• Journal of the Korean earth science society
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• v.42 no.3
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• pp.247-263
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• 2021

Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.

• 한국사회정책
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• v.25 no.2
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• pp.429-446
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• 2018

The $4^{th}$ Industrial Revolution, symbolizing the explosive innovation of digital technologies, is expected to have a great impact on labor relations and produce a lot of contested issues. The labor-management issues, created by the $4^{th}$ Industrial Revolution, are as follows: (1) employment restructuring, job re-allocation, and skill-reformation, driven by the technological displacement, resetting of worker-machine relationship, and negotiation on labor intensity and autonomy, (2) the legislation of institutional protection for the digital dependent self-employed, derived from the proliferation of platform-mediated labor, and the statutory recognition of their 'workerness', (3) unemployment safety net, income guarantee, and skill formation assistance for precarious workeforce, (4) the protection of worker privacy from workplace surveillance, (5) protecting labor rights of the digital dependent self-employed and prcarious workers and guaranteeing their unionization and collective bargaining. In comparing how labor unions in Western countries have responded to the $4^{th}$ Industrial Revolution, German unions have showed a strategic approach of policy formation toward digital technological innovations by effectively building and utilizing diverse channel of social dialogue and collective bargaining, while those in the US and UK have adopted the traditional approach of organizing and protesting in attempting to protect the interest of platform-mediated workers (i.e. Uber drivers). In light of the best practice demonstrated by German unions, it is necessary to build the process of productive policy consultation among three parties- the government, employers, and labor unions - at multi levels (i.e. workplace, sectoral and national levels), in order to prevent the destructive damage as well as labor-management confrotation, caused by digital technological innovations. In such policy consultation procesess, moreover, the inclusive and integrated approach is required to tackle with diverse problems, derived from the $4^{th}$ Industrial Revolution, in a holistic manner.

• Korean Journal of Environment and Ecology
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• v.32 no.6
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• pp.686-697
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• 2018

Due to the advance in remote sensing technology, it has become easier to more frequently obtain high resolution imagery to detect delicate changes in an extensive area, particularly including forest which is not readily sub-classified. Time-series analysis on high resolution images requires to collect extensive amount of ground truth data. In this study, the potential of land coverage mapas ground truth data was tested in classifying high-resolution imagery. The study site was Wonju-si at Gangwon-do, South Korea, having a mix of urban and natural areas. KOMPSAT-3A imagery taken on March 2015 and land coverage map published in 2017 were used as source data. Two pixel-based classification algorithms, Support Vector Machine (SVM) and Random Forest (RF), were selected for the analysis. Forest only classification was compared with that of the whole study area except wetland. Confusion matrixes from the classification presented that overall accuracies for both the targets were higher in RF algorithm than in SVM. While the overall accuracy in the forest only analysis by RF algorithm was higher by 18.3% than SVM, in the case of the whole region analysis, the difference was relatively smaller by 5.5%. For the SVM algorithm, adding the Majority analysis process indicated a marginal improvement of about 1% than the normal SVM analysis. It was found that the RF algorithm was more effective to identify the broad-leaved forest within the forest, but for the other classes the SVM algorithm was more effective. As the two pixel-based classification algorithms were tested here, it is expected that future classification will improve the overall accuracy and the reliability by introducing a time-series analysis and an object-based algorithm. It is considered that this approach will contribute to improving a large-scale land planning by providing an effective land classification method on higher spatial and temporal scales.

• Journal of Dental Rehabilitation and Applied Science
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• v.35 no.2
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• pp.72-80
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• 2019

Purpose: The purpose of this study is to compare and analyze the shear bond strength and fracture pattern in different enamel tooth surface treatments for resin splinting materials. Materials and Methods: G-FIX and LightFix were used as tooth splinting materials. Twenty bovine mandibular incisors were used for the preparation of the specimens. The exposed enamel surface was separated into four parts. Each tooth was treated with 37% phosphoric acid, 37% phosphoric acid + adhesive resin, 37% phosphoric acid + G-premio bond, and G-premio bond for each fraction. Shear bond strength was measured using a universal testing machine. After measuring the shear bond strength, the fractured surface of the specimen was magnified with a microscope to observe the fracture pattern. Two-way ANOVA was used to verify the interaction between the material and the surface treatment method. One-way ANOVA was used for comparison between the surface treatment methods of each material and post-hoc test was conducted with Scheffe's test. An independent t-test was conducted to compare shear bond strengths between materials in each surface treatment method. All statistics were conducted at 95% significance level. Results: G-FIX, a tooth splinting resin, showed similar shear bonding strength when additional adhesive resins were used when material was applied after only acid etching, and LightFix showed the highest shear bonding strength when additional adhesive resins were used after the acid etching. In addition, both G-FIX and LightFix showed the lowest shear bond strength when only self-etching adhesive was applied without additional acid etching. Verification of interactions observed interconnection between resins and surface treatment methods. Most of the mixed failure was observed in all counties. Conclusion: When using G-FIX and LightFix, which are tooth-splinting materials, it is considered that sufficient adhesion will be achieved even after applying only acid etching as instructed by the manufacturer.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.1
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• pp.45-63
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• 2019

The number of domestic construction company is expanding every year while the construction workers' exposure to disaster risk is increasing due to technological advancements and popularity of high-rise buildings. In particular, the industry faces greater fatalities and severe large scale accidents because of construction industry characteristics including influx of foreign workers with different language and culture, large number of aged workers, outsourcing, high place work, heavy machine construction. The construction industry is labor-intensive, which is to be completed under given timeline and consists of unique working environment with a lot of night shifts. In addition, when a fixed construction budget is not secured, there is less investment in safety management resulting in poor risk management at the construction site. Taking account that the construction industry has higher accident risk rate and fatality rate, risky and unique working environment, and various labor pool from foreign to aged workers, preemptive safety management through risk factor identification is a mandatory requirement for the construction industry and site. The study analyzes about 8,500 cases of construction accidents that occurred over the past 10 years and identified risk factor by construction industry sector to secure a systematic insight for risk management. Based on interrelation analysis between accident types, work types, original cause materials and assailing materials, there is correlation between each analysis factor and work industry. Especially for work types, there is great correlation between work tasks and industry type. For reinforced concrete and earthwork are among the most frequent types of accidents, and they are not only high in frequency of accidents, but also have a high risk in categories of occurrence.

