• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1845-1852
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• 2008

The key elements of inter prediction are motion estimation(ME) and motion compensation(MC). Motion estimation is to find the optimum motion vectors, not only by using a distance criteria like the SAD, but also by taking into account the resulting number of 비트s in the 비트 stream. Motion compensation is compensate for movement of blocks of current frame. Inter-prediction Encoding is always the main bottleneck in high-quality streaming applications. Therefore, in real-time streaming applications, dedicated hardware for executing Inter-prediction is required. In this paper, we studied a motion estimator(ME) for H.264/AVC. The designed motion estimator is based on 2-D systolic array and it connects processing elements for fast SAD(Sum of Absolute Difference) calculation in parallel. By providing different path for the upper and lower lesion of each reference data and adjusting the input sequence, consecutive calculation for motion estimation is executed without pipeline stall. With data reuse technique, it reduces memory access, and there is no extra delay for finding optimal partitions and motion vectors. The motion estimator supports variable-block size and takes 328 cycles for macro-block calculation. The proposed architecture is local memory-free different from paper [6] using local memory. This motion estimation encoder can be applicable to real-time video processing.

• The Transactions of the Korea Information Processing Society
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• v.13 no.10
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• pp.475-480
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• 2024

As Internet of Things (IoT) technology is being used in all industries, the importance of secure and convenient firmware update technology is increasing. However, conventional FOTA (Firmware Over-The-Air) technology has a problem because the security is weak when updating firmware with a single path, and strong encryption technology cannot be utilized. Therefore, this study proposes a secure FOTA (S-FOTA) mechanism for lightweight IoT and adaptive S-FOTA ARQ (Automatic Repeat Request) mechanism. This adaptive S-FOTA ARQ mechanism considers the case where the original file cannot be recovered because of the increase in lost files due to the congested channel state and compares and analyzes the conventional method in terms of security, complexity, and transmission speed. Experimental results show that S-FOTA with 40 encrypted files reduced the attacker's attack success rate by at least 62.58% and up to 99.99%, and S-FOTA with 40% of the total number of encrypted file segments takes at least 996.39% more time on average and up to 3374.99% more time than conventional FOTA. In addition, the transmission speed of the adaptive S-FOTA ARQ mechanism was at least 63.16% and up to 2736.36% higher than that of the conventional S-FOTA, and at least 53.89% and up to 70.89% higher than that of the conventional ARQ mechanism.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.101-107
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• 2016

Due to the recent advancement in digital imaging technology, development of intervention equipment has become generalize. Video arbitration procedure is a process to insert a tiny catheter and a guide wire in the body, so in order to enhance the effectiveness and safety of this treatment, the high-quality of x-ray of image should be used. However, the increasing of radiation has become the problem. Therefore, the studies to improve the performance of x-ray detectors are being actively processed. Moreover, this intervention is based on the reference of the angiographic imaging and 3D medical image processing. In this paper, we propose a guidance system to support this intervention. Through this intervention, it can solve the problem of the existing 2D medical images based vessel that has a formation of cerebrovascular disease, and guide the real-time tracking and optimal route to the target lesion by intervention catheter and guide wire tool. As a result, the system was completely composed for medical image acquisition unit and image processing unit as well as a display device. The experimental environment, guide services which are provided by the proposed system Brain Phantom (complete intracranial model with aneurysms, ref H+N-S-A-010) was taken with x-ray and testing. To generate a reference image based on the Laplacian algorithm for the image processing which derived from the cerebral blood vessel model was applied to DICOM by Volume ray casting technique. $A^*$ algorithm was used to provide the catheter with a guide wire tracking path. Finally, the result does show the location of the catheter and guide wire providing in the proposed system especially, it is expected to provide a useful guide for future intervention service.

• Korean Journal of Cognitive Science
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• v.3 no.1
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• pp.61-78
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• 1991

