• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.190-196
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• 2014

This paper proposes a mobile-optimized pedestrian detection method using Cascade of HOG(Histograms of Oriented Gradients) for ADAS(Advanced Driver Assistance System) on smartphones. In order to use the limited resource of mobile platforms efficiently, the method is implemented by the OpenCL(Open Computing Language) library, and its processing time is reduced in the following two aspects. Firstly, the method sets a program build option specifically and adjusts work group sizes as variety of kernels in the host code. Secondly, it utilizes local memory and a LUT(Look-Up Table) in the kernel code to accelerate the program. For performance evaluation, the developed algorithm is compared with the mobile CPU-based OpenCV(Open Computer Vision) for Android function. The experimental results show that the processing speed is 25% faster than the OpenCV hogcascade.

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.10-19
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• 2010

The progress of computers and Web has given rise to a rapid increase of the quantity of the useful information, which is making the demand of recommender systems widely expanding. Like in other domains, a recommender system in a digital library is important, but there are only a few studies about the recommender system of research papers, Moreover none is there in korea to our knowledge. In the paper, we seek for a way to develop the NDSL recommender system of research papers based on the survey of related studies. We conclude that NDSL needs to modify the way to collect user's interests from explicit to implicit method, and to use user-based and memory-based collaborative filtering mixed with contents-based filtering(CF). We also suggest the method to mix two filterings and the use of personal ontology to improve user satisfaction.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.954-963
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• 2007

As RFID systems are applied to various fields and applications such as supply chain management, asset management, location based applications etc. the requirements becomes diverse. For example, Much higher performance, TCP/IP protocol stack are required in some applications. However, low end processors based systems such as 8051 processor can not meet such requirements due to their low processing capacity and limited size of memory. In this paper a UHF band RFID system which meets the EPC Class-1 Generation-2 specification with ARM920T-based processor is implemented and tested.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.430-435
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• 2018

In this paper, an improved decoding scheme for low-complexity parity-check(LCPC) code with small code length is proposed. The LCPC code is less complex than the turbo code or low density parity check(LDPC) code and requires less memory, making it suitable for communication between internet-of-things(IoT) devices. The IoT devices are required to have low complexity due to limited energy and have a low end-to-end delay time. In addition, since the packet length to be transmitted is small and the signal processing capability of the IoT terminal is small, the LCPC coding system should be as simple as possible. The LCPC code can correct all single errors and correct some of the two errors. In this paper, the proposed decoding scheme improves the bit error rate(BER) performance without increasing the complexity by correcting both errors using the soft value of the modulator output stage. As a result of the simulation using the proposed decoding scheme, the code gain of about 1.1 [dB] was obtained at the bit error rate of $10^{-5}$ compared with the existing decoding method.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.1-18
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• 2008

By using previous similar case plans, the case-based planning (CBP) systems can generate efficiently plans for new problems. However, most existing CBP systems show limited functionalities for case retrieval and case generalization. Moreover, they do not allow their users to participate in the process of plan generation. To support efficient memory use and case retrieval, the proposed case-based planning system, JCBP, groups the set of cases sharing the same goal in each domain into individual case bases and maintains indexes to these individual case bases. The system applies the heuristic knowledge automatically extracted from the problem model to the case adaptation phase. It provides a sort of case generalization through goal regression. Also JCBP can operate in an interactive mode to support a mixed-initiative planning. Since it considers and utilizes user's preference and knowledge for solving the given planning problems, it can generate solution plans satisfying more user's needs and reduce the complexity of plan generation.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.32-43
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• 2010

