• Title/Summary/Keyword: mass operator

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A Dual Modeling Method for a Real-Time Palpation Simulator

  • Kim, Sang-Youn;Park, Se-Kil;Park, Jin-Ah
    • Journal of Information Processing Systems
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    • v.8 no.1
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    • pp.55-66
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    • 2012
  • This paper presents a dual modeling method that simulates the graphic and haptic behavior of a volumetric deformable object and conveys the behavior to a human operator. Although conventional modeling methods (a mass-spring model and a finite element method) are suitable for the real-time computation of an object's deformation, it is not easy to compute the haptic behavior of a volumetric deformable object with the conventional modeling method in real-time (within a 1kHz) due to a computational burden. Previously, we proposed a fast volume haptic rendering method based on the S-chain model that can compute the deformation of a volumetric non-rigid object and its haptic feedback in real-time. When the S-chain model represents the object, the haptic feeling is realistic, whereas the graphical results of the deformed shape look linear. In order to improve the graphic and haptic behavior at the same time, we propose a dual modeling framework in which a volumetric haptic model and a surface graphical model coexist. In order to inspect the graphic and haptic behavior of objects represented by the proposed dual model, experiments are conducted with volumetric objects consisting of about 20,000 nodes at a haptic update rate of 1000Hz and a graphic update rate of 30Hz. We also conduct human factor studies to show that the haptic and graphic behavior from our model is realistic. Our experiments verify that our model provides a realistic haptic and graphic feeling to users in real-time.

Psychological Distress and Pain Reporting in Australian Coal Miners

  • Carlisle, Kristy N.;Parker, Anthony W.
    • Safety and Health at Work
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    • v.5 no.4
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    • pp.203-209
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    • 2014
  • Background: Coal mining is of significant economic importance to the Australian economy. Despite this fact, the related workforce is subjected to a number of psychosocial risks and musculoskeletal injury, and various psychological disorders are common among this population group. Because only limited research has been conducted in this population group, we sought to examine the relationship between physical (pain) and psychological (distress) factors, as well as the effects of various demographic, lifestyle, and fatigue indicators on this relationship. Methods: Coal miners (N = 231) participated in a survey of musculoskeletal pain and distress on-site during their work shifts. Participants also provided demographic information (job type, age, experience in the industry, and body mass index) and responded to questions about exercise and sleep quality (on-and off-shift) as well as physical and mental tiredness after work. Results: A total of 177 workers (80.5%) reported experiencing pain in at least one region of their body. The majority of the sample population (61.9%) was classified as having low-level distress, 28.4% had scores indicating mild to moderate distress, and 9.6% had scores indicating high levels of distress. Both number of pain regions and job type (being an operator) significantly predicted distress. Higher distress score was also associated with greater absenteeism in workers who reported lower back pain. In addition, perceived sleep quality during work periods partially mediated the relationship between pain and distress. Conclusion: The study findings support the existence of widespread musculoskeletal pain among the coal-mining workforce, and this pain is associated with increased psychological distress. Operators (truck drivers) and workers reporting poor sleep quality during work periods are most likely to report increased distress, which highlights the importance of supporting the mining workforce for sustained productivity.

Predictive Model of Optimal Continuous Positive Airway Pressure for Obstructive Sleep Apnea Patients with Obesity by Using Machine Learning (비만 폐쇄수면무호흡 환자에서 기계학습을 통한 적정양압 예측모형)

  • Kim, Seung Soo;Yang, Kwang Ik
    • Journal of Sleep Medicine
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    • v.15 no.2
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    • pp.48-54
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    • 2018
  • Objectives: The aim of this study was to develop a predicting model for the optimal continuous positive airway pressure (CPAP) for obstructive sleep apnea (OSA) patient with obesity by using a machine learning. Methods: We retrospectively investigated the medical records of 162 OSA patients who had obesity [body mass index (BMI) ≥ 25] and undertaken successful CPAP titration study. We divided the data to a training set (90%) and a test set (10%), randomly. We made a random forest model and a least absolute shrinkage and selection operator (lasso) regression model to predict the optimal pressure by using the training set, and then applied our models and previous reported equations to the test set. To compare the fitness of each models, we used a correlation coefficient (CC) and a mean absolute error (MAE). Results: The random forest model showed the best performance {CC 0.78 [95% confidence interval (CI) 0.43-0.93], MAE 1.20}. The lasso regression model also showed the improved result [CC 0.78 (95% CI 0.42-0.93), MAE 1.26] compared to the Hoffstein equation [CC 0.68 (95% CI 0.23-0.89), MAE 1.34] and the Choi's equation [CC 0.72 (95% CI 0.30-0.90), MAE 1.40]. Conclusions: Our random forest model and lasso model ($26.213+0.084{\times}BMI+0.004{\times}$apnea-hypopnea index+$0.004{\times}oxygen$ desaturation index-$0.215{\times}mean$ oxygen saturation) showed the improved performance compared to the previous reported equations. The further study for other subgroup or phenotype of OSA is required.

