Earticle

The tribological properties of TiC, TiN and TiC/TiN coatings on steels prepared by the cathodic-arc (CA) ion plating technique were investigated. Experiments were carried out on a tribo-test machine using a Falex journal V block system. The friction and wear characteristics of the coatings were determined by varying the applied load and sliding speed. The TiC, TiN and TiC/TiN coatings markedly increased the tribological characteristics of the surface. As far as a single layer coating was concerned, TiN goes better results than TiC. However, the TiC/TiN multilayer coating performed better than either single layer coating. The major factor in the improved performance of the multilayer coating was the role of TiC in improving the adhesion between the external TiN layer and the substrate steel.

This article dissertation intends to examine the problem of migration and return that developed during the period of Japanese imperialism in connection with the problem of conceptual identity. Since hikiage began in earnest after August 15, 1945 when World War II came to an end, it is associated with postwar Japan and thus the hikiage issue should not be overlooked when discussing postwar Japan. Rather than discussing hikiage in the postwar history, the comparative study shows the need to discuss preand post-war Japan from the perspective of hikiagesha, or returnees from Japanese overseas colonial territories. In post-war Japan, the progress of hikiage and hikiagesha’s experiences were featured in novels, autobiographies, and the media, with their image being formed. Hikiage was extremely simplified and defined as the returning of overseas Japanese people to Japan after Japan lost the war, and the image of hikiagesha was formed, which is different from that of the local Japanese people. Hikiage was described using words like ‘homecoming,’ ‘return,’ ‘repatriation,’ ‘stowing away,’ and ‘eviction,’ concealing the fact that hikiage reflects hikiagesha’s experiences in different countries and regions. In order to clarify this, this article examined hikiage in relation to regional characteristics of several concepts and relationships of international politics. This article also shows that hikiage involves a ‘level’ that is different from ‘human migration’ or an ‘immigration issue,’ which appear in existing studies. In other words, the aspects of hikiage experience are very different and complex to interpret as ‘being victimized’ and ‘victimizing others’ overlap in hikiage. This causes difficulty developing historical awareness or bringing back memories of war. This article examines hikiage in relation to national imperialism and examines how it was perceived by the colonized by looking at the use of such concepts as salvage, homecoming, and return in Korean society. Notably, this article suggests the need to consider the hikiage issue as a medium to reconstruct the war experience and Cold War system experience of East Asia beyond the logic behind the colonizer and the colonized.

우리나라 전력시장 발전부문에 경쟁을 도입함으로써 각발전사들이 얼마나 발전해야 할지는 중요한 문제가 되었고, 안정적인 계통한계가격(System Marginal Price, SMP)유지는 중요한 문제다. 본 연구에서는 인공신경망 중 MLP(Multi-Layer Perceptron), NARX(Nonlinear Autoregressive exogenous)를 이용하여 서로 비교 분석했고 외부변수로 전력수요를 설정하여 SMP를 예측했으며, ARIMA(Autoregressive Integrated Moving Average)와도 비교를 실시했다. 모두 30일, 40일, 50일을 예측해 봤으며 MLP의 경우 은닉층의 개수가 90개, 85개, 80개 였을 때 최적의 결과를 보여준 반면, NARX의 경우 95개, 80개, 70개 였을 때 최적의 결과를 보여주었다. 전반적으로 모든 예측에서 ARIMA, MLP, NARX 순으로 예측 오차가 작게 나타났다.

With the introduction of competition in the power generation sector in Korea, determining how much each electricity company should develop and maintain a stable system marginal price (SMP) has become an important issue. In this study, SMP was predicted by comparing the values for each company using a multilayer perceptron (MLP) and nonlinear autoregressive exogenous (NARX) model among artificial neural networks (ANN), and setting electricity demand as an external variable. The Autoregressive Integrated Moving Average (ARIMA) was also compared. Each method predicted 30, 40, and 50 days. In the case of MLP, optimal results were obtained when the number of hidden layer units were 90, 85, and 80, whereas in the case of NARX, optimal results were obtained when the number of hidden layer units were 95, 80, and 70. Overall, the forecast errors were small in the order of ARIMA, MLP, and NARX for all predictions.

