• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.2 s.302
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• pp.39-48
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• 2005

In this paper, we implement the multimedia remote control system by using existing internet service or wired online. We also provide user-friendly convenient environment with developed application program named EzPlay and PC-EPG. The multimedia remote control system consists of integrated wireless transceiver of PC and TV connected USB type and the users can easily use lots of contents because EzPlay program provides appropriate UI mode on the PC and TV screen. The unposed system can operate real-time playing, reserved video receding and data storing function using internet mesh based on signal detecting control theory. The PC-EPG system is implemented by server/client web program and the client program based on visual C++/MFC processes data storing in client computer through TCP/IP. It also provides intelligent function that constructs database according to user's preference.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.125-130
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• 2014

According to the lunching of Google glass, the interest for wearable computer is increasing. This paper is about how to apply humanity or humanist metaphor to the development and application of wearable computer. Humanity is consisted of dream, imagination and desire of human mind. However the software development methodology and application design of engineering part are consisted of the logical language and also they are testable. In this paper the different academics are combined and researched to develop the human-friendly application which are the design of humanities-applying wearable computer and the service scenarios. This paper shows the specific examples of services to search, share and analyze the information with wearable computer also presents what kinds of humanistic metaphor is able to apply in this process.

• The Journal of Engineering Geology
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• v.21 no.1
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• pp.1-13
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• 2011

Joint roughness is one of the most important parameters in analysis of rock slope stability. Especially in probabilistic analysis, the random properties of joint roughness influence the probability of slope failure. Therefore, a large dataset on joint roughness is required for the probabilistic analysis but the traditional direct measurement of roughness in the field has some limitations. Terrestrial LiDAR has advantagess over traditional direct measurement in terms of cost and time. JRC (Joint Roughness Coefficient) was calculated from statistical parameters which are known from quantitative methods of converting the roughness of the material surface into JRC. The mean, standard deviation and distribution function of JRC were obtained, and we found that LiDAR is useful in obtaining large dataset for random variables.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.382-382
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• 2011

최근의 극심한 기상이변으로 인하여 발생되는 유출량의 예측에 관한 사항은 치수 이수는 물론 방재의 측면에서도 역시 매우 중요한 관심사로 부각되고 있다. 강우-유출 관계는 유역의 수많은 시 공간적 변수들에 의해 영향을 받기 때문에 매우 복잡하여 예측하기 힘든 요소이며, 과거에는 추계학적 예측모형이나 확정론적 예측모형 혹은 경험적 모형 등을 사용하여 유출량을 예측하였으나 최근에는 인공신경망과 퍼지모형 그리고 유전자 알고리즘과 같은 인공지능기반의 모형들이 많이 사용되고 있다. 하지만 유출량을 예측하고자 할 때 학습자료 및 검정자료로써 사용되는 유출량은 수위-유량 관계곡선식으로부터 구하는 경우가 대부분으로 이는 이렇게 유도된 유출량의 경우 오차가 크기 때문에 그 신뢰성에 문제가 있을 것으로 판단된다. 따라서 본 논문에서는 수위를 직접 예측함으로써 이러한 오차의 문제점을 극복 하고자 한다. Neuro-Fuzzy 모형은 과거자료의 입 출력 패턴에서 정보를 추출하여 지식으로 보유하고, 이를 근거로 새로운 상황에 대한 해답을 제시하도록 하는 인공지능분야의 학습기법으로 인간이 과거의 경험과 훈련으로 지식을 축적하듯이 시스템의 입 출력에 의하여 소속함수를 최적화함으로서 모형의 구조를 스스로 조직화한다. 따라서 수학적 알고리즘의 적용이 어려운 강우와 유출관계를 하천유역이라는 시스템에서 발생된 신호체계의 입 출력패턴으로 간주하고 인간의 사고과정을 근거로 추론과정을 거쳐 수문계의 예측에 적용할 수 있을 것이다. 유전자 알고리즘은 적자생존의 생물학 원리에 바탕을 둔 최적화 기법중의 하나로 자연계의 생명체 중 환경에 잘 적응한 개체가 좀 더 많은 자손을 남길 수 있다는 자연선택 과정과 유전자의 변화를 통해서 좋은 방향으로 발전해 나간다는 자연 진화의 과정인 자연계의 유전자 메커니즘에 바탕을 둔 탐색 알고리즘이다. 즉, 자연계의 유전과 진화 메커니즘을 공학적으로 모델화함으로써 잠재적인 해의 후보들을 모아 군집을 형성한 뒤 서로간의 교배 혹은 변이를 통해서 최적 해를 찾는 계산 모델이다. 이러한 유전자 알고리즘은 전역 샘플링을 중심으로 한 수법으로 해 공간상에서 유전자의 개수만큼 복수의 탐색점을 설정할 뿐만 아니라 교배와 돌연변이 등으로 좁아지는 탐색점 바깥의 영역으로 탐색을 확장할 수 있기 때문에 지역해에 빠질 위험성이 크게 줄어든다. 따라서 예측과 패턴인식에 강한 뉴로퍼지 모형의 해 탐색방법을 유전자 알고리즘을 사용한다면 보다 정확한 해를 찾는 것이 가능할 것으로 판단된다. 따라서 본 논문에서는 선행우량 및 상류의 수위자료로부터 하류의 단시간 수위예측에 관해 연구하였으며, 이를 위해 유전자 알고리즘을 이용항여 소속함수를 최적화 시키는 형태의 Neuro-Fuzzy모형에 대하여 연구하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.62-69
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• 2016

