• The Journal of Korean Association of Computer Education
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• v.22 no.1
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• pp.87-98
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• 2019

It is easy to assume that contradictions are logically incorrect or empty sets that have no solvability. This dilemma, which can not be done, is difficult to solve because it has to solve the contradiction hidden in it. Paradoxically, therefore, contradiction resolution has been viewed as an innovative and creative problem-solving. TRIZ, which analyzes the solution of the problem from the perspective of resolving contradictions, has been used for people rather than computers. The Butterfly model, which analyzes the problem from the perspective of solving the contradiction like TRIZ, analyzed the type of contradiction problem using symbolic logic. In order to apply an appropriate concrete solution strategy for a given contradiction problems, we designed the Butterfly algorithm based on decision making tree. We also developed a visualization tool based on Python tkInter to find concrete solution strategies for given contradiction problems. In order to verify the developed tool, the third grade students of middle school learned the Butterfly algorithm, analyzed the contradiction of the wooden support, and won the grand prize at an invention contest in search of a new solution. The Butterfly algorithm developed in this paper systematically reduces the solution space of contradictory problems in the beginning of problem solving and can help solve contradiction problems without trial and errors.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1679-1692
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• 2023

South Korea is a country that emits a large amount of pollutants as a result of population growth and industrial development and is also severely affected by transboundary air pollution due to its geographical location. As pollutants from both domestic and foreign sources contribute to air pollution in Korea, the location of air pollutant emission sources is crucial for understanding the movement and distribution of pollutants in the atmosphere and establishing national-level air pollution management and response strategies. Based on this background, this study aims to effectively acquire spatial information on domestic and international air pollutant emission sources, which is essential for analyzing air pollution status, by utilizing high-resolution optical satellite images and deep learning-based image segmentation models. In particular, industrial parks and quarries, which have been evaluated as contributing significantly to transboundary air pollution, were selected as the main research subjects, and images of these areas from multi-purpose satellites 3 and 3A were collected, preprocessed, and converted into input and label data for model training. As a result of training the U-Net model using this data, the overall accuracy of 0.8484 and mean Intersection over Union (mIoU) of 0.6490 were achieved, and the predicted maps showed significant results in extracting object boundaries more accurately than the label data created by course annotations.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1451-1461
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• 2021

Objective: Adequate methods of combining T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) to assess complete response (CR) to chemoradiotherapy (CRT) for rectal cancer are obscure. We aimed to determine an algorithm for combining T2WI and DWI to optimally suggest CR on MRI using visual assessment. Materials and Methods: We included 376 patients (male:female, 256:120; mean age ± standard deviation, 59.7 ± 11.1 years) who had undergone long-course CRT for rectal cancer and both pre- and post-CRT high-resolution rectal MRI during 2017-2018. Two experienced radiologists independently evaluated whether a tumor signal was absent, representing CR, on both post-CRT T2WI and DWI, and whether the pre-treatment DWI showed homogeneous hyperintensity throughout the lesion. Algorithms for combining T2WI and DWI were as follows: 'AND,' if both showed CR; 'OR,' if any one showed CR; and 'conditional OR,' if T2WI showed CR or DWI showed CR after the pre-treatment DWI showed homogeneous hyperintensity. Their efficacies for diagnosing pathologic CR (pCR) were determined in comparison with T2WI alone. Results: Sixty-nine patients (18.4%) had pCR. AND had a lower sensitivity without statistical significance (vs. 62.3% [43/69]; 59.4% [41/69], p = 0.500) and a significantly higher specificity (vs. 87.0% [267/307]; 90.2% [277/307], p = 0.002) than those of T2WI. Both OR and conditional OR combinations resulted in a large increase in sensitivity (vs. 62.3% [43/69]; 81.2% [56/69], p < 0.001; and 73.9% [51/69], p = 0.008, respectively) and a large decrease in specificity (vs. 87.0% [267/307]; 57.0% [175/307], p < 0.001; and 69.1% [212/307], p < 0.001, respectively) as compared with T2WI, ultimately creating additional false interpretations of CR more frequently than additional identification of patients with pCR. Conclusion: AND combination of T2WI and DWI is an appropriate strategy for suggesting CR using visual assessment of MRI after CRT for rectal cancer.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.389-395
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• 2024

