• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2769-2784
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• 2020

This paper aims to compare the scenic images of four ancient Chinese cities including Lijiang, Pingyao, Huizhou and Langzhong, so as to provide specific development strategies for the ancient cities. In this paper, the ancient cities' scenic images are divided into three sub-indexes and eight evaluation dimensions. Based on this, the study first uses Python software to collect tourists' online comments on the four ancient cities. Then, the social network analysis method is used to build a high-frequency keywords matrix of tourist comments and the R language is used to generate a visual network graph. After this, the entropy weight method is used to determine the weights and values of eight evaluation dimensions. Finally, the tourists' overall satisfaction indexes of the four ancient cities are calculated accordingly. The results show that (1) the overall satisfaction of Lijiang is the highest, while that of Huizhou is the lowest; (2) from the weight of each evaluation dimension, it can be seen that tourists care more about the national culture and historical culture; (3) from tourists' satisfaction index on each evaluation dimension of the four ancient cities, we can find that the four ancient cities has their own advantages and disadvantages in tourism development. (4) local tourism-related institutions should strengthen their advantages and improve their deficiencies so as to enhance tourists' overall image of the ancient city.

• Journal of Gastric Cancer
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• v.15 no.4
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• pp.256-261
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• 2015

Purpose: Gastric cancer is the third leading cause of cancer-related mortality, with the incidence and mortality being higher in men than in women. Various studies have shown that eating carrots may play a major role in the prevention of gastric cancer. We conducted a meta-analysis to determine the relationship between carrot consumption and gastric cancer. Materials and Methods: We searched multiple databases including PubMed, Cochrane Library, Scopus, ScienceDirect, and Persian databases like Scientific Information Database (SID) and IranMedx. The following search terms were used: stomach or gastric, neoplasm or cancer, carcinoma or tumor, and carrot. Statistical analyses were performed using Comprehensive Meta Analysis/2.0 software. Results: We retrieved 81 articles by searching the databases. After considering the inclusion and exclusion criteria, 5 articles were included in this study. The odds ratio (OR) obtained by fixed effects model showed that a 26% reduction in the risk of gastric cancer has been associated with the consumption of carrots) OR=0.74; 95% confidence interval=0.68~0.81; P<0.0001). According to funnel graph, the results showed that the possibility of a publication bias does not exist in this study. Conclusions: The findings of this study showed an inverse relationship between the consumption of carrots and the risk of gastric cancer.

• Journal of the Korea Society for Simulation
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• v.23 no.2
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• pp.17-24
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• 2014

This study attempts to show an example of developing and applying thermal hydraulic simulation model for Aircraft-EHA. The overview of research procedure is as in the following. First, The unit hydraulic simulation model, which reflects physical quantity answering engineer's purpose is developed. Second, The unit hydraulic simulation model is combined, and then branched out to EHA hydraulic model. Third, a simulation model including flow thermal is developed, and then oil temperature rise time according to 'initial temperature and load' is examined. Finally, the master graph that can be used for designing EHA combined with thermal hydraulic analysis results in several cases is compiled, and suggested. AMESim, commercial software, is used through whole procedure.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1522-1536
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• 1998

In this paper, we present a modeling method for the real-time systems. This method is based on the DARTS (Design Approach for Real-Time Systems) and widely extended to analysis phase. The DARTS method provides a good guideline for the real -time software design, but it uses structured analysis and does not provide a specification language. So. this paper provides extended DARTS modeling techniques to the analysis area based on the objects. Internal behavior of system showed by means of a NPN (Numerical Petri Net) for analysis, and the specification language is provided based on the temporal logic for transition synchronization sequence control. By the example, we identified the proposed method was applied well. And through the reachability graph, we verified whether the deadlocks may occur or not in the analysis phase before the design phase. Thus. it gives easy way to analysis, so that it will lead to the design phase naturally.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.81-92
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• 2003

Generalized LR parsing is one of the enhanced LR parsing methods so that it overcome the limit of one-way linear stack of the traditional LR parser using graph-structured stack, and it has been playing an important role of a firm starting point to generate other variations for NL parsing equipped with various mechanisms. In this paper, we propose a conditional Action Model that can solve the problems of conventional probabilistic GLR methods. Previous probabilistic GLR parsers have used relatively limited contextual information for disambiguation due to the high complexity of internal GLR stack. Our proposed model uses Surface Phrasal Types representing the structural characteristics of the parse for its additional contextual information, so that more specified structural preferences can be reflected into the parser. Experimental results show that our GLR parser with the proposed Conditional Action Model outperforms the previous methods by about 6-7% without any lexical information, and our model can utilize the rich stack information for syntactic disambiguation of probabilistic LR parser.

