• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.41-50
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• 2022

In this paper, a method to directly calculate the major elements of skin color such as melanin and hemoglobin from the RGB signal of the camera is proposed. The main elements of skin color typically measure spectral reflectance using specific equipment, and reconfigure the values at some wavelengths of the measured light. The values calculated by this method include such things as melanin index and erythema index, and require special equipment such as a spectral reflectance measuring device or a multi-spectral camera. It is difficult to find a direct calculation method for such component elements from a general digital camera, and a method of indirectly calculating the concentration of melanin and hemoglobin using independent component analysis has been proposed. This method targets a region of a certain RGB image, extracts characteristic vectors of melanin and hemoglobin, and calculates the concentration in a manner similar to that of Principal Component Analysis. The disadvantage of this method is that it is difficult to directly calculate the pixel unit because a group of pixels in a certain area is used as an input, and since the extracted feature vector is implemented by an optimization method, it tends to be calculated with a different value each time it is executed. The final calculation is determined in the form of an image representing the components of melanin and hemoglobin by converting it back to the RGB coordinate system without using the feature vector itself. In order to improve the disadvantages of this method, the proposed method is to calculate the component values of melanin and hemoglobin in a feature space rather than an RGB coordinate system using a feature vector, and calculate the spectral reflectance corresponding to the skin color using a general digital camera. Methods and methods of calculating detailed components constituting skin pigments such as melanin, oxidized hemoglobin, deoxidized hemoglobin, and carotenoid using spectral reflectance. The proposed method does not require special equipment such as a spectral reflectance measuring device or a multi-spectral camera, and unlike the existing method, direct calculation of the pixel unit is possible, and the same characteristics can be obtained even in repeated execution. The standard diviation of density for melanin and hemoglobin of proposed method was 15% compared to conventional and therefore gives 6 times stable.

• Journal of Korean Home Economics Education Association
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• v.33 no.1
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• pp.129-149
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• 2021

The purposes of this study were to examine the current status of the establishment of home economics-related departments in colleges and universities and the changes required in the home economics curriculum of secondary schools, and to structure the elective courses of home economics subject(group) that can be organized in the next high school curriculum. To achieve these purposes, related literature and data were analyzed, and a questionnaire survey and FGI were conducted by home economics experts. The research results are as follows. First, home economics was considered to be highly related not only to the human ecology but also to social sciences, education, engineering, and arts and physical education. The numbers of technical colleges and 4-year universities with departments related to home economics were 1,405 and 961 respectively in 2019. Therefore, it was confirmed that there is a sufficient basis for opening home economics subject(group) elective courses in high school. Second, in the secondary school home economics curriculum, the concepts of culture, relations, independence, and sustainability were emphasized based on the changing life patterns and values. It was proposed that the contents of the home economics course would be structured in a way that allows deep and high-level thinking and helps students to enjoy culture. This demand can be implemented by diversifying, specializing, and structuring the elective courses of the home economics subject(group). Third, a total of 18 elective subjects and subject outlines were structured in the fields of child/family, food/nutrition, clothing, housing, consumption/family management, and home economics integration. This study results will contribute to the establishment of the high school credit system by providing basic information for organizing the next home economics curriculum, and expanding the options for home economics subject(group) to high school students.

• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.68-76
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• 2022

In this study, the Habitat Suitability Index (HSI) was calculated in the Miho stream of the Geum river system, and the environmental ecological flow by point was evaluated. Two points (St.3 and St.8) representing the up and downstream of Miho Stream were selected, in order to calculate the Habitat Suitability Index, the depth and velocity at point where each species is appeared were investigated. The Habitat Suitability Index (HSI) was calculated by the Washington Department of Fish and Wildlife (WDFW) method using the number collected by water depth and velocity section and the results of the flow rate survey. Two target species were selected in this study; dominant species and swimming species sensitive to flow. In the case of a single species of Zacco platypus, the water depth was 0.1 - 0.5 m and the velocity was 0.2 - 0.5 m/s. For species of swimming fish, the water depth was 0.2 - 0.5 m and the velocity was 0.2 - 0.5 m/s. The discharge-Weighted Useable Area (WUA) relationship curve and habitat suitability distribution were simulated at the Miho Stream points St.3 and St.8. At the upstream St.3 of Miho Stream, the optimal discharge was simulated as 4.0 m³/s for swimming fishes and 2.7 m³/s for Zacco platypus. At the downstream point of St.8, species of swimming fish were simulated as 8.8 m³/s and Zacco platypus was simulated as 7.6 m³/s. In both points, the optimal discharge of swimming fish was over estimated. This is a result that the Habitat Suitability Index for swimming fish requires a faster flow rate than the habitat conditions of the Zacco platypus. In the calculation of the minimum discharge, the discharge of Zacco platypus is smaller and is evaluated to provide more Weighted Useable Area. In the case of swimming fishes, narrow range of depth and velocity increases the required discharge and relatively decreases the Weighted Useable Area. Therefore, when calculating the Habitat Suitability Index for swimming fishes, it is more advantageous to calculate the index including the habitat of all fish species than to narrow the range.

