• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1473-1479
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• 2000

This paper presents the performance evaluation of an adaptive QAM scheme under flat and frequency selective fading channels for indoor wireless communication systems. The QAM modulation is combined with differential encoding and the demodulation process is carried out noncoherently. The adaptation is performed by varying the modulation level of QAM, depending upon received signal strength. The adaptation mechanism allows a 2- or 3-bit increase or decrease at a time, if the channel condition is considered to be significantly good or bad. Simulation results show that the average number of bits per symbol (ABPS) for each symbol block transmitted over a flat fading channel is higher than 5.0 and the BER performance is better than 10^-4 for a SNR value higher than 30 dB. For frequency selective fading channels, an oversampling technique in the receiver was employed. The BER performance obtained for frequency selective fading channels is better than 10^-4 with a SNR value of 40 dB and ABPS is found to be approximately 5.5. Therefore, this scheme is very useful in that it provides both very high bandwidth efficiency and acceptable performance with moderate SNR values over flat and frequency selective fading channels. In addition, this scheme provides reduced receiver complexity by way of noncoherent detection.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.61-69
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• 2009

In this paper, to propose a new approach to real-time eye tracking. Existing methods of tracking the user's attention to the little I move my head was not going to get bad results for each of the users needed to perform the calibration process. Infrared eye tracking methods proposed lighting and Generalized Regression Neural Networks (GRNN) By using the calibration process, the movement of the head is large, even without the reliable and accurate eye tracking, mapping function was to enable each of the calibration process by the generalization can be omitted, did not participate in the study eye other users tracking was possible. Experimental results of facial movements that an average 90% of cases, other users on average 85% of the eye tracking results were shown.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.555-558
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• 2003

When a fault relating to the urgent alarm occurs, we must prevent control rods from dropping and make one of two grippers in Control Rod Drive Mechanism (CRDM) grip the drive rod laking a control rod assembly. If a gripper with any problem is ordered to grip the drive rod, the gripper which cannot latch the rod stably will fail to take the rod. On the purpose of escaping this bad case, we order two grippers to hold the drive rod and enhance the reliability of holding control rods. This action is called the double hold. In the middle of the movement of the drive rod, the latching of the drive rod can cause friction between a gripper and the drive rod. This state may give damage to both the gripper and the drive rod. In this paper, we have devised the method which can have two grippers hold the drive rod more stably, without damaging the equipment.

• Journal of IKEEE
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• v.25 no.1
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• pp.83-87
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• 2021

In harsh environments such as fog or fine dust, the cameras' detection ability for object recognition may significantly decrease. In order to accurately obtain important information even in bad weather, fog removal algorithms are necessarily required. Research has been conducted in various ways, such as computer vision/data-based fog removal technology. In those techniques, estimating the amount of fog through the input image's depth information is an important procedure. In this paper, a linear model is presented under the assumption that the image dark channel dictionary, saturation ∗ value, and sharpness characteristics are linearly related to depth information. The proposed method of haze removal through a linear model shows the superiority of algorithm performance in quantitative numerical evaluation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.6
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• pp.149-153
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• 2007

One common type of web-application vulnerabilities is injection flaw, where an attacker exploits faulty application code instead of normal input. In order to be free from injection flaw, an application program should be written in such a way that every potentially bad input character is filtered out. This paper proposes a precise analysis that statically checks whether or not an input string variable may have the given set of characters at hotspot. The precision is accomplished by taking the semantics of condition into account in the analysis.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.11-16
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• 2021

In this paper, a quality inspection system was developed to identify the defective assembly of connectors used in automobile wiring. For waterproof connectors, an internal seal must be inserted for waterproofing. However, there are cases where it is omitted or double-inserted during production. An automatic inspection jig was designed using photosensors and touch switches to classify good and bad connector components. In the case of the existing visual inspection, 6,400 connectors were inspected when 5 people inspected for 8 hours. However, when using the inspection jig developed under the same conditions, 20,000 pieces were inspected. In other words, the productivity is greatly improved compared to the conventional visual inspection.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.51-73
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• 2023

Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.48-52
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• 2023

From the past to the present, banners are consistently used as effective advertising means. In the case of Korea, there are frequent situations in which hidden advertisements are installed. As a result, such hidden advertisement materials may damage urban aesthetics and moreover, incur unnecessary manpower consumption and waste of money. The proposed method classifies the detected banners into good banner and bad banner. The classification results are based on whether the relevant banners are installed in compliance with legal guidelines. In the process, YOLO and Open Computer Vision library are used to determine from various perspectives whether banners in CCTV images comply with the guidelines. YOLO is used to detect the banner area in CCTV images, and OpenCV is used to detect the color values in the area for color comparison. If a banner is detected in the video, the proposed method calculates the location of the banner and the distance from the designated bulletin to determine whether it was installed within the designated location, and then compares whether the color used in the banner is complied with local government guidelines.

• Economic and Environmental Geology
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• v.36 no.2
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• pp.141-148
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• 2003

We investigated the distribution of sea ice using various microwave remote sensing techniques including radar altimeter, radiometer, and scatterometer data in the part of Drake passage, Antarctica, between the area 45$^{\circ}$-75$^{\circ}$W and 55$^{\circ}$-66$^{\circ}$S. Topex/poseidon radar altimeter data were used to analyze the monthly distribution of sea ice surface area between 1992 and 1999 by using Geo_bad_1 flag or MGDR. From satellite radiometer measurements of DMSP's SSM/I, sea ice concentration was extracted during the period from 1993 to 1996. To select a value of ice concentration, normally ranging from 0 to 100%, that can be used as a critical value of judging the existence for ice, sea ice areas estimated from various ice concentrations of radiometer measurements were correlated with the area estimated from the radar altimeter measurements. As a result, 20% of ice concentration was selected, and, then this value was used to integrate radiometer data with radar altimeter and ERS-1/2 scatterometer data. To indirectly verify the result, the last 20 year's sea ice concentration was correlated with surface temperature data near Esper-anza Observation Station. The two data showed a high correlation coefficient of 0.86. The amount of sea ice and temperature variation were found to be closely related in the study area, and this indirectly verifies the result of this study. We provided a method to judge the existence of sea ice from ice concentration of satellite radiometer data and suggested a method to monitor more detailed temporal and spatial variation of sea ice distribution by integra-tion of various microwave remote sensing techniques.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.94-104
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• 2007

Iris recognition is biometric technology which uses a unique iris pattern of user in order to identify person. In the captured iris image by conventional iris recognition camera, it is often the case with eyelid occlusion, which covers iris information. The eyelids are unnecessary information that causes bad recognition performance, so this paper proposes robust algorithm in order to detect eyelid. This research has following three advantages compared to previous works. First, we remove the detected eyelash and specular reflection by linear interpolation method because they act as noise factors when locating eyelid. Second, we detect the candidate points of eyelid by using mask in limited eyelid searching area, which is determined by searching the cross position of eyelid and the outer boundary of iris. And our proposed algorithm detects eyelid by using parabolic hough transform based on the detected candidate points. Third, there have been many researches to detect eyelid, but they did not consider the rotation of eyelid in an iris image. Whereas, we consider the rotation factor in parabolic hough transform to overcome such problem. We tested our algorithm with CASIA Database. As the experimental results, the detection accuracy were 90.82% and 96.47% in case of detecting upper and lower eyelid, respectively.