"Protein Folding Problem" is considered to be one of the "Great Challenges of Computer Science" and prediction of disordered protein is an important part of the protein folding problem. Machine learning models can predict the disordered structure of protein based on its characteristic of "learning from examples". Among many machine learning models, we investigate the possibility of multilayer perceptron (MLP) as the predictor of protein disorder. The investigation includes a single hidden layer MLP, multi hidden layer MLP and the hierarchical structure of MLP. Also, the target node cost function which deals with imbalanced data is used as training criteria of MLPs. Based on the investigation results, we insist that MLP should have deep architectures for performance improvement of protein disorder prediction.

A compact radio frequency (RF) bandpass filter (BPF) in low temperature co-fired ceramic (LTCC) is suggested for WiMAX applications. The center frequency ($f_0$) of the BPF is 5.5 GHz and its pass band or 3-dB bandwidth is 700 MHz to cover all the three major bands, low and middle unlicensed national information infrastructure (U-NII; 5.15-5.35 GHz), World Radiocommunication Conference (5.47-5.725 GHz), and upper U-NII/industrial, scientific, and medical (ISM) (5.725-5.85 GHz), for the WiMAX frequency band. A lumped circuit element design-the 5th order capacitively coupled Chebyshev BPF topology-is adopted. In order to design a compact RF BPF, a very thin ($43.18{\mu}m$) ceramic layer is used in LTCC substrate. An interdigital BPF is also designed in silicon substrate to compare the size and performance of the lumped circuit element BPF. Due to the high relative dielectric constant (${\varepsilon}_r$ = 11.9) of the silicon substrate, the quarter-wavelength resonator of the interdigital BPF can be reduced. In comparison to the 5th order interdigital BPF at $f_0$ = 5.5 GHz, the lumped element design is 24% smaller in volume and has 17 and 7 dB better attenuation characteristics at $f_0{\pm}0.75$ GHz.

Background: In order to measure neutron energy spectra, the conventional Bonner Sphere Spectrometers (BSS) are widely used. In this spectrometer, several measurements with different size Bonner spheres are required. Operators should, therefore, place these spheres in several times to a measurement point where radiation dose might be relatively high. In order to reduce this effort, novel neutron energy spectrometer using an onion-like single Bonner sphere was proposed in our group. This Bonner sphere has multiple sensitive spherical shell layers in the single sphere. In this spectrometer, a band-shaped thermal neutron detection medium, which consists of a LiF-ZnS mixed powder scintillator sheet and a wavelength-shifting (WLS) fiber readout, was looped to each sphere at equal angular intervals. Amount of LiF neutron converter is reduced near polar region, where the band-shaped detectors are concentrated, in order to uniform the directional sensitivity. The LiF-ZnS mixed powder has an advantage of extremely high light yield. However, since it is opaque, scintillation photons cannot be collect uniformly. This type of detector shows no characteristic shape in the pulse height spectrum. Subsequently, it is diffcult to set the pulse height discrimination level. This issue causes sensitivity fluctuation due to gain instability of photodetectors and/or electric modules. Materials and Methods: In order to solve this problem, we propose to replace the LiF-ZnS mixed powder into a flexible and Transparent RUbber SheeT type LiCaAlF6 (TRUST LiCAF) scintillator. TRUST LiCAF scintillator can show a peak shape corresponding to neutron absorption events in the pulse height spectrum. Results and Discussion: We fabricated the prototype detector with five sensitive layers using TRUST LiCAF scintillator and conducted basic experiments to evaluate the directional uniformity of the sensitivity. Conclusion: The fabricated detector shows excellent directional uniformity of the neutron sensitivity.

