• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.555-564
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• 2013

Innovative evolution in mobile devices along with recent spread of Tablet PCs and Smart Phones makes a new change not only in individual life but also in enterprise applications. Especially, in the case of medium-large mobile applications for large enterprises which generally takes more than 3 months of development periods, importance and complexity increase significantly. Generally Agile-methodology is used for a development process for the medium-large scale mobile applications, but some issues arise such as high dependency on skilled developers and lack of detail development directives. In this paper, S-MADP (Smart Mobile Application Development Process) is proposed to mitigate these issues. S-MADP is a service oriented development process extending a object-oriented development process, for medium-large scale mobile applications. S-MADP provides detail development directives for each activities during the entire process for defining services as server-based or client-based and providing the way of reuse of services. Also, in order to support various user interfaces, S-MADP provides detail UI development directives. To evaluate the performance of S-MADP, three mobile application development projects were conducted and the results were analyzed. The projects are 'TBS(TB Mobile Service) 3.0' in TB company, mobile app-store in TS company, and mobile groupware in TG group. As a result of the projects, S-MADP accounts for more detailed design information about 'Minimizing the use of resources', 'Service-based designing' and 'User interface optimized for mobile devices' which are needed to be largely considered for mobile application development environment when we compare with existing Agile-methodology. Therefore, it improves the usability, maintainability, efficiency of developed mobile applications. Through field tests, it is observed that S-MADP outperforms about 25% than a Agile-methodology in the aspect of the required man-month for developing a medium-large mobile application.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.127-136
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• 2008

To identify the potential area of gas hydrate in the Ulleung Basin, 2-D and 3-D seismic surveys using R/V Tamhae II were conducted in 2005 and 2006. Seismic survey equipment consisted of navigation system, recording system, streamer cable and air-gun source. For reliable velocity analysis in a deep sea area where water depths are mostly greater than 1,000 m and the target depth is up to about 500 msec interval below the seafloor, 3-km-long streamer and 1,035 $in^3$ tuned air-gun array were used. During the survey, a suite of quality control operations including source signature analysis, 2-D brute stack, RMS noise analysis and FK analysis were performed. The source signature was calculated to verify its conformity to quality specification and the gun dropout test was carried out to examine signature changes due to a single air gun's failure. From the online quality analysis, we could conclude that the overall data quality was very good even though some seismic data were affected by swell noise, parity error, spike noise and current rip noise. Especially, by checking the result of data quality enhancement using FK filtering and missing trace restoration technique for the 3-D seismic data inevitably contaminated with current rip noises, the acquired data were accepted and the field survey could be conducted continuously. Even in survey areas where the acquired data would be unsuitable for quality specification, the marine seismic survey efficiency could be improved by showing the possibility of noise suppression through onboard data processing.

• Korean Journal of Optics and Photonics
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• v.21 no.2
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• pp.82-88
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• 2010

Photopolymer is a material for recording three dimensional holograms containing photo information. Photopolymer has been found to be a proper material due to many advantages such as high DE value, easy processing, and low price. Compositions of PVA, monomer, initiater and photosensitizer were determined by previous experiments and the compositions of $SeO_2$ and $TiO_2$ were considered as variable to find out the effects of $TiO_2$ on DE. The DE values were constant for the varying compositions of $TiO_2$ (0.1 mg~1.0 mg). In other words, $TiO_2$ is not directly effective on the DE values. Composition change experiments from $SeO_2$ 0.1 mg, $TiO_2$ 0.9 mg to $SeO_2$ 0.9 mg, $TiO_2$ 0.1 showed a maximum DE value of 73.75% at a component of $SeO_2$ 0.8 mg, $TiO_2$ 0.2 mg. It seemed that regardless of the amount of $TiO_2$, increasing the amount of $SeO_2$ gently increases DE`s. If nano particles are heavily added, transparent films could not be made due to the separation of particles by the solubility decrease. Photopolymer films could be made with high DE values for an extensive angle range if $TiO_2$ additions were kept minimum and $SeO_2$ additions were kept maximum.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.143-150
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• 2012

A simulation methodology and corresponding program based on it is to be discussed for analyzing the effects of the networking operation of existing DHC system in connection with CHP system on-site. The practical simulation for arbitrary areas with various building compositions is carried out for the analysis of operational features in both systems, and the various aspects of thermal energy grids with connecting operation are highlighted through the detailed assessment of predicted results. The intrinsic operational features of CHP prime movers, gas engine, gas turbine etc., are effectively implemented by realizing the performance data, i.e. actual operation efficiency in the full and part loads range. For the sake of simplicity, a simple mathematical correlation model is proposed for simulating various aspects of change effectively on the existing DHC system side due to the connecting operation, instead of performing cycle simulations separately. The empirical correlations are developed using the hourly based annual operation data for a branch of the Korean District Heating Corporation (KDHC) and are implicit in relation between main operation parameters such as fuel consumption by use, heat and power production. In the simulation, a variety of system configurations are able to be considered according to any combination of the probable CHP prime-movers, absorption or turbo type cooling chillers of every kind and capacity. From the analysis of the thermal network operation simulations, it is found that the newly proposed methodology of mathematical correlation for modelling of the existing DHC system functions effectively in reflecting the operational variations due to thermal energy grids with connecting operation. The effects of intrinsic features of CHP prime-movers, e.g. the different ratio of heat and power production, various combinations of different types of chillers (i.e. absorption and turbo types) on the overall system operation are discussed in detail with the consideration of operation schemes and corresponding simulation algorithms.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.613-621
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• 2019

