Journal of the Korean Institute of Traditional Landscape Architecture
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v.33
no.2
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pp.49-57
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2015
The purpose of this study is to provide the visual landscape modelling on Josun royal tombs and surrounding. The visual landscape of traditional heritage is illustrated by the main view points of analysis. This analysis examines limited view points and cannot reflect a reality of environments. Nowadays various equipments and methodologies are developed for the visual landscape research. This study used new tools for analysis which are Sketch up (3D simulation) and mini helicopter (UAV). With those tools, this research examines not only view points of the analysis but also axis views and disincentive environments as a complex analysis. First of all, the research examined 3D modelling for the virtual simulation and drew coordinates and routes for the UAV operating. Secondly, UAV followed this routes and took linear and continuous views that are real scenes. As a result, it drew 3D simulation could illustrate and control the changing of environments such as the forest density and seasonal variations. Thus, comparing both of them shows efficiently landscape analysis. Thirdly, the study compared virtual and real landscape. Using this 3D modelling, this paper able to elaborate heritage environment and surrounding which omitted by view point analysis. Although this study has limitation practice and exercise on the field, the results and suggestions contribute to the various historic heritage managements and conservations. Moreover, it helps to explain the complex and dimensional landscape analysis.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.11
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pp.305-313
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2019
Recently, spatial information is being constructed actively based on the images obtained by drones. Because occlusion areas occur due to buildings as well as many obstacles, such as trees, pedestrians, and banners in the urban areas, an efficient way to resolve the problem is necessary. Instead of the traditional way, which replaces the occlusion area with other images obtained at different positions, various models based on deep learning were examined and compared. A comparison of a type of feature descriptor, HOG, to the machine learning-based SVM, deep learning-based DNN, CNN, and RNN showed that the CNN is used broadly to detect and classify objects. Until now, many studies have focused on the development and application of models so that it is impossible to select an optimal model. On the other hand, the upgrade of a deep learning-based detection and classification technique is expected because many researchers have attempted to upgrade the accuracy of the model as well as reduce the computation time. In that case, the procedures for generating spatial information will be changed to detect the occlusion area and replace it with simulated images automatically, and the efficiency of time, cost, and workforce will also be improved.
Hyun, Young Geun;Lim, Jung Teak;Han, Jeong Hyeon;Chae, Uri;Lee, Gi-Hyun;Ko, Jin Deuk;Cho, Young Hee;Lee, Joo Yeoun
Journal of Digital Convergence
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v.18
no.11
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pp.215-226
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2020
Chatbot is emerging as an important interface window for business. This change is due to the continued development of chatbot-related research from NLP to NLU and NLG. However, the reality is that the methodological study of drawing domain knowledge and developing it into a user-friendly interactive interface is weak in the process of developing chatbot. In this paper, in order to present the process criteria of chatbot development, we applied it to the actual project based on the methodology presented in the previous paper and improved the development methodology. In conclusion, the productivity of the test phase, which is the most important step, was improved by 33.3%, and the number of iterations was reduced to 37.5%. Based on these results, the "3 Phase and 17 Tasks Development Methodology" was presented, which is expected to dramatically improve the trial and error of the chatbot development.
Korean Journal of Construction Engineering and Management
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v.10
no.3
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pp.32-41
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2009
In the execution of construction management, such pre-design steps as a planning stage, a basic design stage, and a work design stage are regarded as more important than an actual construction stage. However, the manpower input criterion from the aspect of construction management price standard in the Construction Engineering Management Law does not attach weight to the pre-design stage. In this regard, the aim of this study was to examine the propriety of manpower input in the pre-design stage of construction management and then present an improvement strategy of it. For this, the investigator examined the criterion of service price prescribed in the Construction Engineering Management Law and then comparatively analyzed four sites of construction management services. Study findings are as follows: 1) the actual state of manpower input based on the stepwise average price criterion of construction management service is presented with such steps as the newly established planning step (6.6%), the basic design stage (3.9%$\rightarrow$5.6%), the practical design stage(7.6%$\rightarrow$13.5%), the construction stage (88.5%$\rightarrow$64.0%), and the newly established maintenance stage (10.3%). The average price criterion is classified by total construction expenses and calculated by improved rates and stage; and 2) the three-step criterion of the Construction Engineering Management Law is classified into five stages including the planning stage and the maintenance stage by dividing it with the stepwise construction businesses. Study findings show that the calculation of price criterion in the actual site of construction management services must be operated in a practical and flexible manner and the systematic improvement of stepwise manpower input must be carried out actually.
Han, Daegun;Bae, Young Hye;Kim, Tae-Yong;Jung, Jaewon;Lee, Choongke;Kim, Hung Soo
Journal of Wetlands Research
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v.22
no.4
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pp.245-256
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2020
The purpose of this study is to evaluate the technological competitiveness of the environmental industry with developed countries in order to establish an international market expansion strategy of the Korean environmental industry and technology. In order to evaluate the competitiveness of the environmental industry and technology, core technologies were classified by the environmental industry sectors based on the classification system of the domestic and international environmental industry and technology. After developing the evaluation index data, the Delphi analysis, journal and patent analysis, as well as the export and import analysis were carried out and the standardization analysis was performed on the index data. Moreover, the weights of each evaluation index were calculated using the AHP(Analytic Hierarchy Process) method and the evaluation results of competitiveness of the environmental industry and technology in Korea, the United States, the United Kingdom, Germany, and France were derived. As a result of the evaluation, the United States was rated with the highest technological competitiveness in all the environmental industry sectors, while Korea got the lowest technological competitiveness rating compared to the 4 developed countries. In particular, Korea got the lowest level of technological competitiveness in the sector of multi-media environmental management and development for a sustainable social system. Therefore, in order for the Korean environmental industry and technology to enter the global advanced market, it is necessary to strengthen the competitiveness through the development of the fourth environmental industry based on IoT(Internet of Things), cloud, big data, mobile, and AI(Artificial Intelligence), which are currently the country's domestic strengths.
