• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.687-693
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• 2006

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.

• Asia Marketing Journal
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• v.9 no.2
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• pp.97-129
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• 2007

The critical link between consumer-based internet ordering and the delivery of the product to the consumer is a key success factor in online shopping. Market areas of online shopping company implies the range of space where products ordered from online shopping can be physically delivered to customers distributed over space with reasonable shipping cost and lead time through the physical distribution network. The average rate of growth in online shopping is 36% per year in Korea for the last 5 years. But there are no maps available that describe sales/delivery density of online shopping, few researches are focused on the short-term/long-term adaptation to demand increase by online shopping. In this paper (1) Maps of trade area are described indicating the sales/delivery density around the nation. (2) Empirical researches suggested that short-term adaptation to demand increase resulted in price reduction and service in enhancement of service quality in local transportation. But the long-term adaptation on the parts of parcel delivery industry are to be investigated in future researches.

• Smart Media Journal
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• v.12 no.10
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• pp.55-62
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• 2023

Innovation and change are occurring rapidly in the agriculture and livestock industry, and new technologies such as smart bams are being introduced, and data that can be used to control equipment is being collected by utilizing various sensors. However, there are various challenges in the operation of bams, and virtual sensor technology is needed to solve these challenges. In this paper, we define various data items and sensor data types used in livestock farms, study cases that utilize virtual sensors in other fields, and implement and design a virtual sensor system for the final smart livestock farm. MBE and EVRMSE were used to evaluate the finalized system and analyze performance indicators. As a result of collecting and managing data using virtual sensors, there was no obvious difference in data values from physical sensors, showing satisfactory results. By utilizing the virtual sensor system in smart livestock farms, innovation and efficiency improvement can be expected in various areas such as livestock operation and livestock health status monitoring. This paper proposes an innovative method of data collection and management by utilizing virtual sensor technology in the field of smart livestock, and has obtained important results in verifying its performance. As a future research task, we would like to explore the connection of digital livestock using virtual sensors.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.1-11
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• 2023

Breast cancer is the disease that affects women the most worldwide. Due to the development of computer technology, the efficiency of machine learning has increased, and thus plays an important role in cancer detection and diagnosis. Deep learning is a field of machine learning technology based on an artificial neural network, and its performance has been rapidly improved in recent years, and its application range is expanding. In this paper, we propose a DNN-SVM hybrid model that combines the structure of a deep neural network (DNN) based on transfer learning and a support vector machine (SVM) for breast cancer classification. The transfer learning-based proposed model is effective for small training data, has a fast learning speed, and can improve model performance by combining all the advantages of a single model, that is, DNN and SVM. To evaluate the performance of the proposed DNN-SVM Hybrid model, the performance test results with WOBC and WDBC breast cancer data provided by the UCI machine learning repository showed that the proposed model is superior to single models such as logistic regression, DNN, and SVM, and ensemble models such as random forest in various performance measures.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.21-27
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• 2023

As a means of helping ships navigate safely, navigational aids in operation in the maritime envirionment require periodic management, and due to the nature of the environment, it is difficult to visually check the exact state. As a result, the smart navigation aid system, which improves route safety and operational efficiency, utillizes expertise including sensors, communications, and information technology, unlike general route markings. The communication environment of the smart navigation aid system, which aims to ensure the safety of the navigators operating the ship and the safety of the ship, uses a wireless communication network in accordance with the marine environment. The ship collects the information necessary for the maritime environment on the land and operates. In this process, there is a need to consider the wireless communication security guideline. Basically, based on IHO S-100 a standard for facilitating data exchange and SECOM, which provides an interface for safe communication. This paper research a security system for safe communication in a maritime environment. The security system for the basic interface based on the document was presented, and there were some vulnerabillties to data exchange due to the wireless communication characteristics of the maritime environment, and the user authetication part was added considering the vulnerability that unauthorized users can access the service.

• Journal of the Korea Organic Resources Recycling Association
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• v.32 no.2
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• pp.15-25
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• 2024

In this study, the regeneration effect of pressurized water and ultrasonic cleaning was investigated for contaminated filter cloth from the sewage sludge filter press process. For this purpose, contaminated filter cloth was collected from a 3-ton sewage sludge hydrothermal carbon treatment filter press. First, the contamination characteristics were analyzed. According to the location of the filter cloth, air permeability and unit mass were measured, and compared with the values of a new filter cloth. Next, the results were mapped over the entire area to evaluate the contamination characteristics. Finally, pressure cleaning at 3 bar and ultrasound at frequencies of 34, 76, 120, and 168 kHz were performed on the contaminated filter cloth. In addition, the cleaning efficiency was evaluated by 3 levels of contamination degree. As a result, pore contamination occurred mainly at the bottom and both sides of the filter cloth, where the filter material was continuously injected and compressed. Surface contamination appeared evenly over the entire area. As a result of washing, air permeability increased by 1.3-3.1%p and contaminant removal was by 2.7-4.4% under pressure. In ultrasonic cleaning, air permeability increased by 12.5-61.5%p and contaminants were removed by 2.7-29.2%. In ultrasonic cleaning the lower the frequency, the higher air permeability and contaminant removal rate. Also, The higher pore contamination level, the better the air permeability improvement and contaminant removal.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.11-20
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• 2024