The purpose of this study is to evaluate the effectiveness of supportive devices which are for minimizing the patient's movement during lower extremity angiography and to verify image quality of phantom by analyzing of Mask image, DSA image and Roadmap image into SNR and CNR. As a result of comparing SNR with CNR of mask image obtained by DSA technique using the phantom alone and phantom placed on the supportive devices, there was no significant difference between about 0~0.06 for SNR and about 0~0.003 for CNR. The study showed about 0.11~0.35 for SNR and 0.016~0.031 for CNR of DSA imaging by DSA technique about only water phantom of the blood vessel model and the water phantom placed on the device. Analyzing SNR and CNR of Roadmap technique about water phantom on the auxiliary device (hardboard paper, pomax, polycarbonate, acrylic) and water phantom alone, there was no significant difference between 0.02~0.05 for SNR and 0.002~0.004 for CNR. In conclusion, there was no significant difference on image quality by using supportive devices made by hardboard paper, pomax, polycarbonate or acryl regardless of whether using supportive devices or not. Supportive devices to minimize of the patient's movement may reduce the total amount of contrast, exam-time, radiation exposure and eliminate risk factors during angiogram. Supportive devices made by hardboard paper can be applied easily during angiogram due to advantages of reasonable price and simple processing. It is considered that will be useful to consider cost efficiency and types of materials and their properties in accordance with purpose and method of the study when the operator makes and uses supportive devices.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.13-19
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• 2019

Purpose Tc-99m HMPAO is widely used radiopharmaceutical for brain perfusion SPECT. Tc-99m HMPAO is chemically unstable and is liable to show deterioration of labeling efficiency due to high incidence of secondary Tc-99m HMPAO complex, free pertechnetate and reduced-hydrolyzed Tc-99m. In this study, we investigated whether sialogogues administration could reduce the impurities of Tc-99m HMPAO. Materials and Methods In thirty subjects(20 male and 10 female, age range 19~89 years, mean age $60.7{\pm}14.5years$), brain perfusion SPECT were performed at basal and citric acid stimulation states consecutively after injection of 555 MBq of Tc-99m HMPAO. In the salivary glands, the uptake coefficient was calculated using Siemens processing program. Statistical comparison between before and after the citric acid stimulation performed paired t-test. P value less than 0.05 was regarded as statistically significant. Results Salivary glands uptake was $12900{\pm}3101$ counts in basal and $10677{\pm}2742$ counts in citric acid stimulation states. Unnecessary impurities in the body is much decreased after citric acid administration(t=10.78, P<0.05). The image quality was much improved after administration of citric acid and the regional cerebral perfusion was clearly from demarcated the background. Conclusion The impurity is distributed throughout the body particularly in the salivary glands and nasal mucosa when Tc-99m HMPAO brain perfusion SPECT is performed. If this impurities is not removed, the quality of the image may deteriorate, resulting in errors in visual evaluation. The use of sialogogues could be helpful for decreasing unnecessary impurities in the body.

• Composites Research
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• v.34 no.4
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• pp.241-248
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• 2021

As the electric vehicle market grows, there is an issue of light weight vehicles to increase battery efficiency. Therefore, it is going to replace the battery module cover that protects the battery module of electric vehicles with high strength/high heat-resistant polymer composite material which has lighter weight from existing aluminum materials. It also aims to respond to the early electric vehicle market where technology changes quickly by combining 3D printing technology that is advantageous for small production of multiple varieties without restrictions on complex shapes. Based on the composite material mechanics, the critical length of glass fibers in short glass fiber (GF)/polycarbonate (PC) composite materials manufactured through extruder was derived as 453.87 ㎛, and the side feeding method was adopted to improve the residual fiber length from 365.87 ㎛ and to increase a dispersibility. Thus, the optimal properties of tensile strength 135 MPa and Young's modulus 7.8 MPa were implemented as GF/PC composite materials containing 30 wt% of GF. In addition, the filament extrusion conditions (temperature, extrusion speed) were optimized to meet the commercial filament specification of 1.75 mm thickness and 0.05 mm standard deviation. Through manufactured filaments, 3D printing process conditions (temperature, printing speed) were optimized by multi-optimization that minimize porosity, maximize tensile strength, and printing speed to increase the productivity. Through this procedure, tensile strength and elastic modulus were improved 11%, 56% respectively. Also, by post-processing, tensile strength and Young's modulus were improved 5%, 18% respectively. Lastly, using the FEA (finite element analysis) technique, the structure of the battery module cover was optimized to meet the mechanical shock test criteria of the electric vehicle battery module cover (ISO-12405), and it is satisfied the battery cover mechanical shock test while achieving 37% lighter weight compared to aluminum battery module cover. Based on this research, it is expected that 3D printing technology of polymer composite materials can be used in various fields in the future.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.