This study aims to deeply analyze the military strategies and tactics used in the battles between Israel and Hamas, to understand the military approaches, technical capabilities, and their impact on the outcomes of the conflict. To achieve this, methodologies such as literature review, data analysis, and case studies were utilized. The research findings confirm that Hamas employed asymmetric tactics, such as rocket attacks and surprise attacks through underground tunnels, to counter Israel's military superiority. On the other hand, Israel responded to Hamas's attacks with the Iron Dome interception system and intelligence-gathering capabilities, but faced difficulties due to Hamas's underground tunnel network. After six months of fighting, the casualties in the Gaza Strip exceeded 30,000, and more than 1.7 million people became refugees. Israel also suffered over 1,200 deaths. Militarily, neither side achieved a decisive victory, resulting in a war of attrition. This study suggests that the Israel-Hamas war exemplifies the complexity of modern asymmetric warfare. Furthermore, it recommends that political compromise between the two sides and active mediation efforts by the international community are necessary for the peaceful resolution of the Israel-Palestine conflict.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1985-1999
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• 2021

The purpose of this study is to apply urban heat island reduction techniques(green roof, cool roof, and cool pavements using heat insulation paint or blocks) recommended by the Environmental Protection Agency (EPA) to our study area and determine their actual effects through a comparative analysis between land cover objects. To this end, the area of Mugye-ri, Jangyu-myeon, Gimhae, Gyeongsangnam-do was selected as a study area, and measurements were taken using a drone DJI Matrice 300 RTK, which was equipped with a thermal infrared sensor FLIR Vue Pro R and a visible spectrum sensor H20T 1/2.3" CMOS, 12 MP. A total of nine heat maps, land cover objects (711) as a control group, and heat island reduction technique-applied land covering objects (180) were extracted every 1 hour and 30 minutes from 7:15 am to 7:15 pm on July 27. After calculating the effect values for each of the 180 objects extracted, the effects of each technique were integrated. Through the analysis based on daytime hours, the effect of reducing heat islands was found to be 4.71℃ for cool roof; 3.40℃ for green roof; and 0.43℃ and -0.85℃ for cool pavements using heat insulation paint and blocks, respectively. Comparing the effect by time period, it was found that the heat island reduction effect of the techniques was highest at 13:00, which is near the culmination hour, on the imaging date. Between 13:00 and 14:30, the efficiency of temperature reduction changed, with -8.19℃ for cool roof, -5.56℃ for green roof, and -1.78℃ and -1.57℃ for cool pavements using heat insulation paint and blocks, respectively. This study was a case study that verified the effects of urban heat island reduction techniques through the use of high-resolution images taken with drones. In the future, it is considered that it will be possible to present case studies that directly utilize micro-satellites with high-precision spatial resolution.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of the Korean Graphic Arts Communication Society
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• v.30 no.3
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• pp.89-114
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• 2012

