• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.341-346
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• 2011

Wireless sensor networks (WSNs) are formed by a great quantity of sensor nodes, which are consisted of battery-powered and some tiny devices. In WSN, both efficient energy management and Quality of Service (QoS) are important issues for some applications. Real-time services are usually employed to satisfy QoS requirements in critical environment. This paper proposes a real-time MAC (Medium Access Control) protocol with extended backoff scheme for wireless sensor networks. The basic idea of the proposed protocol employs (m,k)-firm constraint scheduling which is to adjust the contention window (CW) around the optimal value for decreasing the dynamic failure and reducing collisions DBP (Distant Based Priority). In the proposed protocol, the scheduling algorithm dynamically assigns uniform transmitting opportunities to each node. Numerical results reveal the effect of the proposed backoff mechanism.

• Journal of Advanced Navigation Technology
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• v.13 no.4
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• pp.523-531
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• 2009

In this study, we propose a joint source/channel rate control algorithm for video encoder targeting packet erasure channel. Based on the buffer constraints of video communication systems, encoding rate constraint is presented. After defining source distortion models for coded and skipped video frames and a channel distortion model for packet errors and their propagation, an average distortion model of received video is proposed for a given encoding window. Finally, we define an optimization problem to minimize the average distortion for given channel rates and packet loss rates by controlling spatio-temporal parameters of source video and FEC block sizes. Then, we propose a window-based algorithm to solve the problem in real-time.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.571-580
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• 2005

In fast long-distance networks, TCP's congestion control algorithm has the problem of utilizing bandwidth effectively. Several window-based congestion control protocols for high-speed and large delay networks have been proposed to solve this problem. These protocols deliberate mainly three properties : scalability, TCP-friendliness, and RTT-fairness. These protocols, however, cannot satisfy above three properties at the same time because of the trade-off among them This paper presents a new window-based congestion control algorithm, called EM (Exponential Increase/ Multiplicative Decrease), that simultaneously supports all four properties including fast convergence, which is another important constraint for fast long-distance networks; it can support scalability by increasing congestion window exponentially proportional to the time elapsed since a packet loss; it can support RTT-fairness and TCP-friendliness by considering RTT in its response function; it can support last fair-share convergence by increasing congestion window inversely proportional to the congestion window just before packet loss. We evaluate the performance of EIMD and other algorithms by extensive computer simulations.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.214-216
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• 2001

유사 시퀸스 검색에서 시간 왜곡 변환을 지원하기 위한 연구가 최근 활발히 이루어지고 있다. 음성 인식과 같은 몇몇 응용에서는 시간 왜곡 변환을 적용할 때 과도한 타이밍의 차이는 허용하지 않을 필요가 있다. 그래서 대부분의 경우 윈도우라는 제약 조건을 추가하게 된다. 이 논문에서는 윈도우 제약 조건이 있을 때 시간 왜곡 변환을 지원하는 유사 검색 방법으로 세그먼트 분할 기법(Segment Partition Approach:SFA)을 제안한다. SFA는 각 시퀸스를 세그먼트로 분할한 뒤 특징을 추출하여 다차원 인덱스를 구성한다. 유사 검색 질의를 수행할 때 이 인덱스를 검색하여 질의 시퀸스와 유사할 가능성이 큰 후보들을 빠르게 찾아낼 수 있고 찾아낸 후보들에 대해서만 정확한 시간 왜곡 변환 거리를 계산하기 때문에 전체 질의 처리 시간을 단축할 수 있다. SPA는 순차 검색에 비하여 좋은 성능을 보이며, 특히 거리 허용치가 작을 때 더욱 우수한 성능을 보인다.

• Journal of Computing Science and Engineering
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• v.1 no.1
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• pp.56-73
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• 2007

Demands have been growing in safety-critical application fields for producing networked real-time embedded computing (NREC) systems together with acceptable assurances of tight service time bounds (STBs). Here a service time can be defined as the amount of time that the NREC system could take in accepting a request, executing an appropriate service method, and returning a valid result. Enabling systematic composition of large-scale NREC systems with STB certifications has been recognized as a highly desirable goal by the research community for many years. An appealing approach for pursuing such a goal is to establish a hard-real-time (HRT) component model that contains its own STB as an integral part. The TMO (Time-Triggered Message-Triggered Object) programming scheme is one HRT distributed computing (DC) component model established by the first co-author and his collaborators over the past 15 years. The TMO programming scheme has been intended to be an advanced high-level RT DC programming scheme that enables development of NREC systems and validation of tight STBs of such systems with efforts far smaller than those required when any existing lower-level RT DC programming scheme is used. An additional goal is to enable maximum exploitation of concurrency without damaging any major structuring and execution approaches adopted for meeting the first two goals. A number of previously untried program structuring approaches and execution rules were adopted from the early development stage of the TMO scheme. This paper presents new concrete justifications for those approaches and rules, and also discusses new extensions of the TMO scheme intended to enable further exploitation of concurrency in NREC system design and programming.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.2
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• pp.53-58
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• 2021