In this paper, we propose the BAG (Bit-width Aware Generator) and the Intermediate Layer Knowledge Distillation using Channel-wise Attention to reduce the knowledge gap between a quantized network, a full-precision network, and a generator in GDFQ (Generative Data-Free Quantization). Since the generator in GDFQ is only trained by the feedback from the full-precision network, the gap resulting in decreased capability due to low bit-width of the quantized network has no effect on training the generator. To alleviate this problem, BAG is quantized with same bit-width of the quantized network, and it can generate synthetic images, which are effectively used for training the quantized network. Typically, the knowledge gap between the quantized network and the full-precision network is also important. To resolve this, we compute channel-wise attention of outputs of convolutional layers, and minimize the loss function as the distance of them. As the result, the quantized network can learn which channels to focus on more from mimicking the full-precision network. To prove the efficiency of proposed methods, we quantize the network trained on CIFAR-100 with 3 bit-width weights and activations, and train it and the generator with our method. As the result, we achieve 56.14% Top-1 Accuracy and increase 3.4% higher accuracy compared to our baseline AdaDFQ.

• Journal of the Korean Society of Earth Science Education
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• v.17 no.1
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• pp.34-48
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• 2024

With the global rise in interest in competency-based education, the Ministry of Education of the Republic of Korea outlined six core competencies in the 2015 revised curriculum, essential for future society's 'creative and convergent talent'. This study introduces an HTE-STEAM constellation education program designed to develop the core competencies outlined in the 2015 revised curriculum and address the limitations of hands-on astronomy education. The program's effectiveness was assessed through a pilot test. The program was implemented at G Library, an out-of-school education site in Cheongju-si, Chungcheongbuk-do, targeting students from 3rd to 6th grade. The study's results include: First, the HTE-STEAM program significantly impacted all aspects of the STEAM attitude test except for 'self-concept', particularly influencing 'science and engineering career choice', 'consideration', and 'communication'. Thus, it has led to positive outcomes in the cultivation of future society's core competencies, including 'creative thinking skills', 'communication skills', and 'community skills'. Secondly, the HTE-STEAM constellation education program, despite covering the challenging concept of spacetime, was deemed easy by many students. Observations of students applying the spatial concepts they learned by using teaching aids suggest that the program was effective in enhancing students' understanding of the spatial structure of the sky and the universe. Additionally, this program aligns with the 2022 curriculum's updated standards for understanding the sky's spatial structure. Consequently, the HTE-STEAM constellation education program positively cultivates future society's core competencies and serves as a valuable complement to night observation practices in schools.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.4
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• pp.45-55
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• 2024

This study aims to distinguish between utilitarian walking and leisure walking activities and analyze the correlation between these types of walking and the walking environment. To measure the walking environment, we utilized Google Street View (GSV) and employed semantic segmentation deep learning techniques to quantitatively assess urban walking environment elements as perceived by pedestrians. A survey was conducted to measure utilitarian walking, leisure walking, and perceived walking environment satisfaction, collecting valid responses from 192 participants. Using the survey data, we visualized utilitarian walking, leisure walking, and perceived walking environment satisfaction, and analyzed the correlation between these variables and the walkability scores. The results indicated that leisure walking had a significant positive correlation with walkability (Pearson's r = 0.121, p-value = 0.012), while there was no significant correlation between utilitarian walking and walkability (Pearson's r = 0.093, p-value = 0.055). These findings suggest that people prioritize mobility efficiency over the walking environment for utilitarian walking, whereas the quality of the walking environment significantly influences the frequency of leisure walking. Based on these results, the study proposes specific strategies to improve the walking environment around residential areas to promote leisure walking. These strategies include creating vertical gardens or various forms of three-dimensional gardens on narrow walkways and improving sidewalk design. The findings of this study can contribute to promoting leisure walking by creating walk-friendly environments, ultimately enhancing urban sustainability and the quality of life for residents.

• Journal of Korean Society of Forest Science
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• v.113 no.3
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• pp.349-360
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• 2024

This study aimed to analyze the main forest environmental factors affecting the discernment of slow-moving landslide-prone areas in the Republic of Korea, based on data from a detailed landslide survey conducted from 2019 to 2021. Field survey data from 256 sites were collected covering 29 forest environmental factors in seven categories, including geology, soil, and topography. The analysis was conducted using the Random Forest model (AUC = 0.910) and XGBoost model (Accuracy = 0.808, Kappa = 0.594, F1 - measure = 0.494), which were evaluated as having high classification accuracy during the machine learning model development process. Consequently, factors with a high mean decrease Gini (MDG), representing classification importance, were identified as the presence of cracks (average MDG of both models: 22.1), peak elevation (14.8), and the presence of steps (7.0), indicating that these were significant factors in determining slow-moving landslide-prone areas. The presence of cracks and steps aligned well with the characteristics of slow-moving landslides, suggesting that their importance should be emphasized in future detailed landslide surveys. However, the influence of the peak elevation was considered somewhat overestimated due to the characteristics of the input data used in the analysis. These findings are expected to further improve the accuracy and efficiency of final judgments in detailed landslide surveys.