Journal of the Korean Institute of Traditional Landscape Architecture
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v.33
no.3
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pp.95-102
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2015
This study conducted the survey on the resources of traditional villages based on AHP in the subjects with the specialists in Korea and China to seek the resource evaluation standards to apply the preservation and development of traditional villages, and the differences of the importance on the resources among the specialists in both countries. We classified three levels of evaluation items to aim the deductions of the importance and priority in the resources of traditional villages. Upon the analysis results, natural resources were important in the level 1; environmental, historical, facility resources were important in the level 2; and the factors such as air, topography, traditional houses, agricultural landscape, shared community facilities, interchanges between urban and rural areas, family activities, and so on were important in the level 3. The factors that both Korean and Chinese groups evaluated as the most important ones were the same. In terms of overall importance by evaluation items, the factors such as air, water quality, noise, traditional houses, topography, shared community facilities, and so on were rated as relatively important in both Korean and Chinese groups. That is, the traditional villages have the necessity to preserve the cultural resources like their duties, however, it is required to control the natural environment with good quality preferentially. This study results can compare the importance on the resources of traditional village between Korea and China. Moreover, with calculation of the priority and scores for the preservation and management of traditional villages, they are expected to be used as the tool to apply the quantitative data in the evaluation process of traditional village resources in both countries.
Aging and severe environments are major causes of damage in reinforced concrete (RC) structures such as buildings and bridges. Deterioration such as concrete cracks, corrosion of steel, and deformation of structural members can significantly degrade the structural performance and safety. Therefore, effective and easy-to-use methods are desired for repairing and strengthening such concrete structures. Various methods for strengthening and rehabilitation of RC structures have been developed in the past several decades. Recently, FRP composite materials have emerged as a cost-effective alternative to the conventional materials for repairing, strengthening, and retrofitting deteriorating/deficient concrete structures, by externally bonding FRP laminates to concrete structural members. The main purpose of this study is to investigate the effectiveness of adaptive neuro-fuzzy inference system (ANFIS) in predicting behavior of circular type concrete column retrofitted with FRP. To construct training and testing dataset, experiment results for the specimens which have different retrofit profile are used. Retrofit ratio, strength of existing concrete, thickness, number of layer, stiffness, ultimate strength of fiber and size of specimens are selected as input parameters to predict strength, strain, and stiffness of post-yielding modulus. These proposed ANFIS models show reliable increased accuracy in predicting constitutive properties of concrete retrofitted by FRP, compared to the constitutive models suggested by other researchers.
Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.
As the Internet developed, various and complex cyber attacks began to emerge. Various detection systems were used outside the network to defend against attacks, but systems and studies to detect attackers inside were remarkably rare, causing great problems because they could not detect attackers inside. To solve this problem, studies on the lateral movement detection system that tracks and detects the attacker's movements have begun to emerge. Especially, the method of using the Remote Desktop Protocol (RDP) is simple but shows very good results. Nevertheless, previous studies did not consider the effects and relationships of each logon host itself, and the features presented also provided very low results in some models. There was also a problem that the model could not explain why it predicts that way, which resulted in reliability and robustness problems of the model. To address this problem, this study proposes an interpretable RDP-based lateral movement detection system using page rank algorithm and SHAP(Shapley Additive Explanations). Using page rank algorithms and various statistical techniques, we create features that can be used in various models and we provide explanations for model prediction using SHAP. In this study, we generated features that show higher performance in most models than previous studies and explained them using SHAP.
Journal of the Korea Institute of Information Security & Cryptology
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v.31
no.6
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pp.1215-1225
/
2021
Although Artificial Intelligence (AI) techniques have shown impressive performance in various fields, they are vulnerable to adversarial examples which induce misclassification by adding human-imperceptible perturbations to the input. Previous studies to defend the adversarial examples can be classified into three categories: (1) model retraining methods; (2) input transformation methods; and (3) adversarial examples detection methods. However, even though the defense methods against adversarial examples have constantly been proposed, there is no research to classify the type of adversarial attack. In this paper, we proposed an adversarial attack family classification method based on dimensionality reduction and clustering. Specifically, after extracting adversarial perturbation from adversarial example, we performed Linear Discriminant Analysis (LDA) to reduce the dimensionality of adversarial perturbation and performed K-means algorithm to classify the type of adversarial attack family. From the experimental results using MNIST dataset and CIFAR-10 dataset, we show that the proposed method can efficiently classify five tyeps of adversarial attack(FGSM, BIM, PGD, DeepFool, C&W). We also show that the proposed method provides good classification performance even in a situation where the legitimate input to the adversarial example is unknown.
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