• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.1722-1729
• /
• 2011

This paper presents an optimization model for revising train timetable based on an existing timetable to improve transfer time at each station. The transfer time consists of walking and waiting time. The model is formulated as a mixed integer programming. The objective function is to minimize the transfer time from one train to another train at each station. To reflect real situations, range of revising departure time is considered as major condition in the model. To validate the effectiveness of the model, rudimentary computational results are included, and the results are analyzed in terms of transfer time.

• Journal of the Korea Computer Industry Society
• /
• v.7 no.5
• /
• pp.513-520
• /
• 2006

In this paper, we propose a novel real-time frame-layer rate control algorithm using sliding window method for low bit rate video coding. The proposed rate control method performs bit allocation at the frame level to minimize the average distortion over an entire sequence as well as variations in distortion between frames. A new frame-layer rate-distortion model is derived, and a non-iterative optimization method is used for low computational complexity. In order to reduce the quality fluctuation, we use a sliding window scheme which does not require the pre-analysis process. Therefore, the proposed algorithm does not produce time delay from encoding, and is suitable for real-time low-complexity video encoder. Experimental results indicate that the proposed control method provides better visual and PSNR performance than the existing TMN8 rate control method.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.32 no.3
• /
• pp.47-55
• /
• 1990

An adaptive algorithm was applied to forecast daily stream flows in real time using rainfall data. A three-component tank model was selected to simulate the flows and its time-variant parameters were self-calibrated with updated data using a parameter optimization scheme, golden section search method. The resulting adaptive model, APTANK, was applied to six watersheds, ranging from 0.47 to 33.62 km$^2$ size and the simulated daily streamflows were compared with the measured. The simulation results were in good agreement with the field data. APTANK is found to be applied to real-time flow simulation purposes such as a tool for irrigation water resources management and operations. The model is particularly good to simulate streamflows on dry days as compared to wet days having runoff-induced precipitation.

• Current Optics and Photonics
• /
• v.7 no.1
• /
• pp.33-37
• /
• 2023

Real-time adaptive control of laser output polarization is presented in a 10-W-level non-polarization-maintaining (non-PM) fiber amplifier. While the output polarization from a non-PM fiber amplifier tends to be irregular, depending on output power, time, and perturbation, closed-loop polarization control can maintain the polarization extinction ratio at higher than 20 dB. Real-time polarization control can attain the target linear polarization mostly within 1.4-25 ms and shows stability against external perturbations. This approach can satisfy both linear polarization and high output power in a non-PM amplifier, and facilitates optimization of laser performance and maintenance-free operation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.6
• /
• pp.2060-2073
• /
• 2022

Cloud Computing permits users to access vast amounts of services of computing power in a virtualized environment. Providing secure services is essential. There are several problems to real-world optimization that are dynamic which means they tend to change over time. For these types of issues, the goal is not always to identify one optimum but to keep continuously adapting to the solution according to the change in the environment. The problem of scheduling in Cloud where new tasks keep coming over time is unique in terms of dynamic optimization problems. Until now, there has been a large majority of research made on the application of various Evolutionary Algorithms (EAs) to address the issues of dynamic optimization, with the focus on the maintenance of population diversity to ensure the flexibility for adapting to the changes in the environment. Generally, trust refers to the confidence or assurance in a set of entities that assure the security of data. In this work, a dynamic optimization technique is proposed to find an optimal trust weights in cloud during scheduling.

• Journal of Korean Society on Water Environment
• /
• v.22 no.2
• /
• pp.193-202
• /
• 2006

About 99% of microorganisms in the environment are unculturable. However, advances in molecular biology techniques allow for the analysis of living microorganisms in the environment without any cultivation. With the advent of new technologies and the optimization of previous methods, various approaches to studying the analysis of living microorganisms in the environment are expanding the field of microbiology and molecular biology. In particular, real-time PCR provides methods for detecting and quantifying microorganisms in the environment. Through the use of the methods, researchers can study the influence of environmental factors such as nutrients, oxygen status, pH, pollutants, agro-chemicals, moisture and temperature on the performances of environmental processes and some of the mechanisms involved in the responses of cells to their environment. This review will also address information gaps in the analysis of the microorganisms using real-time PCR in the environmental process and possible future research to develop an understanding of microbial activities in the environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.10
• /
• pp.4117-4135
• /
• 2020

