• Journal of KIISE:Software and Applications
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• v.33 no.7
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• pp.624-635
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• 2006

This paper applies simulated annealing algorithm to the problem of generating a plan for intra-block remarshalling with multiple transfer cranes. Intra-block remarshalling refers to the task of rearranging containers scattered around within a block into certain designated target areas of the block so that they can be efficiently loaded onto a ship. In generating a remarshalling plan, the predetermined container loading sequence should be considered carefully to avoid re-handlings that may delay the loading operations. In addition, the required time for the remarshalling operation itself should be minimized. A candidate solution in our search space specifies target locations of the containers to be rearranged. A candidate solution is evaluated by deriving a container moving plan and estimating the time needed to execute the plan using two cranes with minimum interference. Simulation experiments have shown that our method can generate efficient remarshalling plans in various situations.

• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.24-30
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• 2002

Label switching technology is currently emerging as a solution for the rapidly growing of Internet traffic demand. Multiprotocol label switching(MPLS) is one of the standards made by the Internet Engineering Task Force(IETE) intended to enhance speed, scalability, and inter-opearability between label switching technologies. In MPLS, utilization of label space is a very important factor of network performance because labels are basic unit in packet switching. We propose a algorithm to effectively use label space by a multiple disconnect timer at the label switching router. Our algorithm is based on multiple utilization of the connection release timer over the MPLS network with multiple domains. In our algorithm, a relatively linger timeout interval is assigned to the traffic with higher class by the aid of the packet classifier. This reduces delay for making a new connection and also reduces the amount of packets which will be routed to the layer 3. Simulation results shows that reduction of required label number in MPLS network and this indicate our algorithm offers better performance than the existing ones in term of utilization of label space.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.181-193
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• 2009

This paper presents a framework for controlling mobile multiple robots connected by communication networks. This framework provides novel methods to control coordinated systems using mobile agents. The combination of the mobile agent and mobile multiple robots opens a new horizon of efficient use of mobile robot resources. Instead of physical movement of multiple robots, mobile software agents can migrate from one robot to another so that they can minimize energy consumption in aggregation. The imaginary application is making "carts," such as found in large airports, intelligent. Travelers pick up carts at designated points but leave them arbitrary places. It is a considerable task to re-collect them. It is, therefore, desirable that intelligent carts (intelligent robots) draw themselves together automatically. Simple implementation may be making each cart has a designated assembly point, and when they are free, automatically return to those points. It is easy to implement, but some carts have to travel very long way back to their own assembly point, even though it is located close to some other assembly points. It consumes too much unnecessary energy so that the carts have to have expensive batteries. In order to ameliorate the situation, we employ mobile software agents to locate robots scattered in a field, e.g. an airport, and make them autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO). ACO is the swarm intelligence-based methods, and a multi-agent system that exploit artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. In this paper, we focus on the implementation of the controlling mechanism of the multi-robots using the mobile agents.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.120-127
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• 2011

Checkpointing is one of common methods of realizing fault-tolerance for real-time systems. This paper presents a scheme to determine checkpoint intervals using probabilistic optimization. The considered real-time systems comprises multiple tasks in which transient faults can happen with a Poisson distribution. Also, multi-tasks are scheduled by the non-preemptive Rate Monotonic (RM) algorithm. In this paper, we present an optimization problem where the probability of task completion is described by checkpoint numbers. The solution to this problem is the optimal set of checkpoint numbers and intervals that maximize the probability. The probability computation includes schedulability test for the non-preemptive RM algorithm with respect to given numbers of checkpoint re-execution. A case study is given to show the applicability of the proposed scheme.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.7-16
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• 2023

