• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1047-1054
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• 2004

In this paper, we present two systolic arrays for computing multiplications in CF(2$\^$m/) generated by an irreducible all one polynomial (AOP). The proposed two systolic mays have parallel-in parallel-out structure. The first systolic multiplier has area complexity of O(㎡) and time complexity of O(1). In other words, the multiplier consists of m(m+1)/2 identical cells and produces multiplication results at a rate of one every 1 clock cycle, after an initial delay of m/2+1 cycles. Compared with the previously proposed related multiplier using AOP, our design has 12 percent reduced hardware complexity and 50 percent reduced computation delay time. The other systolic multiplier, designed for cryptographic applications, has area complexity of O(m) and time complexity of O(m), i.e., it is composed of m+1 identical cells and produces multiplication results at a rate of one every m/2+1 clock cycles. Compared with other linear systolic multipliers, we find that our design has at least 43 percent reduced hardware complexity, 83 percent reduced computation delay time, and has twice higher throughput rate Furthermore, since the proposed two architectures have a high regularity and modularity, they are well suited to VLSI implementations. Therefore, when the proposed architectures are used for GF(2$\^$m/) applications, one can achieve maximum throughput performance with least hardware requirements.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8B
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• pp.509-520
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• 2007

In this paper, we propose a real-time sensor node platform that guarantees the real-time scheduling of periodic and aperiodic tasks through a multitask-based software decomposition technique. Since existing sensor networking operation systems available in literature are not capable of supporting the real-time scheduling of periodic and aperiodic tasks, the preemption of aperiodic task with high priority can block periodic tasks, and so periodic tasks are likely to miss their deadlines. This paper presents a comprehensive evaluation of how to structure periodic or aperiodic task decomposition in real-time sensor-networking platforms as regard to guaranteeing the deadlines of all the periodic tasks and aiming to providing aperiodic tasks with average good response time. A case study based on real system experiments is conducted to illustrate the application and efficiency of the multitask-based dynamic component execution environment in the sensor node equipped with a low-power 8-bit microcontroller, an IEEE802.15.4 compliant 2.4GHz RF transceiver, and several sensors. It shows that our periodic and aperiodic task decomposition technique yields efficient performance in terms of three significant, objective goals: deadline miss ratio of periodic tasks, average response time of aperiodic tasks, and processor utilization of periodic and aperiodic tasks.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.454-461
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• 2007

Portable embedded systems have recently become smaller in size and offer a variety of junctions for users. These systems require high performance processors to handle the many functions and also a small battery to fit inside the system. However, due to its size, the battery life has become a major issue. It is important to have both efficient power design and management for each function, while optimizing processor voltage and clock frequency in order to extend the battery life of the system. In this paper, we calculated the efficiency of power in optimizing power rail. This system has two microprocessors. One is used to play music and movie files while the other is for DMB. In order to reduce power consumption, the DMB microprocessor is turned of while music or videos are played. Lastly, DVFS is applied to the processor in the system to reduce power consumption. Experimental results of the implemented system have resulted in reduced power consumption.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.191-197
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• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.261-268
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• 2020

In this paper, we propose an effective software education model for youths with disability. This software education model consists of a four-step process. In the first step, it draws the education curriculum of the software education for different types of disabled youths based on the results of comparative analysis of software education field in special education curriculum. In the second step, it suggests achievement standards for effective software education for the disabled students by classifying students with intellectual disabilities and visual, hearing, and physical disabilities without any multiple disabilities. In the third step, the study developed a modular textbook comprised of unplugged activities using coding robot Albert, physical computing, and block/text coding with the reflection of the characteristic of each type of disability. In the fourth step, it applied the textbook to the school field and educated disabled students focusing on experience to allow them to think logically and by stages about different problems they face in daily lives. In addition, by analyzing the results of youths' performance evaluation and surveys, it was shown that 82.3% of developmental disabilities, 78.8% of visual impairments, 90.9% of hearing impairments, and 78.8% of physically disabilities achieved achievements above the "medium" level. These results prove that the software education model for youths with disabilities proposed in this paper is very effective in improving computational chinking of youths with disabilities.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.117-126
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• 2020

