• International Journal of Advanced Culture Technology
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• v.9 no.2
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• pp.100-105
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• 2021

Contactless service is rapidly emerging as a new growth strategy due to consumers who are reluctant to the face-to-face situation in the global pandemic of coronavirus disease 2019 (COVID-19), and various technologies are being developed to support the fast-growing contactless service market. In particular, the restaurant industry is one of the most desperate industrial fields requiring technologies for contactless service, and the representative technical case should be a kiosk, which has the advantage of reducing labor costs for the restaurant owners and provides psychological relaxation and satisfaction to the customer. In this paper, we propose a solution to the restaurant's store operation through the unmanned kiosk using a state-of-the-art artificial intelligence (AI) technology of image recognition. Especially, for the products that do not have barcodes in bakeries, fresh foods (fruits, vegetables, etc.), and autonomous restaurants on highways, which cause increased labor costs and many hassles, our proposed system should be very useful. The proposed system recognizes products without barcodes on the ground of image-based AI algorithm technology and makes automatic payments. To test the proposed system feasibility, we established an AI vision system using a commercial camera and conducted an image recognition test by training object detection AI models using donut images. The proposed system has a self-learning system with mismatched information in operation. The self-learning AI technology allows us to upgrade the recognition performance continuously. We proposed a fully automated payment system with AI vision technology and showed system feasibility by the performance test. The system realizes contactless service for self-checkout in the restaurant business area and improves the cost-saving in managing human resources.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.74-85
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• 2021

Global Navigation Satellite System (GNSS) receivers are intrinsically vulnerable to radio frequency jamming signals due to the fundamental property of radio navigation systems. A GNSS jamming monitoring system that is capable of jamming detection, classification and localization is essential for infrastructure for autonomous driving systems. For these 3 functionalities, a GNSS jamming monitoring network consisting of a multiple of low-cost GNSS receivers distributed in a certain area is needed, and the precise time synchronizaion between multiple independent GNSS receivers in the network is an essential element. This paper presents a precise time synchronization method based on the direct use of Time Difference of Arrival (TDOA) technique in signal domain. A block interpolation method is additionally incorporated into the method in order to maintain the precision of time synchronization even with the relatively low sampling rate of the received signals for computational efficiency. The feasibility of the proposed approach is verified in the numerical simualtions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.189-194
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• 2009

Most of anti-virus programs detect and compare the signature of the malicious code to detect buffer overflow malicious code. Therefore most of anti-virus programs can't detect new or unknown malicious code. This paper introduces a new way to detect malicious code traces memory executable of essentials APIs by malicious code. To prove the usefulness of the technology, 7 sample codes were chosen for compared with other methods of 8 anti-virus programs. Through the simulation, It turns out that other anti-virus programs could detect only a limited portion of the code, because they were implemented just for detecting not heap areas but stack areas. But in other hand, I was able to confirm that the proposed technology is capable to detect the malicious code.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.89-100
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• 2011

Physical memory analysis has been an issue on a field of live forensic analysis in digital forensics until now. It is very useful to make the result of analysis more reliable, because record of user behavior and data can be founded on physical memory although process is hided. But most memory analysis focuses on windows based system. Because the diversity of target system to be analyzed rises up, it is very important to analyze physical memory based on other OS, not Windows. Mac OS X, has second market share in Operating System, is operated by loading kernel image to physical memory area. In this paper, We propose a methodology for physical memory analysis on Mac OS X using symbol information in kernel image, and acquire a process information, mounted device information, kernel information, kernel extensions(eg. KEXT) and system call entry for detecting system call hooking. In additional to the methodology, we prove that physical memory analysis is very useful though experimental study.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.221-235
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• 2010

Internet service providers provide various security services, such as firewall, intrusion detection, intrusion prevention, anti-virus, along with their main Internet services. Those security service users have no idea what kind of quality services they are guaranteed. And therefore, Internet users interest in Security Service Level Agreement(SLA) increases as their interest in secure Internet service increases. However, there wasn't any researches in the S-SLA area domestically and there are only limited SLA indexes related to system or service maintenances at the moment. Therefore, this paper analyses security functions in IPS services and categorize them into common and independent security functions. Finally to improve quality of security services, this paper proposes S-SLA indexes depending on the different security levels. This will be subdivide into agreement on security service.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.213-218
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• 2021

