• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.487-495
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• 2012

In this paper, a Smart Home Service Robot, McBot II, which performs mess-cleanup function etc. in house, is designed much more optimally than other service robots. It is newly developed in much more practical system than McBot I which we had developed two years ago. One characteristic attribute of mobile platforms equipped with a set of dependent wheels is their omni- directionality and the ability to realize complex translational and rotational trajectories for agile navigation in door. An accurate coordination of steering angle and spinning rate of each wheel is necessary for a consistent motion. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy azimuth estimator. A specialized anthropomorphic robot manipulator which can be attached to the housemaid robot McBot II, is developed in this paper. This built-in type manipulator consists of both arms with 4 DOF (Degree of Freedom) each and both hands with 3 DOF each. The robotic arm is optimally designed to satisfy both the minimum mechanical size and the maximum workspace. Minimum mass and length are required for the built-in cooperated-arms system. But that makes the workspace so small. This paper proposes optimal design method to overcome the problem by using neck joint to move the arms horizontally forward/backward and waist joint to move them vertically up/down. The robotic hand, which has two fingers and a thumb, is also optimally designed in task-based concept. Finally, the good performance of the developed McBot II is confirmed through live tests of the mess-cleanup task.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3370-3392
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• 2017

Next Generation Beyond 4G/5G systems will rely on the deployment of small cells over conventional macrocells for achieving high spectral efficiency and improved coverage performance, especially for indoor and hotspot environments. In such heterogeneous networks, the expected performance gains can only be derived with the use of efficient interference coordination schemes, such as Fractional Frequency Reuse (FFR), which is very attractive for its simplicity and effectiveness. In this work, femtocells are deployed according to a spatial Poisson Point Process (PPP) over hexagonally shaped, 6-sector macro base stations (MeNBs) in an uncoordinated manner, operating in hybrid mode. A newly introduced intermediary region prevents cross-tier, cross-boundary interference and improves user equipment (UE) performance at the boundary of cell center and cell edge. With tools of stochastic geometry, an analytical framework for the signal-to-interference-plus-noise-ratio (SINR) distribution is developed to evaluate the performance of all UEs in different spatial locations, with consideration to both co-tier and cross-tier interference. Using the SINR distribution framework, average network throughput per tier is derived together with a newly proposed harmonic mean, which ensures fairness in resource allocation amongst all UEs. Finally, the FFR network parameters are optimized for maximizing average network throughput, and the harmonic mean using a fair resource assignment constraint. Numerical results verify the proposed analytical framework, and provide insights into design trade-offs between maximizing throughput and user fairness by appropriately adjusting the spatial partitioning thresholds, the spectrum allocation factor, and the femtocell density.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.444-453
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• 2007

This paper deals with a powerful countermeasure for power quality problems caused by the operation of electrical arc furnace in bulk power systems. The rapid active load fluctuations of electrical arc furnace could produce several problems such as voltage flicker and active power oscillations. The typical methods using only the reactive power compensation have their own limitation in solving the power quality problems caused by active load variations. The coordination of both active and reactive power compensation is required to solve the power quality problems. This paper focuses on the impacts and the dynamic phenomena caused by the active load fluctuation. This paper proposes the optimal algorithm for the active power compensation based on the function of 1(n ratio and the concepts for the active power compensation. The results from a case study show that the proposed methods can be a practical tool for the power quality problems in power systems.

• Journal of Communications and Networks
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• v.11 no.5
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• pp.518-528
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• 2009

IEEE 802.11 wireless local area network (WLAN) has become the prevailing solution for wireless Internet access while transport control protocol (TCP) is the dominant transport-layer protocol in the Internet. It is known that, in an infrastructure-based WLAN with multiple stations carrying long-lived TCP flows, the number of TCP stations that are actively contending to access the wireless channel remains very small. Hence, the aggregate TCP throughput is basically independent of the total number of TCP stations. This phenomenon is due to the closed-loop nature of TCP flow control and the bottleneck downlink (i.e., access point-to-station) transmissions in infrastructure-based WLANs. In this paper, we develop a comprehensive analytical model to study TCP dynamics in infrastructure-based 802.11 WLANs. We calculate the average number of active TCP stations and the aggregate TCP throughput using our model for given total number of TCP stations and the maximum TCP receive window size. We find out that the default minimum contention window sizes specified in the standards (i.e., 31 and 15 for 802.11b and 802.11a, respectively) are not optimal in terms of TCP throughput maximization. Via ns-2 simulation, we verify the correctness of our analytical model and study the effects of some of the simplifying assumptions employed in the model. Simulation results show that our model is reasonably accurate, particularly when the wireline delay is small and/or the packet loss rate is low.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.105-111
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• 2017

