• 한국환경복원기술학회지
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• 제25권3호
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• pp.63-82
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• 2022

The purpose of this study is to compare growth condition of landscape woody plants growing on the different ground structures in apartment complex. I chose Manseok Beach Town Complex 2, in Manseok-dong, Seo-gu, Incheon which has both natural and artificial ground as a subject site. Analysis of three phases of soil showed that artificial ground had average liquid phase of 30.89%, artificial ground mounding 33.88% and natural ground 24.40%. It means that artificial ground has higher water content than natural ground despite having same earthiness. It is believed that artificial ground is not as well drained as natural ground even though it is connected to the natural ground and has a deep soil depth because of mounding. Comparative study between woody plants on natural ground and those on artificial ground demonstrated that trees on natural ground grew 40.4% compared to those on artificial ground(0.875mm more) in terms of diameter growth. Average diameter growth of trees on natural ground was 3.040mm against 2.165mm for those on artificial ground. All 19 tree species which were measured for root diameter growth showed similar or higher growth on natural ground than on artificial ground. When it comes to growth of height, arborvitae showed highest growth on natural ground, followed by Thuja occidentalis, Pinus strobus, Magnolia denudata, Diospyros kaki and Aesculus turbinata. I measured branch growth and rate of leaf adherence of Pinus strobus. Average annual rate of branch growth of woody plants on natural ground was twice as high as those on artificial ground. I could conclude that ground structure influences branch growth of Pinus strobus. Statistics analysis of tree damage demonstrated significant result, meaning that there is a difference in the average damage rate depending on structure of ground. In order to validate growth difference by planting ground, I conducted T-Test of growth of diameter, root diameter, branch and height on woody plants growing on natural and artificial ground. As a result, it is believed that there is a difference in the growth of trees depending on the ground structure. Putting all these results together demonstrates that woody plants on natural ground generally grow better than those on artificial ground, which means ground structure does have an influence on the environment of growth of trees.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1999년도 춘계학술대회논문집
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• pp.99-102
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• 1999

In this study, to investigate the effect of process variables such as reduction in area, semi-die angle and the rectangular ratio to the corner filling which influences the dimensional accuracy of the final product in the drawing of the cluadrangle rod from a round bar, it has been simulated by three dimensional rigid-plastic finite element method. In order to reduce the number of simulation artificial neural network has been introduced. Also, through the experimental investigation, the present results have been implemented on the industrial product. In results, the main process variable is the combination of the semi-die angle in case of the irregular shaped drawing process and reduction in area in the event of regular shaped drawing process, respectively.

• 소성∙가공
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• 제20권6호
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• pp.461-467
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• 2011

An artificial body force method is presented to accurately simulate drawing processes in which back pressing is exerted. A rigid-plastic finite element method is applied together with a numerical scheme to eliminate the numerically incurred plastic deformation in rigid or elastic region, which significantly influences simulation results because it eventually changes reduction of area in drawing. Back tension or compression is applied by body force at the rear part of material to obtain numerically stable solution. Two typical examples are shown, a drawing process with back tension applied and a tube drawing with a fixed plug and back pressing applied.

• Macromolecular Research
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• 제10권1호
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• pp.13-17
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• 2002

An artificial neural network (ANN) was used to study the relationship between the glass transition temperature (T$_{g}$) and the structure of homopolymers. The input is very important for the ANN. In this paper, six kinds of input vectors were designed for the ANN. Of the six approaches, the best one gave the is T$_{g}$ of 251 polymers with a standard deviation of 8 K and a maximum error of 29 K. The trained ANN also predicted the T$_{g}$ of 20 polymers which are not included in the 251 polymers with a standard deviation of 7 K and a maximum error of 21 K. 21 K.

• 한국자동차공학회논문집
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• 제12권1호
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• pp.184-189
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• 2004

In this paper, the warm forging process sequence has been determined to manufacture the warm forged product for the precision bevel gear used as the differential gear unit of a commercial automobile. The preform shape of bevel gear influences the dimensional accuracy and stiffness of final product. The aspect ratio and chamfer length are considered as design parameters to achieve adequate metal distribution in the finish forging operation. Then the optimal conditions of design parameters have been selected by artificial neural network (ANN). Finally, to verify the optimal preform shape, the experiments of the warm forging of the bevel gear have been executed. The proposed method can give more systematic and economically feasible means for designing the preform shape in metal forming process.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 가을 학술논문 발표대회
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• pp.53-54
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• 2022

There is an increasing demand for prediction of asbestos concentration which has an fatal effect on human body. While demolishing asbestos, the dust scatters and makes workers be exposed to danger. Up to this date, however, factors that particularly influences have not considered in predicting asbestos concentration. Most of the studies could not quantify the distribution of asbestos. Also, they did not use nominal data on buildings as important factors. Therefore, this study aims to build an asbestos concentration prediction model by quantifying distribution of asbestos and using nominal data of buildings based on Artificial Neural Network (ANN). This model can give significant contribution of improving the safety of workers and be useful for finding effective ways to demolish asbestos in planning.