This paper descibes the study of application of a modified Neocognitron model with backward path for the recognition of Hangul(Korean) syllabic characters. In this original report, Fukushima demonstrated that Neocognitron can recognize hand written numerical characters of $19{\times}19$ size. This version accepts $61{\times}61$ images of handwritten Hangul syllabic characters or a part thereof with a mouse or with a scanner. It consists of an input layer and 3 pairs of Uc layers. The last Uc layer of this version, recognition layer, consists of 24 planes of $5{\times}5$ cells which tell us the identity of a grapheme receiving attention at one time and its relative position in the input layer respectively. It has been trained 10 simple vowel graphemes and 14 simple consonant graphemes and their spatial features. Some patterns which are not easily trained have been trained more extrensively. The trained nerwork which can classify indivisual graphemes with possible deformation, noise, size variance, transformation or retation wre then used to recongnize Korean syllabic characters using its selective attention mechanism for image segmentation task within a syllabic characters. On initial sample tests on input characters our model could recognize correctly up to 79%of the various test patterns of handwritten Korean syllabic charactes. The results of this study indeed show Neocognitron as a powerful model to reconginze deformed handwritten charavters with big size characters set via segmenting its input images as recognizable parts. The same approach may be applied to the recogition of chinese characters, which are much complex both in its structures and its graphemes. But processing time appears to be the bottleneck before it can be implemented. Special hardware such as neural chip appear to be an essestial prerquisite for the practical use of the model. Further work is required before enabling the model to recognize Korean syllabic characters consisting of complex vowels and complex consonants. Correct recognition of the neighboring area between two simple graphemes would become more critical for this task.

• The KIPS Transactions:PartA
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• v.11A no.1
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• pp.49-56
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• 2004

The performance of the multiprocessor systems is limited by the several factors. The system performance is affected by the processor speed, memory delay, and interconnection network bandwidth/latency. By the evolution of semiconductor technology, off the shelf microprocessor speed breaks beyond GHz, and the processors can be scalable up to multiprocessor system by connecting through the interconnection networks. In this situation, the system performances are bound by the latencies and the bandwidth of the interconnection networks. SCI, Myrinet, and Gigabit Ethernet are widely adopted as a high-speed interconnection network links for the high performance cluster systems. Performance improvement of the interconnection network can be achieved by the bandwidth extension and the latency minimization. Speed up of the operation clock speed is a simple way to accomplish the bandwidth and latency betterment, while its physical distance makes the difficulties to attain the high frequency clock. Hence the system performance and scalability suffered from the interconnection network limitation. Duplicating the link of the interconnection network is one of the solutions to resolve the bottleneck of the scalable systems. Dual-ring SCI link structure is an example of the interconnection network improvement. In this paper, I propose a network topology and a transaction path algorism, which optimize the latency and the efficiency under the duplicated links. By the simulation results, the proposed structure shows 1.05 to 1.11 times better latency, and exhibits 1.42 to 2.1 times faster execution compared to the dual ring systems.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1259-1268
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• 2021

The 2nd Geostationary Ocean Color Imager (GOCI-II) is the successor to the Geostationary Ocean Color Imager (GOCI), which employs one near-ultraviolet wavelength (380 nm) and eight visible wavelengths(412, 443, 490, 510, 555, 620, 660, 680 nm) and three near-infrared wavelengths(709, 745, 865 nm) to observe the marine environment in Northeast Asia, including the Korean Peninsula. However, the multispectral radiance image observed at satellite altitude includes both the water-leaving radiance and the atmospheric path radiance. Therefore, the atmospheric correction process to estimate the water-leaving radiance without the path radiance is essential for analyzing the ocean environment. This manuscript describes the GOCI-II standard atmospheric correction algorithm and its initial phase validation. The GOCI-II atmospheric correction method is theoretically based on the previous GOCI atmospheric correction, then partially improved for turbid water with the GOCI-II's two additional bands, i.e., 620 and 709 nm. The match-up showed an acceptable result, with the mean absolute percentage errors are fall within 5% in blue bands. It is supposed that part of the deviation over case-II waters arose from a lack of near-infrared vicarious calibration. We expect the GOCI-II atmospheric correction algorithm to be improved and updated regularly to the GOCI-II data processing system through continuous calibration and validation activities.

• Korean Journal of Occupational Therapy
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• v.26 no.4
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• pp.57-72
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• 2018

