• KIPS Transactions on Computer and Communication Systems
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• v.7 no.6
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• pp.155-164
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• 2018

Many malicious programs have been compressed or encrypted using various commercial packers to prevent reverse engineering, So malicious code analysts must decompress or decrypt them first. The OEP (Original Entry Point) is the address of the first instruction executed after returning the encrypted or compressed executable file back to the original binary state. Several unpackers, including PinDemonium, execute the packed file and keep tracks of the addresses until the OEP appears and find the OEP among the addresses. However, instead of finding exact one OEP, unpackers provide a relatively large set of OEP candidates and sometimes OEP is missing among candidates. In other words, existing unpackers have difficulty in finding the correct OEP. We have developed new tool which provides fewer OEP candidate sets by adding two methods based on the property of the OEP. In this paper, we propose two methods to provide fewer OEP candidate sets by using the property that the function call sequence and parameters are same between packed program and original program. First way is based on a function call. Programs written in the C/C++ language are compiled to translate languages into binary code. Compiler-specific system functions are added to the compiled program. After examining these functions, we have added a method that we suggest to PinDemonium to detect the unpacking work by matching the patterns of system functions that are called in packed programs and unpacked programs. Second way is based on parameters. The parameters include not only the user-entered inputs, but also the system inputs. We have added a method that we suggest to PinDemonium to find the OEP using the system parameters of a particular function in stack memory. OEP detection experiments were performed on sample programs packed by 16 commercial packers. We can reduce the OEP candidate by more than 40% on average compared to PinDemonium except 2 commercial packers which are can not be executed due to the anti-debugging technique.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• Journal of Navigation and Port Research
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• v.37 no.1
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• pp.9-14
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• 2013

The e-navigation has been being developed in IMO is a sort of strategy to provide user-oriented services for safe navigation and environmental protection based on the architecture and its related services complying with the user needs. At NAV $57^{th}$ meeting in 2011, the overarching e-navigation architecture was approved which represent overall relationship only between onboard and ashore elements, so more detail technical architecture for each element should be developed for implementation in view of services and systems. Considering the continuous and iterative verification of e-navigation development process required by IMO, the relationship and traceability should be took in consideration between the outcome of e-navigation process and the element of the architecture. In this paper, we have surveyed literarily the user needs, result of gap analysis and practical solutions to address them and defined the architecture elements and their relationship considering the three kinds of views of DoDAF(Architecture Framework) of US department of Defence, in result, proposed the e-navigation shipboard technical architecture.

• Korean Journal of Plant Resources
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• v.26 no.2
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• pp.320-327
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• 2013

This study was carried out to address an efficient in vitro regeneration system from seed-derived callus of Phragmites communis, and to evaluate genetic variations of the regenerants using ISSR markers. Shoot regeneration via calli was greatly influenced by N6 medium compared with MS medium, and plant regeneration frequency was 90% in N6 supplemented with BA 0.25 mg/L and BA 0.5 mg/L. According to ISSR analysis of the thirty regenerants, out of 94 loci detected overall, 16 were identified to be polymorphic with a rate (PR) of 17.0%. The mean gene diversity (h) of different in vitro condition was 0.03 and ranged from 0.008 for N6 with BA 5 mg/L, to 0.040 for MS with IAA 0.1 mg/L+kinetin 2 mg/L. The results indicate that the regenerants have a low genetic variation, and ISSR analysis is effective to detect genetic variation of regenerants.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.3
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• pp.229-239
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• 2015

In light of the significant increase in the quantities of goods transported and the development of the shipping industry, the frequency of usage of port structures has increased; yet, the government's budget for the shipping & port of SOC has been reduced. Port structures require systematically effective maintenance and management trends that address their growing frequency of usage. In order to construct a productive maintenance system, it is essential to develop deterioration models of port structures that consider various characteristics, such as location, type, use, constructed level, and state of maintenance. Processes for developing such deterioration models include examining factors that cause the structures to deteriorate, collecting data on deteriorating structures, and deciding methods of estimation. The techniques used for developing the deterioration models are multiple regression analysis and Markov chain theory. Multiple regression analysis can reflect changes over time and Markov chain theory can apply status changes based on a probabilistic method. Along with these processes, the deterioration models of open-type and gravity-type wharfs were suggested.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.19-30
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• 2012

The majority of daily travel demands concentrate at particular time-periods, which causes the difficulties in the travel demand analysis and the corresponding benefit estimation. Thus, it is necessary to consider time-specific traffic characteristics to yield more reliable results. Traditionally, na$\ddot{i}$ve, heuristic, and statistical approaches have been applied to address the peak-hour ratio. In this study, a hybrid clustering model which is one of the statistical methods is applied to calculate the peak-hour ratio and its duration. The 2009 national 24-hour traffic data provided by the Korea institute of Construction Technology are used. The analysis is conducted dividing vehicle types into passenger cars and trucks. For the verification for the usefulness of the methodology, the toll collection system data by the Korea Express Corporation are collected. The result of the research shows lower errors during the off-peak hours and night times and increasing error ratios as the travel distance increases. Since the method proposed can reduce the arbitrariness of analysts and can accommodate the statistical significance test, the model could be considered as a more robust and stable methodology. It is hoped that the result of this paper could contribute to the enhancement of the reliability for the travel demand analysis.

