• Journal of the Korean Society of Radiology
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• v.9 no.7
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• pp.515-521
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• 2015

This study assessed the degradation of image quality caused by grid artifacts and $moir{\acute{e}}$ pattern artifacts in a stationary grid, and the degradation of image quality caused by cut off artifacts in a moving grid. X-ray images were acquired in a stationary grid and a moving grid with X-ray exposure conditions of 100 cm, 80 kVp, and 30 mA using a CDRAD phantom and a 24 cm thickness acrylic phantom. Observer's perception of X-ray imaging using CDRAD Analyzer was mean 49.36, standard deviation 3.76, maximum 55.56, and minimum 38.67 in the stationary grid, and 47.04, 12.69, 55.56, and 20.89, respectively, in the moving grid. The stationary grid was superior to the moving grid in terms of the mean and standard deviation of observer's perception.

• The Journal of the Acoustical Society of Korea
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• v.39 no.4
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• pp.364-370
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• 2020

Rocket noise generated from the exhaust plume produces the enormous acoustic loading, which adversely affects the integrity of the electronic components and payload (satellite) at liftoff. The prediction of rocket noise consists of two steps: the supersonic jet exhaust is simulated by a method of the Computational Fluid Dynamics (CFD), and an acoustic transport method, such as the Helmholtz-Kirchhoff integral, is applied to predict the noise field. One of the difficulties in the CFD step is to remove the boundary reflection artifacts from the finite computation boundary. In general, artificial damping, known as a sponge layer, is added nearby the boundary to attenuate these reflected waves but this layer demands a large computational area and an optimization procedure of related parameters. In this paper, a cost-efficient way to separate the reflected waves based on the two microphone method is firstly introduced and applied to the computation result of a laboratory-scale supersonic jet noise without sponge layers.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.4
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• pp.171-178
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• 2019

The use of anti-scatter grids in radiographic imaging has the advantage of preventing the image distortion caused by scattered radiation. However, it carries the side effect of leaving artifacts in the X-ray image. In this paper, we propose a grid line suppression technique using discrete cosine transform(DCT). In X-ray images, the grid lines have different characteristics depending on the shape of the object and the area of the image. To solve this problem, we adopt the DCT transform based on a dynamic segmentation, and propose a filter transfer function for each individual segment. An algorithm for detecting the band of grid lines in frequency domain and a band stop filter(BSF) with a filter transfer function of a combination of Kaiser window and Butterworth filter have been proposed. To solve the blocking effects, we present a method to determine the pixel values using multiple structured images. The validity of the proposed theory has been evaluated from the experimental results using 140 X-ray images.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.353-363
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• 2021

As the Untact era is rapidly changing, collaboration tools are increasing their utilization and value as digital technologies for non-face-to-face work. While instant messenger-based collaboration tools support a variety of functions, crime and accident concerns are also increasing in proportion to their convenience, such as information leakage and security incidents. Meanwhile, the digital forensics perspective on collaborative tools is not enough, so forensics research is needed. This study analyzes significant artifacts in the two operating environments through Windows and Android forensics research on Microsoft Teams, the collaboration tool with the highest share in the world. Also, based on differences in artifacts and data attributes according to the operating environment, by applying 'differential forensic', we proved that the usefulness of evidence can be improved by presenting a complementary analysis method and timeline configuration through information linkage.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.1-9
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• 2022

As various services are linked to IoT(Internet of Things) and portable communication terminals, cyber attacks that exploit security vulnerabilities of the devices are rapidly increasing. In particular, cyber attacks targeting heterogeneous devices in large-scale network environments through advanced persistent threat (APT) attacks are on the rise. Therefore, in order to improve the effectiveness of the response system in the event of a breach, it is necessary to apply a data enrichment mechanism for the collected artifact data to improve threat analysis and detection performance. Therefore, in this study, by analyzing the data supplementation common elements performed in the existing incident management framework for the artifacts collected for the analysis of intrusion accidents, characteristic elements applicable to the actual system were derived, and based on this, an improved accident analysis framework The prototype structure was presented and the suitability of the derived data supplementary extension elements was verified. Through this, it is expected to improve the detection performance when analyzing cyber incidents targeting artifacts collected from heterogeneous devices.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.737-751
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• 2023

The importance of digital forensics in the cloud environment is increasing as businesses and individuals move their data from On-premise to the cloud. Cloud data can be stored on various devices, including mobile devices and desktops, and encompasses a variety of user behavior artifacts, such as information generated from linked accounts and cloud services. However, there are limitations in securing and analyzing digital evidence due to environmental constraints of the cloud, such as distributed storage of data and lack of artifact linkage. One solution to address this is archiving services, and Google's Takeout is prime example. In this paper, user behavior data is analyzed for cloud forensics based on archiving data and necessary items are selected from an investigation perspective. Additionally, we propose the process of analyzing selectively collected data based on time information and utilizing web-based visualization to meaningfully assess artifact associations and multi-behaviors. Through this, we aim to demonstrate the value of utilizing archiving data in response to the increasing significance of evidence collection for cloud data.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.335-341
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• 2018

