• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.369-375
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• 2008

To achieve zero-emission, one of the main goals of an eco-industrial park (EIP), it is needed to develop an effective water exchange network. The network includes various subsystems and decision making processes, which make the modeling process extremely complicated. Agent-based modeling was used to simulate water exchange network in an EIP. Firm agents were created based on the behavior pattern of firms, and an agent-based model (ABM) was made with the agents, showing the growth of the exchange network. An existing steel and iron making industrial park was chosen as a case study, and the ABM model shows eco-efficient behavior with a decreased environmental cost. Water reuse network based on the ABM model results in 35% decrease of the fresh water supply and 50% reduction of the wastewater generation in EIP. A case study shows that agent-based model can be a powerful tool in modeling and designing complex eco-industrial parks, especially when a part of the system needs to be changed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.49-57
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• 2010

We extended a general attack tree to apply cyber attack model for network vulnerability analysis. We defined an extended cyber attack tree (E-CAT) which extends the general attack tree by associating each node of the tree with a transition of attack that could have contributed to the cyber attack. The E-CAT resolved the limitation that a general attack tree can not express complex and sophisticate attacks. Firstly, the Boolean expression can simply express attack scenario with symbols and codes. Secondary, An Attack Generation Probability is used to select attack method in an attack tree. A CONDITION-composition can express new and modified attack transition which a aeneral attack tree can not express. The E-CAT is possible to have attack's flexibility and improve attack success rate when it is applied to cyber attack model.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.8
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• pp.49-58
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• 2016

In designing heterogeneous architecture based application-specific network-on-chips (NoCs), the opportunities of performance improvement would be expanded when applying asynchronous on-chip communication protocol. This is because the wire latency can be configured independently considering the wirelength of each link. In this paper, we develop the delay model of link-wire-length in asynchronous NoC and propose simulated annealing (SA) based floorplan-aware topology generation algorithm to optimize link-wirelengths. Incorporating the generated topology and the associated latency values across all links, we evaluate the performance using the floorplan-annotated sdf (standard delay format) file and RTL-synthesized gate-level netlist. Compared to TopGen, one of general topology generation algorithms, the experimental results show the reduction in latency by 13.7% and in execution time by 11.8% in average with regards to four applications.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.884-892
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• 2014

In this paper, a meta model using neural network substituting for the simulator aerodynamic database is proposed to improve simulation fidelity near the critical flight area and real-time performance. It is shown that the accuracy of the meta model is relatively higher than the existing table lookup methods for arbitrary nonlinear database and the calculation speed is also improved for a specific F-16 maneuver simulation. The increase in the number of hidden nodes in the meta model for better accuracy of database representations causes a delay in function generation due to increased time required for computing exponential functions. In order to make up this drawback, we additionally study the fast exponential function method.

• Smart Media Journal
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• v.10 no.1
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• pp.63-69
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• 2021

When a person sees a sentence and understands the sentence, the person understands the sentence by reminiscent of the main word in the sentence as an image. Text-to-image is what allows computers to do this associative process. The previous deep learning-based text-to-image model extracts text features using Convolutional Neural Network (CNN)-Long Short Term Memory (LSTM) and bi-directional LSTM, and generates an image by inputting it to the GAN. The previous text-to-image model uses basic embedding in text feature extraction, and it takes a long time to train because images are generated using several modules. Therefore, in this research, we propose a method of extracting features by using the attention mechanism, which has improved performance in the natural language processing field, for sentence embedding, and generating an image by inputting the extracted features into the GAN. As a result of the experiment, the inception score was higher than that of the model used in the previous study, and when judged with the naked eye, an image that expresses the features well in the input sentence was created. In addition, even when a long sentence is input, an image that expresses the sentence well was created.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.291-299
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• 2005