We develop an intelligent information system in a multilayer electronic supply chain network. Using the internet for supply chain management (SCM) is a key interest for contemporary managers and researchers. It has been realized that the internet can facilitate SCM by making real time information available and enabling collaboration between trading partners. Here, we propose a multi-agent system to analyze the performance of the elements of a supply network based on the attributes of the information flow. Each layer consists of elements which are differentiated by their performance throughout the supply network. The proposed agents measure and record the performance flow of elements considering their web interactions for a dynamic route selection. A dynamic programming approach is applied to determine the optimal route for a customer in the end-user layer.

부동산 가격평가를 위한 전통적 접근은 선형회귀모형을 활용하는 것으로서, 이러한 접근은 설명변수와 종속변수(주택 가격)간 선형의 관계를 가정한다는 한계가 있다. 본 연구는 이러한 한계를 극복하고자 딥러닝 방식, 즉 다층신경망 모형(multilayer neural net model)을 활용하였다. 다층신경망 모형이 전통적 회귀모형보다 주택 가격 예측 성능이 일관되게 탁월함을 4개 사례지역(서울 강남구, 경남 김해시, 전주 덕진구, 전남 해남군) 모두에서 확인하였다. 이러한 성능 향상의 주원인은 다층신경망 모형이 설명변수와 종속변수 간 비선형 관계를 효율적으로 포착할 수 있기 때문인 것으로 해석된다. 설명변수 중 하나인 지리좌표(X, Y)값과 주택 가격 간의 관계를 효율적으로 모델링한 것을 비선형 관계 포착의 예로 들 수 있다. 또 다른 특이점은 사례지역의 이질성이 강해질수록 두 모형 간 성능 격차가 커지는 것을 발견할 수 있었다. 즉, 사례지역에 소재하는 주택의 이질성이 심한 경우, 전통적 모형은 가격 예측의 정확성이 상당히 감소하였으나 다층신경망 모형은 상대적으로 강건한 예측 성능을 보여주었다.

The traditional approach to property valuation has been the use of a linear regression model, which has been criticized for assumption of a linear relationship between predictors and the house prices. We tried to overcome the limitation through the deep learning approach, that is, using a multi-hidden layer neural net model. Our finding is that the neural net model outperformed the traditional approach across all the four study areas. We interpreted that the outstanding performance of the neural net model could be attributed to the capability of non-linear modeling of predictors with the example being geographical coordinates. Another noticeable result is that the gap of the model performance between the neural net model and the traditional approach widened as the study area became more heterogeneous. The neural net model was proven to be able to perform more efficiently in the heterogeneous area where the traditional linear regression model suffered when predicting the house prices.

본 연구는 공공데이터포털을 통해 제공되는 2023년 건강검진정보 데이터를 머신러닝으로 학습하여 성별 생물학적 연령을 예측하는 판별 인공지능을 개발하는 것이다. 전체 데이터(100만명) 중 건강검진 결과가 측정된 330,752명(남자 179,556명, 여자 151,196명)을 머신러닝 학습 데이터로 활용했다. 연령대를 출력변수로, 키, 몸무게, 허리둘레, 수축기 혈압, 이완기 혈압, 공복 혈당, 중성지방, HDL 콜레스테롤, LDL 콜레스테롤, 헤모글로빈, 혈청 GOT, 혈청 GPT, 감마 GTP 등 26개 항목을 입력 변수로 사용하였다. 판별 인공지능 개발에는 머신러닝 알고리즘 중 딥러닝이 가능한 다층신경망을 사용하였으며, 인공지능의 성능평가에는 ROC 곡선을 사용하였다. 다층신경망으로 성별 생물학적 나이를 예측한 결과 입력변수(검강검진정보)를 학습하지 않은 학습데이터의 출력변수(연대기적 나이)의 연령분포와 입력변수를 학습한 인공지능이 예측한 출력변수(생물학적 나이)의 확률 값이 거의 비슷하게 나타났다. 인공지능 예측방법은 머신러닝 및 딥러닝을 이용하여 대용량 고차원 데이터에서 변수 간 비선형성과 복잡한 상호작용까지 포착하여 효율적으로 처리할 수 있다. 따라서, 다양한 임상 및 바이오마커 정보를 통합 분석함으로써 개인의 노화 정도를 정밀하게 파악할 수 있기 때문에, 예방 중심의 보건정책 수립에 중요한 과학적 근거를 제공할 수 있을 것이다.