For decades, creating a desired locomotive motion in a goal-oriented manner has been a challenge in character animation. Data-driven methods using generative models have demonstrated efficient ways of predicting long sequences of motions without the need for explicit conditioning. While these methods produce high-quality long-term motions, they can be limited when it comes to synthesizing motion for challenging novel scenarios, such as punching a random target. A state-of-the-art solution to overcome this limitation is by using a GAN Discriminator to imitate motion data clips and incorporating reinforcement learning to compose goal-oriented motions. In this paper, our research aims to create characters performing combat sports such as boxing, using a novel reward design in conjunction with existing GAN-based approaches. We experimentally demonstrate that both the Adversarial Motion Prior [3] and Adversarial Skill Embeddings [4] methods are capable of generating viable motions for a character punching a random target, even in the absence of mocap data that specifically captures the transition between punching and locomotion. Also, with a single learned policy, multiple task controllers can be constructed through the TimeChamber framework.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1098-1104
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• 2015

With the widespread use of smartphones and IoT (Internet of Things), data are being generated on a large scale, and there is increased for the analysis of such data. Hence, distributed processing systems have gained much attention. Hadoop, which is a distributed processing system, saves the metadata of stored files in name nodes; in this case, the main problems are as follows: the memory becomes insufficient; load occurs because of massive small files; scheduling and file processing time increases because of the increased number of small files. In this paper, we propose a solution to address the increase in processing time because of massive small files, and thus improve the processing performance, using the Reuse JVM method provided by Hadoop. Through environment setting, the Reuse JVM method modifies the JVM produced conventionally for every task, so that multiple tasks are reused sequentially in one JVM. As a final outcome, the Reuse JVM method showed the best processing performance when used together with CombineFileInputFormat.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.9
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• pp.495-502
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• 2004

A rapid growth of the Internet user and rich media content cause an excessive server load and high network traffic, and thus it decreases the quality of service. A solution to this problem is to distribute the content on multiple replicated servers. However, in this circumstance, clients face additional task of selecting the best server to provide proper so${\gamma}$vice which clients request. This paper is intended to propose an adaptive server selection mechanism for a client request based on distance and server load. This will offer a fast and scalable service in response to the increase of massive and realtime multimedia content and contribute to floating a new business model of digital content service.

• Journal of Auto-vehicle Safety Association
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• v.16 no.3
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• pp.7-17
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• 2024

Ensuring an automated fallback strategy in response to malfunctions during the execution of the Dynamic Driving Task (DDT) is imperative for Level 4 autonomous driving systems. While Triple Modular Redundancy (TMR) represents a prominent Fail-Operational structure, its practical application to multiple systems is constrained by the substantial increase in costs. In this paper, we propose a pragmatic Fail-Operational safety concept utilizing on-board camera sensors and the Vehicle-to-Infrastructure (V2I) communication module, known as the On-Board Unit (OBU), to provide traffic signal information within the vehicle. The viability of the designed safety concept is validated through error injection simulations. This approach addresses the practical limitations associated with applying Fail-Operational functionality to numerous systems due to the considerable cost escalation. Leveraging camera sensors and V2I communication modules presents a practical and cost-effective solution for maintaining operational safety in Level 4 autonomous driving systems, particularly when responding to malfunctions in the DDT.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.875-881
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• 2014

The redundancy resolution of the seven DOF (Degree of Freedom) upper limb exoskeleton is key to the synchronous motion between a robot and a human user. According to the seven DOF human arm model, positioning and orientating the wrist can be completed by multiple arm configurations that results in the non-unique solution to the inverse kinematics. This paper presents analysis on the kinematic and dynamic aspect of the human arm movement and its effect on the redundancy resolution of the seven DOF human arm model. The redundancy of the arm is expressed mathematically by defining the swivel angle. The final form of swivel angle can be represented as a linear combination of two different swivel angles achieved by optimizing two cost functions based on kinematic and dynamic criteria. The kinematic criterion is to maximize the projection of the longest principal axis of the manipulability ellipsoid of the human arm on the vector connecting the wrist and the virtual target on the head region. The dynamic criterion is to minimize the mechanical work done in the joint space for each of two consecutive points along the task space trajectory. The contribution of each criterion on the redundancy was verified by the post processing of experimental data collected with a motion capture system. Results indicate that the bimodal redundancy resolution approach improved the accuracy of the predicted swivel angle. Statistical testing of the dynamic constraint contribution shows that under moderate speeds and no load, the dynamic component of the human arm is not dominant, and it is enough to resolve the redundancy without dynamic constraint for the realtime application.