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AI를 위한 논증 타당성 확인 알고리즘 구현 - 프로그램 언어 R을 활용한 명제 논증의 타당성 입증을 중심으로
정재환 ( Chung Jaehwan ),정진규 ( Jeong Jinkyu ) 중앙대학교 인문콘텐츠연구소 2022 인공지능인문학연구 Vol.10 No.-
This proposes an overall algorithm that AI may use to check whether an individual argument is valid or invalid. We can generally convince that humans are not logical, but it is challenging to persuade people AI is not rational. To produce such an AI, we will make the following proposals in this study. First, an algorithm that allows AI to examine the validity of individual arguments through the R program. The R program was chosen because the language is inherently functional. Therefore, R program always produces the same result for particular data input. It has ‘referential transparency’, and there is no ‘side effect’. Second, we will propose converting propositional logic into JSON format so that AI can know what elements constitute a specific logical expression, what characteristics it has, and what a specific symbol means. The JSON format can be easily read and written by humans while also easy for machines to parse and generate. Also, the propositional logic expression converted to this format can be used in other programming languages. Therefore, converting propositional logic expressions into JSON format is a good methodology for AI to handle propositional logic.
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이상 유동에서의 유체-구조 연성해석을 위한 Direct Forcing/Ficititious Domain-Level Set Method
전충호(Chung Ho Jeon),윤현식(Hyun-Sik Yoon),정재환(JaeHwan Jung) 한국해양공학회 2011 韓國海洋工學會誌 Vol.25 No.4
In the present paper, a direct forcing/fictitious domain (DF/FD) level set method is proposed to simulate the FSI (fluid-solid interaction) in two-phase flow. The main idea is to combine the direct-forcing/fictitious domain (DF/FD) method with the level set method in the Cartesian coordinates. The DF/FD method is a non-Lagrange-multiplier version of a distributed Lagrange multiplier/fictitious domain (DLM/FD) method. This method does not sacrifice the accuracy and robustness by employing a discrete δ (Dirac delta) function to transfer quantities between the Eulerian nodes and Lagrangian points explicitly as the immersed boundary method. The advantages of this approach are the simple concept, easy implementation, and utilization of the original governing equation without modification. Simulations of various water-entry problems have been conducted to validate the capability and accuracy of the present method in solving the FSI in two-phase flow. Consequently, the present results are found to be in good agreement with those of previous studies.
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군병원에서 수술중 신경생리검사장비 운용의 경험 및 유용성에 대한 연구
윤상훈 ( Sang Hoon Yoon ),함정식 ( Jeong-sik Ham ),박호영 ( Ho-young Park ),이건영 ( Gunyoung Lee ),정재환 ( Jaehwan Chung ),조현준 ( Hyun Jun Jo ),김현빈 ( Hyunbin Kim ),김새롬 ( Sae Rom Kim ),조병규 ( Byung-kyu Cho ) 국군의무사령부 2016 대한군진의학학술지 Vol.47 No.1
Objectives; The authors aimed to introduce the clinical experience and efficacy using intraoperative neurophysiologic monitoring (IONM) system for neurological surgery from January 2015 to August 2016 in Armed Forces Capital Hospital. Methods; Retrospective observational study was performed. This system was used in 17 operations above the periods. Every operation and monitoring result were reviewed in electronic medical records. Three patients with brain lesions (1 AVM, 2 brain tumor) underwent surgical resection with IONM. Two brain tumor were a facial schwannoma and a frontal neuronal tumor. Fourteen spinal operations consisted with nine benign degenerative compressive lesions, two neurogenic tumor, a intramedullary cavernous hemangioma, two neurogenic tumors, a vertebral fracture and tumor. IONM was tailored to the single patient, and consisted in transcranial MEP monitoring, cortical MEP monitoring, SSEP monitoring and direct electrical stimulation. Results; None of patients suffered from permanent motor deficits; a patient had a transient peripheral type facial nerve palsy requiring rehabilitation. None of the patients had intraoperative seizures and postoperative IONM related complication. Seven cases (41.2%) met the criteria of neurophysiologic changes during operation. Of these, six cases were restored to normal during operation spontaneously or with surgical manipulation. An unrestored neurophysiologic cases showed new post-operative neurological deficits (peripheral type facial palsy; H-B grade 4). No patients showed neurological deficits without any changes in IONM. Conclusions; Proper application of IONM may be useful to detect intraoperative neurological injury during all neurosurgical operations and improve surgical outcomes especially in subgroup of invasive brain surgery. Larger series of patients are required to confirm this preliminary data. More expert clinical neurophysiologists and neurologists should be recruited to enlarge opportunity to perform surgery under IONM for patient’s safety and good surgical outcome.
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