A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.81-94
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• 2010

Input variable selection is one of the various techniques for improving the performance of artificial neural network. In this study, mutual information is applied for input variable selection technique instead of correlation coefficient that is widely used. Among 152 variables of RDAPS (Regional Data Assimilation and Prediction System) output results, input variables for artificial neural network are chosen by computing mutual information between rainfall records and RDAPS' variables. At first the rainfall forecast variable of RDAPS result, namely APCP, is included as input variable and the other input variables are selected according to the rank of mutual information and correlation coefficient. The input variables using mutual information are usually those variables about wind velocity such as D300, U925, etc. Several statistical error estimates show that the result from mutual information is generally more accurate than those from the previous research and correlation coefficient. In addition, the artificial neural network using input variables computed by mutual information can effectively reduce the relative errors corresponding to the high rainfall events.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.29-37
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• 2000

Asynchronous transfer mode is flexible to support multimedia communication services using asynchronous time-sharing and statistical multimedia techniques to the existing data communication area, ATM ABR service controls network traffic using feedback information on the network congestion situation in order to guarantee the demanded service qualities and the available cell rates, In this paper we apply the control method using queue length prediction to the formation of feedback information for more efficient ABR traffic control. If backward node receive the longer delayed feedback information on the impending congestion, the switch can be already congested from the uncontrolled arriving traffic and the fluctuation of queue length can be inefficiently high in the continuing time intervals, The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series, The predicted congestion information is backward to the node, NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction, Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.132-144
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• 2001

The broadcast environment is asymmetric communication aspect that is typically much greater communication capacity available from server to clients than in the opposite direction. In addition, most of mobile computing systems only allow the generation of read-only transactions from mobile clients for retrieving different types of information such as stock data, traffic information and news updates. Since previous concurrency control protocols, however, do not consider such a particular characteristics, the performance degradation occurs when those schemes are applied to the broadcast environment having quite a high data contention. In this paper, we propose OCC/2VTS (Optimistic Concurrency Control based on 2-Version and TimeStamp) that is most appropriate for broadcast environment. OCC/2VTS lets each client process and commit query transactions for itself by using two version data in cache. If the values of appropriate data items are not changed twice by invalidation report after a query transaction starts, the query transaction is committed safely independent of commitment of update transactions. OCC/2VTS decreases the number of informing server for the purpose of commitment. Due to broadcasting the validation reports including updated recent values, it reduces the opportunity of requesting a recent data values of server as well. As a result, OCC/2VTS makes full use of the asymmetric bandwidth. It also improves transaction throughput by increasing the query transaction commit ratio as much as possible.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.99-113
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• 2004

A new architecture called SAN(Storage Area Network) was developed in response to the requirements of high availability of data, scalable growth, and system performance. In order to use SAN more efficiently, most of SAN operating softwares support storage virtualization concepts that allow users to view physical storage devices attached to SAN as a large volume virtually h logical volume manager plays a key role in storage virtualization. It realizes the storage virtualization by mapping logical addresses to physical addresses. A logical volume manager also supports a snapshot that preserves a volume image at certain time and on-line reorganization to allow users to add/remove storage devices to/from SAN even while the system is running. To support the snapshot and the on-line reorganization, most logical volume managers have used table based mapping methods. However, it is very difficult to manage mapping table because the mapping table is large in proportion to a storage capacity. In this paper, we design and implement an efficient and flexible hybrid mapping method based on mathematical equations. The mapping method in this paper supports a snapshot and on-line reorganization. The proposed snapshot and on-line reorganization are performed on the reserved area which is separated from data area of a volume. Due to this strategy normal I/O operations are not affected by snapshot and reorganization. Finally, we show the superiority of our proposed mapping method through various experiments.