Objective : This study aims to identify the self-reported driving abilities of elderly drivers and their correlations to the demographic factors that influence them, and to verify the adequacy of the hypothetical model, constructed based on vision, auditory, cognition, motor, and psychological factors, in order to present a path model on the self-reported driving abilities of elderly drivers. Methods : The participants in this study were 122 elderly drivers aged 65 years or older residing in the community. This study evaluated the following factors of the participants: Vision and hearing, motor ability, cognitive ability, depression, self-reported driving abilities. Results : The results of this study are as follows. In the case of men, the self-reported driving ability score was higher than for women, and those driving 6-7 days per week had higher scores than those driving 3 days or less. The period of holding a driver's license and driving experience positively correlated with self-reported driving abilities. The final model of factors influencing the self-reported driving abilities of elderly drivers had a p value (.911) exceeding .05; TLI (1.202), NFI (.949), and CFI (1.000) of over .90; and RMSEA (.000) of lower than 0.1, indicating that the hypothesis model fit the data well. First, the directly influential factors on the self-reported driving abilities of elderly drivers were depression, decreased hearing, and grip strength. Second, age was found to have a direct influence on depression and grip strength; moreover, depression and grip strength as a mediator indirectly influenced their self-reported driving abilities. Third, depression was found to have a direct influence on their delayed cognitive processing and grip strength. Conclusion : The significance of this study is in the identification of direct and indirect factors influencing the self-reported driving abilities of elderly drivers in regional communities, and in the verification of multi-dimensional effects of diverse factors influencing such abilities.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.783-790
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• 2009

The necessity of wireless sensor networks is increasing in the recent years. So many researches are studied in wireless sensor networks. The clustering algorithm provides an effective way to prolong the lifetime of the wireless sensor networks. The one-hop routing of LEACH algorithm is an inefficient way in the energy consumption of cluster-head, because it transmits a data to the BS(Base Station) with one-hop. On the other hand, other clustering algorithms transmit data to the BS with multi-hop, because the multi-hop transmission is an effective way. But the multi-hop routing of other clustering algorithms which transmits data to BS with multi-hop have a data bottleneck state problem. The unequal clustering algorithm solved a data bottleneck state problem by increasing the routing path. Most of the unequal clustering algorithms partition the nodes into clusters of unequal size, and clusters closer to the BS have small-size the those farther away from the BS. However, the energy consumption of cluster-head in unequal clustering algorithm is more increased than other clustering algorithms. In the thesis, I propose an energy efficient unequal clustering algorithm which decreases the energy consumption of cluster-head and solves the data bottleneck state problem. The basic idea is divided a three part. First of all I provide that the election of appropriate cluster-head. Next, I offer that the decision of cluster-size which consider the distance from the BS, the energy state of node and the number of neighborhood node. Finally, I provide that the election of assistant node which the transmit function substituted for cluster-head. As a result, the energy consumption of cluster-head is minimized, and the energy consumption of total network is minimized.

• The KIPS Transactions:PartD
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• v.19D no.3
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• pp.237-246
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• 2012

Although the development of Global Positioning System (GPS) are more and more mature, its accuracy is just acceptable for outdoor positioning, not positioning for the indoor of building and the underpass. For the positioning application area for the indoor of building and the underpass, GPS even cannot achieve that accuracy because of the construction materials while the requirement for accurate positioning in the indoor of building and the underpass, because a space, a person is necessary, may be very small space with several square meters in the indoor of building and the underpass. The Received Signal Strength (RSS) based localization is becoming a good choice especially for the indoor of building and the underpass scenarios where the WiFi signals of IEEE 802.11, Wireless LAN, are available in almost every indoor of building and the underpass. The fundamental requirement of such localization system is to estimate location from Access Point (AP) to mobile device using RSS at a specific location. The Multi-path fading effects in this process make RSS to fluctuate unpredictably, causing uncertainty in localization. To deal with this problem, the combination for the method of Neural Networks and Push-Pull Estimation is applied so that the carried along the devices can learn and make the decision of position using mobile device where it is in the indoor of building and the underpass.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.155-164
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• 2015

This paper describes a design and implementation of CABAC decoder, which would handle HEVC syntax elements in adaptively pipelined-parallel computation manner. Even though CABAC offers the high compression rate, it is limited in decoding performance due to context-based sequential computation, and strong data dependency between context models, as well as decoding procedure bin by bin. In order to enhance the decoding computation of HEVC CABAC, the flag-type syntax elements are adaptively pipelined by precomputing consecutive flag-type ones; and multi-bin syntax elements are decoded by processing bins in parallel up to three. Further, in order to accelerate Binary Arithmetic Decoder by reducing the critical path delay, the update and renormalization of context modeling are precomputed parallel for the cases of LPS as well as MPS, and then the context modeling renewal is selected by the precedent decoding result. It is simulated that the new HEVC CABAC architecture could achieve the max. performance of 1.01 bins/cycle, which is two times faster with respect to the conventional approach. In ASIC design with 65nm library, the CABAC architecture would handle 224 Mbins/sec, which could decode QFHD HEVC video data in real time.