This study aims to develop a discriminative artificial intelligence system that predicts gender and biological age by learning from 2023 health checkup information data provided through the public data portal using machine learning. Among the total data (1 million people), 330,752 individuals (179,556 men and 151,196 women) whose health screening results were measured were used as machine learning training data. Age group was used as the output variable, and 26 items, including height, weight, waist circumference, systolic blood pressure, diastolic blood pressure, fasting blood glucose, triglycerides, HDL cholesterol, LDL cholesterol, hemoglobin, serum GOT, serum GPT, and gamma GTP, were used as input variables. In the development of discriminatory artificial intelligence, a multilayer neural network capable of deep learning among machine learning algorithms was used, and the ROC curve was used to evaluate the performance of artificial intelligence. As a result of predicting biological age by gender using a multilayer neural network, the age distribution of the output variable (chronological age) of the training data that did not learn the input variable (health examination information) and the probability value of the output variable (biological age) predicted by the artificial intelligence that learned the input variable were almost similar. Artificial intelligence prediction methods can efficiently process large amounts of high-dimensional data by capturing nonlinearities and complex interactions between variables using machine learning and deep learning. Therefore, by integrating and analyzing various clinical and biomarker information, it is possible to precisely determine the degree of aging in an individual, thereby providing important scientific evidence for establishing prevention-oriented health policies.

상징은 그것이 표상하고 있는 의미뿐만 아니라 그 속에 담긴 힘을 나타내고 있는 것으로 의식과 무의식의 떨어져 있는 두 차원을 연결하는 다리의 역할을 하며 상징이 가지고 있는 정동과 힘으로 한계를 뚫고 새로운 차원의 삶으로 나아갈 수 있게 하는 변환의 기능이 있다. 본 연구는 한국의 벽화와 그림, 문화에 투사된 소의 상징성 중 모성성을 중심으로 고찰해 보고자 한다. 한국의 벽화와 그림에 나타난 소는 인간과 오래전부터 긴밀한 관계를 맺으며, 듬직하고 믿음직스런 모습으로 생업을 함께하는 모습으로 나타났다. 또한 새끼를 사랑스럽게 돌보는가 하면 여유로운 모습으로 유유자적하거나 주인에 대한 충직스런 모습을 보이고 있다. 소는 한국문화에서 양육하고 돌보는 긍정적인 모성성을 상징하며, 인간에게 친밀하고 도움을 주며 신뢰로움의 상징성을 가지고 있다.

The symbol represents not only the meaning it represents but also the power contained in it, serving as a bridge that connects the two dimensions apart of consciousness and unconsciousness.. There is a function of transformation that allows the power of symbols to break through the limits and move toward a new level of life. This study focuses on motherhood among the symbols of cows projected on Korean murals, paintings, and culture. The cows shown in Korean murals and paintings have long been closely related to humans and share their lives with humans in a trustworthy manner. They also take care of babies lovingly, a relaxed appearance, or show loyalty to their owners.Cows symbolize the positive maternal nature of nurturing and caring in Korean culture, and they are friendly, helpful and trustworthy to humans.

다층퍼셉트론 혹은 전방향 신경회로망이 임의의 함수를 근사시킬 수 있다는 이론적 연구결과에 기초하여 많은 분야에 응용되고 있다. 이 다층퍼셉트론을 실제 문제에 응용하는 경우에 여러 가지 파라미터 혹은 학습 방법 등을 결정하여야 한다. 이 논문에서는 패턴인식 문제에 다층퍼셉트론을 적용하는 경우에 실제 결정하여야 할 파라미터의 결정방법과 학습 방법에 대하여 논의한다. 이 논의는 각층의 노드 수 결정 방법, 다층 퍼셉트론의 가중치 초기화, 그리고, 성능향상을 위하여 학습에 사용되는 여러 가지 오차 함수, 데이터 불균형 문제의 학습, 깊은 구조 등을 다루었다.

