• 한국언론정보학보
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• 제73권
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• pp.56-91
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• 2015

본 연구는 개국 5년차에 접어든 종합편성채널의 독립제작 환경과 관행을 미디어 생산과정의 유연전문화 및 조직 관행 관점에서 구체적으로 살펴보았다. 이를 위해 독립PD, 방송작가, 종편 관계자 등 13명을 심층 인터뷰한 결과, 첫째, 종편은 보도프로그램을 제외한 프로그램제작에서 독립제작에 의존도 높은 유연전문화 제작구조가 정착되었고, 시청률과 성과 중심의 계약 관행으로 인해 다양성이 담보된 프로그램 제작이 어려울 수 있음을 알 수 있었다. 둘째, 일부 채널에서는 지상파 보다 높은 제작비 및 인센티브 제도 등의 제작여건 개선도 있었지만, 이러한 보상체계는 방송사 내부의 경쟁과 독립제작자들 간의 경쟁을 심화시켜 저작권의 일방적 소유, 불공정거래로 이어졌음을 알 수 있었다. 셋째, 신문방송 겸영에 따른 사주의 영향력 뿐 아니라 신문사 출신 관리자의 관리구조로 인한 위계적인 독립제작 관행이 정착될 수 있음을 확인하였다. 마지막으로 종편 내부 관계자와 독립제작자들의 '종합편성'에 대한 인식을 살펴본 결과 일부 종편사 관계자는 다양성보다는 수익과 성과 측면에서 편성 장르와 내용이 우선적인 고려사항이라고 밝혔고, 광고주와 광고국에 의해 독립제작자들의 제작권이 침해받을 경우 다양한 소재와 장르에 대한 접근이 어려움을 알 수 있었다. 따라서 종편채널의 편성과 프로그램 독립제작은 기존의 '외주제작' 정책과 다른 관점에서의 제도적 보완과 규제가 필요함을 논의하였다.

• 공연문화연구
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• 제34호
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• pp.133-172
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• 2017

만수성절은 본래 중국 황제의 생일을 일컫는 용어이다. 조선의 경우 만수성절의 칭호를 쓸 수 없었지만, 개항 이후 자주적인 대외관계를 펼치기 위해 미국공사관을 설치한 해인 1888년부터 고종의 생일을 만수성절이라 칭했던 용례가 나타난다. 이어 1895년 무렵에는 만수성절이란 호칭이 더욱 널리 사용되었고, 고종이 황제로 즉위하면서 이를 기념한 경축 행사가 활성화 되었다. 대한제국 시기 만수성절 축하 행사는 각계각층에서 일어났다. 국내 관원, 외국인, 학생, 종교인, 언론인, 상인, 민간단체, 전국의 개항장 등 다양한 지역과 계층에서 고종황제 탄신을 기념하여, 축하 계층이 두텁고 넓었다. 즉 계층 지역 인종에서 보편성 전국성 국제성을 띠었다는 점에서 차별화 되었다. 이러한 특성으로 인해 축하 문화 역시 다양하게 전개되었으며, 이들에게 황실후원금도 지급되었다. 당시 만수성절 경축은 황제에 대한 존경심과 애국심으로 확장되었기 때문에, 황제권 강화와 내국인의 민심 결속에 크게 기여하였고, 그런 모습이 국내에 상주하는 각국 외교관과 취재기자를 통해 세계에 보도되어, 국권 신장에도 영향을 끼쳤다. 그러나 러일전쟁 발발 이후 일제가 대한제국의 황실 재정을 장악하고 황권을 위축시키면서 만수성절 행사도 축소된다. 통감부 시기에는 황실지원금의 단절, 일제의 단속, 고종황제 강제 퇴위로 인해 만수성절 기념 행사가 거의 사라졌고, 궁중에서만 친일관료와 일본인을 중심으로 형식적인 경축연만 설행되었다. 고종황제의 권력 실축과 대한제국의 멸망은 한 몸이었고, 만수성절 경축도 동반 추락하였다. 그런 가운데 궁중 전통 연향 문화는 해체되고, 일제에 의한 공연 환경의 변화로 인해 대한제국 최고의 공연자들은 일개 유희물로 전락해 버렸다. 비록 황제를 향한 존경심과 애국심의 표출 창구였던 만수성절은 굴절되었지만 황실 자본력에 힘입어 구축된 행사 과정에서 창출된 문화적 성취들은 한국근현대문화사가 전개되는 내적 동력으로 작동하였다는 점에서 의미가 있다고 본다.