In this paper, an alternative finite memory structure(FMS) smoothing filter is developed for discrete-time state-space model with a control input. To obtain the FMS smoothing filter, unbiasedness will be required beforehand in addition to a performance criteria of minimum variance. The FMS smoothing filter is obtained by directly solving an optimization problem with the unbiasedness constraint using only finite measurements and inputs on the most recent window. The proposed FMS smoothing filter is shown to have intrinsic good properties such as deadbeat and time-invariance. In addition, the proposed FMS smoothing filter is shown to be equivalent to existing FMS filters according to the delay length between the measurement and the availability of its estimate. Finally, to verify intrinsic robustness of the proposed FMS smoothing filter, computer simulations are performed for a temporary model uncertainty. Simulation results show that the proposed FMS smoothing filter can be better than the standard FMS filter and Kalman filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3312-3327
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• 2020

Plant diseases are a significant yield and quality constraint for farmers around the world due to their severe impact on agricultural productivity. Such losses can have a substantial impact on the economy which causes a reduction in farmer's income and higher prices for consumers. Further, it may also result in a severe shortage of food ensuing violent hunger and starvation, especially, in less-developed countries where access to disease prevention methods is limited. This research presents an investigation of Directional Local Quinary Patterns (DLQP) as a feature descriptor for plants leaf disease detection and Support Vector Machine (SVM) as a classifier. The DLQP as a feature descriptor is specifically the first time being used for disease detection in horticulture. DLQP provides directional edge information attending the reference pixel with its neighboring pixel value by involving computation of their grey-level difference based on quinary value (-2, -1, 0, 1, 2) in 0°, 45°, 90°, and 135° directions of selected window of plant leaf image. To assess the robustness of DLQP as a texture descriptor we used a research-oriented Plant Village dataset of Tomato plant (3,900 leaf images) comprising of 6 diseased classes, Potato plant (1,526 leaf images) and Apple plant (2,600 leaf images) comprising of 3 diseased classes. The accuracies of 95.6%, 96.2% and 97.8% for the above-mentioned crops, respectively, were achieved which are higher in comparison with classification on the same dataset using other standard feature descriptors like Local Binary Pattern (LBP) and Local Ternary Patterns (LTP). Further, the effectiveness of the proposed method is proven by comparing it with existing algorithms for plant disease phenotyping.

• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.269-278
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• 2001

Routing region modeling method of auto_routing systems are use the grid and the non-grid type. Though grid type has a few electrical and physical element on PCB, grid type has disadvantage which decrease the auto-routing speed dur to constraint with board and gird size. Thus it increase the memory capacity, Non-grid type(Shape baed type) use the region processing type, so it has 44.2% memory decrease effect than grid type in routing region. Thus, via number has 55% decrease effect, total routing time is increased 83.8% than conventional PCB system. In this paper we developed high speed PCB auto-routing system without memory waste by using shaped type applicant with auction algorithm which reaching the destination from one-point with best speed and solving the path problem. Also, this system developed by Visual C++ in IBM Pentium computer Window environment, and compatible with other PC.

• Journal of Internet of Things and Convergence
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• v.10 no.5
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• pp.27-37
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• 2024

In the context of multi-vehicle and multi-task logistics distribution within a park, traditional algorithms are often hindered by high computational complexity and slow convergence rates. Particle Swarm Optimization (PSO) has gained popularity in path planning for autonomous delivery vehicles due to its straightforward algorithmic principles, broad applicability, and comprehensive search capabilities. However, the conventional PSO is susceptible to premature convergence, leading to local optima. To address this, this study incorporates the Tent map into the PSO to enhance the algorithm's global search ability and prevent premature convergence. Benchmark function tests demonstrate that the improved Particle Swarm Optimization algorithm (TPSO), as proposed in this study, exhibits faster convergence and greater accuracy.In the instance verification section, X Park was selected as an example to construct a multi-vehicle and multi-task model for the logistics distribution within the park. The TPSO algorithm proposed in this paper was used to solve the model, and finally, the superiority of the TPSO algorithm was verified through comparative simulation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.201-209
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• 2012

The point-based complex event processing handled an instantaneous event by using one time stamp in each event. However, the activity period of the event plays the important role in the field which is the same as the finance, multimedia, medicine, and meteorology. The point-based event is insufficient for expressing the complex temporal relationship in this field. In the application field of the real-time world, the event has the period. The events more than two kinds can be temporally overlapped. In addition, one event can include the other event. The relation about the events of kind of these can not be successive like the point-based event. This thesis designs and implements the method detecting the patterns of the complex event by using the interval-based events. The interval-based events can express the overlapping relation between events. Furthermore, it can include the others. By using the end point of beginning and end point of the termination, the operator of interval-based events shows the interval-based events. It expresses the sequence of the interval-based events and can detect the complex event patterns. This thesis proposes the algorithm using the active instance stack in order to raise efficiency of detection of the complex event patterns. When comprising the event sequence, this thesis applies the window push down technique in order to reduce the number of intermediate results. It raises the utility factor of the running time and memory.