Multilayer perceptrons(MLPs) or feed-forward neural networks are widely applied to many areas based on their function approximation capabilities. When implementing MLPs for application problems, we should determine various parameters and training methods. In this paper, we discuss the design of MLPs especially for pattern classification problems. This discussion includes how to decide the number of nodes in each layer, how to initialize the weights of MLPs, how to train MLPs among various error functions, the imbalanced data problems, and deep architecture.

본 논문에서는 주어진 문제를 해결하기 위해 사용될 최적의 다충 퍼센트론을 구성 하기 위한 하나의 점진적 학습 방법을 제시한다. 고정된 크기의 트레이닝 패턴 집합을 반복적으로 사용하는 기존의 알고리즘들과는 달리, 제시되는 방법에서는 학습 패턴의 수를 점차 증가시키면서 전체 데이터를 학습하기 위해 필요하고도 충분한 은닉뉴런의 수를 찾는다. 이와 같이 신경망 크기의 최적화에 학습 패턴을 점차적으로 선택하여 늘려나감으로써 일반화 능력과 학습 속도가 기존의 방법에서보다 향상됨을 필기체 숫자인식 문제에 있어서 실험적으로 보여준다.

An incremental learning algorithm is presented that constructs a multilayer perceptron whose size is optimal for solving a given problem. Unlike conventional algorithms in which a fixed size training set is processed repeat-edly, the method uses an increasing number of critical examples to find a necessary and sufficient number of hidden units for learning the entire data. Experimental results in hand- writtern digit recognition shows that the network size optimization combined with incremental pattern selection generalizes significantly better and converges faster than conventional methods.

본 논문에서는 LTCC 다층기판으로 구현할 수동 소자를 수축공정과 무수축공정으로 구분하여 설계, 제작하고 분석하였다. 유전율 7 또는40의 두 종류 세라믹 소재를 사용하여 기본 형태의 수동소자를 다양하게 두 가지 공정으로 제작하여 특성을 비교하였다. 유전율40 기판을 사용할 때 수축공정은 X, Y 방향에서 17%, Z 방향에서 36%의 수축율을 보이는 것과 비교하여, 무수축공정은 X,Y 방향에서 변화하지 않고 Z 방향으로만 43% 수축하여 평면상에서 높은 치수 정밀도와 표면 평탄도를 얻을 수 있다. 측정 값으로 부터 매개 변수를 이용한 경험적 해석 식을 이용하여 제작한 LTCC 소자의 인덕턴스 및 커패시턴스를 추정하였으며 설계 라이브러리 형태로 구현하였다. 유전율과 제작 공정에 따라 인덕터의 권선수와 단위 면적에 따른 커패시턴스를 측정하여 권선수 및 단위면적에 따른 소자값을 예측할 수 있는 다항식을 제시하였다.

This paper has designed, fabricated, and analyzed the passive devices realized using low temperature co-fired ceramic (LTCC) multi layer substrates by dividing into the shrinkage process and the non-shrinkage process. Using two types of ceramic materials with dielectric constant 7 or 40, we have fabricated the same shape of various elements in 2 different processes and compared the characteristics. For the substrate of dielctric constant 40, compared with the shrinkage process which has 17% shrink in the X and Y directions with 36% shrink in the Z direction, the non-shrinkage process has 43% shrink in the Z direction without shrink in the X and Y directions, so high dimensional accuracy and surface flatness can be obtained. The inductances and capacitances of the fabricated elements are estimated from measurement using empirical analysis equations of parameters and implemented as a design library. Depending on the substrate and the process, the inductance and capacitance depending on the turn number of winding and unit area have been measured, and empirical polynomials are proposed to predict element values.