With the improvement of medical state, patients' expectations for the most advanced medical equipment are increasing. Particularly, Magnetic Resonance Image (MRI) is used as one of the core image diagnosis methods in all clinical area. However, it has been reported that many of patients who go through the examination suffer from anxiety to the severe noise level during the examination. In this study, both the noise reduction evaluation of headsets with sound-blocking materials added to existing sound-absorbing materials and the existence of sound blocking materials as artifacts on the examination image are tested. An MRI test noise is recorded as a speaker by cross-ordination the sound material (sponge) and the sound material (acrylic plate, copper plate, and 3D copper plate) inside the headset made from 3D pring. A quantitative assessment of headsets showed that the average headset value was 81.8 dB. The average dB value of the most soundproof material combination(Copper, acrylic plate, sponge, sponge) headsets on headsets with added charactering material was measured at 70.4 dB, and MRI showed that the copper was diamagnetic substance and excluded. The second most soundproof headset(Sponge, acrylic plate, 3D copper plate, sponge) was measured at 70.6 dB and MRI showed no artifacts. The same simulation of the material printed with a 3D copper PLA containing approximately 40 % copper powder resulted in no artifacts, therefore, the material output as a 3D printing was better suited for use. For MRI related research, the mutual development of 3D printing is highly anticipated.

• Journal of radiological science and technology
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• v.33 no.4
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• pp.369-378
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• 2010

The purpose of this study was to investigate image differences between KVCT vs MVCT depending on a high densities metal included in the phantom and to analyze the r values for the purpose of the dose differences between each methods. We verified the possibilities for clinical indications that using MVCT is available for the radiation therapy treatment planning. Cheese phantom was used to get a density table for each CT and CT sinogram data was transferred to radiation planning computer through DICOM_RT. Using this data, the treatment dose plan has been calculated in RTP system. We compared the differences of r values between calculated and measured values, and then applied this data to the real patient's treatment planning. The contrast of MVCT image was superior to KVCT. In KVCT, each pixel which has more than 3.0 of density was difficult to be differentiated, but in MVCT, more than 5.0 density of pixels were distinguished clearly. With the normal phantom, the percentage of the case which has less than 1($r\leq1$, acceptable criteria) of gamma value, was 94.92% for KVCT and 93.87% for MVCT. But with the cheese phantom, which has high density plug, the percentage was 88.25% for KVCT and 93.77% for MVCT respectively. MVCT has many advantages than KVCT. Especially, when the patient has high density metal, such as total hip arthroplasty, MVCT is more efficient to define the anatomical structure around the high density implants without any artifacts. MVCT helps to calculate the treatment dose more accurately.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.4
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• pp.95-102
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• 2016

Computer security incident such as confidential information leak and data destruction are constantly growing and it becomes threat to information in digital devices. To respond against the incident, digital forensic techniques are also developing to help digital incident investigation. With the development of digital forensic technology, a variety of forensic artifact has been developed to trace the behavior of users. Also, a diversity of forensic tool has been developed to extract information from forensic artifact. However, there is a issue that information from forensic tools has its own forms. To solve this problem, it needs to process data when it is output from forensic tools. Then it needs to compare and analyze processed data to identify how data is related each other and interpret the implications. To reach this, it calls for effective method to store and output data in the course of data processing. This paper aims to propose DFIOC (Digital Forensic Indicators Of Compromise) that is capable of transcribing a variety of forensic artifact information effectively during incident analysis and response. DFIOC, which is XML based format, provides "Evidence" to represent various forensic artifacts in the incident investigation. Furthermore, It provides "Forensic Analysis" to report forensic analysis result and also gives "Indicator" to investigate the trace of incidence quickly. By logging data into one sheet in DFIOC format for forensic analysis process, it is capable of avoiding unnecessary data processing. Lastly, since collected information is recorded in a normalized format, data input and output becomes much easier as well as it will be convenient to use for identification of collected information and analysis of data relationship.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1377-1383
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• 2015

As the cloud services users' increase, there are important files created by individual in cloud storage. Thus, investigation of cloud artifact should be conducted. There are two methods of analyzing cloud service, one is that investigates cloud server provider (CSP), and another is that investigates client. In this paper, we presents an automated framework to detect the altered artifact and developes a tool that detects the cloud artifact. We also developed Cloud Artifact Tool that can investigate client computer. Cloud Artifact Tool provides feature of collection and analysis for the services such as Google Drive, Dropbox, Evernote, NDrive, DaumCloud, Ucloud, LG Cloud, T Cloud and iCloud.