A Case Study on the Aggregate Planning of Multi-product Small-batch Production Facilities: Focusing on System Dynamics Simulation Modeling (다품종 소량생산 설비의 총괄생산계획에 관한 사례 연구: 시스템다이내믹스 시뮬레이션 모델링을 중심으로)

  • Lee, Seungdoe;Kim, Sang Won
    • Journal of Korean Society for Quality Management
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    • v.50 no.1
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    • pp.153-167
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    • 2022
  • Purpose: The purpose of this study is to guide the operation managers who plan daily production of large mass-processing facility that services multi-customers with multi-product, small-batch item characteristics by providing the practical best production quantity and the inventory allowed to build. Methods: Close observation of a subcontract paint-shop operator captured the daily decision process which was reflected in the subcontractor-unique mathematical model and the system dynamics simulation model. Multiple simulations were run to find the practical best production quantity and the maximum allowable stock level of inventory that did not undermine the profit from practical best daily production. Actual data and a few constant values were obtained from the firm under study. Results: While the inventory holding cost for the customer-owned material harms the total profit of the subcontractor, the running cost of the processing facility hinders production in small batches. This balances the maximum possible productions and results in practical best daily production which can be found through simulation runs with actual data. The maximum level of stocked inventory is deduced from the practical best daily production. Conclusion: To build a large volume that enables economy-of-scale production, operators should deal with multi-product small-batch items from multiple customers. When the planned schedule of the time and amount of material in-flow tend not to be reliable, operators can find it practical to execute level production across the planning horizon instead of adjusting to day-to-day in-flow fluctuations.

Automatic Left Ventricle Segmentation Algorithm using K-mean Clustering and Graph Searching on Cardiac MRI (K-평균 클러스터링과 그래프 탐색을 통한 심장 자기공명영상의 좌심실 자동분할 알고리즘)

  • Jo, Hyun-Wu;Lee, Hae-Yeoun
    • The KIPS Transactions:PartB
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    • v.18B no.2
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    • pp.57-66
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    • 2011
  • To prevent cardiac diseases, quantifying cardiac function is important in routine clinical practice by analyzing blood volume and ejection fraction. These works have been manually performed and hence it requires computational costs and varies depending on the operator. In this paper, an automatic left ventricle segmentation algorithm is presented to segment left ventricle on cardiac magnetic resonance images. After coil sensitivity of MRI images is compensated, a K-mean clustering scheme is applied to segment blood area. A graph searching scheme is employed to correct the segmentation error from coil distortions and noises. Using cardiac MRI images from 38 subjects, the presented algorithm is performed to calculate blood volume and ejection fraction and compared with those of manual contouring by experts and GE MASS software. Based on the results, the presented algorithm achieves the average accuracy of 6.2mL${\pm}$5.6, 2.9mL${\pm}$3.0 and 2.1%${\pm}$1.5 in diastolic phase, systolic phase and ejection fraction, respectively. Moreover, the presented algorithm minimizes user intervention rates which was critical to automatize algorithms in previous researches.

Study on the Front Detection Techniques by using Satellite Data (위성 자료를 이용한 전선 탐지 기법 연구)

  • Hwang, Do-Hyun;Bak, Su-Ho;Enkhjargal, Unuzaya;Jeong, Min-Ji;Kim, Na-Kyeong;Park, Mi-So;Kim, Bo-Ram;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.6
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    • pp.1201-1208
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    • 2020
  • A mass of seawater with similar properties in the ocean is called a water mass, and the front is a sea area where two masses of different properties meet. The gradient algorithm is a method of extracting where the sea water temperature pixel changes rapidly assuming that the slope is large, and the place with the large slope is assumed to be a front. This method is able to process large amounts of satellite data at once. Therefore, in this study, we tried to find the front lines in the sea area around the Korean Peninsula by using a gradient algorithm. The study data used gridded sea surface temperature satellite data. The resolution was 1/4°, and the monthly average data from January 1993 to December 2018 were used. There were major five fronts representatively, China Coastal Front, South Sea Coastal Front, Kuroshio Front/ Kuroshio Extension Front, Subpolar Front and the Subarctic Front. As a result of comparing the distribution of front by season, more types of front were distributed in winter and spring than in summer and autumn, and the distribution range was wider.