This paper proposes to select Measure of Performance(MOP) for object attainment in the counterfire operation and deduce the reasonable combination of blue force's hitting resources satisfying MOP's optimal value and regression equation for the object achievement time. Also, in the study-methodological perspective, a series of procedures for drawing the regression equation from the real world is presented. Firstly the model was made by simplifying the weapon-system information of red force and blue force, then the time for object attainment was derived from its simulation. Simulating the model for the counterfire operation was divided into three phases-detection, decision and hitting. The probability method by applying the random numbers were used for detection, fixed constant numbers for decision and hitting. The simulation was repeatedly performed to get the minimum time for the object attainment against the fixed enemy, and it was estimated as the optimal value of simulation. From this result, the optimum combination of blue force's weapon system against the red force and finally, the regression equation were obtained by using the response surface analyzing method in MINITAB. Thereafter this equation was completely verified by using 'the 2-sample t-test.' As a result, the regression equation is suitable.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.94-100
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• 2019

This study presents the superiority of his calligraphy by analyzing the use, meaning, and calligraphy of nickname three dragon-man(yong-jeong) written by Kim Junghee before and after exile in Jeju Island. Based on the basic structure of the three dragon-man, the relationship between the times, the context, and the characters was studied. Through this change process, the difference of art engineering with other works was analyzed. Kim Junghee intentionally went through a difficult situation by using a nickname with a dragon. He wrote different meanings, uses, and typefaces of the nickname three dragon-man, depending on the circumstances. Finally, Kim Junghee used 'three dragon-man' to King Heonjong and Monk Choui to express his feelings and intentions. His writing was excellent in art engineering and unique in the world. All were found to be supported by his epigraphy insights. The results of this study will be a new methodology for analyzing the meaning of nicknames of ordinary artists.

• Journal of Korean Society on Water Environment
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• v.37 no.3
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• pp.157-167
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• 2021

Korea needs to develop a rational system to separate stormwater utility fee from current sewerage fee. In this study, the scenario for calculating stormwater utility fee of Bupyeong-gu was suggested and the results were considered. For this purpose, the application of stormwater utility fee overseas and current domestic system were analyzed. A three step calculating scenario considering suitable domestic situation and impervious surface area was suggested. Water, sewerage usage, and hydrant data were collected. The total amount of water and sewerage fees for land use were calculated. The sewerage fee of Bupyeong-gu for the year 2014 was 21,685,446,578 won. Assuming that 40% of this amount was the cost associated to stormwater, the result showed that the fees for residential area in third step decreased by 0.77% compared to that of the first step. For commercial area, the stormwater utility fee decreased by 36.87%. For industrial area, although the consumption of water was similar to that of commercial area, the stormwater utility fee increased by 8.35%. For green area, the fee increased by 37.46%. This study demonstrated that the calculation of actual stormwater utility fee using impervious surface map and impervious Surface Ratio Estimation Methodology developed in previous studies is feasible.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.677-696
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• 2004

Component-based software engineering (CBSE) composes reusable components and develops applications with the components. CBSE is admitted to be a new paradigm that reduces the costs and times to develop software systems. The high quality of component designs can be assured if the consistency and correctness among the elements of a component are verified with formal specifications. Current formal languages for components include only some parts of contracts between interfaces, structural aspects and behavioral aspects of component, component-based system, component composition and variability. Therefore, it is not adequate to use current formal languages in all steps of a component design process. In this paper, we suggest a formal language to specify component designs Component-Z. Component-Z extends Object-Z, adds new notations to specify components. It can be possible to specify interfaces, the inner structure of a component, inner workflows, and workflows among interfaces with Component-Z. In addition, Component-Z provides the notations and semantics to specify variability with variation points, variants and required interfaces. The relation between interfaces and components is defined with mapping schemas. Parallel operator is used to specify component composition. It can be possible to describe deployed components with the specifications of component-based systems. Therefore, the formal specification language proposed in this paper can represent all elements to design components. In the case study, we specify an account management system in a bank so that we show that Component-Z can be used in all steps of component design.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.6
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• pp.415-422
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• 2010

Development of the reliability-based design program in the GUI environment is inadequate for engineers familiar with the deterministic design to deal with the international design criterion based on the probabilistic design. In this study, the design program based on the GUI environment is developed in order to more efficiently input the design factor and more easily carry out the design works. The GUI environment is the GUIDE (Graphic User Interface Development Environment) tool supported by the latest MATALB version 7.1. In order to test the model reliability, the probabilities of failure (POF) on the breakwater armor block (AB) and gravity quay-wall (QW) in the sliding mode are computed using the model in the Level II and Level III. The POF are 55.4~55.7% for breakwater AB and 0.0006~0.0007% for gravity QW. A non-GUI environment program results of the POF are 55.6% for breakwater AB and 0.0018% for gravity QW. In comparison, the POF difference is negligible for breakwater AB because the exact input design parameters are available, whereas the large POF difference, but within the same order, for gravity QW can be explained by the difference of the input design factors because of the poor input data information.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.