The FPCB is used for electronic products such as LCD display. The process of manufacturing FPCB includes a cutting process, in which each single FPCB is cut and separated from the panel where a series of FPCBs are arrayed. The most-widely used cutting method is the mechanical punching, which has the problem of creating burrs and cracks. In this paper, the cutting characteristics of the FPCB have been experimented using Nd:YAG DPSS UV laser as a way of solving this problem. To maximize the industrial application of this laser cutting process, test samples of the multilayered FPCB have been chosen as it is actually needed in industry. The cutting area of the FPCB has four different types of layer structure. First, to cut the test sample, the threshold laser cut-off fluence has been found. Various combinations of laser and process parameters have been made to supply the acquired laser cut-off fluence. The cutting characteristics in terms of the variation of the parameters are analyzed. The laser and process parameters are optimized, in order to maximize the cutting speed and to reach the best quality of the cutting area. The laser system for the process automation has been also developed.

It is well known that Morpho butterflies show distinctive, brilliant and iridescent colors and have micro-nano scale structures, instead of dyes and pigments, on their wings. This structural coloration is regarded as a novel technique to express color with a long lifetime, ease and precise tenability. Here, we studied optical multilayer thin films with thickness of several tens of nm ($TiO_2$ and $SiO_2$) and lens-shape micro-patterns. Fabrication and characterization of the multilayer stacking structure and the micro-pattern structure were performed and the films were analyzed via several optical measuring techniques. Finally, we discussed how the micro-pattern structure could enhance independence with color changes according to the viewing angle.

Effective elastic constants of biomimetic multilayer structures with hierarchical structures are evaluated based on the potential energy balance method. The effective anisotropic elastic constants are used in analyzing low-velocity impact of biomimetic multilayer structures consisting of mineral and protein. It is shown that displacements of biomimetic multilayer structures strongly depend on the volume fraction of mineral and hierarchical level. The effect of the volume fraction of mineral and hierarchical level on the contact force and stresses at the impact point are also discussed.

<금환기봉>은 <김희경전>의 초기 이본으로 여러 이본 중에서도 제목이 남녀주인공의 결연담을 중심으로 되어있으며 후대 <김희경전>의 이본에서 생략된 후일담의 부분들을 빠짐없이 담고 있다. 또한 <금환기봉> 서사는 초반부, 중반부, 후반부로 서사의 비중이 균등하게 나뉘어 구성되어 있으며 한 작품 안에서 서사의 성격이 각기 다른 다층적인 성격을 지닌 장편여성영웅소설 작품이라 할 수 있다. 본 논의에서는 <금환기봉>의 서사가 장편화되고 다층적인 성격을 가질 수 있도록 핵 심적인 역할을 한 여주인공의 여성 인식에 주목해보고자 한다. 선행연구에서는 공통적으 로 <금환기봉>의 서사가 <김희경전>의 초기 이본으로서 가장 길고 확장된 양상을 보이 고 있다는 지점을 밝히고 있지만, 서사의 후반부까지 각기 성격을 달리하며 확장되기에 가장 큰 영향을 미친 여주인공의 삶에 대한 태도와 이로 비롯된 사건들에는 크게 주목하 지 않았다. 그러므로 본고에서는 여주인공 장설빙의 여성인식과 관련한 서사의 양상을 살펴봄으로써 <금환기봉> 서사의 다층적인 특징을 밝혀보고자 하였다. 먼저 <금환기봉>의 초반부 서사는 절세가인으로 태어나 남주인공과 만나 결연을 맺는 가인 장설빙의 삶을 중심으로 하며 여주인공 장설빙이 배필을 선택하고 애정을 성취하여 여성으로서의 삶을 안전하게 유지하고자 하는 서사가 배치되어 여타 여성영웅소설에서 큰 비중을 두지 않는 ‘배필 만나기’를 중요하게 다루고 확장시킨다. 여기서의 장설빙의 여성인식은 천정배필인 남주인공 곁에서 안전한 여성으로 살아가는 삶이며 배필을 잃는 다는 것은 곧 죽음이라는 인식을 가진 전형적인 여성으로 동기화된다. 하지만 중반부에 죽음을 겪고 남성의 삶을 경험한 장설빙의 인식은 완전히 달라진다. 남성의 삶을 통해 아버지의 억울함을 풀고 안전을 보장받게 된 장설빙은 스스로를 남성 으로 인식하는 변화를 맞이하며 영웅의 삶을 산다. 따라서 <금환기봉>의 중반부는 남편 이나 아버지를 구출하기 위해 잠시 남장을 선택했다가 다시 여성으로 돌아가려는 장설빙 의 삶이 아니라 남성으로 살고자 하는 장수정의 삶을 그리며 확장되는 것이다. 이어서 <김희경전>의 이본에서 다수 생략된 후반부의 서사는 <금환기봉>에서 생략되지 않고 후 반부로 큰 비중을 차지한다. 후반부에서는 장설빙이 남성의 삶을 포기한 후 여성이라는 정체를 밝히고 돌아간 가문에서 여성으로 살아가는 삶을 다룬다. 가문의 규율을 따르는 여성의 삶을 최고의 가치로 여기는 남주인공 및 다수의 여성 결연자들을 직면하고 장설 빙이 자신의 모습을 불완전한 여성으로서 인식하는 고뇌가 잘 담겨 있다. 후반부의 서사 는 남주인공을 중심으로 살펴보면 장설빙이 남주인공의 여성 결연자들과 화합하며 지내 는 모습으로 읽을 수 있지만 실상은 장설빙이 여성으로 살아야 한다는 사실을 인지하면 서도 여성이기에 겪어야만 하는 불합리함을 벗어나 남성의 삶을 지속하고 싶은 고민을 그려내고 있다. 따라서 <금환기봉>은 여주인공 장설빙의 여성인식에 따라 다층적인 성격 을 잘 보여줄 수 있는 이본이라는 점에서도 의의를 지닌다고 할 수 있겠다.

