of PNH-related experts, etc.). The post-corona era will be aggressive in sharing data knowledge and developing related technologies, and Korea needs to actively participate in the large-scale global healthcare markets. This review provides the importance of scientific evidence based on a huge dataset, which is the primary prerequisite for the DTC obesity gene-based PNH technologies to be competitive in the healthcare market. Furthermore, based on comparing domestic and internationally approved DTC obese genes and the current status of Korean obesity genome-based PNH research, we intend to provide a direction to PNH planners (individuals and industries) for establishing scientific PNH guidelines for the prevention of obesity.

• Korean Journal of Plant Resources
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• v.31 no.1
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• pp.77-85
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• 2018

The cultivation area of rapeseed (Brassica napus L.) has been increased for oil production and landscaping purpose in Korea. However, as the color of rapeseed flower is very simple, diversified flower color is necessary to improve landscape effect. Interspecific and intergeneric crosses between rapeseed (Brassica napus) and three Cruciferae crops were performed in order to grow diverse flower color of rapeseed. The silique formation rate of interspecific cross rapeseed with cabbage (B. oleracea L) was relatively high (65.8%) and higher than intergeneric cross with rapeseed and radish (Raphanus sativus L.), rapeseed and Orychophragmus, respectively. During silique developing period after artificial pollination, there were many siliques without seeds due to the failure of fertilization. The average number of seed per silique obtained from cross rapeseed and cabbage, rapeseed and radish, rapeseed and O. violaceus were 0.12, 0.4 and 0.12, respectively. The phenotypes of $F_1$ hybrid plants from cross rapeseed and Cruciferae crops were mostly similar to maternal line, but leaf length and leaf width were increased. The interspecific cross of rapeseed and cabbage generated ivory color of flower which is the medium color of parents, and intergeneric cross of rapeseed and O. violaceus created entities with larger flowers which seems to enhance landscape effect. The fatty acid composition of most hybrid seeds intermediated of the two parents for oleic acid, linoleic acid and linolenic acid, content. Whereas hybrid of rapeseed and radish produced less erucic acid than radish parent.

• The Journal of Engineering Geology
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• v.19 no.2
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• pp.131-138
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• 2009

A simulation-optimization model is developed for development of groundwater and control of a saltwater wedge for protecting over-exploiting freshwater pumping wells. To achieve the goal an objective function is developed for three types of wells: freshwater pumping, freshwater injection and saltwater pumping. Integrity of groundwater environment is accounted for by including three indices. Illustrative cross-sectional examples show that both types of barriers can protect freshwater pumping wells from saltwater intrusion. A barrier well operating at the same rate located anywhere within a certain reach can protect a pumping well. However, the location of the reach appears to contradict the common practice of barrier placements. Consideration of the groundwater environment yields a unique optimal location for barrier wells.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.411-416
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• 2008

The development of games has brought about the birth of game characters that are visually very realistic. At present, one sees much enthusiasm for giving the characters emotions through such devices as avatars and emoticons. However, in a freely changing environment of games, the devices merely allow for the expression of the value derived from a first input rather than creating expressions of emotion that actively respond to their surroundings. As such, there are as of yet no displays of deep emotions among game characters. In light of this, the present article proposes the 'CROSS(Character Reaction on Specific Situation) Model AE Engine' for game characters in order to develop characters that will actively express action and emotion within the environment of the changing face of games. This is accomplished by classifying the emotional components applicable to game characters based on the OCC model, which is one of the most well known cognitive psychological models. Then, the situation of game playing analysis of the commercialized RPG game is systematized by ontology.

• Computers and Concrete
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• v.21 no.4
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• pp.407-417
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• 2018

Concrete which is a composite material is one of the most important construction materials. Compressive strength is a commonly used parameter for the assessment of concrete quality. Accurate prediction of concrete compressive strength is an important issue. In this study, we utilized an experimental procedure for the assessment of concrete quality. Firstly, the concrete mix was prepared according to C 20 type concrete, and slump of fresh concrete was about 20 cm. After the placement of fresh concrete to formworks, compaction was achieved using a vibrating screed. After 28 day period, a total of 100 core samples having 75 mm diameter were extracted. On the core samples pulse velocity determination tests and compressive strength tests were performed. Besides, Windsor probe penetration tests and Schmidt hammer tests were also performed. After setting up the data set, twelve artificial intelligence (AI) models compared for predicting the concrete compressive strength. These models can be divided into three categories (i) Functions (i.e., Linear Regression, Simple Linear Regression, Multilayer Perceptron, Support Vector Regression), (ii) Lazy-Learning Algorithms (i.e., IBk Linear NN Search, KStar, Locally Weighted Learning) (iii) Tree-Based Learning Algorithms (i.e., Decision Stump, Model Trees Regression, Random Forest, Random Tree, Reduced Error Pruning Tree). Four evaluation processes, four validation implements (i.e., 10-fold cross validation, 5-fold cross validation, 10% split sample validation & 20% split sample validation) are used to examine the performance of predictive models. This study shows that machine learning regression techniques are promising tools for predicting compressive strength of concrete.

• Genomics & Informatics
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• v.13 no.4
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• pp.137-145
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• 2015

Selective sweep can cause genetic differentiation across populations, which allows for the identification of possible causative regions/genes underlying important traits. The pig has experienced a long history of allele frequency changes through artificial selection in the domestication process. We obtained an average of 329,482,871 sequence reads for 24 pigs from three pig breeds: Yorkshire (n = 5), Landrace (n = 13), and Duroc (n = 6). An average read depth of 11.7 was obtained using whole-genome resequencing on an Illumina HiSeq2000 platform. In this study, cross-population extended haplotype homozygosity and cross-population composite likelihood ratio tests were implemented to detect genes experiencing positive selection for the genome-wide resequencing data generated from three commercial pig breeds. In our results, 26, 7, and 14 genes from Yorkshire, Landrace, and Duroc, respectively were detected by two kinds of statistical tests. Significant evidence for positive selection was identified on genes ST6GALNAC2 and EPHX1 in Yorkshire, PARK2 in Landrace, and BMP6, SLA-DQA1, and PRKG1 in Duroc. These genes are reportedly relevant to lactation, reproduction, meat quality, and growth traits. To understand how these single nucleotide polymorphisms (SNPs) related positive selection affect protein function, we analyzed the effect of non-synonymous SNPs. Three SNPs (rs324509622, rs80931851, and rs80937718) in the SLA-DQA1 gene were significant in the enrichment tests, indicating strong evidence for positive selection in Duroc. Our analyses identified genes under positive selection for lactation, reproduction, and meat-quality and growth traits in Yorkshire, Landrace, and Duroc, respectively.