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A robot manipulator on the mobile platform for an off-road environment
Chanhun Park,Dongil Park,GwangJo Jung,Doohyung Kim,KyungTaik Park,Chulhun Park,Taeyong Choi 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10
Need for the robot-manipulator on the mobile robot is increasing. If the mobile manipulator is used in the on-road environment, the design concept of the manipulator is not different. But if it is designed for an off-road environment, it has to be designed to get over the vibrational forces induced by the off-road traveling. For the mobile platform, the design concept and process have been developed by many researchers, but for the manipulator on the mobile robot for an off-road environment, enough researches have not been done. For this reason, the authors are developing the design concept of the off-road manipulator. In this paper, the research results of the design of a robot manipulator on the mobile platform for an off-read environment will be introduced.
Roles of Inflammatory Biomarkers in Exhaled Breath Condensates in Respiratory Clinical Fields
Hye Jung Park, M.D., Ph.D.,Yong Jun Choi, M.D.,Min Jae Lee, M.D.,Min Kwang Byun, M.D., Ph.D.,Sangho Park, B.S.,Jimyung Park, M.D., Ph.D.,Dongil Park, M.D., Ph.D.,Sang-Hoon Kim, M.D., Ph.D.,Young Sam K 대한결핵및호흡기학회 2024 Tuberculosis and Respiratory Diseases Vol.87 No.1
Background: Exhaled condensates contain inflammatory biomarkers; however, theirroles in the clinical field have been under-investigated. Methods: We prospectively enrolled subjects admitted to pulmonology clinics. Wecollected exhaled breath condensates (EBC) and analysed the levels of six and 12biomarkers using conventional and multiplex enzyme-linked immunosorbent assay, respectively. Results: Among the 123 subjects, healthy controls constituted the largest group (81participants; 65.9%), followed by the preserved ratio impaired spirometry group (21patients; 17.1%) and the chronic obstructive pulmonary disease (COPD) group (21patients; 17.1%). In COPD patients, platelet derived growth factor-AA exhibited strongpositive correlations with COPD assessment test (ρ=0.5926, p=0.0423) and COPD-specificversion of St. George’s Respiratory Questionnaire (SGRQ-C) score (total, ρ=0.6725,p=0.0166; activity, ρ=0.7176, p=0.0086; and impacts, ρ=0.6151, p=0.0333). GranzymeB showed strong positive correlations with SGRQ-C score (symptoms, ρ=0.6078,p=0.0360; and impacts, ρ=0.6007, p=0.0389). Interleukin 6 exhibited a strong positivecorrelation with SGRQ-C score (activity, ρ=0.4671, p=0.0378). The absolute serum eosinophiland basophil counts showed positive correlations with pro-collagen I alpha 1(ρ=0.6735, p=0.0164 and ρ=0.6295, p=0.0283, respectively). In healthy subjects, forcedexpiratory volume in 1 second (FEV1)/forced vital capacity demonstrated significantcorrelation with CC chemokine ligand 3 (CCL3)/macrophage inflammatory protein 1alpha (ρ=0.3897 and p=0.0068). FEV1 exhibited significant correlation with CCL11/eotaxin(ρ=0.4445 and p=0.0017). Conclusion: Inflammatory biomarkers in EBC might be useful to predict quality of lifeconcerning respiratory symptoms and serologic markers. Further studies are needed.
