• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.167-194
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• 2019

This research starts from the four basic concepts of incentive incompatibility, limited information, myopia and decision variable which are confronted when making decisions in keyword bidding. In order to make these concept concrete, four framework approaches are designed as follows; Strategic approach for the incentive incompatibility, Statistical approach for the limited information, Alternative optimization for myopia, and New model approach for decision variable. The purpose of this research is to propose the statistical optimization model in constructing the portfolio of Sponsored Search Advertising (SSA) in the Sponsor's perspective through empirical tests which can be used in portfolio decision making. Previous research up to date formulates the CTR estimation model using CPC, Rank, Impression, CVR, etc., individually or collectively as the independent variables. However, many of the variables are not controllable in keyword bidding. Only CPC and Rank can be used as decision variables in the bidding system. Classical SSA model is designed on the basic assumption that the CPC is the decision variable and CTR is the response variable. However, this classical model has so many huddles in the estimation of CTR. The main problem is the uncertainty between CPC and Rank. In keyword bid, CPC is continuously fluctuating even at the same Rank. This uncertainty usually raises questions about the credibility of CTR, along with the practical management problems. Sponsors make decisions in keyword bids under the limited information, and the strategic portfolio approach based on statistical models is necessary. In order to solve the problem in Classical SSA model, the New SSA model frame is designed on the basic assumption that Rank is the decision variable. Rank is proposed as the best decision variable in predicting the CTR in many papers. Further, most of the search engine platforms provide the options and algorithms to make it possible to bid with Rank. Sponsors can participate in the keyword bidding with Rank. Therefore, this paper tries to test the validity of this new SSA model and the applicability to construct the optimal portfolio in keyword bidding. Research process is as follows; In order to perform the optimization analysis in constructing the keyword portfolio under the New SSA model, this study proposes the criteria for categorizing the keywords, selects the representing keywords for each category, shows the non-linearity relationship, screens the scenarios for CTR and CPC estimation, selects the best fit model through Goodness-of-Fit (GOF) test, formulates the optimization models, confirms the Spillover effects, and suggests the modified optimization model reflecting Spillover and some strategic recommendations. Tests of Optimization models using these CTR/CPC estimation models are empirically performed with the objective functions of (1) maximizing CTR (CTR optimization model) and of (2) maximizing expected profit reflecting CVR (namely, CVR optimization model). Both of the CTR and CVR optimization test result show that the suggested SSA model confirms the significant improvements and this model is valid in constructing the keyword portfolio using the CTR/CPC estimation models suggested in this study. However, one critical problem is found in the CVR optimization model. Important keywords are excluded from the keyword portfolio due to the myopia of the immediate low profit at present. In order to solve this problem, Markov Chain analysis is carried out and the concept of Core Transit Keyword (CTK) and Expected Opportunity Profit (EOP) are introduced. The Revised CVR Optimization model is proposed and is tested and shows validity in constructing the portfolio. Strategic guidelines and insights are as follows; Brand keywords are usually dominant in almost every aspects of CTR, CVR, the expected profit, etc. Now, it is found that the Generic keywords are the CTK and have the spillover potentials which might increase consumers awareness and lead them to Brand keyword. That's why the Generic keyword should be focused in the keyword bidding. The contribution of the thesis is to propose the novel SSA model based on Rank as decision variable, to propose to manage the keyword portfolio by categories according to the characteristics of keywords, to propose the statistical modelling and managing based on the Rank in constructing the keyword portfolio, and to perform empirical tests and propose a new strategic guidelines to focus on the CTK and to propose the modified CVR optimization objective function reflecting the spillover effect in stead of the previous expected profit models.

• The Korean Society of Law and Medicine
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• v.23 no.4
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• pp.29-74
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• 2022

