• Journal of Intelligence and Information Systems
• /
• v.13 no.1
• /
• pp.49-58
• /
• 2007

MDPDPTW (Multi-Depot Pickup and Delivery Problem with Time Windows) is a typical model among the optimization models based on the pickup and delivery flow in supply chains. It is based on multi-vehicles in multi-depots and does not consider moving vehicles near pickup and delivery locations. In ubiquitous environments, it is possible to obtain information on moving vehicles and their baggage. Providing the proper context from the perspective of moving vehicles and their baggage allows for more effective vehicle routings. This study proposes Integer Programming-based MDPDPTW including the information on moving vehicles and their baggage in a ubiquitous environment: u-MDPDPTW, and shows the viability and effectiveness of u-MDPDPTW through comparative experiments of MDPDPTW and u-MDPDPTW.

• Journal of the Korea Computer Graphics Society
• /
• v.25 no.2
• /
• pp.19-29
• /
• 2019

We develop a complete system that includes data collection, signal processing, and real-time interaction for effective neurofeedback training. Our system supports a sophisticated technique to find threshold values which are quite important for effective neurofeedback system. A therapist specifies a target success rate of positive feedback, allowable error and time. The system computes a current success rate and compare it with the target one. If the difference between two rates exceeds the allowable error for allowable time, we find an optimum threshold value to obtain the target success rate by using numerical optimization technique. We conduct several experiments by varying input parameters: target success rate, allowable error and time, and demonstrate the effectiveness of our technique by showing the desired target success rate is stably obtained and systematically controlled by input parameters.

• Journal of KIISE:Databases
• /
• v.29 no.1
• /
• pp.79-88
• /
• 2002

Data on the Internet are usually represented and transfered as XML. the XML data is represented as a tree and therefore, object repositories are well-suited to store and query them due to their modeling power. XML queries are represented as regular path expressions and evaluated by traversing each object of the tree in object repositories. Several indexes are proposed to fast evaluate regular path expressions. However, in some cases they may not cover all possible paths because they require a great amount of disk space. In order to efficiently evaluate the queries in such cases, we propose an optimized traversing which combines the signature method and block traversing. The signature approach shrink the search space by using the signature information attached to each object, which hints the existence of a certain label in the sub-tree. The block traversing reduces disk I/O by early evaluating the reachable objects in a page. We conducted diverse experiments to show that the hybrid approach achieves a better performance than the other naive ones.

• The Korean Journal of Applied Statistics
• /
• v.18 no.2
• /
• pp.421-434
• /
• 2005

Machine learning has been extensively studied in recent years as effective tools in pattern classification problem. Although there have been several approaches to machine learning, we focus on the mathematical programming (in particular, multi-objective and goal programming; MOP/GP) approaches in this paper. Among them, Support Vector Machine (SVM) is gaining much popularity recently. In pattern classification problem with two class sets, the idea is to find a maximal margin separating hyperplane which gives the greatest separation between the classes in a high dimensional feature space. However, the idea of maximal margin separation is not quite new: in 1960's the multi-surface method (MSM) was suggested by Mangasarian. In 1980's, linear classifiers using goal programming were developed extensively. This paper proposes a new family of SVM using MOP/GP techniques, and discusses its effectiveness throughout several numerical experiments.

• KSBB Journal
• /
• v.15 no.2
• /
• pp.181-187
• /
• 2000

The production of heterologous protein using GAL promoter in conventional S. cerevisiae has several problems to s이ve for c commercialization. In this research, S. cerevisiae mutant(reg1-501, gaI1), which cannot use galactose and has alleviated g glucose repression level, is used as host for optimizing induction of GAL promoter. In this experiment, the effects of specific g growth rate on specific recombinant protein expression rate were tested in both cases and optimum fed batch fermentation m method was obtained in both cases. Through these experiments, optimum condition of recombinant protein production by G GAL promoter using S. cerevisiae mutant (reg1-501, gal1) were found.

• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.5
• /
• pp.527-531
• /
• 2008

For statistical modeling, the model parameters are usually estimated by maximizing a probability measure, such as the likelihood or the posterior. In contrast, a variational Bayesian method treats the parameters of a model as probability distributions and computes optimal distributions for them rather than values. It has been shown that this approach effectively avoids the overfitting problem, which is common with other parameter optimization methods. This paper applies a variational Bayesian technique to surface fitting for height field data. Then, we propose point cloud denoising based on the basic surface fitting technique. Validation experiments and further tests with scan data verify the robustness of the proposed method.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.3
• /
• pp.130-139
• /
• 2024

Artificial intelligence models are being used to detect facility anomalies using physics data such as vibration, current, and temperature for predictive maintenance in the manufacturing industry. Since the types of facility anomalies, such as facility defects and failures, anomaly detection methods using autoencoder-based unsupervised learning models have been mainly applied. Normal or abnormal facility conditions can be effectively classified using the reconstruction error of the autoencoder, but there is a limit to identifying facility anomalies specifically. When facility anomalies such as unbalance, misalignment, and looseness occur, the facility vibration frequency shows a pattern different from the normal state in a specific frequency range. This paper presents an N-segmentation anomaly detection method that performs anomaly detection by dividing the entire vibration frequency range into N regions. Experiments on nine kinds of anomaly data with different frequencies and amplitudes using vibration data from a compressor showed better performance when N-segmentation was applied. The proposed method helps materialize them after detecting facility anomalies.

• Journal of the Korea Computer Graphics Society
• /
• v.14 no.3
• /
• pp.1-9
• /
• 2008

This paper presents a novel optimization-based saliency-preserving method for converting color images to grayscale in a manner consistent with conventional approaches of black-and-white photographers. In black-and-white photography, a colored filter called a contrast filter has been commonly employed on a camera to lighten or darken selected colors. In addition, local exposure controls such as dodging and burning techniques are typically employed in the darkroom process to change the exposure of local areas within the print without affecting the overall exposure. Our method seeks a digital version of a conventional contrast filter to preserve visually-important image features. Furthermore, conventional burning and dodging techniques are addressed, together with image similarity weights, to give edge-aware local exposure control over the image space. Our method can be efficiently optimized on GPU. According to the experiments, CUDA implementation enables 1 megapixel color images to be converted to grayscale at interactive frames rates.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.5
• /
• pp.231-242
• /
• 2016

In order to meet rapid changes of Web information, it is necessary to extend the current Web technologies to represent both the valid time and location of each fact and knowledge, and reason their relationships. Until recently, many researches on qualitative temporal reasoning have been conducted in laboratory-scale, dealing with small knowledge bases. However, in this paper, we propose the design and implementation of a parallel qualitative temporal reasoner, MRQUTER, which can make reasoning over Web-scale large knowledge bases. This parallel temporal reasoner was built on a Hadoop cluster system using the MapReduce parallel programming framework. It decomposes the entire qualitative temporal reasoning process into several MapReduce jobs such as the encoding and decoding job, the inverse and equal reasoning job, the transitive reasoning job, the refining job, and applies some optimization techniques into each component reasoning job implemented with a pair of Map and Reduce functions. Through experiments using large benchmarking temporal knowledge bases, MRQUTER shows high reasoning performance and scalability.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.12
• /
• pp.702-708
• /
• 2020

Recently, as LED display systems have become larger, research on effective power control methods for the systems has been in progress. This paper proposes a power control method to minimize power loss due to the difference in LED characteristics for each channel of a backlight unit (BLU) system. The proposed LED driver IC has a power optimization function and detects the minimum headroom voltage for constant current operation of all channels and linearly controls the DC-DC converter output. Thus, it minimizes power consumption due to unnecessary additional voltage. In addition, it does not require a voltage sensing comparator or a voltage generation circuit for each channel. This has a great advantage in reducing the chip size and for stabilization when implementing an integrated circuit. In order to verify the proposed function, an IC was designed using Cadence and Synopsys' design tools, and it was fabricated with a Magnachip 0.35um 5V/40V CMOS process. The experiments confirmed that the proposed power control method controls the minimum required voltage of the BLU system.