• Journal of ILASS-Korea
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• v.24 no.1
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• pp.21-26
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• 2019

In Korea, Medium-duty trucks are classified into GVW (Gross Vehicle Weight) 3.5~10tons. MDTs are mostly used for logistics or delivery between regions. There have been studied on diesel fuel vehicles for SUVs(Sports Utility Vehicle) or light-duty trucks. But MDTs have been not studied. Therefore, this study have been used MDTs for characteristic exhaust emission. Test was carried out using the certification test mode (NEDC, New European Driving cycle) and the NIER mode in chassis dynamometer of the MDTs. And emission gas was analyzed for PN (Particulate Number), PN size distribution and aldehydes, VOCs (Volatile Organic Compounds), PAHs (Polycyclic Aromatic Hydrocarbons). This paper concluded that EURO-IV trucks produced more MSATs than EURO V trucks. Depending on the engine temperature, more MSATs were generated in cold temperature than in the hot start operation. However, the driving speed, the opposite results was obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1708-1727
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• 2021

In the advent of the twenty-first century, human beings began to closely interact with technology. Today, technology is developing, and as a result, the world wide web (www) has a very important place on the Internet and the significant task is fulfilled by Web services. A lot of Web services are available on the Internet and, therefore, it is difficult to find matching Web services among the available Web services. The recommendation systems can help in fixing this problem. In this paper, our observation was based on the recommended method such as the collaborative filtering (CF) technique which faces some failure from the data sparsity and the cold-start problems. To overcome these problems, we first applied an ontology-based clustering and then the k-nearest neighbor (KNN) algorithm for each separate cluster group that effectively increased the data density using the past user interests. Then, user ratings were predicted based on the model-based approach, such as singular value decomposition (SVD) and the predictions used for the recommendation. The evaluation results showed that our proposed approach has a less prediction error rate with high accuracy after analyzing the existing recommendation methods.

• The Korea Journal of Herbology
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• v.36 no.6
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• pp.9-16
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• 2021

Objectives : The researcher had investigated the efficacy of ginseng using Microneedle Therapy System (MTS) and confirmed the effect of ginseng Cold Process (CP) soap just before and after washing face. The purpose of this study was to find out what kind of effect appeared through a period of 6 weeks when environmental factors were involved using ginseng CP soap. Methods : The researcher selected 47 subjects, 37 as the experimental group and 10 as the control group. The researcher asked participants to wash their face twice a day in the morning and evening using ginseng CP soap, and the period was set for 6 weeks. The researcher had the people who selected as the control group use a commercially available foam cleanser. They performed a skin test before the start of the test, and the change status was continuously investigated 2 weeks, 4 weeks, and 6 weeks after using the soap. Results : In the case of T-zone oil, there was a significant decrease in the use of foam cleansing and ginseng CP soap, and in the case of pores and pigmentation, a significant decrease was observed only in the use of ginseng CP soap. In skin tone change, there was a significant effect in both the experimental group and the control group, but the significance was greatly increased in the case of ginseng CP soap compared to foam cleansing. Conclusions : Ginseng CP soap is considered to be a more suitable cleanser for skin care compared to foam cleansing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3913-3934
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• 2021

Real-time prediction of Web service of quality (QoS) provides more convenience for web services in cloud environment, but real-time QoS prediction faces severe challenges, especially under the cold-start situation. Existing literatures of real-time QoS predicting ignore that the QoS of a user/service is related to the QoS of other users/services. For example, users/services belonging to the same group of category will have similar QoS values. All of the methods ignore the group relationship because of the complexity of the model. Based on this, we propose a real-time Matrix Factorization based Clustering model (MFC), which uses category information as a new regularization term of the loss function. Specifically, in order to meet the real-time characteristic of the real-time prediction model, and to minimize the complexity of the model, we first map the QoS values of a large number of users/services to a lower-dimensional space by the PCA method, and then use the K-means algorithm calculates user/service category information, and use the average result to obtain a stable final clustering result. Extensive experiments on real-word datasets demonstrate that MFC outperforms other state-of-the-art prediction algorithms.

• Journal of ILASS-Korea
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• v.28 no.3
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• pp.143-149
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• 2023

Amidst the drive towards carbon neutrality, interest in renewable synthetic e-fuels is rising rapidly. These fuels, generated through the synthesis of atmospheric carbon and green hydrogen, offer a sustainable solution, showing advantages like high energy density and compatibility with existing infrastructure. The physical properties of e-fuels can be different from those of conventional gasoline based on manufacturing methods, which requires investigations into how the physical properties of e-fuels affect the fuel injection characteristics. This study performs a comparative analysis between conventional and Fischer-Tropsch (F-T) synthetic gasoline (e-gasoline) across various fuel temperatures, including the cold start condition. The fuel properties of F-T synthetic and conventional gasoline are analyzed using a gas chromatography-mass spectrometry technique and the injection rates are measured using a Bosch-tube injection rate meter. The F-T synthetic gasoline exhibited higher density and kinematic viscosity, but lower vapor pressure compared to the conventional gasoline. Both fuels showed an increase in injection rate as the fuel temperature decreased. The F-T synthetic gasoline showed higher injection rates compared to conventional gasoline regardless of the fuel temperature.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.427-430
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• 2022