As social disasters occur under the Disaster Management Act, which can damage the people's "life, body, and property" due to the rapid spread and spread of unexpected COVID-19 infectious diseases in 2020, information collected through inspection and reporting of infectious disease pathogens (Article 11), epidemiological investigation (Article 18), epidemiological investigation for vaccination (Article 29), artificial technology, and prevention policy Decision), (3) It was used as an important basis for decision-making in the context of an infectious disease crisis, such as promoting vaccination and understanding the current status of damage. In addition, medical policy decisions using infectious disease data contribute to quarantine policy decisions, information provision, drug development, and research technology development, and interest in the legal scope and limitations of using infectious disease data has increased worldwide. The use of infectious disease data can be classified for the purpose of spreading and blocking infectious diseases, prevention, management, and treatment of infectious diseases, and the use of information will be more widely made in the context of an infectious disease crisis. In particular, as the serious stage of the Disaster Management Act continues, the processing of personal identification information and sensitive information becomes an important issue. Information on "medical records, vaccination drugs, vaccination, underlying diseases, health rankings, long-term care recognition grades, pregnancy, etc." needs to be interpreted. In the case of "prevention, management, and treatment of infectious diseases", it is difficult to clearly define the concept of medical practicesThe types of actions are judged based on "legislative purposes, academic principles, expertise, and social norms," but the balance of legal interests should be based on the need for data use in quarantine policies and urgent judgment in public health crises. Specifically, the speed and degree of transmission of infectious diseases in a crisis, whether the purpose can be achieved without processing sensitive information, whether it unfairly violates the interests of third parties or information subjects, and the effectiveness of introducing quarantine policies through processing sensitive information can be used as major evaluation factors. On the other hand, the collection, provision, and use of infectious disease data for research purposes will be used through pseudonym processing under the Personal Information Protection Act, consent under the Bioethics Act and deliberation by the Institutional Bioethics Committee, and data provision deliberation committee. Therefore, the use of research purposes is recognized as long as procedural validity is secured as it is reviewed by the pseudonym processing and data review committee, the consent of the information subject, and the institutional bioethics review committee. However, the burden on research managers should be reduced by clarifying the pseudonymization or anonymization procedures, the introduction or consent procedures of the comprehensive consent system and the opt-out system should be clearly prepared, and the procedure for re-identifying or securing security that may arise from technological development should be clearly defined.

• Radiation Oncology Journal
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• v.22 no.4
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• pp.237-246
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• 2004

Purpose: To investigate the effects of radiation dose-escalation on the treatment outcome, complications and the other prognostic variables for glioblastoma patients treated with 3D-conformal radiotherapy (3D-CRT). Materials and Methods: Between Jan 1997 and July 2002, a total of 75 patients with histologically proven diagnosis of glioblastoma were analyzed. The patients who had a Karnofsky Performance Score (KPS) of 60 or higher, and received at least 50 Gy of radiation to the tumor bed were eligible. All the patients were divided into two arms; Arm 1, the high-dose group was enrolled prospectively, and Arm 2, the low-dose group served as a retrospective control. Arm 1 patients received $63\~70$ Gy (Median 66 Gy, fraction size $1.8\~2$ Gy) with 3D-conformal radiotherapy, and Arm 2 received 59.4 Gy or less (Median 59.4 Gy, fraction size 1.8 Gy) with 2D-conventional radiotherapy. The Gross Tumor Volume (GTV) was defined by the surgical margin and the residual gross tumor on a contrast enhanced MRI. Surrounding edema was not included in the Clinical Target Volume (CTV) in Arm 1, so as to reduce the risk of late radiation associated complications; whereas as in Arm 2 it was included. The overall survival and progression free survival times were calculated from the date of surgery using the Kaplan-Meier method. The time to progression was measured with serial neurologic examinations and MRI or CT scans after RT completion. Acute and late toxicities were evaluated using the Radiation Therapy Oncology Group neurotoxicity scores. Results: During the relatively short follow up period of 14 months, the median overall survival and progression free survival times were $15{\pm}1.65$ and $11{\pm}0.95$ months, respectively. The was a significantly longer survival time for the Arm 1 patients compared to those in Arm 2 (p=0.028). For Arm 1 patients, the median survival and progression free survival times were $21{\pm}5.03$ and $12{\pm}1.59$ months, respectively, while for Arm 2 patients they were $14{\pm}0.94$ and $10{\pm}1.63$ months, respectively. Especially in terms of the 2-year survival rate, the high-dose group showed a much better survival time than the low-dose group; $44.7\%$ versus $19.2\%$. Upon univariate analyses, age, performance status, location of tumor, extent of surgery, tumor volume and radiation dose group were significant factors for survival. Multivariate analyses confirmed that the impact of radiation dose on survival was independent of age, performance status, extent of surgery and target volume. During the follow-up period, complications related directly with radiation, such as radionecrosis, has not been identified. Conclusion: Using 3D-conformal radiotherapy, which is able to reduce the radiation dose to normal tissues compared to 2D-conventional treatment, up to 70 Gy of radiation could be delivered to the GTV without significant toxicity. As an approach to intensify local treatment, the radiation dose escalation through 3D-CRT can be expected to increase the overall and progression free survival times for patients with glioblastomas.