• Journal of The Korean Dental Society of Anesthesiology
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• v.14 no.1
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• pp.29-39
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• 2014

Background: Dental phobia or anxiety of patients is the serious impediment to appropriate and effective dental treatment. Sedative technique helps to mitigate patients' fear and anxiety thus make them more cooperative and familiar to dental practices. With increasing attention to sedative dentistry in dentists, educational requirements and technical qualification also become stricter but actual survey on recent sedative dentistry has not been reported yet. Especially there is insufficient study reporting the survey of sedative dentistry subjected to Korean adults. In this paper, we conducted a survey study on the actual condition and practice related to sedation with a questionnaire to dentists in South Korea. Methods: The survey was done for members of The Korean Dental Society of Anesthesiology (KDSA), who had great interest in sedation and for whom survey-by-mail was convenient. 472 members of The KDSA having dental license and solid address and contact information were subjected to the survey by sending them survey questions about their sedative techniques and knowledge. In order to increase the response rate, small gifts were presented to those who accurately responded to the survey questions and text messages and phone calls were made to encourage their participation. We collected their responses over two months and examined the returned surveys. Statistical analysis was performed using IBM SPSS Statistics 21 for each question. Results: Out of 472 dentists, 181 responded (38.4% response rate). 63.0% (114 dentists; 77 male and 37 female) of respondents had experience on sedative technique and their average age was $39.8{\pm}7.6$ year. 74 of them were private practitioners, 17 of them were professors (14.9%), 11 of them were dentists-in-service (9.6%), 11 of them were residents (specialist training) (9.6%) and 1 of them was military doctors (0.9%). There were 89 dentists (78.1%) who were specialists or receiving trainings to be specialist, most of whom were pediatric dentists (55, 48.2%) and oral surgeon (31, 27.2%). The most popular route for drug medications was orderly oral, inhalational, intravenous medication. Combination of oral and inhalational medications or single use of intravenous medication was the most common. The most preferred sedative drug was pocral in oral sedation and midazolam in intravenous sedation. 48.2% of practitioners responded that they experienced side effects and emergency situations. Airway obstruction was the most frequent. Conclusions: Results from the survey show that the protocol and system for sedative dentistry have been improved compared to the past. Nevertheless, quality of emergency protocol, monitoring devices and preparation of sedative drugs was still insufficient to achieve safe sedative procedure. This study acquires novelty since actual survey on recent sedative dentistry for adult patients has not been reported yet.

• The Journal of Society for e-Business Studies
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• v.19 no.3
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• pp.91-105
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• 2014

This study purposed to benchmark the number of patients who visited an oriental medicine hospital from its surrounding regions using data envelopment analysis (DEA) model, and to analyze the relationships between regional characteristics and efficiency scores from DEA. Study data was collected from one oriental medicine hospital operated in a metropolitan city in Korea. Patient locations were identified at the smallest administrative district, Dong, and number of patients was calculated at the Dong level based on the address of patients in hospital information system. Socio-demographic variables of each Dong were identified from the Statistics of Korea web-sites. DEA was used to benchmark the number of patients between Dongs and to compute the efficiency scores. Tobit regression analysis model was applied to analyze the relationship between efficiency scores and regional variables. 6 Dongs were identified as efficient after DEA. In Tobit analysis, number of medical aid recipients and number of total population in each Dong was significant in explaining the differences of efficiency scores. The study model introduced the application of DEA model in benchmarking the patients between regions. It can be applied to identify the number of patients in each region which a hospital needs to improve their performances.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.10
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• pp.4591-4597
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• 2016

Purpose: Decisions as to whether to provide adjuvant treatment in older breast cancer patients remains challenging. Side effects of chemotherapy have to be weighed against life expectancy, comorbidities, functional status, and frailty. To aid decision-making, we retrospectively analyzed 110 women with breast cancer treated with a curative intention from 2006 to 2012. Survival data with clinical and pathological parameters were evaluated to address the role of adjuvant chemotherapy in this study population. Method: A total of 110 elderly (>70 years) patients that received mastectomy at two hospitals in Taiwan were observed retrospectively for a medium of 51 months. After mastectomy, patients received conservative treatment or adjuvant chemotherapy, or hormone therapy following clinical guidelines or physician's preference. Data were collected from the cancer registry system. Results: Median age at diagnosis was 75.7 years. Thirty-five percent of patients received adjuvant chemotherapy, these having a significantly younger age ($mean=74.0{\pm}5.3$ vs $77.5{\pm}5.3$, p<0.001) and higher tumor staging (p=0.003) compared with their non-chemotherapy counterparts.Five-year overall survival was non-significantly higher in patients who received adjuvant chemotherapy (with chemotherapy 64.2% vs without chemotherapy 62.6%, p=0.635), while five-year recurrence free survival was non-significantly lower (with chemotherapy 64.1% vs without chemotherapy 90.5%, p=0.80). Conclusions: In this analysis, adjuvant chemotherapy tended to be given to patients with a younger age and higher tumor staging at our institute. It was not associated with any statistically significant improvement in survival and recurrence rate. Until age specific recommendations are available, physicians must use their clinical judgment and assess the tumor biology with the patient's comorbidities to make the best choice. Clinical trials focusing on this critical issue are warranted.