• Journal of Communications and Networks
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• v.11 no.4
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• pp.406-415
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• 2009

In this work, we consider performance modeling of a wireless sensor network with a time division multiple access (TDMA) media access protocol with slot reuse. It is assumed that all the nodes are peers of each other and they have two modes of operation, active and sleep modes. We model the sensor network as a Jackson network with unreliable nodes with on and off states. Active and sleep modes of sensor nodes are modeled with on and off states of unreliable nodes. We determine the joint distribution of the sensor node queue lengths in the network. From this result, we derive the probability distribution of the number of active nodes and blocking probability of node activation. Then, we present the mean packet delay, average sleep period of a node and the network throughput. We present numerical results as well as simulation results to verify the analysis. Finally, we discuss how the derived results may be used in the design of sensor networks.

• Architectural research
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• v.11 no.2
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• pp.43-49
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• 2009

Since the late 1980s, the schedule technique applied to the construction industry around the world has rapidly changed from the traditional ADM (Arrow Diagramming Method) to the PDM (Precedence Diagramming Method) technique. The main reason for this change is to overcome the limits and inconveniences of the traditional ADM technique. The time-cost trade-off is one of the core scheduling techniques to establish the best optimized combination plan in terms of a relationship between the cost and schedule. However, most of the schedule-related textbooks and research papers have discussed and proposed applications of a time-cost trade-off technique based only on the Finish to Start relationship. Therefore, there are almost no consideration and discussion of problems or restrictions that emerge when the time-cost trade-off technique is applied to the PDM network that has overlapping relationships. This paper proposes the lead-time adjustment method as a methodology for overcoming some restrictions that are encountered when the time-cost trade-off technique is applied to the overlapping relationships of the PDM network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8B
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• pp.699-706
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• 2003

This paper is to verify that 2-state MMPP Model conform to ATM VBR traffic characteristics by measuring and analyzing real-time VBR traffic in KT's ATM network. As a result, we validated the fact that real-time VBR traffic of ATM network cannot be apply to MMPP model and must be represented by previously general On-Off Model with characteristics as follows: arrival rate of On state (λ$_1$) is deterministic, arrival rate of Off state (λ$_2$) is zero, and two transition rate (T$_1$,T$_2$) is only random variable. As research results are to handle real traffic, these results can be used to all ATM network traffic model with traffic management function such as KT's ATM network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7C
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• pp.670-676
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• 2002

The object of ATM network is to the guarantee quality of service(QoS). Therefore, various of traffic management schemes have been proposed. Among these schemes, call admission control(CAC) is very important to provide real-time services and ON-OFF model, which is single source traffic model, has been used. But ON-OFF model differ from GCRA(Generic Cell Rate Algorithm) controlled traffic in ATM network. In this paper, we analyze the traffic, which is controlled as dual GCRA, and propose TWM(Three-state Worst-case Model), which is new single source traffic model. We also proposed CAC to guarantee peak-to-peak CDV(Cell Delay Variation) based on the TWM. In experiments, ON-OFF model and TWM are compared to show that TWM is superior to ON-Off model in terms of QoS guaranteeing.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.1
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• pp.20-27
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• 2008

In this paper, a nonlinear classifier of a feed-forward neural network is implemented on an FPGA chip. The feedforward neural network is implemented in hardware for fast parallel processing. After off line training of neural network, weight values are saved and used to perform forward propagation of neural processing. As an example, AND and XOR digital logic classification is conducted in off line, and then weight values are used in neural network. Experiments are conducted successfully and confirmed that the FPGA neural network hardware works well.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.282-289
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• 2007

While demands for express couriers service are rapidly increasing due to recent progress of electronic commerce, express courier service companies are struggling to take a larger market share through ongoing improvement in their service processes. Cut-off time is the time limit that all orders delivered before the limit are guaranteed for the delivery within the very next day. Extending cut-off time for express service centers can provide the express company with increase of total sales, but it may also cause increasing the possibility not to satisfy customer needs due to work delay in the consolidation terminal. We develop a design model for express courier service network based on a recursive optimization/simulation procedure. With the optimization model, we seek key design parameters such as the cut-off time for express service centers and the capacity of the consolidation terminal maximizing total sales profit while satisfying the desired level of performances. With the simulation model, we consider the dynamic nature of the network and obtain relationships between the design parameters and the performance measures with the multiple linear regression. The validity of the model is examined with an example.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.65.2-65
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• 2002

This paper is concerned with the accurate position control of a rodless pneumatic cylinder using On/Off solenoid valve. A novel Intelligent Modified Pulse Width Modulation(MPWM) is newly proposed. The control performance of this pneumatic cylinder depends on the external loads. To overcome this problem , switching of control parameter using artificial neural network is newly proposed, which estimates external loads on rodless pneumatic cylinder using this training neural network. As an underlying controller, a state feedback controller using position, velocity and acceleration is applied in the switching control the system. The effectiveness of the proposed control algorithms are demonstrated...on/off solenoid valve, load estimation, MPWM, Artificial neural network.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.7
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• pp.680-687
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• 2000

The objective of this study is to improve the control performance of Ondol system which causes overheating and underheating with 2-position on/off control. For this, a predictive control that determines the suitable on/off positions using Artificial Neural Network(ANN) model was proposed Dynamic analyses using computer simulation show that the neural network used in the predictive control is adapted to each room whose loads variation and thermal characteristics are different. To examine the applicability of this predictive control with ANN it was compared with 2-position on/off control through experiments.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.16 no.4
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• pp.16-23
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• 2020

In this study, the control characteristics and effects of control methods on heating performance and energy consumption for the hot water floor radiant heating control system of a residential apartment were research by experiment. As a control method, On-Off control and outdoor reset control methods with GRNN(General Regression Neural Network) and without GRNN are considered. Also, the control performances with regard to improvement of indoor thermal environment and reduction of energy consumption are compared, respectively. Experiment results show that the performance of the control method with GRNN is better than that of conventional on-off control method without GRNN in the responses of room set temperature and energy saving.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.65-75
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• 2019

Non-Functional Requirements (NFR) play a crucial role during the software development process. Currently, NFRs are considered more important than Functional Requirements and can determine the success of a software system. NFRs can be very complicated to understand due to their subjective manner and especially their conflicting nature. Self-adaptive systems (SAS) are operating in dynamically changing environment. Furthermore, the configuration of the SAS systems is dynamically changing according to the current systems context. This means that the configuration that manages the trade-off between NFRs in this context may not be suitable in another. This is because the NFRs satisfaction is based on a per-context basis. Therefore, one context configuration to satisfy one NFR may produce a conflict with another NFR. Furthermore, current approaches managing Non-Functional Requirements trade-off stops managing them during the system runtime which of concern. To solve this, we propose fragmentizing the NFRs and their alternative solutions in form of Multi-entity Bayesian network fragments. Consequently, when changes occur, our system creates a situation specific Bayesian network to measure the impact of the system's conditions and environmental changes on the NFRs satisfaction. Moreover, it dynamically decides which alternative solution is suitable for the current situation.