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신승준,박동하 대한성형외과학회 2006 Archives of Plastic Surgery Vol.33 No.4
Purpose: The cutaneous squamous cell carcinoma is the second most common skin malignancy. It is noted that keratoacanthoma is difficult to differentiate from squamous cell carcinoma, clinically or historically. It is still a hypothetical question whether keratoacanthoma is a pseudomalignancy or a form of squamous cell carcinoma. Methods: We report the case of squamous cell carcinoma around left ala of nose in a 64-year-old female patient. Through an incisional biopsy, the mass was found to be keratoacanthoma in the pathologic report. An excisional biopsy was performed. Results: Pathologic report notified that it was found well-differentiated squamous cell carcinoma arising in keratoacanthoma with focal involvement of deep resection margin. Wide excision was made with 0.5-1.5cm margin and immediate reconstruction was performed. Conclusion: The relationship between keratoacanthoma and squamous cell carcinoma has been debated in the treatment. It is still controversial whether to excise it or not. We concluded that kerathoacanthoma must be removed completely.
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스마트공장을 위한 빅데이터 애널리틱스 플랫폼 아키텍쳐 개발
신승준,우정엽,서원철 한국멀티미디어학회 2016 멀티미디어학회논문지 Vol.19 No.8
While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.
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