• Economic and Environmental Geology
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• v.56 no.4
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• pp.421-433
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• 2023

The final disposal of spent nuclear fuel(SNF) from nuclear power plants takes place in a deep geological repository. The metal canister encasing the SNF is made of cast iron and copper, and is engineered to effectively isolate radioactive isotopes for a long period of time. The SNF is further shielded by a multi-barrier disposal system comprising both engineering and natural barriers. The deep disposal environment gradually changes to an anaerobic reducing environment. In this environment, sulfide is one of the most probable substances to induce corrosion of copper canister. Stress-corrosion cracking(SCC) triggered by sulfide can carry substantial implications for the integrity of the copper canister, potentially posing a significant threat to the long-term safety of the deep disposal repository. Sulfate can exist in various forms within the deep disposal environment or be introduced from the geosphere. Sulfate has the potential to be transformed into sulfide by sulfate-reducing bacteria(SRB), and this converted sulfide can contribute to the corrosion of the copper canister. Bentonite, which is considered as a potential material for buffering and backfilling, contains oxidized sulfate minerals such as gypsum(CaSO4). If there is sufficient space for microorganisms to thrive in the deep disposal environment and if electron donors such as organic carbon are adequately supplied, sulfate can be converted to sulfide through microbial activity. However, the majority of the sulfides generated in the deep disposal system or introduced from the geosphere will be intercepted by the buffer, with only a small amount reaching the metal canister. Pyrite, one of the potential sulfide minerals present in the deep disposal environment, can generate sulfates during the dissolution process, thereby contributing to the corrosion of the copper canister. However, the quantity of oxidation byproducts from pyrite is anticipated to be minimal due to its extremely low solubility. Moreover, the migration of these oxidized byproducts to the metal canister will be restricted by the low hydraulic conductivity of saturated bentonite. We have comprehensively analyzed and summarized key research cases related to the presence of sulfates, reduction processes, and the formation and behavior characteristics of sulfides and pyrite in the deep disposal environment. Our objective was to gain an understanding of the impact of sulfates and sulfides on the long-term safety of high-level radioactive waste disposal repository.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.252-264
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• 2023

This paper proposes a design of a dual-band band-pass filter that integrates a λg/2 open SIR structure, a transmission line, and a fork-type structure with symmetric and asymmetric open stubs. To obtain the dual-band effect, the proposed filter uses the SIR structure and adjusts the impedance ratio of the SIR structure. Therefore, the position of the harmonics of the filter is shifted through the adjustment of the impedance ratio, and this can obtain a double-band effect. In order to obtain the dual-band characteristics, the dual-band effect is obtained by inserting a open stub between the SIR structures with the SIR structure divided in half. In addition, the second frequency response is obtained by adjusting the length of the open symmetrical stub in the fork-shaped structure. The asymmetrical open stub in the fork form achieves optimum bandwidth by adjusting the length. Therefore, the first center frequency of the proposed band-pass filter is 5.896 GHz and the bandwidth is 13.6 %. At this time, the measurement results are 0.13 dB and 33.6 dB. The second center frequency is 5.906 GHz and the bandwidth is 13.6 %. At this time, the measurement results are 0.15 dB and 19.8 dB. The reason is that when the impedance ratio (Δ) is higher than 1, the position of the harmonic is shifted to a lower frequency band. However, if the impedance ratio (Δ) is lowered by one step, the position of harmonics will move to a higher frequency band. The function of the filter designed using these characteristics can be obtained from the measurement result. The proposed band-pass filter has no coupling loss and no via energy concentration loss because there is no coupling structure of input/output and no via hole. Therefore, system integration is possible due to its excellent performance, and it is expected that dedicated short-range communication (DSRC) system applications used in traffic communication systems will be possible.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.287-310
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• 2022

Companies' interest in developing AI-based intelligent new products is increasing. Recently, the main concern of companies is to innovate customer experience and create new values by developing new products through the effective use of Artificial intelligence technology. However, due to the nature of products based on radical technologies such as artificial intelligence, intelligent products differ from existing products and development methods, so it is clear that there is a limitation to applying the existing development methodology as it is. This study proposes a new research method based on KANO-TOPSIS for the successful development of AI-based intelligent new products by using car voice assistants as an example. Using the KANO model, select and evaluate functions that customers think are necessary for new products, and use the TOPSIS method to derives priorities by finding the importance of functions that customers need. For the analysis, major categories such as vehicle condition check and function control elements, driving-related elements, characteristics of voice assistant itself, infotainment elements, and daily life support elements were selected and customer demand attributes were subdivided. As a result of the analysis, high recognition accuracy should be considered as a top priority in the development of car voice assistants. Infotainment elements that provide customized content based on driver's biometric information and usage habits showed lower priorities than expected, while functions related to driver safety such as vehicle condition notification, driving assistance, and security, also showed as the functions that should be developed preferentially. This study is meaningful in that it presented a new product development methodology suitable for the characteristics of AI-based intelligent new products with innovative characteristics through an excellent model combining KANO and TOPSIS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.35-50
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• 2022