The purpose of this discussion is to reveal the characteristics and meaning of the <Geumhwangibong> narrative by examining the multi-layered aspects and characteristics of the narrative, centering on the heroine who played a key role in making the feature female hero novel <Geumhwangibong> stand out in multilayered character. this discussion, I would like to pay attention to the female perception of the heroine who played a key role in ensuring that the narrative of <Geumhwangibon g> has a feature-length and multi-layered character. This paper attempted to reve al the multi-layered characteristics of the <Geumhwangibong> narrative by examin ing the aspects of the narrative related to the female recognition of the heroine Jang Seol-bing. First of all, the early narrative of <Geumhwangibong> centers on the life of Jang Seol-bing, a man born as a man of saving time and meets and for ms a bond with the male protagonist, and the female protagonist Jang Seol-bing chose Bae Pil and achieved affection to keep her life as a woman safe t deals with and expands 'meeting a fiance', which does not place much weight on other femal e hero novels. Jang Seol-bing's perception of women here is synchronized with a typical woman who lives as a safe woman next to her fiancé, and who has the perception that losing her fiancé is death. However, Jang Seol-bing, who suffered death in the middle of the year and experienced the life of a man, has completely changed his perception. Jang Seol-bing, who has been relieved of his father's injustice and guaranteed safety through his male life, lives a hero's life facing a change in recognizing himself as a man Jang Seol-bing, who is guaranteed, lives a hero's life facing a change in recognizing herself as a man. Therefore, the middle part of <Geumhwangibong> expands by depicting the life of Jang Soo-jung, who wants to live as a man, not the life of Jang Seol-bing, who wants to choose a male costume for a while to rescue her husband or father and return to a woman. Subsequently, the narrative of the second half, which is often omitted from the original version of <Kimhuigyeongjeon>, occupies a large proportion from <Geumhwangibong> to the second half. In the second half, Jang Seol-bing deals with the life of a woman in a family who revealed her identity as a woman after giving up on the life of a man and returned. It is well contained in the agony of facing male protagonists and a number of female associates who consider the life of a woman who follows the rules of the family as the best value and recognizing Jang Seol-bing as an imperfect woman. In fact, Jang Seol-bing recognizes that she has to live as a woman, but she depicts the agony of wanting to continue her male life beyond the irrationality of having to go through as a woman. Therefore, it can be said that <Geumhwangibong> is also meaningful in that it is a novel that can show a multi-layered character well according to the female recognition of the heroine Jang Seol-bing.