• 정신신체의학
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• 제29권1호
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• pp.49-57
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• 2021

연구목적 전공의 공통역량으로서 의료커뮤니케이션의 중요성을 환기시키기 위하여 전공의를 대상으로 의료커뮤니케이션 능력을 조사하고 의료커뮤니케이션 능력, 진료수행 자기효능감 그리고 공감능력의 관련성을 분석하고자 하였다. 방 법 일 대학병원 소속 총 106명 전공의를 대상으로 자기평가 의료커뮤니케이션 능력, 수정된 진료수행 자기효능감 척도, 한국판 의사 공감 척도를 조사하였다. 성별, 나이, 전공과목(인턴, 내과계, 외과계), 연차(인턴, 1~2년차, 3~4년차)에 따른 의료커뮤니케이션 능력의 차이를 조사하였다. 상관분석으로 의료커뮤니케이션 능력, 수정된 진료수행 자기효능감, 공감능력의 상관계수를 구하였고 구조방정식 모형을 이용하여 의료커뮤니케이션 능력에 영향을 미치는 각 변수의 효과를 검증하였다. 결 과 인턴 31명(31.6%), 내과계 레지던트 45명(45.9%), 외과계 레지던트 22명(22.4%)으로 총 98명이 참가하였다. 성별, 나이, 전공과목, 연차에 따른 자기평가 의료커뮤니케이션 능력 점수는 통계적으로 유의한 차이가 없었다. 의료커뮤니케이션 능력은 수정된 진료수행 자기효능감(r=0.782, p<0.001) 및 공감능력(r=0.210, p=0.038)과 유의한 정적 상관관계가 있었다. 공감능력은 진료수행 자기효능감에 직접적으로 유의한 영향을 미쳤으며(β=0.30, p<0.01), 진료수행 자기효능감은 의료커뮤니케이션 능력에 직접적으로 유의한 영향을 보였다(β=0.80, p<0.001). 공감능력은 진료수행 자기효능감을 매개하여(β=0.26, p<0.05) 간접적으로 의료커뮤니케이션 능력에 영향을 미치고 있었다. 결 론 전공의 의료커뮤니케이션 능력은 성공적 진료를 위해 필요한 진료수행 자기효능감과 직접적 연관성이 있었으므로 전공의 공통교육과정의 하나로서 중요한 위치를 차치한다고 할 수 있다. 그리고 현재의 의료커뮤니케이션 모델은 공감 능력과는 구별해서 이해될 필요가 있음이 시사된다.

• 기독교교육논총
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• 제72권
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• pp.245-271
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• 2022

연구 목적 : 본 연구는 간호대학생을 대상으로 사례기반학습 및 코티칭을 적용한 간호 임상실습 교육모형을 개발하고, 개발된 모형의 타당성 확보를 목적으로 한다. 연구 내용 및 방법 : 간호 임상실습 교육모형의 타당성 검증을 위해 전주시 소재 J대학교 2021학년도 2학기'건강 반응과 간호 VI(지각·인지) 실습'과목에 적용하고 모형에 대한 교수자 반응평가를 실시하였고, 학습자 반응평가를 위해 임상 수행 자신감, 교수학습 모형에 대한 설문조사와 포커스 그룹 인터뷰를 진행하였다. 선행문헌 고찰과 사례 연구를 통해 사례기반학습 단계와 코티칭 요소를 도출한 후 전문가 검토를 받아 초기 모형을 구안하였고, 구안한 모형은 간호교육 전문가에게 내적 타당화를 검토받은 후 수정·보완하였다. 외적 타당화 검증을 위해 임상실습 교과에 모형을 적용한 후 실시한 학습자 반응평가 결과 임상 수행 자신감은 4.22점, 교수학습 모형 만족도는 4.68점으로 높게 나타났다. 포커스그룹 인터뷰 결과를 종합하면, 사전학습의 중요성과 실제 사례를 기반으로 선정한 사례를 학습하면서 전문용어, 전문지식 등을 습득함으로써 실습 현장에 대한 두려움이 없어지고 익숙함을 느꼈고, 다양한 사례를 학습하며 실습 현장에서 학습하였던 지식을 정리하는 시간을 통해 비판적 사고를 할 수 있었다고 하였다. 또 코티칭을 통하여 현장지도자와 지도교수가 함께 사례를 통해 이론과 실무적인 측면을 동시에 교수함으로써 실무와 더 가까워진 실습교육을 경험한 것으로 나타났다. 결론 및 제언 : 본 연구를 통하여 개발한 사례기반학습 및 코티칭을 적용한 간호 임상실습 교육모형은 이론과 실무 간의 차이를 줄여주고 간호 대학생의 임상수행 능력을 향상시킬 수 있는 효과적인 교수학습모형이 될 것으로 기대한다.

