• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.496-499
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• 1990

In this paper, the robustness of implict self tunning controller on the continuous time system is investigated. Continuous time exponentially weighted least square algorithm is used for estimating the system parameters. The pole-zero placement method is adapted for the control algorithm. On considering the control weighting factor and realizability filter the effects of unmodeled dynamics of the plant are examined by the simulation.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.747-749
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• 2000

A new scheduling algorithm called the Adaptive Weighted Round Robin with Delay Tolerance (AWRR/DT) is presented. The proposed scheme can reduce the average delay of non-real-time (NRT) class while maintaining the QoS of real-time (RT) classes. Our scheme can also reflect the traffic fluctuation of networks with a small processing burden.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5023-5038
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• 2017

Big data is an emerging technology which deals with wide range of data sets with sizes beyond the ability to work with software tools which is commonly used for processing of data. When we consider a huge network, we have to process a large amount of network information generated, which consists of both normal and abnormal activity logs in large volume of multi-dimensional data. Intrusion Detection System (IDS) is required to monitor the network and to detect the malicious nodes and activities in the network. Massive amount of data makes it difficult to detect threats and attacks. Sequential Pattern mining may be used to identify the patterns of malicious activities which have been an emerging popular trend due to the consideration of quantities, profits and time orders of item. Here we propose a sequential pattern mining algorithm with fuzzy logic feature selection and fuzzy weighted support for huge volumes of network logs to be implemented in Apache Hadoop YARN, which solves the problem of speed and time constraints. Fuzzy logic feature selection selects important features from the feature set. Fuzzy weighted supports provide weights to the inputs and avoid multiple scans. In our simulation we use the attack log from NS-2 MANET environment and compare the proposed algorithm with the state-of-the-art sequential Pattern Mining algorithm, SPADE and Support Vector Machine with Hadoop environment.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.8
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• pp.1-8
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• 2007

In this paper, we evaluate a performance on a resource allocation algorithm for prioritized data services in CDMA networks supporting real-time and non-real-time data services. The weighted aggregate data throughput is used to characterize the performance of the prioritized data service. Our prioritized data service is implemented so that the weighted aggregate data throughput is maximized via efficient power and spreading gain allocation. Numerical experiments are performed to evaluate a suboptimal resource allocation algorithm for typical parameters.

• ETRI Journal
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• v.27 no.6
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• pp.777-787
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• 2005

In this paper, we propose an urgency- and efficiency-based wireless packet scheduling (UEPS) algorithm that is able to schedule real-time (RT) and non-real-time (NRT) traffics at the same time while supporting multiple users simultaneously at any given scheduling time instant. The UEPS algorithm is designed to support wireless downlink packet scheduling in an orthogonal frequency division multiple access (OFDMA) system, which is a strong candidate as a wireless access method for the next generation of wireless communications. The UEPS algorithm uses the time-utility function as a scheduling urgency factor and the relative status of the current channel to the average channel status as an efficiency indicator of radio resource usage. The design goal of the UEPS algorithm is to maximize throughput of NRT traffics while satisfying quality-of-service (QoS) requirements of RT traffics. The simulation study shows that the UEPS algorithm is able to give better throughput performance than existing wireless packet scheduling algorithms such as proportional fair (PF) and modified-largest weighted delay first (M-LWDF), while satisfying the QoS requirements of RT traffics such as average delay and packet loss rate under various traffic loads.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.115-121
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• 2006

In this paper, we proposed about data error check and correction on channel transmission in the communication system. LDPC codes are used for minimizing channel errors by modeling AWGN Channel as a VDSL system. Because LDPC Codes use low density parity bit, mathematical complexity is low and relating processing time becomes shorten. Also the performance of LDPC code is better than that of turbo code in long code word on iterative decoding algorithm. This algorithm is better than conventional algorithms to correct errors, the proposed algorithm assigns weights for errors concerning parity bits. The proposed weighted Bit-flipping algorithm is better than the conventional Bit-flipping algorithm and we are recognized improve gain rate of 1 dB.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.913-917
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• 2009