Due to the angle of view, illumination and scene diversity, real-time dynamic face detection and recognition is no small difficulty in those unrestricted environments. In this study, we used the intrinsic correlation between detection and calibration, using a multi-task cascaded convolutional neural network(MTCNN) to improve the efficiency of face recognition, and the output of each core network is mapped in parallel to a compact Euclidean space, where distance represents the similarity of facial features, so that the target face can be identified as quickly as possible, without waiting for all network iteration calculations to complete the recognition results. And after the angle of the target face and the illumination change, the correlation between the recognition results can be well obtained. In the actual application scenario, we use a multi-camera real-time monitoring system to perform face matching and recognition using successive frames acquired from different angles. The effectiveness of the method was verified by several real-time monitoring experiments, and good results were obtained.

• Journal of Biomedical Engineering Research
• /
• v.28 no.2
• /
• pp.294-299
• /
• 2007

For efficient and accurate diagnosis of ultrasound images, appropriate time gain compensation(TGC) and dynamic range(DR) control of ultrasound echo signals are important. TGC is used for compensating the attenuation of ultrasound echo signals along the depth, and DR controls the image contrast. In recent ultrasound systems, these two factors are automatically set by a system and/or manually adjusted by an operator to obtain the desired image quality on the screen. In this paper, we propose an algorithm to find the optimized parameter values far TGC and DR automatically. In TGC optimization, we determine the degree of attenuation compensation along the depth by dividing an image into vertical strips and reliably estimating the attenuation characteristic of ultrasound signals. For DR optimization, we define a novel cost function by properly using the characteristics of ultrasound images. We obtain experimental results by applying the proposed algorithm to a real ultrasound(US) imaging system. The results verify that the proposed algorithm automatically sets values of TGC and DR in real-time such that the subjective quality of the enhanced ultrasound images may be sufficiently high for efficient and accurate diagnosis.

• Smart Media Journal
• /
• v.7 no.2
• /
• pp.40-46
• /
• 2018

The conventional CCTV surveillance system for preventing accidents and incidents misses 95% of the data after 22 minutes where one person monitors multiple CCTV. To address this issue, researchers have studied the computer-based intelligent video surveillance system for notifying people of the abnormal situation. However, because the system is involved in the problems of power consumption and costs, the intelligent video surveillance system based on embedded modules has been studied. This paper implements the intelligent video surveillance system based on embedded modules for detecting intruders, detecting fires and detecting loitering, falling. Moreover, the algorithm and the embedded module optimization method are applied to implement real-time processing. The intelligent video surveillance system based on embedded modules is implemented in Raspberry Pi. The algorithm processing time is 0.95 seconds on Raspberry Pi before optimization, and 0.47 seconds on Raspberry Pi after optimization, reduced processing time by 50.52%. Therefore, this suggests real processing possibility of the intelligent video surveillance system based on the embedded modules is possible.

• Proceedings of the KSME Conference
• /
• 2003.04a
• /
• pp.1262-1269
• /
• 2003

In structural optimization, static loads are generally utilized although real external forces are dynamic. Dynamic loads have been considered in only small-scale problems. Recently, an algorithm for dynamic response optimization using transformation of dynamic loads into equivalent static loads has been proposed. The transformation is conducted to match the displacement fields from dynamic and static analyses. The algorithm can be applied to large-scale problems. However, the application has been limited to size optimization. The present study applies the algorithm to shape optimization. Because the number of degrees of freedom of finite element models is usually very large in shape optimization, it is difficult to conduct dynamic response optimization with the conventional methods that directly threat dynamic response in the time domain. The optimization process is carried out via interfacing an optimization system and an analysis system for structural dynamics. Various examples are solved to verify the algorithm. The results are compared to the results from static loads. It is found that the algorithm using static loads transformed from dynamic loads based on displacement is valid even for very large-scale problems such as shape optimization.