• 로봇학회논문지
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• 제1권1호
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• pp.25-35
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• 2006

Improving practicality of SLAM requires various sensors to be fused effectively in order to cope with uncertainty induced from both environment and sensors. In this case, combining sonar and vision sensors possesses numerous advantages of economical efficiency and complementary cooperation. Especially, it can remedy false data association and divergence problem of sonar sensors, and overcome low frequency SLAM update caused by computational burden and weakness in illumination changes of vision sensors. In this paper, we propose a SLAM method to join sonar sensors and stereo camera together. It consists of two schemes, extracting robust point and line features from sonar data and recognizing planar visual objects using multi-scale Harris corner detector and its SIFT descriptor from pre-constructed object database. And fusing sonar features and visual objects through EKF-SLAM can give correct data association via object recognition and high frequency update via sonar features. As a result, it can increase robustness and accuracy of SLAM in indoor environment. The performance of the proposed algorithm was verified by experiments in home -like environment.

• 한국정밀공학회지
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• 제33권12호
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• pp.1015-1020
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• 2016

An advantage of electric vehicles is that they are environmentally sustainable because they do not emit exhaust gases, such as $CO_2$ or Nox. A disadvantage is the low power performance of the motor and battery source, necessitating a reduction in the weight of the vehicle to increase efficiency. Another disadvantage is that the rechargeable battery enables an electric vehicle to only run for a limited number of miles before requiring electric charging. To solve these problems, the hybrid vehicle has been developed by combining environmental sustainability with the high performance of a conventional internal combustion engine. In this study, an electric UTV (Utility Terrain Vehicle) was transformed into a hybrid vehicle system by outfitting the vehicle with a drive auxiliary power system including a 125 cc internal combustion engine. This modification enabled us to extend the range of the hybrid UTV from 50km to 100km per one electric charging.

• The Korean Journal of Physiology and Pharmacology
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• 제23권5호
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• pp.305-310
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• 2019

The physiomic approach is now widely used in the diagnosis of cardiovascular diseases. There are two possible methods for cardiovascular physiome: the traditional mathematical model and the machine learning (ML) algorithm. ML is used in almost every area of society for various tasks formerly performed by humans. Specifically, various ML techniques in cardiovascular medicine are being developed and improved at unprecedented speed. The benefits of using ML for various tasks is that the inner working mechanism of the system does not need to be known, which can prove convenient in situations where determining the inner workings of the system can be difficult. The computation speed is also often higher than that of the traditional mathematical models. The limitations with ML are that it inherently leads to an approximation, and special care must be taken in cases where a high accuracy is required. Traditional mathematical models are, however, constructed based on underlying laws either proven or assumed. The results from the mathematical models are accurate as long as the model is. Combining the advantages of both the mathematical models and ML would increase both the accuracy and efficiency of the simulation for many problems. In this review, examples of cardiovascular physiome where approaches of mathematical modeling and ML can be combined are introduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• Smart Structures and Systems
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• 제30권2호
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• pp.145-157
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• 2022

The design of safe and economical structures depends on the reliable live load from load survey. Live load surveys are traditionally conducted by randomly selecting rooms and weighing each item on-site, a method that has problems of low efficiency, high cost, and long cycle time. This paper proposes a deep learning-based method combined with Internet big data to perform live load surveys. The proposed survey method utilizes multi-source heterogeneous data, such as images, voice, and product identification, to obtain the live load without weighing each item through object detection, web crawler, and speech recognition. The indoor objects and face detection models are first developed based on fine-tuning the YOLOv3 algorithm to detect target objects and obtain the number of people in a room, respectively. Each detection model is evaluated using the independent testing set. Then web crawler frameworks with keyword and image retrieval are established to extract the weight information of detected objects from Internet big data. The live load in a room is derived by combining the weight and number of items and people. To verify the feasibility of the proposed survey method, a live load survey is carried out for a meeting room. The results show that, compared with the traditional method of sampling and weighing, the proposed method could perform efficient and convenient live load surveys and represents a new load research paradigm.

• 가정간호학회지
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• 제30권1호
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• pp.69-83
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• 2023

Purpose: This study aimed to present Blue Ocean strategies by deriving the strategic elements of a visiting nursing center and conducting a survey on the importance and satisfaction of care clients. Methods: First, a FGI was conducted targeting the head of the visiting nursing center to derive its strategic elements. Subsequently, importance and satisfaction surveys on the derived strategy elements were analyzed, an IPA matrix was derived, and an as-is ERRC Blue Ocean strategy was established. Kano's Three-Factor Theory was used to derive a competitive position matrix and establish a to-be ERRC Blue Ocean strategy. The Blue Ocean Strategy for Visiting Nursing Center Management is presented in this study. Results: Four as raise factors were derived from combining the results of the as-is, to-be ERRC strategy element analysis: retention of competent nurses, education in medication management, maintenance of high customer satisfaction, and prompt handling of customer complaints. Additionally, the customer's health condition evaluation was derived. Conclusion: Blue Ocean Strategies can be used to analyze, derive, and establish management strategies in various nursing-related entrepreneurship fields.