• 대한교통학회:학술대회논문집
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• 대한교통학회 1995년도 제27회 학술발표회
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• Asia pacific journal of information systems
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• 제24권4호
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• Radiation Oncology Journal
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• 제16권3호
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• pp.291-301
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• 1998

목적 : 국한성 병기 소세포폐암으로 복합 화학요법과 방사선치료를 받은 환자들에서 통상적 방사선치료와 다분할 방사선치료 간의 종양 관해율, 생존율, 재발율 및 부작용에 대해 비교분석하고자 하였다. 대상 및 방법 : 1989년 11월부터 1996년 12월까지 충남대학교 병원 치료방사선과에서 국한성병기 소세포폐암으로 치료받았던 78명 환자 중 고식적 방사선치료 및 재발성 병변으로 치료받았던 10명을 제외한 68명을 대상으로 후향성 분석을 하였다. 대상환자 중 통상적 방사선치료군(A군)은 26명, 다분할 방사선치료군 (B군)은 42명 이었다. 전체 환자의 연령, 성별 및 ECOG 활동지수는 각각 32-75세 (중앙값 58세), 남자 58명 여자 10명, ECOG 0-1이 58명 2 이상이 10명 이었으며 두군 간에 유사한 분포를 보였다. 방사선치료로서 A군은 총 조사선량 5040-6940 cGy (중앙값 5040 cGy), 180 cGy/fx 로 치료하였고 B군은 총 조사선량 4320-5100 cGy (중앙값 4560 cGy)으로 29명 (69$\%$)은 120 cGy/fx 로, 13명 (31$\%$)은 150 cGy/fx 로 1일 2회 조사하였다. 화학요법은 전체 68명 중 65명에서 VPP (cisplatin 60 mg/$m^2$, etoposide 100 mg/$m^2$) 요법과 CAV (cytoxan 1000 mg/$m^2$, adriamycin 40 mg/$m^2$, vincristine 1 mg/$m^2$) 요법을 교대로 시행하였으며, 화학요법 횟수는 A군 3-10회 (중앙값 6회), B군은 1-11회 (중앙값 6회) 시행하였다. 화학요법 시기는 A군에서 23명이 연속 화학요법을, B군에서는 39명이 동시 화학요법을 시행하였다. 예방적 전뇌조사는 두군 모두에서 완전관해 후 시행하였는데 A군 8명, B군 16명에서 조사선량 2500 cGy/10fx 로 조사하였다. 추적기간은 2-99개월 (중앙값 14개월)였다. 결과 : 종양 관해는 완전관해율, 부분관해율이 각각 A군 35$\%$ (9/26), 54$\%$ (14/26), B군 43$\%$ (18/42), 55$\%$ (23/42)(p=0.119) 였다. 중앙생존기간 및 2년 생존율은 전체환자에서 15개월, 26.8$\%$였고, A군 17개월, 26.9$\%$, B군 15개월, 28$\%$ 0=0.51)였다. 전체환자 중 완전관해 및 부분관해 환자의 2년 생존율은 각각, 35$\%$ 와 24.2$\%$ (p=0.05)였다. 실패양상으로 두 군간에 국소재발 및 원격전이의 통계적인 차이는 없었다 (p=0.125, 0.335). 방사선치료중 발생한 급성합병증으로 RTOG criteria상 중등도 이상의 식도염 및 백혈구 감소가 B 군에서 더 높게 나타났다 (p=0.028, 0.003). 결론 : 국한성 병기 소세포폐암의 복합 화학요법과 방사선치료시 종양의 부분관해 이상의 반응율이 연속화학요법을 받은 통상적 방사선 치료군과 동시화학요법을 받은 다분할 방사선 치료군 모두에서 높게 나타났다. 그러나 두 군간의 생존율에는 통계적인 차이를 보이지 않았다. 급성합병증으로서 식도염과 백혈구 감소가 동시화학요법을 받은 다분할 방사선치료군에서 더 높게났지만, 국한성 병기 소세포폐암에서 동시화학요법과 다분할 방사선치료가 적절한 치료의 한 방법이 될 수 있을 것으로 사료된다. 그러나 국한성 병기 소세포폐암에서 다분할 방사선치료의 장점을 밝히기 위하여 좀더 많은 대상환자와 추적관찰이 필요할 것으로 사료된다.