• 한국정보시스템학회지:정보시스템연구
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• 제32권4호
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• pp.189-210
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• 2023

Purpose This study aims to investigate factors that positively influence the continuous Artificial Intelligence(AI) Learning Continuity of business major students. Design/methodology/approach To evaluate the impact of AI education, a survey was conducted among 119 business-related majors who completed a software/AI course. Frequency analysis was employed to examine the general characteristics of the sample. Furthermore, factor analysis using Varimax rotation was conducted to validate the derived variables from the survey items, and Cronbach's α coefficient was used to measure the reliability of the variables. Findings Positive correlations were observed between business major students' AI Learning Continuity and their AI Interest, AI Awareness, and Data Analysis Capability related to their majors. Additionally, the study identified that AI Project Awareness and AI Literacy Capability play pivotal roles as mediators in fostering AI Learning Continuity. Students who acquired problem-solving skills and related technologies through AI Projects Awareness showed increased motivation for AI Learning Continuity. Lastly, AI Self-Efficacy significantly influences students' AI Learning Continuity.

• International Journal of Aeronautical and Space Sciences
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• 제15권2호
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• pp.123-137
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• 2014

The aviation gas turbine is composed of many expensive and highly precise parts and operated in high pressure and temperature gas. When breakdown or performance deterioration occurs due to the hostile environment and component degradation, it severely influences the aircraft operation. Recently to minimize this problem the third generation of predictive maintenance known as condition based maintenance has been developed. This method not only monitors the engine condition and diagnoses the engine faults but also gives proper maintenance advice. Therefore it can maximize the availability and minimize the maintenance cost. The advanced gas turbine health monitoring method is classified into model based diagnosis (such as observers, parity equations, parameter estimation and Gas Path Analysis (GPA)) and soft computing diagnosis (such as expert system, fuzzy logic, Neural Networks (NNs) and Genetic Algorithms (GA)). The overview shows an introduction, advantages, and disadvantages of each advanced engine health monitoring method. In addition, some practical gas turbine health monitoring application examples using the GPA methods and the artificial intelligent methods including fuzzy logic, NNs and GA developed by the author are presented.

• 환경위생공학
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• 제16권3호
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• pp.22-27
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• 2001

It have been investigated how algal and bacterial symbiotic reaction influences on removal of organic carbon in river ecosystem. And artificial experimentation apparatus was made for algae'and bacteia'culture as lab scale. Investigating and researching minutely the change of concentration of organic carbon substrate and the change of population density of algae'and of bacteria'with this artificial experimentation apparatus, the next results could be obtained. 1. Successful decrease of DOC(dissolved organic carbon) could not be expected unless algal and bacterial biomass floe was nut formed effectively and unless biosorption was not proceeded effectively in the very culture system in which artificial synthetic wastewater was supplied continuously at constant rate. 2. In conditions of culture liquid of 1335 glucnse mg/L(type 1) and of 267 glucose mg:L(type 2), the algal dominant species was always Chlorella vulgaris in both types in which artificial synthetic wastewater were supplied continuously at constant rate and algae population density was around maximum 107 cells/mL. 3. It was around 108 ~ 107 cells/mL that the population density of heterotrophic bacterium. In culture medium systems type 1 and type 2 in which artificial wastewater were supplied continuously at constant rate, the same density appeared initially when using the population density of Escherichia coli w 3110 as indirect indicator. And this density decreased rapidly till the culturing date 35 days were passed away, while this density increased with gentle slope after same date and then the trend of change at type 2 was more severe than one at type 1. 4. When seeing such a change of population density of Escherichia coli w 3110, the growth of heterotrophic bacterium appeared as survival instinct pattern of broader requirement of nutrient at condition of low concentration of organic carbon substrate than condition of high concentration of same substrate.

• 한국IT서비스학회지
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• 제17권2호
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• pp.191-205
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• 2018

With the advancement of artificial intelligence (AI) techniques, many consumer products have adopted AI features for providing proactive and personalized services to customers. One of the most prominent products featuring AI techniques is a smart speaker. The fundamental of smart speaker is a portable wireless Internet connecting speaker which already have existed in a consumer market. By applying AI techniques, smart speakers can recognize human voices and communicate with them. In addition, they can control other connecting devices and provide offline services. The goal of this study is to identify the impact of AI techniques for customer rating to the products. We compared customer reviews of other portable speakers without AI features and those of a smart speaker. Amazon echo is used for a smart speaker and JBL Flip 4 Bluetooth Speaker and Ultimate Ears BOOM 2 Panther Limited Edition are used for the comparison. These products are in the same price range ($50~100) and selected as featured products in Amazon.com. All reviews for the products were collected and common words for all products and unique words of the smart speaker were identified. Information gain values were calculated to identify the influences of words to be rated as positive or negative. Positive and negative words in all the products or in Amazon echo were identified, too. Topic modeling was applied to the customer reviews on Amazon echo and the importance of each topic were measured by summating information gain values of each topic. This study provides a way of identifying customer responses on the AI feature and measuring the importance of the feature among diverse features of the products.