Vendor Managed Inventory is a well-known vendor-retailer coordination approach in supply chain management where the vendor manages inventory of the retailer and determines the order interval and order quantity for the retailer. To consider practical situation, the upper limit of inventory for the retailer is set. If the inventory level for the retailer exceeds the upper limit, then the penalty cost is charged to the retailer. Furthermore, maximum allowable inventory level is set for the vendor to prevent the vendor from keeping much inventory. Single-vendor multi-retailer supply chain model with upper limit of inventory for vendor and retailers is studied. All the retailers' are assumed to have the common cycle time, and a vendor manages retailers' inventory and replenishes products. The mathematical formulation is introduced to minimize the total cost including the penalty cost violating the upper limit of inventory for retailers with the constraint of maximum allowable inventory level. The solution procedure based on Karush-Kuhn-Tucker (KKT) conditions is derived. KKT conditions are often applied to find an optimal solution of nonlinear programming problem with constraints. An illustrative example is used to show the application of the proposed solution procedure. Furthermore, sensitivity analysis is done to find out the relationship between maximum allowable inventory level and other values such as order quantity, the number of shipment, vendor's cost, retailer's cost, and total cost. As maximum allowable inventory level decreases, the number of shipment decreases but total cost increases. Order quantity has the trend of decline and is affected by the number of shipment.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.35-41
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• 2018

The Q-learning algorithm based on reinforcement learning is useful for learning the goal for one behavior at a time, using a combination of discrete states and actions. In order to learn multiple actions, applying a behavior-based architecture and using an appropriate behavior adjustment method can make a robot perform fast and reliable actions. Q-learning is a popular reinforcement learning method, and is used much for robot learning for its characteristics which are simple, convergent and little affected by the training environment (off-policy). In this paper, Q-learning algorithm is applied to a lamp robot to learn multiple behaviors (human recognition, desk object recognition). As the learning rate of Q-learning may affect the performance of the robot at the learning stage of multiple behaviors, we present the optimal multiple behaviors learning model by changing learning rate.

• Journal of Ginseng Research
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• v.39 no.4
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• pp.345-353
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• 2015

Background: Ginseng is a semishade perennial plant cultivated in sloping, sun-shaded areas in Korea. Recently, owing to air-environmental stress and various fungal diseases, greenhouse cultivation has been suggested as an alternative. However, the optimal light transmission rate (LTR) in the greenhouse has not been established. Methods: The effect of LTR on photosynthesis rate, growth, and ginsenoside content of ginseng was examined by growing ginseng at the greenhouse under 6%, 9%, 13%, and 17% of LTR. Results: The light-saturated net photosynthesis rate ($A_{sat}$) and stomatal conductance ($g_{s}$) of ginseng increased until the LTR reached 17% in the early stage of growth, whereas they dropped sharply owing to excessive leaf chlorosis at 17% LTR during the hottest summer period in August. Overall, 6-17% of LTR had no effect on the aerial part of plant length or diameter, whereas 17% and 13% of LRT induced the largest leaf area and the highest root weight, respectively. The total ginsenoside content of the ginseng leaves increased as the LTR increased, and the overall content of protopanaxatriol line ginsenosides was higher than that of protopanaxadiol line ginsenosides. The ginsenoside content of the ginseng roots also increased as the LTR increased, and the total ginsenoside content of ginseng grown at 17% LTR increased by 49.7% and 68.3% more than the ginseng grown at 6% LTR in August and final harvest, respectively. Conclusion: These results indicate that 13-17% of LTR should be recommended for greenhouse cultivation of ginseng.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3862-3888
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• 2017

In high diversity node situation, single-channel MAC protocols suffer from many collisions. To solve this problem, the research of multichannel MAC protocol has become a hotspot. And the cyclic quorum-based multichannel (CQM) MAC protocol outperformed others owing to its high frequency utilization. In addition, it can avoid the bottleneck that others suffered from and can be easily realized with only one transceiver. To obtain the accurate performance of CQM MAC protocol, a Markov chain model, which combines the channel hopping strategy of CQM protocol and IEEE 802.11 distributed coordination function (DCF), is proposed. The metrics (throughput and average packet transmission delay) are calculated in performance analysis, with respect to node number, packet rate, channel slot length and channel number. The results of numerical analysis show that the optimal performance of CQM protocol can be obtained in saturation bound situation. And then we obtain the saturation bound of CQM system by bird swarm algorithm (BSA). Finally, the Markov chain model and saturation bound are verified by Qualnet platform. And the simulation results show that the analytic and simulation results match very well.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.2
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• pp.75-86
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• 2002

The selection of the optimal checkpointing interval has been a very critical issue to implement a checkpointing recovery scheme for the fault tolerant distributed system. This paper presents a new scheme that allows a process to select the proper checkpointing interval dynamically. A process in the system evaluates the cost of checkpointing and possible rollback for each checkpointing interval and selects the proper time interval for the next checkpointing Unlike the other scheme, the overhead incurred by both of the checkpointing and rollback activities are considered for the cost evaluation and current communication pattern is reflected in the selection of the checkpointing interval. Moreover, the proposed scheme requires no extra message communication for the checkpointing interval selection and can easily be incorporated into the existing checkpointing coordination schemes.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.85-90
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• 2019

This paper is a study on IoT based map inside the building and fire perception system using microprocessor and LABVIEW program. The smart control system implemented in this paper is designed to identify the location of fire by using microprocessor, flame detection sensor, carbon monoxide sensor and temperature sensor, and to guide the optimal travel route through Zigbee communication. And the proposed system uses QR code to interoperate with smartphone. The coordinator control verified that the sensor value of the smart control system installed through the LABVIEW software was confirmed. The IoT based control system studied in this paper was implemented with Arduino mega board and LABVIEW software, and the operation status was confirmed by display device and coordination.