An obstacle avoidance algorithm for a network-based autonomous mobile robot is proposed in this paper. The obstacle avoidance algorithm is based on the VFH(Vector Field Histogram) algorithm and two delay compensation methods with the VFH algorithm are proposed for a network-based robot with distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the environmental sensor information is compensated by prospection with acquired environmental sensor information, measured network delays, and the kinematic model of the robot. The compensated environmental sensor information is used for building polar histogram with the VFH algorithm. Secondly, a sensor fusion algorithm for localization of the robot is proposed to compensate the delay of odometry sensor information and the delay of environmental sensor information. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal positioning is shown here.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4293-4304
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• 2014

In order to ensure the wireless connectivity and seamless service to mobile users, the next generation network system will be an integration of multiple wireless access networks. In a heterogeneous wireless access system, bandwidth allocation becomes crucial for load balancing to avoid network congestion and improve system utilization efficiency. In this article, we propose a new dynamic bandwidth allocation scheme for hierarchical wireless network systems. First, we derive a multi-objective decision criterion for each access point. Second, a bargaining strategy selection algorithm is developed for the dynamic bandwidth re-allocation. Based on the intervenient Stackelberg game model, the proposed scheme effectively formulates the competitive interaction situation between several access points. The system performance of proposed scheme is evaluated by using extensive simulations. With a simulation study, it is confirmed that the proposed scheme can achieve better performance than other existing schemes under widely diverse network environments.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.56-69
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• 2000

A frequency assignment problem on time division duplex system is considered. Republic of Korea Army (ROKA) has been establishing an infrastructure of tactical communication (SPIDER) system for next generation and it will be a core network structure of system. VHF system is the backbone network of SPIDER, that performs transmission of data such as voice, text and images. So, it is a significant problem finding the frequency assignment with no interference under very restricted resource environment. With a given arbitrary configuration of communications network, we find a feasible solution that guarantees communication without interference between sites and relay stations. We formulate a frequency assignment problem as an Integer Programming model, which has NP-hard complexity. To find the assignment results within a reasonable time, we take a genetic algorithm approach which represents the solution structure with available frequency order, and develop a genetic operation strategies. Computational result shows that the network configuration of SPIDER can be solved efficiently within a very short time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3383-3397
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• 2023

Scene graphs serve as semantic abstractions of images and play a crucial role in enhancing visual comprehension and reasoning. However, the performance of Scene Graph Generation is often compromised when working with biased data in real-world situations. While many existing systems focus on a single stage of learning for both feature extraction and classification, some employ Class-Balancing strategies, such as Re-weighting, Data Resampling, and Transfer Learning from head to tail. In this paper, we propose a novel approach that decouples the feature extraction and classification phases of the scene graph generation process. For feature extraction, we leverage a transformer-based architecture and design an adaptive calibration function specifically for predicate classification. This function enables us to dynamically adjust the classification scores for each predicate category. Additionally, we introduce a Distribution Alignment technique that effectively balances the class distribution after the feature extraction phase reaches a stable state, thereby facilitating the retraining of the classification head. Importantly, our Distribution Alignment strategy is model-independent and does not require additional supervision, making it applicable to a wide range of SGG models. Using the scene graph diagnostic toolkit on Visual Genome and several popular models, we achieved significant improvements over the previous state-of-the-art methods with our model. Compared to the TDE model, our model improved mR@100 by 70.5% for PredCls, by 84.0% for SGCls, and by 97.6% for SGDet tasks.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.5
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• pp.43-50
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• 2004

The clock skew is one of the major constraints for high-speed operation of synchronous integrated circuits. In this paper, we propose a hierarchical partitioning based clock network design algorithm called Advanced Clock Tree Generation (ACTG). Especially new effective partitioning and refinement techniques have been developed in which the capacitance and edge length to each sink are considered from the early stage of clock design. Hierarchical structures obtained by parhtioning and refinement are utilized for balanced clock routing. We use zero skew routing in which Elmore delay model is used to estimate the delay. An overlap avoidance routing algorithm for clock tree generation is proposed. Experimental results show significant improvement over conventional methods.