• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2212-2214
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• 1998

As there comes out better and better solutions for delivering multimedia data on the internet, the number of WebCAM sites which transmits pictures of any spot to the user's system is getting increased. WebCAM service over the internet can be compared with the CATV in that it is beyond the spatial constraints. In this project, we construct a WebCAM site which performs not only the fundamental WebCAM functions of capturing images and of transmitting them periodically but also various kinds of modules carrying out tasks such as image processing, remote control of the camera, processing multiple user requests, making panorama views and so on using Java which is the most popular language for the internet or CGI. The past images are stored in a database implemented for the WebCAM system, so the system can be extended to get over the constraints in time also.

• Language and Information
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• v.11 no.1
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• pp.77-96
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• 2007

This paper investigates syntactic variations in English such as Dative Alternation, Particle Inversion, and Object Postposition (Heavy NP Shift) within the framework of Optimality Theory, and shows that the same set of morphological, informational, and processing constraints affect all these variations. In particular, it shows that the variants that used to be regarded as ungrammatical are in fact used fairly often in reality, especially when processing or informational conditions are met, and therefore, grammatical judgment may not be always categorical but sometimes gradient. It is argued that the notion of distance in constraint ranking in stochastic OT can effectively explain the gradience and variability of grammaticality in the variation phenomena.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.226-238
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• 2024

Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2679-2691
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• 2012

In this paper, a high accuracy stereo reconstruction method for surgery instruments positioning is proposed. Usually, the problem of surgical instruments reconstruction is considered as a basic task in computer vision to estimate the 3-D position of each marker on a surgery instrument from three pairs of image points. However, the existing methods considered the 3-D reconstruction of the points separately thus ignore the structure information. Meanwhile, the errors from light variation, imaging noise and quantization still affect the reconstruction accuracy. This paper proposes a method which takes the structure information of surgical instruments as constraints, and reconstructs the whole markers on one surgical instrument together. Firstly, we calibrate the instruments before navigation to get the structure parameters. The structure parameters consist of markers' number, distances between each markers and a linearity sign of each instrument. Then, the structure constraints are added to stereo reconstruction. Finally, weighted filter is used to reduce the jitter. Experiments conducted on surgery navigation system showed that our method not only improve accuracy effectively but also reduce the jitter of surgical instrument greatly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1379-1397
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• 2013

We consider a system where a licensed radio spectrum is shared by multiple primary users(PUs) and secondary users(SUs). As the spectrum of interest is licensed to primary network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to PUs. For this system, we study the joint beamforming and power allocation problem via game theory in this paper. The problem is formulated as a non-cooperative beamforming and power allocation game, subject to the interference constraints of PUs as well as the peak transmission power constraints of SUs. We design a joint beamforming and power allocation algorithm for maximizing the total throughput of SUs, which is implemented by alternating iteration of minimum mean square error based decision feedback beamforming and a best response based iterative power allocation algorithm. Simulation results show that the algorithm has better performance than an existing algorithm and can converge to a locally optimal sum utility.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.649-660
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• 1998

Steel making in Mini Mill consists of three major processing stages: molten steel making in an electric arc fuenace, slab casting in a continuous caster, and hot rolling in a finishing mill. Each processing stage has its own lot grouping criterion. However, these criteria in three stages are conflicting with each other. Therefore, delveloping on efficient lot grouping algorithm to enhance the overall productivity of the Mini Mill is an extremely difficult task. The algorithm proposed in this paper is divided into three steps hierarchically: change grouping, cast grouping, and roll grouping. An efficient charge grouping heuristic is developed by exploiting the characteristics of the orders, the processing constraints and the requirements for the downstream stages. In order to maximaize the productivity of the continuous casters, each cast must contain as many charges as possible. Based on the constraint satisfaction problem technique, an efficient cast grouping heuristic is developed. Each roll consists of two casts satisfying the constraints for rolling. The roll grouping problem is formulated as a weighted non-bipartite matching problem, and an optimal roll grouping algorithm is developed. The proposed algorithm is programmed with C language and tested on a SUN Workstation with real data obtained from the H steel works. Through the computational experiment, the algorithm is verified to yield quite satisfactory solutions within a few minutes.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.340-347
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• 2019

Due to advances in machine intelligence and increased demands for autonomous machines, the complexity of the underlying software platform is increasing at a rapid pace, overwhelming the developers with implementation details. We attempt to ease the burden that falls onto the developers by creating a graphical programming framework we named Splash. Splash is designed to provide an effective programming abstraction for autonomous machines that require stream processing. It also enables programmers to specify genuine, end-to-end timing constraints, which the Splash framework automatically monitors for violation. By utilizing the timing constraints, Splash provides three key language semantics: timing semantics, in-order delivery semantics, and rate-controlled data-driven stream processing semantics. These three semantics together collectively serve as a conceptual tool that can hide low-level details from programmers, allowing developers to focus on the main logic of their applications. In this paper, we introduce the three-language semantics in detail and explain their function in association with Splash's language constructs. Furthermore, we present the internal workings of the Splash programming framework and validate its effectiveness via a lane keeping assist system.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.447-450
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• 2011

This paper shows the application of P-N Learning [4] method in the soccer ball detection and improvement for increasing the speed of processing. In the P-N learning, the learning process is guided by positive (P) and negative (N) constraints which restrict the labeling of the unlabeled data, identify examples that have been classified in contradiction with structural constraints and augment the training set with the corrected samples in an iterative process. But for the long-view in the soccer game, P-N learning will produce so many ferns that more time is spent than other methods. We propose that color histogram of each frame is constructed to delete the unnecessary details in order to decreasing the number of feature points. We use the mask to eliminate the gallery region and Line Hough Transform to remove the line and adjust the P-N learning's parameters to optimize accurate and speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4948-4967
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• 2017

On mobile devices, image sequences are widely used for multimedia applications such as computer vision, video enhancement, and augmented reality. However, the real-time processing of mobile devices is still a challenge because of constraints and demands for higher resolution images. Recently, heterogeneous computing methods that utilize both a central processing unit (CPU) and a graphics processing unit (GPU) have been researched to accelerate the image sequence processing. This paper deals with various optimizing techniques such as parallel processing by the CPU and GPU, distributed processing on the CPU, frame buffer object, and double buffering for parallel and/or distributed tasks. Using the optimizing techniques both individually and combined, several heterogeneous computing structures were implemented and their effectiveness were analyzed. The experimental results show that the heterogeneous computing facilitates executions up to 3.5 times faster than CPU-only processing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1272-1277
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• 2010

Target detection and tracking wireless sensor network must have various signal processing ability. Wireless sensor nodes need to light weight signal processing algorithm because of energy constraints and communication bandwidth constraints. General signal processing algorithm of wireless sensor node consists of de-noising, received signal strength computation, feature extraction and signal compression. Wireless sensor network life-time and performance of target detection and classification depend on sensor node signal processing. In this paper, we propose energy efficient signal processing algorithm using wavelet transform. The proposed method estimates exact target position.