• Tuberculosis and Respiratory Diseases
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• 제42권6호
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• pp.900-912
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• 1995

연구배경: 최대운동부하 검사는 심폐기능의 종합적인 평가를 위하여 널리 이용되고 있으나 아직 우리나라에는 최대운동시의 호흡성 가스교환이나 폐기능의 정상치가 제대로 확립되어 있지 않은 설정이다. 본 연구의 목적은 한국성인에서 최대운동시의 이들 지표의 연령과 성별에 따른 정상치 내지 참고치를 마련하는 동시에 이들 중 일부지표의 추정정상치를 산출하는 회귀방정식을 구하는데 있다. 방법: 건강한 성인 남성 603명, 여성 397명, 합계 1,000명(20~66세)을 대상으로 Bruce법으로 증상제한성 최대운동부하 검사를 실시하였으며, 이중 885명에서는 VC, $FEV_1$ 및 MVV도 측정하였다 대상자들은 모두 전문체육인이 아닌 스포츠센터의 회원이었으며, 운동부하검사 중에는 안전상의 문제 때문에 부득이 트레드밀의 손잡이를 잡는 것을 허용하였다. 곁과: $VO_2\;max/m^2$, $VCO_2\;max/m^2$ 및 VE max/$m^2$는 모두 남성에서 뚜렷이 컸으며, 남녀에서 모두 연령의 증가에 따라 감소하였다. 한편 RR max는 성별에 따른 차이는 없었으나, 연령의 증가에 따라 약간씩 감소하였으며, $V_T$ max는 남성에서 월등히 많았으나 남녀에서 다같이 연령에 따른 일정한 경향의 변화는 없었다. 그리고 $V_T$ max/VC, $V_E$ max/MVV 및 BR의 평균은 최대운동시에 나이가 많은 여성에서도 상당한 환기예비가 있음을 보여주었다. 저자들은 성적을 토대로 운동시간(분), 나이(세), 시장(cm), 체중(kg), 성별(남=0, 여=1), VC(L), $FEV_1$(L) 및 VE max(L) 등을 변수로 해서 구한 주요 지표들의 회귀방정식은 다음과 같다. $VO_2\;max/m^2(L/min)=1.449+0.073{\times}$운동시간-$0.007{\times}$연령+$0.010{\times}$체중-$0.006{\times}$신장-$0.209{\times}$성별, $VCO_2\;max/m^2(L/min)=1.672+0.063{\times}$운동시간-$0.008{\times}$연령+$0.010{\times}$체중-$0.005{\times}$신장-$0.319{\times}$성별, $V_E\;max/m^2(L/min)=58.161+1.503{\times}$운동시간-$0.315{\times}$연령-$9.871{\times}$성별 또는 $V_E\;max/m^2(L/min)=47.873+6.458{\times}FEV_1-5.715{\times}$성별 및 $V_T\;max(L)=1.497+0.223{\times}VC-0.493{\times}$성별. 결론: 본 연구에서 얻은 최대운동시의 호흡성 가스 교환 및 환기기능에 관한 성적은 건강과 체력에 대해서 일반인보다 관심이 높을 것으로 생각되는 스포츠센터 회원들을 대상으로 한 것이기 때문에, 안전상의 문제로 트레드밀의 손잡이를 잡고 검사를 해야하는 환자나 건강인을 위한 이상적인 목표치 내지 정상치를 제공한 것으로 생각된다. Background: Although graded exercise stress tests are widely used for the evaluation of cardiorespiratory performance, normal standards on respiratory gas exchange and ventilatory functions at maximal exercise in Koreans have not been well established. The purpose of this study is to provide reference values on these by sex and age, along with derivation of some of their prediction equations. Method: Symptom-limited maximal exercise test was carried out by Bruce protocol in 1,000 healthy adults consisting of 603 males and 397 females, aged 20~66 years. Among them VC, $FEV_1$ and MVV were also determined in 885 cases. All the subjects were members of a health center, excluding athletes. During the exercise, subjects were allowed to hold on to front hand rail of the treadmill for safety purpose. Results: The $VO_2\;max/m^2$, $VCO_2\;max/m^2$ and $V_E\;max/m^2$ were greater in males than in females and decreased with age. The RR max in men and women was similar but decreased slightly with age. The $V_T$ max was markedly greater in men but showed no significant changes with age in either gender. The mean of $V_T$ max/VC, $V_E$ max/MVV and BR revealed that there were considerable ventilatory reserves at maximal exercise even in older females. The regression equations of the cardinal parameters obtained using exercise time(ET, min), age(A, yr), height(Ht, cm), weight(W, kg), sex(S, 0=male; 1=female), VC(L), $FEV_1$(L) and $V_E$ max(L) as variables are as follows: $VO_2\;max/m^2$(L/min)=1.449+0.073 ET-0.007A+0.010W-0.006Ht-0.209S, $VCO_2\;max/m^2$(L/min)=1.672+0.063ET-0.008A+0.010W-0.005Ht-0.319S, VE max/$m^2$(L/min)=58.161+1.503ET-0.315A-9.871S or VE max/$m^2$(L/min)=47.873+6.548 $FEV_1$-5.715 S, and VT max(L)=1.497+0.223VC-0.493S. Conclusion: Respiratory gas exchange and ventilatory variables at maximal exercise were studied in 1,000 non-athletes by Bruce protocol. During exercise, the subjects were allowed to hold on to hand rail of the treadmill for safety purpose. We feel that our results would provide ideal target values for patients and healthy individuals to be achieved, since our study subjects were members of a health center whose physical fitness levels were presumably higher than ordinary population.