• Journal of the Korea Organic Resources Recycling Association
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• v.26 no.4
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• pp.11-19
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• 2018

This study was conducted to develop the manufacturing method of biochar using pruned stems of pear tree and its application effect on the crop growth and soil physico-chemical properties. In this study, biochar derived from pruned stems of pear tree at heating temperature of $300^{\circ}C$, $500^{\circ}C$ and $700^{\circ}C$ in heating times of 2, 3 and 4 hours, were tested in the changes of their chemical properties during biochar processing. The pH, Exch. K, Exch. Mg and cation exchange capacity (CEC) increased as the pyrolysis temperature increased during the production of biochar, and the change of these properties rapidly occurred at $500^{\circ}C$. However, as the pyrolysis temperature increased, ash content increased and total carbon (T-C), yield decreased. And the change of the properties in response to the heating time was not shown. It was thought that it would be desirable to set the production conditions of biochar at $500^{\circ}C$ for 2 hours in consideration of the change of chemical properties and the ash content and yield. And also, were conducted the experiments to establish manufacturing method of farm-made biochar using drum biochar manufacturing machine and investigate the application effects of biochar on the cultivation of chinese cabbage and tomato. Application of biochar derived from pruned stems of pear tree could enhance pH, organic matter (OM), total carbon (T-C) of soil. On the other hand, soil electrical conductivity (EC), NO3-N were lowered compared to the control which has no application. The bulk density, porosity and aggregate formation of soil were improved by biochar application. The fresh matter yields of chinese cabbage and tomato were significantly increased in proportion to the application rate of biochar. This study demonstrated the effect of the biochar derived from agricultural byproduct to be as a low cost potential soil ameliorant by physico-chemical properties in eco-friendly greenhouse cultivation.

• Journal of Science and Technology Studies
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• v.19 no.2
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• pp.169-206
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• 2019

This article seeks to explore new relationships and ethics of human and technology by analyzing a cultural imaginary produced by artificial intelligence. Drawing on theoretical reflections of the Feminist Scientific and Technological Studies which understand science and technology as the matter of care(Puig de la Bellacas, 2011), this paper focuses on the fact that artificial intelligence and robots materialize cultural imaginary such as autonomy. This autonomy, defined as the capacity to adapt to a new environment through self-learning, is accepted as a way to conceptualize an authentic human or an ideal subject. However, this article argues that artificial intelligence is mediated by and dependent on invisible human labor and complex material devices, suggesting that such autonomy is close to fiction. The recent growth of the so-called 'assistant technology' shows that it is differentially visualizing the care work of both machines and humans. Technology and its cultural imaginary hide the care work of human workers and actively visualize the one of the machine. And they make autonomy and agency ideal humanness, leaving disabled bodies and dependency as unworthy. Artificial intelligence and its cultural imaginary negate the value of disabled bodies while idealizing abled-bodies, and result in eliminating the real relationship between man and technology as mutually dependent beings. In conclusion, the author argues that the technology we need is not the one to exclude the non-typical bodies and care work of others, but the one to include them as they are. This technology responsibly empathizes marginalized beings and encourages solidarity between fragile beings. Inspired by an art performance of artist Sue Austin, the author finally comes up with and suggests 'artificial intelligence in wheelchair' as an alternative figuration for the currently dominant 'autonomous artificial intelligence'.

• Journal of Science and Technology Studies
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• v.19 no.1
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• pp.1-51
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• 2019

The understanding of law and science as fundamentally different two systems, in which fact stands against justice, rapid progress against prudent process, is far too simple to be valid. Nonetheless, such account is commonly employed to explain the tension between law and science or justice and truth. Previous STS research raises fundamental doubts upon the off-the-shelf concept of "scientific truth" that can be introduced to the court for legal judgment. Delimiting the qualification of the expert, the value of the expert knowledge, or the criteria of the scientific expertise have always included social negotiation. What are the values that are affecting the boundary-making of the thing called "modern science" that is supposedly useful in solving legal conflicts? How do the value of law and the meaning of justice change as the boundaries of modern science take shapes? What is the significance of "science" when it is emphasized, particularly in relation to the legal provisions of paternity, and how does this perception of science affect unfoldings of legal disputes? In order to explore the answers to the above questions, we follow a process in which a type of "knowledge-deficient model" of a court-that is, law lags behind science and thus, under-employs its useful functions-can be closely examined. We attend to a series of discussions and subsequent changes that occurred in the US courts between 1930s and 1970s, when blood type tests began to be used to determine parental relations. In conclusion, we argue that it was neither nature nor truth in itself that was excavated by forensic scientists and legal practitioners, who regarded blood type tests as a truth machine. Rather, it was their careful practices and crafty narratives that made the roadmaps of modern science, technology, and society on which complex tensions between modern states, families, and courts were seen to be "resolved".

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.