• International Journal of Highway Engineering
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• v.10 no.1
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• pp.155-164
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• 2008

It is critical to develop a core ITS technology such as real-time travel time estimation in order that the efficient use of the ITS implementation can be achieved as the ITS infrastructure and relevant facilities are broadly installed in recent years. The provision of travel time information in real-time allows travellers to make informed decisions and hence not only the traveller's travel utilities but also the road utilization can be maximized. In this paper, a hybrid model is proposed to combine VDS and AVI which have different characteristics in terms of space and time dimensions. The proposed model can incorporate the immediacy of VDS data and the reality of AVI data into one single framework simultaneously. In addition, the solution algorithm is made to have no significant computational burden so that the model can be deployable in real world. A set of real field data is used to analyze the reliability and applicability of the proposed model. The analysis results suggest that the proposed model is very efficient computationally and improves the accuracy of the information provided, which demonstrates the real-time applicability of the proposed model. In particular, the data fusion methodology developed in this paper is expected to be used more widely when a new type of traffic data becomes available.

• Journal of Satellite, Information and Communications
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• v.6 no.1
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• pp.80-85
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• 2011

In this paper, a software-based real-time GPS L1 receiver is proposed for the block correlation techniques. Recently various navigation satellite navigation receivers in the environment for the development of more efficient software-based real-time receiver need to be developed. It is composed of components such as signal supplier, signal acquisition, signal tracking, navigation data processing, and navigation solution. They are designed and implemented as component based software for enhancing reusability and modifiability for user to have more flexibility during development of receiver. This paper will describe design, implementation, and verification of the developed realtime software GNSS receiver.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.1
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• pp.67-76
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• 2003

Recently consideration of health and interest on bio aerosols have been growing steadily. In this study, inertial impactor, which can be used to collect airborne particles and bio aerosols, was newly devised for real-time observation on the particles collected on impaction plate. and named Visual Impactor. Flow field and particle trajectory in the space between nozzle and impaction plate was analyzed numerically, and the collection effciencies were calculated. Calibration and performance evaluation of the Visual Impactor was conducted with polydisperse aerosols generated from 0.1％ sodium chloride solution. Cut-off diameter from numerical simulation was in good agreement with that from experimental results. Because of particle bounce and particle deposition on nozzle tip due to short jet-to-plate distance, the collection efficiencies from numerical and experimental analyses were different slightly. Visual Impactor was used to collect airborne particles, and the features of collected particles could be seen in real-time. Airborne particles in different weather conditions (fine, cloudy, and rainy) were sampled and compared one another The features of collected airborne particles were dependent strongly upon relative humidity. In addition, with hours elapsing, shapes and colors of collected particles were changed by evaporation and surface tension, etc.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.16-22
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• 2019

After Dantzig and Rasmer introduced Vehicle Routing Problem in 1959, this field has been studied with numerous approaches so far. Classical Vehicle Routing Problem can be described as a problem of multiple number of homogeneous vehicles sharing a same starting node and having their own routes to meet the needs of demand nodes. After satisfying all the needs, they go back to the starting node. In order to apply the real world problem, this problem had been developed with additional constraints and pick up & delivery model is one of them. To enhance the effectiveness of pick up & delivery, hub became a popular concept, which often helps reducing the overall cost and improving the quality of service. Lots of studies have suggested heuristic methods to realize this problem because it often becomes a NP-hard problem. However, because of this characteristic, there are not many studies solving this problem optimally. If the problem can be solved in polynomial time, optimal solution is the best option. Therefore, this study proposes a new mathematical model to solve this problem optimally, verified by a real world problem. The main improvements of this study compared to real world case are firstly, make drivers visit every nodes once except hub, secondly, make drivers visit every nodes at the right time, and thirdly, make drivers start and end their journey at their own homes.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.263-269
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• 2015