In this paper, we detect and track vehicles by type based on highway daytime driving videos taken with black boxes for vehicles. In addition, we design a real-time MR contents production method that can be newly created by placing substitute videos of each type of detected vehicles in the same location as the new background video. To detect and track vehicles by type, we use the YOLO algorithm. And we also use the mask technique based on RGB color for substitute videos of each type of vehicles detected. The size of the vehicle substitute videos to be used for MR content are substituted by the same size as the area size of the detected vehicles. In this paper, we confirm that real-time MR contents design is possible as a result of experiments and simulations and believe that It will be usefully utilized in the field of VR contents.

• Applied Chemistry for Engineering
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• v.32 no.1
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• pp.42-48
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• 2021

In this study, a sensor for detection of nitric oxide (NO) gas was developed using petroleum pitch-based activated carbon which was synthesized from pyrolysis fuel oil (PFO). Polyethylene terephthalate (PET) was added to increase molecular weight by stimulating a polymerization of components in PFO during the pitch synthesis process. The increase in the molecular weight of pitch contributed to the improvement of textural properties of activated carbon, such as the specific surface area and micropore volume. It also enhanced the sensitivity of NO gas sensor based on the activated carbon. In addition, the effect of PET addition during the pitch synthesis on the surface oxygen content and conductivity of activated carbon was investigated. Finally, the correlation of the sensitivity with physical properties of activated carbon was analyzed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.146-152
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• 2020

This study was initiated to develop an effective inspection method to detect defects such as corrosion in closed-cell steel members in steel-box girder bridges. The ultrasonic velocity method among various non-destructive method was selected as a rapid and effective method to derive the average propagation velocity in the medium by using the ultrasonic wave velocity method for specimens of different thickness. The regression analysis was performed based on the experimental results, and the results was interpolated to evaluate the prediction accuracy. If the material properties are identical, this ultrasonic velocity method can predict the thickness using the averaged transmitted velocity. In addition, a continuous scanning method moving at 200 mm/s was tested for scanning a wide area of a bridge. The results exhibited that the continuous scanning method was able to effectively scan the different thickness of a bridge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1492-1499
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• 2020

A weather radar system generally shows the weather phenomena related with rainfall and wind velocity. These systems are usually very helpful to monitor the relatively high altitude weather situation for the wide and long range area. However, since the weather hazards due to the strong hail and heavy rainfall occurring locally are observed frequently in recent days, it is important to detect these wether phenomena. For this purpose, it is necessary to detect the fast varying low altitude weather conditions. In this environment, the effect of surface clutter is more evident and the antenna dwell time is much shorter. Therefore, the conventional Doppler spectrum estimation method may cause serious problems. In this paper, the AR(autoregressive) Doppler spectrum estimation methods were applied to solve these problems and the results were analyzed. Applied methods show that improved Doppler spectra can be obtained comparing with the conventional FFT(Fast Fourier Transform) method.

• Imaging Science in Dentistry
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• v.51 no.1
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• pp.27-34
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• 2021

Purpose: This study was performed to compare the ability of limited- and large-volume cone-beam computed tomography (CBCT) to display isthmuses in the apical root canals of mandibular molars. Materials and Methods: Forty human mandibular first molars with isthmuses in the apical 3 mm of mesial roots were scanned by micro-computed tomography (micro-CT), and their thickness, area, and length were recorded. The samples were examined using 2 CBCT systems, using the smallest voxels and field of view available for each device. The Mann-Whitney, Friedman, and Dunn multiple comparison tests were performed (α=0.05). Results: The 3D Accuitomo 170 and i-Cat devices detected 77.5% and 75.0% of isthmuses, respectively (P>0.05). For length measurements, there were significant differences between micro-CT and both 3D Accuitomo 170 and i-Cat(P<0.05). Conclusion: Both CBCT systems performed similarly and did not detect isthmuses in the apical third in some cases. CBCT still does not equal the performance of micro-CT in isthmus detection, but it is nonetheless a valuable tool in endodontic practice.