• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.810-816
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• 2007

A security robot system named EGIS-SR is a mobile security robot through one of the new growth engine project in robotic industries. It allows home surveillance through an autonomous mobile platform using onboard cameras and wireless security sensors. EGIS-SR has many sensors to allow autonomous navigation, hierarchical control architecture to handle lots of situations in monitoring home surveillance and mighty networks to achieve unmanned security services. EGIS-SR is tightly coupled with a networked security environment, where the information of the robot is remotely connected with the remote cockpit and patrol man. It achieved an intelligent unmanned security service. The robot is a two-wheeled mobile robot and has casters and suspension to overcome a doorsill. The dynamic motion is verified through $ADAMS^{TM}$ simulation. For the main controller, PXA270 based hardware platform based on linux kernel 2.6 is developed. In the linux platform, data handling for various sensors and the localization algorithm are performed. Also, a local path planning algorithm for object avoidance with ultrasonic sensors and localization using $StarGazer^{TM}$ is developed. Finally, for the automatic charging, a docking algorithm with infrared ray system is implemented.

• Journal of Microbiology and Biotechnology
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• v.11 no.5
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• pp.739-748
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• 2001

A self-organizing fuzzy logic controller using a genetic algorithm is described, which controlled the glucose concentration for the enhancement of flavonoid production in a fed-batch cultivation of Scutellaria baicalensis G. plant cells. The substrate feeding strategy in a fed-batch culture was to increase the flavonoid production by using the proposed kinetic model. For the two-stage culture, the substrate feeding strategy consisted of a first period with 28 g/I of glucose to promote cell growth, followed by a second period with 5 g/I of glucose to promote flavonoid production. A simple fuzzy logic controller and the self-organizing fuzzy logic controller using a genetic algorithm was constructed to control the glucose concentration in a fed-batch culture. The designed fuzzy logic controllers were applied to maintain the glucose concentration at given set-points of the two-stage culture in fed-batch cultivation. The experimental results showed that the self-organizing fuzzy logic controller improved the controller\`s performance, compared with that of the simple fuzzy logic controller. The specific production yield and productivity of flavonoids in the two-stage culture were higher than those in the batch culture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3057-3075
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• 2020

End-to-end network delay plays an vital role in distributed services. This delay is used to measure QoS (Quality-of-Service). It would be beneficial to know all node-pair delay information, but unfortunately it is not feasible in practice because the use of active probing will cause a quadratic growth in overhead. Alternatively, using the measured network delay to estimate the unknown network delay is an economical method. In this paper, we adopt the state-of-the-art matrix completion technology to better estimate the network delay from limited measurements. Although the number of measurements required for an exact matrix completion is theoretically bounded, it is practically less helpful. Therefore, we propose an online adaptive sampling algorithm to measure network delay in which statistical leverage scores are used to select potential matrix elements. The basic principle behind is to sample the elements with larger leverage scores to keep the traits of important rows or columns in the matrix. The amount of samples is adaptively decided by a proposed stopping condition. Simulation results based on real delay matrix show that compared with the traditional sampling algorithm, our proposed sampling algorithm can provide better performance (smaller estimation error and less convergence pressure) at a lower cost (fewer samples and shorter processing time).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5243-5263
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• 2017

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.2
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• pp.1-5
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• 2008

Although we can make a sparse matrices for LDPC codes, the encoding complexity per a block increases quadratically by $n^2$. We propose modified PEG algorithm using PEG algorithm having a large girth by establishing edges or connections between symbol and check nodes in an edge-by-edge manner. M-PEG construct parity check matrices. So we propose parity check matrices H form a dual-diagonal matrices that can construct a more efficient decoder using a M-PEG(modified Progressive Edge Growth).