• Asia pacific journal of information systems
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• 제20권3호
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• Asian-Australasian Journal of Animal Sciences
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• 제19권11호
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• pp.1566-1573
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• 2006

The study was conducted on 30 true acyclic Sahiwal cows (15 cows, ${\geq}90$ days postpartum; 15 postpubertal heifers, ${\geq}30$ months of age) and a similar 20 untreated controls (10 cows, 10 heifers). An 'Eazi' breed Controlled Internal Drug Release (CIDR) device (containing 1.38 g progesterone) was inserted intravaginally for 7 days (days 0 to 7) followed by 500 IU eCG i.m. at CIDR removal in all the treated animals. Heifers also received 5 mg oestradiol valerate i.m at CIDR insertion. The reproductive performance of these animals was recorded in terms of oestrus induction response, conception and pregnancy rates. Plasma progesterone ($P_4$) and oestradiol-$17{\beta}$ ($E_2$) profiles of 4 representative animals from each treatment group before, during and after CIDR treatment were also monitored. An oestrus induction response of 100% was observed in treated cows and heifers. The majority of cows (53.3%) and heifers (60%) were induced to oestrus within 24-36 and 36-48 h, respectively after CIDR withdrawal; with mean intervals of $44{\pm}3.18$ and $48{\pm}2.35h$, respectively. The conception rate at induced oestrus was higher in cows (40%) than heifers (20%). The final pregnancy rates after 2 subsequent oestruses were 80 and 60% in cows and heifers, respectively (overall 70% for all treated animals). In comparison, only 10% of control animals (2 cows only, 2/20) showed oestrus and become pregnant (10%) during theentire study period. The pretreatment (day 0) mean plasma P4 levels were statistically (p>0.05) similar in cows and heifers ($0.40{\pm}0.04$ and $0.49{\pm}0.11ng/ml$, respectively). The peak $P_4$ levels were observed on day 1 in cows ($13.94{\pm}1.41ng/ml$) and day 2 in heifers ($19.15{\pm}3.30ng/ml$) with a progressive decline up to the day of CIDR withdrawal ($3.35{\pm}0.92$ and $8.79{\pm}1.71ng/ml$, respectively). Mean $P_4$ levels on day 9 and 10 in cows and heifers did not differ significantly from their respective day 0 values and the lowest values were recorded on day 10 both in cows and heifers ($0.13{\pm}0.03$ and $0.14{\pm}0.02ng/ml$, respectively). Wide variations in individual pretreatment $E_2$ levels were observed both in the cows (range = 4-26, mean = $13.00{\pm}4.65pg/ml$) and heifers (range = 10-14, mean = $11.50{\pm}0.96pg/ml$). Thereafter also, $E_2$ levels in cows showed variation and reached a peak level ($53.50{\pm}2.99pg/ml$) on day 8. In heifers, peak mean $E_2$ level ($111.25{\pm}39.81pg/ml$) was recorded on day 1, followed by a non-significant decline on day 2, a significant fall on day 6 and a non-significant increase on day 9 and 10. However, mean $E_2$ levels on days 7 (p<0.05), 8 and 9 (p<0.01) were significantly higher in cows compared to heifers. The post-CIDR withdrawal mean highest $P_4$ and lowest $E_2$ levels coincided with the period when the majority of animals were induced to oestrus. CIDR and eCG treatment resulted in effective induction of oestrus with satisfactory pregnancy rates in true acyclic Sahiwal cows and heifers.