• Journal of Information Processing Systems
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• 제19권5호
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• pp.590-601
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• 2023

University books are an important information resource. University book resources can be shared not only in the traditional paper form, but also electronic form under the background of the Internet. In order to better manage the sharing of electronic book resources in universities, this study put forward three resource sharing strategies: centralized sharing strategy, distributed sharing strategy, and centralized-distributed sharing strategy by analyzing the combined development of books and the Internet as well as the significance and development of book resource sharing. The centralized sharing strategy, however simple, was difficult to handle large traffic; while the resource nodes were independent and self-consistent, the distributed sharing strategy was not easy to find and had a high repetition rate. Combining the advantages of both strategies, the centralized-distributed sharing strategy was more suitable for the heterogeneous form of university book sharing. Finally, a teaching resources sharing platform for university libraries was designed based on the strategy of centralized and distributed sharing, and three interfaces including platform login, resource search, and resource release were displayed. The results of the simulated comparison experiment showed that centralized and distributed sharing strategies had limitations in resource searching and had low efficiencies; the efficiency of the centralized strategy reduced with an increase in search subjects; however, the centralized-distributed sharing strategy was able to search more resources efficiently and main stability.

• 한국지하수토양환경학회지:지하수토양환경
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• 제9권1호
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• pp.1-11
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• 2004

다공성 매질내의 거품(foam)은 가스상의 이동성을 감소시키는 특성을 가진다. 이러한 성질은 석유산업에서 중력으로 인한 유체유동을 방지하거나 산(acid)을 이용하여 유정(wellbore) 근처 유체투과율이 낮은 지층을 처리하는데도 사용될 뿐만 아니라, 지하 대수층의 오염물 회수율을 높이는 데도 사용된다. 최근의 연구결과를 통하여 다공성 매질 내 거품의 유동은 유동영역(flow regime)에 의하여 크게 영향을 받는다는 사실을 규명하였다. 이 논문은 실험자료와 수치해석기법을 이용하여, 지하 오염물질 정화를 위한 거품 유동분할 작업의 타당성에 관한 연구이다. 두 종류의 유체 투과율(k=9.1과 30.4 darcy)을 가지고 실험한 결과, 대수층 조건과 비슷한 실험환경에서도 정상상태의 거품은 유동영역에 따라 다른 성질을 보인다는 사실을 알 수 있었다. 거품의 질이 낮은 영역(low-quality regime)에 있는 거품은 shear thinning 거동을 보이며 고질영역(high-quality regime)에 있는 거품은 Newtonian 거동과 유사하였다. 이상의 실험 결과를 유체투과율이 서로 다른 두 지층에 대하여 거품의 유동분할을 예측하기 위하여 간단한 수치해석 모델을 개발하였다. 수치해석의 결과로부터 고질영역에 있는 거품은 유동분할 양상을 보였지만 저질영역에 있는 거품은 그렇지 않았다. 민감도 분석의 결과 고질영역에서의 유동분할은 각 지층들의 한계 모세관압, 즉 거품이 생성되고 유지되기 위한 최소 모세관압에 의해 좌우된다는 사실을 확인하였다.

• Biotechnology and Bioprocess Engineering:BBE
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• 제5권6호
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• pp.456-459
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• 2000

A pilot scale experiment was performed for a year to develop a two-phase anaerobic process for piggery wastewater treatment (COD: 6,000mg/L, BOD: 4,000mg/L, SS: 500mg/L, pH 8.4, alkalinity 6,000mg/L). The acidogenic reactor had a total volume of 3㎥, and the methanogenic reactor, an anaerobic up-flow sludge filter, combining a filter and a sludge bed, was also of total volume 3㎥(1.5㎥ of upper packing material). Temperatures of the acidogenic and methanogenic reactors kept at 20$^{\circ}C$ and 35$^{\circ}C$, respectively. When the pH of the acidogenic reactor was controlled at 6.0-7.0 with HCl, the COD removal efficiency increased from 50 to 80% over a period of six months, and as a result, the COD of the final effluent fell in the range of 1,000-1,500 mg/L. BOD removal efficiency over the same period was above 90%, and 300 to 400 mg/L was maintained in the final effluent. The average SS in the final effluent was 270 mg/L. The methane production was 0.32㎥ CH$_4$/kg COD(sub)removed and methane content of the methanogenic reactor was high value at 80-90%. When the pH of the acidogenic reactor was not controlled over the final two months, the pH reached 8.2 and acid conversion decreased compared with that of pH controlled, while COD removal was similar to the pH controlled operation. Without pH control, the methane content in the gas from methanogenic reactor improved to 90%, compared to 80% with pH control.

• 한국전자파학회논문지
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• 제22권8호
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• pp.768-775
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• 2011

대용량 데이터 전송을 위한 무선 통신 시스템에서는 높은 신뢰도를 보장하는 오류 보상 기법이 요구되며, 그러한 기법 중 하나로 재전송 방식과 터보 부호를 결합한 터보 HARQ(Hybrid Automatic Repeat Request) 기법이 여러 문헌에서 연구되어 오고 있다. 기존 터보 HARQ 기법의 경우, 수신 데이터의 일부분이 오류 정정 가능함에도 불구하고 NAK 신호 발생 시에 송신단에서는 정해진 정보 패킷 전체를 반복 전송하게 된다. 이와 같은 과정에서 재전송이 요구되는 정보 패킷 중 필요한 일부만을 송신할 경우 시스템의 전송 효율을 높일 수 있다. 본 논문에서는 전송 효율을 높이기 위한 방법으로 사후 정보 값의 부호 변화를 이용한 오류 데이터 판단 기준 및 부분 재전송 방식을 이용한 터보 HARQ 기법을 제안한다. 제안된 기법에 대한 모의 실험을 통해 전송 효율을 도출하고 성능을 분석한다.