• ETRI Journal
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• v.31 no.2
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• pp.173-181
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• 2009

The growth of the World Wide Web and web-based applications is creating demand for high performance web servers to offer better throughput and shorter user-perceived latency. This demand leads to widely used cluster-based web servers in the Internet infrastructure. Load balancing algorithms play an important role in boosting the performance of cluster web servers. Previous load balancing algorithms suffer a significant performance drop under dynamic and database-driven workloads. We propose an estimation-based load balancing algorithm with admission control for cluster-based web servers. Because it is difficult to accurately determine the load of web servers, we propose an approximate policy. The algorithm classifies requests based on their service times and tracks the number of outstanding requests from each class in each web server node to dynamically estimate each web server load state. The available capacity of each web server is then computed and used for the load balancing and admission control decisions. The implementation results confirm that the proposed scheme improves both the mean response time and the throughput of clusters compared to rival load balancing algorithms and prevents clusters being overloaded even when request rates are beyond the cluster capacity.

• Journal of the Korea Safety Management & Science
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• v.19 no.1
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• pp.203-210
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• 2017

Companies are pursuing the management of small quantity batch production or JIT(Just-in-time) system for improving the delivery response and LOB(Line Balancing) in order to satisfy consumers' increasing demands in the current global economic recession. And in order to improve the growth of production for reducing manufacturing cost, improvements of the Load Balancing have become an important reformation factor. Thus this paper is aimed at warehouse which procures materials on the assembly line in procurement logistics of automotive logistics and proceed with research on heuristic algorithm development which can increase the Load Balancing of workers. As a result of this study, when applied the primary target value, it was verified that the whole workers decreased from 28 to 24. Furthermore, when specified the secondary target value and applied algorithm once more, it was verified that the Load Balance Ratio was improved from 44.96% to 91.7%.

• Journal of KIBIM
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• v.5 no.4
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• pp.11-22
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• 2015

Government efforts for green growth policy initiatives demand low-carbon technologies in the road construction industry. The purpose of this paper is to develop an algorithm of a road alignment design solution for establishing the multi-dimensional information, and to calculate carbon emission quantity due to the geometric design elements in the planning phase of road alignment. The paper developed a calculation method for carbon emission quantity by drawing a speed profile reflected in the operating speed, acceleration and deceleration, which are majors factor of carbon emissions while driving and by applying a carbon emission factor. From this effort, it enabled alignment planning to reduce carbon emission. Object-based parametric design methods of the cross-sections were proposed for alignment planning, and the paper demonstrated a BIM-based road alignment planning solution. The proposed solutions can provide multi-dimensional information on carbon emission quantity and cross section elements through driving simulation. It is expected to allow construction of eco-friendly roads by deriving optimal road alignment to minimize environmental costs.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.6
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• pp.422-426
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• 2018

The lithium-ion battery pack of an electric vehicle (EV) deserves to be considered for an alternative use within smart-grid infrastructure. Despite the long automotive service life, EV batteries retain over 70~80% of their initial capacity. These battery packs must be managed for their reliability and safety. Therefore, a battery management system (BMS) should use specific algorithms to measure and estimate the status of the battery. Most importantly, the BMS of a grid-connected energy storage system (ESS) must ensure that the lithium-ion battery does not catch fire or explode due to an internal short from uncontrolled dendrite growth. In other words, the BMS of a lithium-ion battery pack should be capable of detecting the battery's status based on the electrochemical reaction continuously until the end of the battery's lifespan. In this paper, we propose a new protection algorithm for a dendritic lithium battery. The proposed algorithm has applied a parameter from battery pack aging results and has control power managing.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1602-1613
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• 2014

The continuous growth of electric vehicles has caused electric power shortages in conventional utilities owing to the charging of electric-vehicle batteries. In order to increase the capacity of these utilities, photovoltaic systems may be an appropriate solution because of their benefits. However, a large amount of loss is generated in a conventional charging structure using photovoltaic sources owing to the many power conversion processes. This paper describes a simple integrated battery charger that utilizes a PV generation system. Moreover, the system control algorithm is deduced by analyzing the operation modes in order to control the proposed integrated system. The proposed system and algorithm are verified by a 3.3-kW prototype, resulting in an increase in the efficiency of approximately 7% to 15% compared with the conventional system. And, to examine the feasibility of the proposed system, the simulation for multi-charger with various conditions are progressed.