• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.225-237
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• 2022

The term "artificial intelligence" is considered a component of sophisticated technological developments, and several intelligent tools have been developed to assist organizations and entrepreneurs in making business decisions. Artificial intelligence (AI) is defined as the concept of transforming inanimate objects into intelligent beings that can reason in the same way that humans do. Computer systems can imitate a variety of human intelligence activities, including learning, reasoning, problem-solving, speech recognition, and planning. This study's objective is to provide responses to the questions: Which factors should be taken into account while deciding whether or not to use AI applications? What role do these elements have in AI application adoption? However, this study proposes a framework to explore the significance and relation of success factors to AI adoption based on the technology-organization-environment model. Ten critical factors related to AI adoption are identified. The framework is empirically tested with data collected by mail surveying organizations in Vietnam. Structural Equation Modeling is applied to analyze the data. The results indicate that Technical compatibility, Relative advantage, Technical complexity, Technical capability, Managerial capability, Organizational readiness, Government involvement, Market uncertainty, and Vendor partnership are significantly related to AI applications adoption.

• The Journal of Natural Sciences
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• v.14 no.1
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• pp.151-163
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• 2004

The landscape design was presented to a design for the theme park in Honseong. The site is located in Janchuk-li Unha-meon Hongseong-gun, Chungcheongnam-do and an area of about $1,594,001m^2$. This landscape design set the several main criteria as follows: an identity of GayanCheon's Picked Shrimps theme park, a cultural and tourist place for people, efficiency of landuse, and an environment friendly design. This GyanCheon's Picked Shrimps theme park is a multiple place for enjoying, resting, learning, and playing. An identity of this park was expressed by introducing the ocean scenery into park area which was devided 5 sub-spaces: a Place of the ocean King, an Entrance space for a Theme park, a Clock tower plaza, a Shrimp village, and a Distribution complex. Each space has the Theme about "shrimp" and is carefully connected with each other in terms of spatial sequence. By introducing diverse gathering and symbolical spaces for many kinds of events, the site could function as a cultural and tourist place of the Hongsung-gun.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.115-123
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• 2021

Pine nuts are Korea's representative nut forest products and profitable crops. However, pine nuts are harvested by climbing the trees themselves, thus the risk is high. In order to solve this problem, it is necessary to harvest pine nuts using a robot or an unmanned aerial vehicle(UAV). In this paper, we propose a deep learning based detection method for harvesting pine nut in UAV aerial images. For this, a video was recorded in a real pine forest using UAV, and a data augmentation technique was used to supplement a small number of data. As the data for 3D detection, Unity3D was used to model the virtual pine nut and the virtual environment, and the labeling was acquired using the 3D transformation method of the coordinate system. Deep learning algorithms for detection of pine nuts distribution area and 2D and 3D detection of pine nuts objects were used DeepLabV3+, YOLOv4, and CenterNet, respectively. As a result of the experiment, the detection rate of pine nuts distribution area was 82.15%, the 2D detection rate was 86.93%, and the 3D detection rate was 59.45%.

• Communications of Mathematical Education
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• v.26 no.1
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• pp.109-135
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• 2012

On the standards or elements of teaching evaluation, the Korea Institute of Curriculum and Evaluation(KICE) has carried out the following research such as : 1) development of the standards on teaching evaluation between 2004 and 2006, and 2) investigation on the elements of Teacher Knowledge. The purposes of development of evaluation standards for mathematics teaching through those studies were to improve not only mathematics teachers' professionalism but also their own teaching methods or strategies. In this study, the standards were revised and modified by analyzing the results of those studies focused on the knowledge of subject matter knowledge, knowledge of learners' understanding, teaching and learning methods and assessments, and teaching contexts. For this purpose, the part of subject matter knowledge was consisted of four evaluation domains such as the knowledge of curriculum reconstruction, knowledge of mathematical contents, methodological knowledge, mathematical value. The part of Learners' unders tanding included the evaluation domains such as students' intellectual and achievement level, students' misconception in math, students' motivation on learning, students' attitude on mathematics learning, and students' learning strategies. The part of teaching methods and evaluation was consisted of seventh evaluation domains such as instruction involving instructional goal and content, instruction involving problem-solving activity, instruction involving learners' achievement level and attitude, instruction on communication skills, planning of assessment method and procedure, development on assessment tool, application on assessment result in class were new established. Also, the part of teaching context was consisted of four evaluation domains such as application of instructional tools and materials, commercial manipulatives, environment of classroom including distribution and control of class group, atmosphere of classroom, management of teaching contexts including management of student. According to those evaluation domains of each teacher knowledge, elements on teaching evaluation focused on the teacher's knowledge were established using the instructional evaluation framework, which is developed in this study, including the four areas of obtaining, planning, acting, and reflecting.