This paper proposes a new approach for solving the weather routing problem by dividing it into two phases with the goal of fuel saving. The problem is to decide two optimal variables: the heading angle and speed of the ship under several constraints. In the first phase, the optimal route is obtained using the Real-Time Adaptive A* algorithm with a fixed ship speed. In other words, only the heading angle is decided. The second phase is the speed scheduling phase. In this phase, the original problem, which is a nonlinear optimization problem, is converted into a geometric programming problem. By solving this geometric programming problem, which is a convex optimization problem, we can obtain an optimal speed scheduling solution very efficiently. A simple case of numerical simulation is conducted in order to validate the proposed method, and the results show that the proposed method can save fuel compared to a constant engine output voyage and constant speed voyage.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.224-230
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• 2015

This manuscript presents a real-time solution for 3D human body reconstruction with multiple RGB-D cameras. The proposed system uses four consumer RGB/Depth (RGB-D) cameras, each located at approximately $90^{\circ}$ from the next camera around a freely moving human body. A single mesh is constructed from the captured point clouds by iteratively removing the estimated overlapping regions from the boundary. A cell-based mesh construction algorithm is developed, recovering the 3D shape from various conditions, considering the direction of the camera and the mesh boundary. The proposed algorithm also allows problematic holes and/or occluded regions to be recovered from another view. Finally, calibrated RGB data is merged with the constructed mesh so it can be viewed from an arbitrary direction. The proposed algorithm is implemented with general-purpose computation on graphics processing unit (GPGPU) for real-time processing owing to its suitability for parallel processing.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2369-2373
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• 2001

Usually the static scheduling algorithms such as DMS (Deadline Monotonic Scheduling) or RMS(Rate Monotonic Scheduling) are used for CAN scheduling due to its ease with implementation. However, due to their inherently low utilization of network media, some dynamic scheduling approaches have been studied to enhance the utilization. In case of dynamic scheduling algorithms, two considerations are needed. The one is a priority inversion due to rough deadline encoding into stricted arbitration fields of CAN. The other is an arbitration delay due to the non-preemptive feature of CAN. In this paper, an extended algorithm is proposed from an existing EDS(Earliest Deadline Scheduling) approach of CAN scheduling algorithm haying a solution to the priority inversion. In the proposed algorithm, the available bandwidth of network media can be checked dynamically by all nodes. Through the algorithm, arbitration delay causing the miss of their deadline can be avoided in advance. Also non real-time messages can be processed with their bandwidth allocation. The proposed algorithm can achieve full network utilization and enhance aperiodic responsiveness, still guaranteeing the transmission of periodic messages.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.366-373
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• 2019

The development of monitoring and analysis systems to increase productivity while saving energy is needed as a method to reduce huge amount of energy consumed in the process of producing large forged products. In this paper, we propose a system to monitor and analyze energy usage in real-time collected from gas-meter, wattmeter, and thermometer based on IoT installed in forging factories. The system consists of a data collection server for collecting and processing data from IoT- based platform and existing SCADA equipment and ERP/MES system in forging factories, and an application server for providing services to users. To develop the system, the overall system structure is logically diagrammed, and the databases configuration and implementation modules to efficiently store and manage data are presented. In the future, the system will be utilized to reduce energy consumption by analyzing energy usage pattern and optimizing process works with real-time energy usage and production process data for each facility.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• Geomechanics and Engineering
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• v.34 no.3
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• pp.329-339
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• 2023

The objective of this study is to develop a Stability Evaluation System for retaining walls to assess their safety in real-time during excavation. A ground investigation is typically conducted before construction to gather information about the soil properties and predict wall stability. However, these properties may not accurately reflect the actual ground being excavated. To address this issue, the study employed a differential evolution algorithm to estimate the soil parameters of the actual ground. The estimated results were then used as input for an artificial neural network to evaluate the stability of the retaining walls. The study achieved an average accuracy of over 90% in predicting differential settlement, wall displacement, anchor force, and structural stability of the retaining walls. If implemented at actual excavation sites, this approach would enable real-time prediction of wall stability and facilitate effective safety management. Overall, the developed Stability Evaluation System offers a promising solution for ensuring the stability of retaining walls during construction. By incorporating real-time soil parameter analysis, it enhances the accuracy of stability predictions and contributes to proactive safety management in excavation projects.