추천시스템에서 콜드스타트 문제를 해결하기 위해 다양한 연구들이 진행되고 있다. 하지만, 대부분의 연구는 아직도 사용자 기반의 히스토리 데이터셋을 반드시 필요로 하여, 콜드스타트 문제를 완벽히 해결하지 못하고 있다. 이에 본 논문은 콜드스타트 문제를 완화할 수 있는 기저속성 기반의 추천시스템을 제안한다. 제안하는 방법론을 검증하기 위해, 직접 수집한 한국어 영화 리뷰 데이터셋을 기반으로 성능을 검증하였으며, 평가 결과 제안한 방법론이 키워드와 사용자의 리뷰 점수를 효과적으로 반영한 추천시스템임을 확인할 수 있었고, 데이터 희소성 및 콜드스타트 문제를 완화하여 기존의 텍스트 기반 랭킹 시스템의 성능을 압도하는 것을 확인하였다. 더 나아가 제안된 기저속성 추천시스템은 추론 시에 GPU 컴퓨팅 자원을 요구하지 않기에 서비스 측면에서도 많은 이점이 있음을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.385-387
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• 2022

With the tremendous rise in popularity of the Internet and technological advancements, many news keeps generating every day from multiple sources. As a result, the information (News) on the network has been highly increasing. The critical problem is that the volume of articles or news content can be overloaded for the readers. Therefore, the people interested in reading news might find it difficult to decide which content they should choose. Recommendation systems have been known as filtering systems that assist people and give a list of suggestions based on their preferences. This paper studies a personalized news recommendation system to help users find the right, relevant content and suggest news that readers might be interested in. The proposed system aims to build a hybrid system that combines collaborative filtering with content-based filtering to make a system more effective and solve a cold-start problem. Twitter social media data will analyze and build a user's profile. Based on users' tweets, we can know users' interests and recommend personalized news articles that users would share on Twitter.

• Journal of Creative Information Culture
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• v.4 no.3
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• pp.221-230
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• 2018

Collaborative filtering technique is a major method of recommender systems and has been successfully implemented and serviced in real commercial online systems. However, this technique has several inherent drawbacks, such as data sparsity, cold-start, and scalability problem. Clustering-based collaborative filtering has been studied in order to handle scalability problem. This study suggests a collaborative filtering system which utilizes genetic algorithms to improve shortcomings of K-means algorithm, one of the widely used clustering techniques. Moreover, different from the previous studies that have targeted for optimized clustering results, the proposed method targets the optimization of performance of the collaborative filtering system using the clustering results, which practically can enhance the system performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.1-8
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• 2023

Cross-domain recommendation is a method that shares related user information data and item data in different domains. It is mainly used in online shopping malls with many users or multimedia service contents, such as YouTube or Netflix. Through K-means clustering, embeddings are created by performing clustering based on user data and ratings. After learning the result through a transformer network, user satisfaction is predicted. Then, items suitable for the user are recommended using a transformer-based recommendation model. Through this study, it was shown through experiments that recommendations can predict cold-start problems at a lesser time cost and increase user satisfaction.

• Journal of Veterinary Clinics
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• v.26 no.5
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• pp.441-444
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• 2009

Ischemia-reperfusion (I/R) injury is associated with an increased risk of acute rejection, delayed graft function and long-term changes after kidney transplantation. The reperfusion models remain unsolved complications such as vascular obstruction and blood leakage. We developed an alternative model of isolated hemoperfusion in porcine kidneys. In the present study we introduced a newly developed reperfusion method. A connector was used instead of surgical suture for the vascular anastomosis on the inguinal region in which main femoral vessels are parallel and big enough to perfuse the kidney. To assess renal perfusion quality of the modified hemoreperfusion model, we analyzed both hemodynamic values and patterns of I/R injury following a renal reperfusion. Following unilateral nephrectomy, the kidneys were preserved for 0, 24 and 48 hours at $4^{\circ}C$ with histidine-tryptophan ketogluatarate (HTK) solution and reperfused for 3 hours by vascular anastomosis connected to the femoral artery and vein in inguinal region. Histolopathological examinations were assessed on kidney biopsy specimens, taken after each cold storage and reperfusion. No differences of hemodynamic values were observed between aorta and femoral artery. The average warm ischemia time before reperfusion start was $7.0{\pm}1.1$ minutes. There were no complications including vascular obstruction and blood leakage during the reperfusion. I/R injury of the perfused kidneys in this model was dependent upon the cold ischemia time. The results support that the modified perfusion model is simple and appropriate for the study of early renal I/R injury and transplant immunology.