Flash memories have asymmetric I/O costs for read and write in terms of latency and energy consumption. However, the ratio of these costs is dependent on the type of storage. Moreover, it is becoming more common to use two flash memories on a system as an internal memory and an external memory card. For this reason, buffer cache replacement algorithms should consider I/O costs of device as well as possibility of reference. This paper presents WWCLOCK(Write-Weighted CLOCK) algorithm which directly uses I/O costs of devices along with recency and frequency of cache blocks to selecting a victim to evict from the buffer cache. WWCLOCK can be used for wide range of storage devices with different I/O cost and for systems that are using two or more memory devices at the same time. In addition to this, it has low time and space complexity comparable to CLOCK algorithm. Trace-driven simulations show that the proposed algorithm reduces the total I/O time compared with LRU by 36.2% on average.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.169-180
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• 2015

Recently, scheduling problems with position-dependent processing times have received considerable attention in the literature, where the processing times of jobs are dependent on the processing sequences. However, they did not consider cases in which each processed job has different learning or aging ratios. This means that the actual processing time for a job can be determined not only by the processing sequence, but also by the learning/aging ratio, which can reflect the degree of processing difficulties in subsequent jobs. Motivated by these remarks, in this paper, we consider a two-agent single-machine scheduling problem with linear job-dependent position-based learning effects, where two agents compete to use a common single machine and each job has a different learning ratio. Specifically, we take into account two different objective functions for two agents: one agent minimizes the total weighted completion time, and the other restricts the makespan to less than an upper bound. After formally defining the problem by developing a mixed integer non-linear programming formulation, we devise a branch-and-bound (B&B) algorithm to give optimal solutions by developing four dominance properties based on a pairwise interchange comparison and four properties regarding the feasibility of a considered sequence. We suggest a lower bound to speed up the search procedure in the B&B algorithm by fathoming any non-prominent nodes. As this problem is at least NP-hard, we suggest efficient genetic algorithms using different methods to generate the initial population and two crossover operations. Computational results show that the proposed algorithms are efficient to obtain near-optimal solutions.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.2
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• pp.278-294
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• 2015

Considering the guidance and control problem of the near space interceptor (NSI) during the terminal course, this paper proposes a three-channel independent integrated guidance and control (IGC) scheme based on the backstepping sliding mode and finite time disturbance observer (FTDO). Initially, the three-channel independent IGC model is constructed based on the interceptor-target relative motion and nonlinear dynamic model of the interceptor, in which the channel coupling term and external disturbance are regarded as the total disturbances of the corresponding channel. Then, the FTDO is introduced to estimate the target acceleration and control system loop disturbances, and the feed-forward compensation term based on the estimated values is employed to effectively remove the effect of disturbances in finite time. Subsequently, the IGC algorithm based on the backstepping sliding mode is also given to obtain the virtual control moment. Furthermore, a robust least-squares weighted control allocation (RLSWCA) algorithm is employed to distribute the previous virtual control moment among the corresponding aerodynamic fins and reaction jets, which also takes into account the uncertainty in the control effectiveness matrix. Finally, simulation results show that the proposed IGC method can obtain the small miss distance and smooth interceptor trajectories.

• Convergence Security Journal
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• v.19 no.2
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• pp.73-81
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• 2019

In this paper, we propose a user-dependent mid-point navigation system using a time weighted mid-point navigation algorithm and a user preference based mid-point neighborhood recommendation system. The proposed system consists of a mid-point navigation module for calculating an mid-point by applying a time weight of each user based on a departure point between users, and a search module for providing a search for a route to the calculated mid-point. In addition, based on the mid-point search result, it is possible to increase the utilization rate of users by including a place recommending function based on user's preference. Experimental results show that the proposed system can increase the efficiency of using by the user-dependent mid-point navigation and place recommendation function.