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기업수명주기이론에 따른 중국 제조업 상장기업의 이익조정에 관한 연구
상가석(Jiashuo Shang),이장희(Janghee Lee) 글로벌경영학회 2016 글로벌경영학회 학술대회 발표논문집 Vol.2016 No.2
본 연구는 기업수명주기에 따라 중국 제조업 상장기업의 이익조정 정도의 변화를 연구한다. 사용한 수명주기 측정 기준은 Dickinson(2006)의 구분 방법이다. 즉, 기업의 현금흐름으로 수명주기에 구분한다. 연구 대상은 2011년부터 2015년 까지 중국 상해와 선전 증권거래소에서 부통주 발급한 제조업 상장기업이다. 연구 결과는 성장기 기업의 발생액 이익조정 정도가 성수기 기업보다 크지만 P값이 유의하지 않은 것으로 나타났다; 성숙기 기업에 비해서 성장기 기업의 실제 이익조정 정도 가 큰 것으로 나타났다; 쇠퇴기 기업의 발생액과 실제 이익조정 정도가 성숙기 기업보다큰 것으로 나타났다. 추가분석에서 발생액 이익조정에 대해 상향조정과 하향조정을 구분하고 결과는 쇠퇴기 기업의 발생액 상향조정 정도가 성숙기 기업보다 큰 것으로만 나타났다. This paper is a study about the earnings management based on life cycle theory. We used the Dickinson method to divide the stage of films by cash flow patterns. The research object was the manufacturing industry listed companies which was issued A-stocks in the Shanghai and Shenzhen Securities Exchange Market from 2011-2015. The Results shows that compare with the film at the maturity, the degree of real earnings management at the growth is bigger, and the degree of accrual and real earnings management at the decline stage is more than the degree of accrual and real earnings management at the maturity stage. In the additional analysis, we further the manipulation of plus or minus accrued profits from the increase, reduction of the surplus management point to test the hypothesis, the results only show that compare with the film at the maturity stage, the degree of positive accrual earnings management at the decline stage is h
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Zhou Qing-Qing,Wang Jiashuo,Tang Wen,Hu Zhang-Chun,Xia Zi-Yi,Xue-Song Li,Zhang Rongguo,Yin Xindao,Zhang Bing,Zhang Hong 대한영상의학회 2020 Korean Journal of Radiology Vol.21 No.7
Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists’ workload.
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Core@shell MOFs derived Co2P/CoP@NPGC as a highly-active bifunctional electrocatalyst for ORR/OER
Weijia Gong,Hongyu Zhang,Liuyang Zhou,Ya Yang,Jiashuo Wang,Heng Liang 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.106 No.-
In this study, Co2P/CoP hybrid nanoparticles (NPs) imbedded on the surface of core–shell metal–organicframeworks (MOFs) derived three-dimensional N, P co-doped graphitized carbon (Co2P/CoP@NPGC) areprepared via direct pyrolysis of P-containing MOF precursors. P dopant dosage is tailored to adjust activesites and crystalline phases of Co2P/CoP@NPGC. The active Co2P and CoP NPs and the synergistic effectfrom the Co-Nx/C and Co-P/C active sites and porous NPGC make the dominant contributions to theORR/OER. For ORR, the half-wave potential of Co2P/CoP@NPGC-1 is 0.93 V, which is superior to that ofPt/C (E1/2 = 0.875 V). As for OER, Co2P/CoP@NPGC-1 displays a lower overpotential (ƞ = 340 mV) comparedto RuO2 (ƞ = 380 mV, at 10 mA cm2). The Co2P@CoOOH heterojunction guarantees intrinsic conductivity. Furthermore, doping with N and P can modify the surface electronic structure of catalyst to lower theenergy of oxygen adsorption and dissociation, which are beneficial to enhance the ORR and OER activity. Additionally, its bifunctional activity parameter (DE) for ORR and OER is only 0.64 V, which is lower thanthat of Pt/C and RuO2 (0.76 V). Therefore, this work proposes a new sight into constructing a competitivecore–shell MOFs derived electrocatalyst for ORR/OER.
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