• Journal of Radiation Protection and Research
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• v.41 no.3
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• pp.260-267
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• 2016

Background: This study analyzes the differences in the annual averaged atmospheric dispersion factor and ground deposition factor produced using two classification methods of atmospheric stability, which are based on a vertical temperature difference and the standard deviation of horizontal wind direction fluctuation. Materials and Methods: Daedeok and Wolsong nuclear sites were chosen for an assessment, and the meteorological data at 10 m were applied to the evaluation of atmospheric stability. The XOQDOQ software program was used to calculate atmospheric dispersion factors and ground deposition factors. The calculated distances were chosen at 400 m, 800 m, 1,200 m, 1,600 m, 2,400 m, and 3,200 m away from the radioactive material release points. Results and Discussion: All of the atmospheric dispersion factors generated using the atmospheric stability based on the vertical temperature difference were shown to be higher than those from the standard deviation of horizontal wind direction fluctuation. On the other hand, the ground deposition factors were shown to be same regardless of the classification method, as they were based on the graph obtained from empirical data presented in the Nuclear Regulatory Commission's Regulatory Guide 1.111, which is unrelated to the atmospheric stability for the ground level release. Conclusion: These results are based on the meteorological data collected over the course of one year at the specified sites; however, the classification method of atmospheric stability using the vertical temperature difference is expected to be more conservative.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.5
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• pp.179-186
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• 2014

Current networks such as social network, web page link, traffic network are big data which have the large numbers of nodes and edges. Many applications such as social network services and navigation systems use these networks. Since big networks are not fit into the memory, existing in-memory based analysis techniques cannot provide high performance. Frontier-Expansion-Merge (FEM) framework for graph search operations using three corresponding operators in the relational database (RDB) context. FEM exploits an index table that stores pre-computed partial paths for efficient shortest path discovery. However, the index table of FEM has low hit ratio because the indices are determined by distances of indices rather than the possibility of containing a shortest path. In this paper, we propose an method that construct index table using high degree nodes having high hit ratio for efficient shortest path discovery. We experimentally verify that our index technique can support shortest path discovery efficiently in real-world datasets.

• Imaging Science in Dentistry
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• v.48 no.1
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• pp.45-49
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• 2018

Purpose: The aim of this study was to evaluate the quantitative strain elastography of tongue carcinoma using intraoral ultrasonography. Materials and Methods: Two patients with squamous cell carcinoma (SCC) who underwent quantitative strain elastography for the diagnosis of tongue lesions using intraoral ultrasonography were included in this prospective study. Strain elastography was performed using a linear 14 MHz transducer (Aplio 300; Canon Medical Systems, Otawara, Japan). Manual light compression and decompression of the tongue by the transducer was performed to achieve optimal and consistent color coding. The variation in tissue strain over time caused by the compression exerted using the probe was displayed as a strain graph. The integrated strain elastography software allowed the operator to place circular regions of interest (ROIs) of various diameters within the elastography window, and automatically displayed quantitative strain (%) for each ROI. Quantitative indices of the strain (%) were measured for normal tissues and lesions in the tongue. Results: The average strain of normal tissue and tongue SCC in a 50-year-old man was 1.468% and 0.000%, respectively. The average strain of normal tissue and tongue SCC in a 59-year-old man was 1.007% and 0.000%, respectively. Conclusion: We investigated the quantitative strain elastography of tongue carcinoma using intraoral ultrasonography. Strain elastography using intraoral ultrasonography is a promising technique for characterizing and differentiating normal tissues and SCC in the tongue.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.35-40
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• 2010

NAND flash memory has been widely used than traditional HDD in PDA and other mobile devices, embedded systems, PC because of faster access speed, low power consumption, vibration resistance and other benefits. DiskSim and other HDD simulators has been developed that for find improvements for the software or hardware. But there is a few Linux-based simulators for NAND flash memory and SSD. There is necessary for Windows-based NAND flash simulator because storage devices and PC using Windows. This paper describe for development of simulator-NFSim for FTL performance analysis in NAND flash. NFSim is used to measure performance of various FTL algorithms and FTL wear-level. NAND flash memory model and FTL algorithm developed using Windows Driver Model and class for scalability. There is no need for another tools because NFSim using graph tool for data measure of FTL performance.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.477-482
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• 2016

As being the advanced analytics indispensable on big data for agile decision-making and tactical planning in enterprises, distributed processing platforms, such as Hadoop and Spark which distribute and handle the large volume of data on multiple nodes, receive great attention in the field. In Spark platform stack, Spark SQL unveiled recently to make Spark able to support distributed processing framework based on SQL. However, Spark SQL cannot effectively handle advanced analytics that involves machine learning and graph processing in terms of iterative tasks and task allocations. Motivated by these issues, this paper proposes the design of SQL-based big data optimal processing engine and processing framework to support advanced analytics in Spark environments. Big data optimal processing engines copes with complex SQL queries that involves multiple parameters and join, aggregation and sorting operations in distributed/parallel manner and the proposing framework optimizes machine learning process in terms of relational operations.