A study of Artificial Intelligence (AI) Speaker's Development Process in Terms of Social Constructivism: Focused on the Products and Periodic Co-revolution Process (인공지능(AI) 스피커에 대한 사회구성 차원의 발달과정 연구: 제품과 시기별 공진화 과정을 중심으로)

  • Cha, Hyeon-ju;Kweon, Sang-hee
    • Journal of Internet Computing and Services
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    • v.22 no.1
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    • pp.109-135
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    • 2021
  • his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

Stability Analysis of a Haptic System with a Human Impedance model using the Routh-Hurwitz Criterion (루드-후르비쯔 (Routh-Hurwitz) 안정성 판별법을 이용한 인간의 임피던스가 포함된 햅틱 시스템의 안정성 분석)

  • Lee, Kyungno
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.4
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    • pp.1813-1818
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    • 2014
  • This paper presents the stability analysis of the haptic system including a human impedance using the Routh-Hurwitz criterion. The reflective force is computed from a virtual spring model and is transferred to a human operator using the first-order-hold method. The stability boundary conditions are induced and the relation among a virtual spring ($K_w$), the mass ($M_h$), the damping ($B_h$) and the stiffness ($K_h$) of a human impedance is analyzed. Hence the stability boundary of the virtual spring ($K_w$) is proposed as $K_w{\leq}54413{\sqrt{(M_h+M_d)(B_h+B_d)}}-0.486K_h$ when the sampling time is 1 ms. The average relative error is about 0.5% when the mathematical analysis results are compared with the results of the stability boundary model.

A Study on the Management of Local Channel and Renewed License of Cable TV System Operator in Korea (케이블TV SO의 지역채널 운영 및 재허가 심사에 관한 연구)

  • Jung, In-Sook;Chung, Sang-Yune
    • Korean journal of communication and information
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    • v.54
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    • pp.58-75
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    • 2011
  • This study explores the management of cable local channel and its related issue of renewed license. Programming of the local channel is the special obligation duty on the cable system operators(SO) under the article 70 (3) of the Broadcast Act. The law provides that SO should operate a local channel which produce, program and transmit the local information, a broadcast program guide and the official announcement items etc. under the conditions as prescribed by Presidential Decree. And the article 55 of the Enforcement Decree defines the scope of broadcast program which transmit through the local channels. And the Korea Communications Commission(KCC) grants a renewed licence 3-5 years based on the level of contribution to the development of local community under the article 31 of the Broadcasting Act and the Rules of Broadcast Evaluation. However, the management of local channel does not give the operators real benefit for the investment of a significant cost, and it could be a reason why the local channel programming has not been vitalizing despite of the legal coercion. To solve the several research questions, this study used in-depth interviews with the experts concerned and literature review for the government documents. The result shows that each SO local channel schedule almost 24 hour a day, but much of them is the repeat programming. In addition to that, the outcome reveals that the scale of the cost investment on the local channel is decreasing and the evaluation score of its management is not so positive figures. These result indicates that the policy of the cable local channel needs revised policy alternatives or paradigm on the basis of realistic goals.

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The Correlation Between Deltamethrin Exposure and Urinary 3-PBA Concentrations in Rats (Deltamethrin에 노출된 흰쥐의 뇨 중 3-PBA 검출 및 노출상관성)

  • Kim, Areumnuri;Chon, Kyongmi;Park, Kyung-Hun;Moon, Byeong-Chul;Ro, Jin-Ho;Paik, Min Kyoung
    • Korean Journal of Environmental Agriculture
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    • v.36 no.4
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    • pp.293-298
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    • 2017
  • BACKGROUND: Pyrethroids (PYRs) are a widely used insecticide in agriculture and household area. In mammals, PYRs such as deltamethrin is metabolized to 3-phenoxybenzoic acid (3-PBA) in liver that is mainly excreted in urine. This study is designed to single exposure of deltamethrin to rats in a dose-dependent manner and identify the correlation between deltamethrin exposure and its metabolite (3-PBA) in urine. METHODS AND RESULTS: Exposure levels of deltamethrin were control (0 mg/kg bw), low (0.0705 mg/kg bw), medium (0.705 mg/kg bw) and high (7.05 mg/kg bw) dose. Low concentration was derived by ussing Korea predictive operator exposure model (KoPOEM). Dermal exposure persisted for 6 h, and urine specimens were collected for 24 h. The urine matrix was removed after a series of procedures and 3-PBA was analyzed by gas chromatography/mass spectrometry. CONCLUSION: There was a strong correlation ($R^2=0.83$) between the amount of oral exposure to delta me thrin and urinary levelof3-PBAexcreted. In dermal exposure groups of deltamethrin except high-dose, also there was a good correlation between urinary 3-PBA and deltamethrin exposure, but not stronger than in oral deltamethrin exposure groups. Based on these results, therefore, the amount of 3-PBA in urine can be used as a good monitoring indicator that reflexing the exposure level of deltamethrin to human body.