IPTV is an emerging technology that combines both broadcasting and tele-communication technologies, and provides various multi-media contents to the service subscribers. In general, IPTV broadcasters transmit scrambled signals (multi-media contents) to the paying subscribers, and the users within the acknowledged network descramble the signals using the smart-card. That is, users are verified through communication between STB (Set-Top Box) and smart-card. In 2004, Jiang et al. proposed a secure protocol regarding the verification process. The method has been modified and enhanced by several following research works. However, all the methods that have been proposed so far required modular exponentiation operations which may raise the smart-card costs. In this paper, we propose a new efficient mutual authentication and session-key establishment protocol using only hash functions and exclusive-or operations, and show that the proposed protocol is still secure under various security attacks.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.443-449
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• 2017

Swarm of low-cost UAVs for search mission has benefit in the sense of rapid search compared to use of single high-end UAV. As the number of UAVs forming swarm increases, not only the time for the mission planning increases, but also the system to operate UAVs has excessive burden. This paper addresses a decentralized area search algorithm adequate for multiple UAVs which takes advantages of flexibility, robustness, and simplicity. To down the cost, it is assumed that each UAV has limited ability: close-communication, basic calculation, and limited memory. In close-communication, heath conditions and search information are shared. And collision avoidance and consensus of next search direction are then done. To increase weight on un-searched area and to provide overlapped search, the score function is introduced. Performance and operational characteristics of the proposed search algorithm and mission planning logic are verified via numerical simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10B
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• pp.630-638
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• 2005

As real-time media applications based on IP multicast networks spread widely, the end-to-end QoS (quality of service) provisioning for these applications have become very important. To guarantee the end-to-end QoS of multi-party media applications, it is essential to monitor the time-varying status of both network metrics (i.e., delay, jitter and loss) and system metrics (i.e., CPU and memory utilization). In this paper, targeting the multicast-enabled AG (Access Grid) group collaboration tool based on multi-Party real-time media services, a hybrid monitoring scheme that can monitor the status of both multicast network and node system is investigated. It combines active monitoring and passive monitoring approaches to measure multicast network. The active monitoring measures network-layer metrics (i.e., network condition) with probe packets while the passive monitoring checks application-layer metrics (i.e., user traffic condition by analyzing RTCP packets). In addition, it measures node system metrics from system API. By comparing these hybrid results, we attempt to pinpoint the causes of performance degradation and explore corresponding reactions to improve the end-to-end performance. The experimental results show that the proposed hybrid monitoring can provide useful information to coordinate the performance improvement of multi-party real-time media applications.

• Journal of KIISE:Information Networking
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• v.33 no.2
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• pp.165-174
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• 2006

Data dissemination using either flooding or legacy ad-hoc routing protocol is not realistic approach in the wireless sensor networks, which are composed of sensor nodes with very weak computing power, small memory and limited battery. In this paper, we propose the ELF(Energy-efficient Localized Flooding) protocol. The ELF is energy-efficient data dissemination protocol for wireless sensor networks. In the ELF protocol, there are two data delivery phases between fixed source and mobile sink node. The first phase, before the tracking zone, sensing data are forwarded by unicasting. After that, within the tracking zone, sensing data are delivered by localized flooding. Namely, the ELF Properly combines advantages from both unicasting and flooding. According to evaluation results by simulation, the proposed ELF protocol maintains very high data delivery ratio with using a little energy. Also, the property of average delay is better than others. From our research results, the ELF is very effective data dissemination protocol for wireless sensor networks.

• Journal of KIISE
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• v.42 no.4
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• pp.522-529
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• 2015

Ever since the R-tree was proposed to index multi-dimensional data, many efforts have been made to improve its query performances. One common trend to improve query performance is to parallelize query processing with the use of multi-core architectures. To this end, a GPU-base R-tree has been recently proposed. However, even though a GPU-based R-tree can exhibit an improvement in query performance, it is limited in its ability to handle large volumes of data because GPUs have limited physical memory. To address this problem, we propose MGR-tree (Multi-GPU R-tree), which can manage large volumes of data by dividing nodes into multiple GPUs. Our experiments show that MGR-tree is up to 9.1 times faster than a sequential search on a GPU and up to 1.6 times faster than a conventional GPU-based R-tree.