• Korean Institute of Interior Design Journal
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• v.22 no.3
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• pp.195-204
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• 2013

Today, the children's museum evolved from place of exhibition for seeing and feeling, to that of exhibition for searching and touching, or so-called the hands-on exhibition. This will allow for grabbing the interest from children and provide an opportunity for learning by an actual experience at this intellectual and benign environment. But in this modern society that constantly undergoes evolution even as we speak, it is not an easy task to bring our children to museums, because they are vastly exposed to various media. Moreover, if the children who visited museums carelessly bypass the specific areas intended for exhibition, the educational purpose of "enhanced learning effect with hands-on experience" is easily underachieved. According to children's visual stimuli, their behavioral charactoristics are appeared to freewill curiosity but they show shorter elapsed time(impermanence), intensity(stubbornness), frequent occurrence(frequentness) and changeable (translatability). So, We need Improvement of visual image affordance through the measurement of stay time. Firstly, five factors are extracted by factor analysis on twenty questions based on visual image factors; Color accessability and Satistaction(factor1), brightness and color harmony(factor2), feeling on harmonization of color and stay time(factor3), simplex & complex of space(factor4), feeling on scale(factor5) Secondly, the following result are derived through a distribution chart on an exhibition room of K-museum. As shown above, this study based on various analyzed aspects proposes the directions of a color image plan to improve stay time in exhibition space of children museums with a hope to support educational goals of experience education-focused children museums.

• Korean Institute of Interior Design Journal
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• v.15 no.2 s.55
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• pp.138-149
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• 2006

A museum's collections is fundamental factors to construct important activity of museum performing a role as cultural facility for learning, education and research. Therefore, conservation of collections through appropriate environments is previously established in step of planing a museum. Hereby, the purpose of this study is to set up the classification of collections and suggest a useful guidance of the storage division in a domestic museum. The results of this study are as follows. First, the main factors of deterioration are temperature and relative humidity in a museum storage, so classification of collections should be set up according to the objective standards of these factors. Second, the classification of collections can be performed as follow: the group for nonorganic materials subdivide metal, chinaware, earthenware, and jade stone, the group for organic materials subdivide leather hair paper fabric, bone horn shell mound and wood herbage and the group for composed materials. Third, for storage division of a domestic museum, basically has to consider that it is reasonable to plan $4{\sim}5$ storages in metal, jade stone, chinaware earthenware, and organic materials of $1{\sim}2$ units in case of a serial of history like archaeological, antique museum. And in case of folk relics of modern and contemporary arts are collected, it is reasonable to plan over 5 storages add composed materials to foregoing classification.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.479-486
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• 2021

