• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7A
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• pp.654-661
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• 2011

RTLS (Real-time locating systems) are used for tracking the location of people or assets in real time. In this system, RTLS readers continuously communicate with RTLS tags for measuring time or ranges and location engine tries to calculate accurate location of tags. However, when we attempt to apply this system to real world, the non-line-of-sight(NLOS) problem can be critical to the system performance because of the obstacles. In this paper, we suggest a new location estimation method for an NLOS environment using a reader-selection strategy. We have implemented all components of the locating system and carried out experiments in a test-bed. The accuracy of the system is 50% better than that of the existing general locating system.

• Journal of IKEEE
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• v.24 no.4
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• pp.991-997
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• 2020

Reinforcement learning has been applied mainly in sequential decision-making problems. Especially in recent years, reinforcement learning combined with neural networks has brought successful results in previously unsolved fields. However, reinforcement learning using deep neural networks has the disadvantage that it is too complex for immediate use in the field. In this paper, we implemented path planning algorithm for mobile robots using Q-learning, one of the easy-to-learn reinforcement learning algorithms. We used real-time Q-learning to update the Q-table in real-time since the Q-learning method of generating Q-tables in advance has obvious limitations. By adjusting the exploration strategy, we were able to obtain the learning speed required for real-time Q-learning. Finally, we compared the performance of real-time Q-learning and DQN.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.130-135
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• 2009

In recent years, researches on rotary inverted pendulum control systems have been significantly focused due their highly nonlinear dynamics and complicated geometric structures. This paper presents a novel control approach for such systems by means of similarity transformation theory. At first, we represent nonlinear system dynamics to the controllability-formed state space model including a time-varying parameter vector. We establish the state-feedback control configuration based on the transformed model and derive an adaptive control law for adjusting desired characteristic equation. Numerical analysis is achieved to evaluate our control method and demonstrate its superiority by comparing it to the traditional control strategy. Furthermore, real-time control experiment is carried out to test its practical reliability.

• IE interfaces
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• v.11 no.1
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• pp.119-129
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• 1998

The relative importance of Logistics in steelworks industry is rather higher among other business activities. The objective of the paper is to propose the methodology for real-time vehicle scheduling for scrap disposal in the steelworks industry. Currently, the rule necessary to assign vehicles to a specific job is strictly fixed. The paper adopts the multi-pass rule selector (MPRS) that suggests a promising rule used for vehicle dispatching for a period of time. The MPRS is regularly invoked if necessary and then evaluates a set of rule candidates to select the best rule with respect to the system performance criteria. The experiment shows that the proposed approach outperforms the current single-pass strategy.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.1-8
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• 2010

In this paper, we propose a scheduling strategy for grid environment that reduces resource cost. This strategy considers resource cost and job failure rate to efficiently allocate local computing resources. The key idea of our strategy is that we use two-level scheduling using remote and local scheduler. The remote scheduler determines the expected total execution times of jobs using the current network and local system status maintained in its resource database and allocates jobs with minimum total execution time to local systems. The local scheduler recalculates the waiting time and execution time of allocated job and uses it to determine whether the job can be processed within the specified deadline. If it cannot finish in time, the job is migrated other local systems, through simulation, we show that it is more effective to reduce the resource cost than the previous Greedy strategy. We also show that the proposed strategy improves the performance compared to previous Greedy strategy.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.829-835
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• 2008

The objective of this study is to present the two-step dispatching strategy for the purpose of the transport vehicle with multi-function used in container terminal. The two-step dispatching is a method to save the waiting time between transport vehicle and cranes using real time location control. The first step dispatching is to allocate the destination location based on the real time location information. The second step dispatching is to indicate the specific job such as loading, unloading, and pick-up based on the condition of working area. This two-step dispatching strategy decreases the waiting times of the stevedoring system and will contribute at a productivity improvement in container terminal.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.629-634
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• 2009

In real-time system application, the feature extraction and scoring algorithm for classification of the passive sonar target has the following problems: it requires an accurate and efficient feature extraction method because it is very difficult to distinguish the features of the propeller shaft rate (PSR) and the blade rate (BR) from the frequency spectrum in real-time, it requires a robust and effective feature scoring method because the classification database (DB) composed of extracted features is noised and incomplete, and further, it requires an easy design procedure in terms of structures and parameters. To solve these problems, an intelligent feature extraction and scoring algorithm using the evolution strategy (ES) and the fuzzy theory is proposed here. To verify the performance of the proposed algorithm, a passive sonar target classification is performed in real-time. Simulation results show that the proposed algorithm effectively solves sonar classification problems in real-time.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.65-79
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• 2006

The ATIS(Advance Traveler Information System), as one part of ITS, is a system aiming to disperse traffic volume on transportation networks by providing traffic information to transportation users on pre-trip and en-route trips. One of tools in ATIS is usage of VMS(Variable Message Signs). It provides to the drivers with direct information about state of processing direction. which is considered as the most effective method in ATIS. The purposes of providing VMS information are classified two categories. One is to provide simple information to drivers for their convenience. The other is to manage traffic demand to improve transportation network performance. However, for more effective and reliable VMS information, several strategies should be taken into account. The main VMS management strategy is "Traffic Diversion Strategy for minimum delay" when traffic congestion or incident are occurred. For effective operation. firstly. reasonable diversion traffic volume is determined by network traffic condition Secondly, it is necessary to make providing information strategy which reflects driver response behavior for controling diversion traffic volume. This paper focuses on the providing real-time route guidance information by VMS when congestion is occurred by the incidents. This sturdy estimates time-dependent system optimal diversion rate that inflects travel time and queue lengths using traffic flow simulation model on base Cellular Automata. In addition, route choice behavior models are developed using binary logit model for traffic information variable by traffic system controller. Finally, this study provides time-dependent VMS massage contents and degree of providing information in order to optimize the traffic flow.

• Korean Management Science Review
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• v.21 no.3
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• pp.101-113
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• 2004

In the rapidly propagating Internet based electronic transaction environment. the importance of real time order confirmation has been more emphasized, In this paper, using data mining techniques, we develop intelligent operations decision model to allow real time order confirmation at the time the customer places an order with required delivery terms. Among various operation plannings used for order fulfillment. mill routing is the first interface decision point to link the order receiving at the marketing with the production planning for order fulfillment. Though linear programming based mathematical optimization techniques are mostly used for mill routing problems, some early orders should wait until sufficient orders are gathered for optimization. And that could effect longer order fulfillment lead-time, and prevent instant order confirmation of delivery terms. To cope with this problem, we provide the intelligent decision model to allow instant order based mill routing decisions. Data mining techniques of decision trees and neural networks. which are more popular in marketing and financial applications, are used to develop the model. Through diverse computational trials with the industrial data from the steel company. we have reported that the performance of the proposed approach is effective compared to the present heuristic only mill routing results. Various issues of data mining techniques application to the mill routing problems having linear programming characteristics are also discussed.