• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1A
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• pp.16-24
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• 2010

High Speed Uplink Packet Access(HSUPA) is a WCDMA Release 6 technology which corresponds to High Speed Downlink Packet Access(HSDPA). Node B Supports fast scheduling, Hybrid ARQ(HARQ), short Transmission Time Interval(TTI) for high rate uplink packet data. It is very important to detect Iub congestion to improve end user's Quality of Service(QoS). This paper proposes Node B Congestion Detection(BCD) mechanism and suggests to use the hybrid of Transport Network Layer(TNL) congestion detection and BCD. It is shown that HSUPA user throughput performance can be improved by the proposed method even with small Iub bandwidth.

• Convergence Security Journal
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• v.8 no.2
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• pp.79-85
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• 2008

Our paper deals with a method for supporting multiple call/sessions in a mobile terminal. The different identifier for each protocol layer is assigned to each session when a mobile terminal sets SDP for multimedia services. In particular, QoS based tasks are used for managing the traffics in radio interface. Also, queuing, admission control, load control, resource allocation and scheduling are done based on the priority of sessions. The various multimedia services which is different in the requirement of resource allocation are able to be serviced simultaneously because a mobile terminal can provide the various services based on this scheme.

• Journal of the Korea Society of Computer and Information
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• v.23 no.10
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• pp.57-63
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• 2018

The operating system for an isolated microgrid, which is completely disconnected from the central power system, aims at preventing blackouts and minimizing power generation costs of diesel generators through efficient operation of the energy storage system (ESS) that stores energy produced by renewable energy generators and diesel generators. In this paper, we predict the amount of renewable energy generation using the weather forecast and build an optimal diesel power generation plan using a genetic algorithm. In order to avoid inefficiency due to inaccurate prediction of renewable energy generation, our search algorithm imposes penalty on candidate diesel power generation plans that fail to maintain the SOC (state of charge) of ESS at an appropriate level. Simulation experiments show that our optimization method for maintaining an appropriate SOC balance can prevent the blackout better when compared with the previous method.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.79-87
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• 2010

It is widely accepted that the coverage with high user densities in mobile multimedia environments can only be achieved with small cell such as micro- and pico-cell. If handover events occur during the transmission of multimedia, the efficient resource reservation and handover methods are necessary in order to maintain the same QoS of transmitted multimedia traffic because the QoS may be defected by some delay and information loss. In this paper, we propose a resource allocation method in the next generation mobile communication systems, in which the resource allocation process has a tight relation with call admission, call load, and packet scheduling. The simulation results show that our proposed method provides a excellent performance.

• Journal of IKEEE
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• v.21 no.1
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• pp.92-95
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• 2017

In this paper, we proposed a way to improve function of small scale GP-GPU. Instead of using superscalar which increase scheduling-complexity, we suggested the application of simple core to maximize GP-GPU performance. Our studies also demonstrated that simplified Stream Processor is one of the way to achieve functional improvement in GP-GPU. In addition, we found that developing of optimal thread-assigning method in Warp Scheduler for specific application improves functional performance of GP-GPU. For examination of GP-GPU functional performance, we suggested the thread-assigning way which coordinated with Deep-Learning system; a part of Neural Network. As a result, we found that functional index in algorithm of Neural Network was increased to 90%, 98% compared with Intel CPU and ARM cortex-A15 4 core respectively.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.814-823
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• 2012

Electric power transmission utilities make an effort to maximize profit by reducing their electricity supply and operation costs while maintaining their reliability. The development of maintenance strategies for aged components is one of the more effective ways to achieve this goal. The reliability centered approach is a key method in providing optimal maintenance strategies. It considers the tradeoffs between the upfront maintenance costs and the potential costs incurred by reliability losses. This paper discusses the application of the Particle Swarm Optimization (PSO) technique used to find the optimal maintenance strategy for a transmission component in order to achieve the minimum total expected cost composed of Generation Cost (GC), Maintenance Cost (MC), Repair Cost (RC) and Outage Cost (OC). Three components of a transmission system are considered: overhead lines, underground cables and insulators are considered. In regards to aged and aging component, a component state model that uses a modified Markov chain is proposed. A simulation has been performed on an IEEE 9-bus system. The results from this simulation are quite encouraging, and then the proposed approach will be useful in practical maintenance scheduling.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1299-1319
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• 2017

This paper presents a scalable multiple camera collaboration strategy for active tracking applications in large areas. The proposed approach is based on distributed mechanism but emulates the master-slave mechanism. The master and slave cameras are not designated but adaptively determined depending on the object dynamic and density distribution. Moreover, the number of cameras emulating the master is not fixed. The collaboration among the cameras utilizes global and local sectors in which the visual correspondences among different cameras are determined. The proposed method combines the local information to construct the global information for emulating the master-slave operations. Based on the global information, the load balancing of active tracking operations is performed to maximize active tracking coverage of the highly dynamic objects. The dynamics of all objects visible in the local camera views are estimated for effective coverage scheduling of the cameras. The active tracking synchronization timing information is chosen to maximize the overall monitoring time for general surveillance operations while minimizing the active tracking miss. The real-time simulation result demonstrates the effectiveness of the proposed method.

• Smart Structures and Systems
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• v.24 no.6
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.1-6
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• 2021

In this paper, an efficient implementation of AES encryption algorithm is presented for CCTV image security using C# language. In this approach, an efficient S-Box is first designed for reducing the computation time which is required in each round process of AES algorithm, and then an CCTV image security system is implemented on the basis of this algorithm on a composite field GF(((22)2)2). In addition, the shared S-Box structure is designed for realizing the minimized memory space, which is used in each round transformation and key scheduling processes. Through performance evaluation, it was confirmed that the proposed method is more efficient than the existing method. The proposed CCTV system in C# language using Visual studio 2010.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.76-83
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• 2020

Postal logistics organizations are characterized as having high labor intensity and short response times. These characteristics, along with rapid change in mail volume, make load scheduling a fundamental concern. Load analysis of major postal infrastructures such as post offices, sorting centers, exchange centers, and delivery stations is required for optimal postal logistics operation. In particular, the performance of mail traffic forecasting is essential for optimizing the resource operation by accurate load analysis. This paper addresses a traffic forecast problem of postal parcel that arises at delivery stations of Korea Post. The main purpose of this paper is to describe a method for predicting short-term traffic of postal parcel based on self-similarity analysis and to introduce an application of the traffic prediction model to postal logistics system. The proposed scheme develops multiple regression models by the clusters resulted from feature engineering and individual models for delivery stations to reinforce prediction accuracy. The experiment with data supplied by main postal delivery stations shows the advantage in terms of prediction performance. Comparing with other technique, experimental results show that the proposed method improves the accuracy up to 45.8%.