For as to world, the concern about the environment problem is enhanced than any other time in the past because of being 21 century. And the environment problem is highlighted as the world-wide issue. The time of the environment problem intimidates the alive of the mankind and presence of an earth over the time. It becomes the essentiality not being selection in the personal living or the economical viewpoint now to prepare for the climatic modification. As to the company management, the green growth period which it excludes the environment management considering an environment, cannot carry on the company the continued management comes. That is, in the change center of the management paradigm, there is the environment management. Nearly, the greenhouse gas which the publication industry is the environmental toxic material like all industries is generated. The greenhouse gas is ejected in the process of running the manufacturing process and print shop of the various kinds material used as the raw material of the book. Particularly, the tree felling for getting the material of the paper is known to reach the direct influence on the global warming. This study does according to an object it considers and organizes the environment parameter based on this kind of fact as to the publication industry. And it is determined as the reference which is used as the basic materials preparing the case that carbon exhaust right transaction(CAP and TRADE) drawing are enforced in all industries and is sustainable the management of the publication industry and reduces the environmental risk among the company many risk management elements and plans and enforces the publication related policy that there is a value. In the printing publication industry, this study tried to inquire into elements discharging the environmental pollutant or the greenhouse gas. Additionally, in the printed publication production process, it tried to inquire into the effort for an environment-friendly and necessity at the printing paper and the printers ink, regarded as the element discharging the greenhouse gas all kinds of the printing materials, operation of the print shop and all kinds of the machines and recycle process, and etc. These considerations make these industrial field employees aware of the significance about a conservation and environmental protection. They try to give a help in the subsequent study producing quantitatively each environmental parameter emission of green house gas. This makes the calculation of the relative $CO_2$ output reproached ultimately possible. Meanwhile, in a sense, many research protects and improving an environment in connection with the contents of research at the printing publication industrial field is in progress. There will be the voluntary human face that it has to protect an environment but this can not do by the outside factor according to all kinds of environment related law and regulation. Anyway, because of acting on company management as the factor of oppression, the increase of this environment-related correspondence cost could know that the research that the environment loading relates with a procurement and development, environment management system introduction, quality control standard, including, normalizing including a material, and etc. through the part of the effort to reduce the cost low was actively in progress. As to the green growth era, as follows, this paper prescribed the subject and alternative of the print publication industry. It is surrounded by the firstly new digital environment and the generation of the subject. And secondly the printing industry is caused by the point of time when the green growth leaves by the topic which is largest in the global industry and it increases. The printing publication industry has to prepare the bridgehead for the environment-friendly green growth as the alternative for this resolution with first. The support blown in each industry becomes the obligation not being selection. Prestek in which the print publishing was exposed to spend many energies and which is known as the practice of the sustainable print publishing insisted that it mentioned importance of the green printing through the white pages in 2008 and a company had to be the green growth comprised through the environment-friendly activity. The core management for the sustainable printing publication industry presented from Presstack white pages is compacted to 4 words that it is a remove, reduce, recover, and recycle. Second, positively the digital printing(POD) system should be utilized. In the worldwide print out market, the digital printing area stops at the level of 10% or so but the change over and growth of the market of an analog-to-digital will increase rapidly in the future. As to the CEO Jeff Hayes of the Infoland, the offset print referred to that it of the traditional method got old and infirm with the minor phase of the new printing application like the customer to be wanted publication and the print of the digital method led the market. In conclusion, print publishers have to grasp well the market flow in the situation where a digitalization cannot be generalized and a support cannot avoid. And it keeps pace with the flow of the digital age and the recognition about the effort for the development and environment problem have to be raised. Particularly, the active green strategy is employed for the active green strategy.

• Korean small business review
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• v.42 no.1
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• pp.79-105
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• 2020

While individual enterprises with different objectives each other within supply chains require a variety of resources to achieve their own seeking goals and performances, it is necessary to form interdependent relationships among the enterprises to secure the resources what they need, as the individual enterprises are supposed to have limitations on such as time, space and cost to secure all the resources. In this process, conflict possibilities rise and opportunistic behaviors increase due to those environmental factors such as unbalanced information among enterprises, limited rationality, pursuit of interests, and risk aversion. Those existing studies on conflicts in the field of supply chains have limitations in that they failed to present specific conflict management strategies based on the conflict types from the perspective of the conflict resolution mechanism as the studies have made only focused on investigating the causes of conflicts and the impact of conflicts on performance. In this study, therefore, it used the TKI model of Kilmann and Thomas(1977) to subdivide the conflict management strategies in the process of transactions within supply chains by enterprises, and looked into the impact on partnership and performance according to each strategy. As the results, it showed that those types of conflict management strategies such as concession type and cooperation type had a positive(+) impact on the relationship commitment as a factor of partnership, and it was identified that the relationship commitment had a positive(+) impact on performance. In other words, it can be considered that the enterprises making use of the concession type & the cooperation type conflict management strategies under the situation of conflict would be able to have a very positive impact on their performances if they can make good relationship commitment such as investments in and efforts for the sustainable relationship along with the conflict management, while recognizing the importance of relationship. The most important meaning of this study lies on in terms of that it would be contributable to strengthening the partnership between enterprises and minimizing the risk of supply chains caused by conflicts through these results from the study.