After the introduction of the central bus lane system, bus traffic was prioritized. This resulted in improved trust from bus users. However, the low capacity at the central bus stop reduces traffic speed and punctuality. In addition, physical constraints are inevitable because the construction of central bus lanes and bus stops considers the city's road geometry. Therefore, this study attempted to optimize the effective green time of the traffic signal system at the entrance and exit of the central bus stop to remedy its insufficient operational capacity. The Transit Capacity and Quality of Service Manual and Korea Highway Capacity Manual were used as the analysis methodologies. The number of stop areas for central bus stops to be built was determined by excluding variable physical factors, and field survey data collected from nine randomly selected central bus stops currently installed in Seoul were used. A scenario analysis was conducted on the central bus stops with insufficient capacity by adjusting the effective green time, and the capacity of the central bus stop was set as the dependent variable. According to the results, 26.7 percent of the central bus stops with insufficient capacity can solve the problem of insufficient capacity. Therefore, the results of this study can be verified by improving the operation level, and it can be effective even if the number of central bus stops calculated by engineering is not guaranteed during the planning stage of the central bus stop. As the number of central bus stops is expected to increase further as the number of central bus stops increases, it is necessary to improve the number of central bus stops. Therefore, it is hoped that the results presented in this study will be used as basic data for the improvement plan at the operational level before introducing the physical improvement plan.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.25-32
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• 2009

Currently, various types of TDM (Transportation Demand Management) policies are being studied and implemented in an attempt to overcome the limitations of supply oriented policies. In this context, this paper addressed issues of effectiveness and possible domestic implementation of the HOT lane. The possible site of implementation selected for this simulation study is part of the Kyung-bu freeway, where a dedicated bus lane is currently being operated. Minimum length of distance required in between interchanges and access points of the HOT lane for vehicles to safely enter and exit the lane, and traffic management policies for effectively managing the weaving traffic trying to enter and exit the HOT lane were presented. A 5.2km section of freeway from Ki-heuing IC to Suwon IC and a 8.3km section from Hak-uei JC to Pan-gyo JC have been selected as possible sites of implementation for the HOT lane, in which congestion occurs regularly due to the high level of travel demand. VISSIM simulation program has been used to analyze the effects of the HOT lane under the assumption that one-lane HOT lane has been put into operation in these sections and that the lane change rate were in between 5% to 30%. The results of each possible scenario have proven that overall travel speed on the general lanes have increased as well by 1.57~2.62km/h after the implementation of the HOT lane. It is meaningful that this study could serve as a basic reference data for possible follow-up studies on the HOT lane as one effective method of TDM policies. Considering that the bus travel rate would continue increase and assuming the improvement in travel speed on general lanes, similar case study can be implemented where gaps between buses on bus lane are available, as a possible alternative of efficient bus lane management policies.

• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.167-178
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• 2024

In this study, we investigated the perceptions of science-related careers and career education among middle school science teachers. Sixty-four science teachers experienced in teaching unit 7 in the first year of middle school participated. The results of the study revealed that not only careers in science but also careers with science were found to be quite high when teachers were asked to provide examples of science-related careers. Jobs related to research/engineering, which are careers in science, comprised the highest proportion of teachers' answers, followed by jobs related to education/law/social welfare/police/firefighting/military, and health/medical, which are careers with science. However, the proportion of jobs mentioned related to installation/maintenance/production was extremely low. The skills required for science-related careers were mainly perceived to consist of tools for working and ways of working. The number of skills classified under living in the world was perceived to be extremely low across most careers, irrespective of career type. Most teachers only taught unit 7 for two to four sessions and devoted little time to science-related career education, even in general science classes. In the free semester system, a significant number of teachers responded that they provide science-related career education for more than 8 hours. Teachers mainly utilize lecture, discussion/debate, and self-study activities. Meanwhile, in the free semester system, the resource-based learning method was utilized at a high proportion compared to other class situations. Teachers generally made much use of media materials, with the use of textbooks and teacher guides found to be lower than expected. There were also cases of using materials supported by science museums or the Ministry of Education. Teachers preferred to implementing student-centered classes and utilizing various teaching and learning methods. Based on the above research results, discussions were proposed to improve teachers' perceptions of science-related careers and career education.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.