This study aims to explore the relationships between strategic planning, strategic maneuverability, and firm performance in the current dynamic business environment. It employs a quantitative research method and reports on a survey, using a questionnaire, of service companies in Indonesia's oil and gas industry. Of the 337 companies selected by simple random sampling from a vendor database, responses were received from 70 companies. The analysis was performed using Partial Least Square Structural Equation Modeling and SmartPLS software. The analysis consisted of descriptive statistics, evaluation of the measurement model, evaluation of the structural model, and hypotheses testing. The results show that both strategic planning and strategic maneuverability have a positive relationship with firm performance. In addition, there is a positive relationship between strategic planning and firm performance through the mediating role of strategic maneuverability. The findings suggest that the organizational agility, organizational flexibility, and organizational responsiveness that constitute strategic maneuverability have a positive direct and indirect effect on firm performance, namely financial performance, customer performance, internal process performance, and learning and growth. This study contributes to the strategic management literature and the theory of maneuvers by providing empirical evidence on the relationship between strategic planning, strategic maneuverability, and firm performance.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.3
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• pp.1-17
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• 2023

Korea's natural parks are managed by dividing them into four use districts: nature preservation district, natural environment district, cultural heritage district, and park village district within the park under the goal of 'conservation and sustainable use of natural parks'. However, the use districts divided in this way are designated by reflecting the results derived from the simple drawing overlapping method, and there is a limit in that objective and scientific evidence for this is insufficient. In addition, in Taeanhaean National Park, the case of this study, only a very small area of less than 1% of the nature preservation district is designated, and the natural environment district that serves as a buffer space is designated on an excessively wide scale, making it difficult to efficiently manage the national park. Therefore, the use district is not fulfilling its role. In this study, the purpose of this study was to present a method for analyzing the spatial characteristics of natural parks using environmental indicators and unsupervised learning analysis methods to set the use districts of natural parks. In this study, evaluation indicators that can evaluate the natural and human environments were derived, and the distribution patterns for each indicator were analyzed. Afterwards, by applying Self-Organizing Map (SOM) analysis, one of the unsupervised learning analysis methods, districts with similar characteristics were derived in Taeanhaean National Park, and the characteristics of each district were analyzed. As a result of the study, 7 districts with different characteristics were derived in Taeanhaean National Park, and by examining the contribution of each indicator together, it was possible to reveal that each district had different representative characteristics even though it was an adjacent area. This study evaluated natural parks by comprehensively considering the indicators of the natural and human environments. In addition, the SOM method used in the study is meaningful in that it can provide scientific and objective grounds for the existing zoning and apply it to the management plan.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.221-229
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• 2023

Urbanization and industrialization have significantly increased the amount of solid waste produced in recent decades, posing considerable disposal problems and environmental burdens. The practice of waste utilization in concrete has gained popularity among construction practitioners and researchers for the efficient use of resources and the transition to the circular economy in construction. This study employed Lytag aggregate, an environmentally friendly pulverized fuel ash-based lightweight aggregate, as a substitute for natural coarse aggregate. At the same time, fly ash, an industrial by-product, was used as a partial substitute for cement. Concrete mix M20 was experimented with using fly ash and Lytag lightweight aggregate. The percentages of fly ash that make up the replacements were 5%, 10%, 15%, 20%, and 25%. The Compressive Strength (CS), Split Tensile Strength (STS), and deflection were discovered at these percentages after 56 days of testing. The concrete cube, cylinder, and beam specimens were examined in the explorations, as mentioned earlier. The results indicate that a 10% substitution of cement with fly ash and a replacement of coarse aggregate with Lytag lightweight aggregate produced concrete that performed well in terms of mechanical properties and deflection. The cementitious composites have varying characteristics as the environment changes. Therefore, understanding their mechanical properties are crucial for safety reasons. CS, STS, and deflection are the essential property of concrete. Machine learning (ML) approaches have been necessary to predict the CS of concrete. The Artificial Fish Swarm Optimization (AFSO), Particle Swarm Optimization (PSO), and Harmony Search (HS) algorithms were investigated for the prediction of outcomes. This work deftly explains the tremendous AFSO technique, which achieves the precise ideal values of the weights in the model to crown the mathematical modeling technique. This has been proved by the minimum, maximum, and sample median, and the first and third quartiles were used as the basis for a boxplot through the standardized method of showing the dataset. It graphically displays the quantitative value distribution of a field. The correlation matrix and confidence interval were represented graphically using the corrupt method.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.