Geometric Nonlinear Behavior Of Shallow Shells By Boundary Conditions
Park, Kanggeun,Lee, Dongwoo,Choe, Dongil,Park, Mijin SSNG Education Society 2017 International journal of latest trends in engineer Vol.8 No.4
<P> This paper investigates the mechanical characteristics of geometrical nonlinear behavior of shallow shells for boundary conditions of support. The shallow shells with a low rise-span ratio have a snap back and through behavior for a load condition or a support condition. The analytical models are a spherical shell, a cylindrical shell and a quadratic shell. The shells with all its edges hinged or fixed support condition are subjected to a concentrated load at the crown. The load is applied gradually by incrementing the deflection by displacement control. The objective of the study is to compare the load deflection curves according to support conditions or thicknesses. The element in the nonlinear analysis used 3-D four/eight nodes shell element and 3-D laminated composite shell element. In geometric nonlinear behavior of shallow shells, it will be observed for snap back and through behavior for a hinged and fixed support condition. The snap through phenomenon cannot be found in the load deflection curve of shells with the fixed support and the good results are observed for large deflection analysis of shells with hinged supports. </P>
Dongil Shin,Sungnam Kim,Geunseok Jeong,Jaesu Park,Joungwook Park,Ki Jin Han,Jingook Kim [Institute of Electrical and Electronics Engineers 2015 IEEE transactions on electromagnetic compatibility Vol.57 No.4
<P>A common-mode (CM) active filter was designed in a compact package to suppress CM conducted emissions at a switching mode power supply (SMPS). Based on the analytical expressions considering both stability and performance, the design and optimization rules for the proposed active filter have been presented. After verifying its performance by measurements using vector network analysis, the proposed filter was installed in a 200-W SMPS board with 64 and 110 kHz switching frequencies, demonstrating its usefulness by experiments. The performance degradation due to the magnetic saturation and the AEF grounding impedance was also analyzed and investigated.</P>
실험동물 사육실용 바이오 크린룸(BCR)의 급기 온도 및 풍속 변화 특성에 관한 수치해석적 연구
박동일(Dongil Park),정광섭(Kwangseop Chung),김영일(Youngil Kim),김성민(Sungmin Kim) 대한설비공학회 2012 설비공학 논문집 Vol.24 No.7
In this study, the analysis on the distribution of indoor airflow velocity and temperature by using numerical simulation has carried out to make fundamental data for establishing the optimum design of laboratory animal facilities. From the results, it was found that replacement of cage lacks, air supply and exhaust system, supply air temperature, supply air velocity affect to the optimum design of laboratory animal facilities as a important element.
LID-DS 데이터 세트를 사용한 기계학습 알고리즘 비교 연구
박대경 ( Park Daekyeong ),류경준 ( Ryu Kyungjoon ),신동일 ( Shin Dongil ),신동규 ( Shin Dongkyoo ),박정찬 ( Park Jeongchan ),김진국 ( Kim Jingoog ) 한국정보처리학회 2021 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.10 No.3
오늘날 정보통신 기술이 급격하게 발달하면서 IT 인프라에서 보안의 중요성이 높아졌고 동시에 지능형 지속 공격(Advanced Persistent Threat)처럼 고도화되고 다양한 형태의 사이버 공격이 증가하고 있다. 점점 더 고도화되는 사이버 공격을 조기에 방어하거나 예측하는 것은 매우 중요한 사안으로, NIDS(Network-based Intrusion Detection System) 관련 데이터 분석만으로는 빠르게 변형하는 사이버 공격을 방어하지 못하는 경우가 많이 보고되고 있다. 따라서 현재는 HIDS(Host-based Intrusion Detection System) 데이터 분석을 통해서 위와 같은 사이버 공격을 방어하는데 침입 탐지 시스템에서 생성된 데이터를 이용하고 있다. 본 논문에서는 기존에 사용되었던 데이터 세트에서 결여된 스레드 정보, 메타 데이터 및 버퍼 데이터를 포함한 LID-DS(Leipzig Intrusion Detection-Data Set) 호스트 기반 침입 탐지 데이터를 이용하여 기계학습 알고리즘에 관한 비교연구를 진행했다. 사용한 알고리즘은 Decision Tree, Naive Bayes, MLP(Multi-Layer Perceptron), Logistic Regression, LSTM(Long Short-Term Memory model), RNN(Recurrent Neural Network)을 사용했다. 평가를 위해 Accuracy, Precision, Recall, F1-Score 지표와 오류율을 측정했다. 그 결과 LSTM 알고리즘의 정확성이 가장 높았다. Today's information and communication technology is rapidly developing, the security of IT infrastructure is becoming more important, and at the same time, cyber attacks of various forms are becoming more advanced and sophisticated like intelligent persistent attacks (Advanced Persistent Threat). Early defense or prediction of increasingly sophisticated cyber attacks is extremely important, and in many cases, the analysis of network-based intrusion detection systems (NIDS) related data alone cannot prevent rapidly changing cyber attacks. Therefore, we are currently using data generated by intrusion detection systems to protect against cyber attacks described above through Host-based Intrusion Detection System (HIDS) data analysis. In this paper, we conducted a comparative study on machine learning algorithms using LID-DS (Leipzig Intrusion Detection-Data Set) host-based intrusion detection data including thread information, metadata, and buffer data missing from previously used data sets. The algorithms used were Decision Tree, Naive Bayes, MLP (Multi-Layer Perceptron), Logistic Regression, LSTM (Long Short-Term Memory model), and RNN (Recurrent Neural Network). Accuracy, accuracy, recall, F1-Score indicators and error rates were measured for evaluation. As a result, the LSTM algorithm had the highest accuracy.