본격적인 데이터 경제 시대를 맞이해 정부나 기관단체들은 이에 관 한 법 개정 및 정책을 빠르게 실행시키고 있다. 이에 저작권법은 저작물 이용산업 및 인공지능 기술개발의 촉진을 위한 ‘데이터마이닝 허용’을 개정을 추진 중이다. 즉, “인공지능 학습(딥러닝) 및 빅데이터 분석 등을 위하여 저작물의 이용이 필요하다고 인정되는 범위 내에서 저작물의 이용 허락을 받지 않아도 되도록(침해 면책) 허용”될 가능성이 크다. 본 글은 이러한 데이터 마이닝이 저작권에 편입됨에 따라 데이터에 관해 심도 있는 이해의 필요로 시작하였다. 인간적 사고가 기계적 사고 와 다른 점은 다층적인 사고가 가능한 점에서부터 온다. 그렇기에 데이 터를 이해하기 위해서는 이러한 다층적 관점의 분석이 필요했다. 우선, 현재 데이터에 대한 유형을 검토하여 그 데이터의 성격이 현 저작권 등에 의한 보호 방법에 충분한 편입이 가능한 대상인지를 제기 하여 데이터 경제에 따른 쟁점을 선행적으로 검토함을 목적으로 한다. 11년간의 ‘구글과 오라클’ 사건은 API 데이터가 기존 저작권의 보호 대상일지와 API에 관한 통상적인 사용행태가 공정이용의 대상이 될 수 있느냐가 문제였듯이 데이터는 그동안 지식재산권법의 기준만으로 해석하기엔 다양한 가능성의 형태로 침해 문제가 발생할 수 있음을 알 수 있었다. 특히 데이터의 객체 지향과 상호운용의 성격은 이를 더욱 혼란스럽게 하고 있다. 저작권에서의 데이터 마이닝 허용은 그 취지와 같이 인공지능과 4차 산업과 같은 데이터 경제의 중요한 부분임은 분명하다. 더욱이 자본주 의 경제에 대응할 또 따른 경제체제의 시작을 알리기도 한다. 따라서 현재로서는 법적 보호장치를 섣불리 구획하기는 어렵다. 아이가 처음 발걸음을 디딜 때처럼 기업과 정부, 사회단체…. 나아가 법률을 개정 혹은 제정하는 많은 부분의 관심을 통해 섣부르지 않은 방향점 도출을 위한 노력의 필요성을 제기하였다.

In the era of a full-fledged data economy, governments and institutional organizations are rapidly implementing laws and policies on. Accordingly, the Copyright Act is pushing for a revision of "allowing data mining" to promote the development of the work-use industry and artificial intelligence technology. In other words, it is highly that "the use of the work is allowed (infringement exemption) to the extent that it is recognized that the use of the work is necessary for artificial intelligence learning (deep learning) and big data analysis."As such data mining was incorporated into copyrights, this study began requiring in-depth understanding of data. The difference between human thinking and mechanical thinking comes from the possibility of multi-layered thinking. Therefore, to understand the data, it was necessary to analyze this multi-layered perspective. First, the purpose of this study is to review the issues of the data economy in advance by reviewing the types of current data and raising whether the nature of the data can be sufficiently incorporated into the protection method by current copyrights. Just as the 11-year "Google and Oracle" case was a question of whether API data could be protected and API behavior could be used fairly, the Data showed that infringement problems could occur in the form of various possibilities to be interpreted only by the standards of the Intellectual Property Act. In particular, “object orientation and interoperability of data” is further confusing. allowing data mining in copyright is an important part of the data economy such as artificial intelligence and ‘The Fourth Industrial Revolution’, as its purpose. Moreover, it also marks the beginning of another economic system to respond to the capitalist economy. Therefore, it is difficult to divide legal protection devices hastily at the moment. Companies, governments, social organizations, just like when a child first steps. . .Furthermore, through the interest of many parts of revising or enacting the law, the need for efforts to derive hasty directions were raised.