• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.192-196
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• 2024

The memory coherence problem occurs while mapping shared virtual memory in a loosely coupled multiprocessors setup. Memory is considered coherent if a read operation provides same data written in the last write operation. The problem is addressed in the literature using different algorithms. The big question is on the correctness of such a distributed algorithm. Formal verification is the principal term for a group of techniques that routinely use an analysis that is established on mathematical transformations to conclude the rightness of hardware or software behavior in divergence to dynamic verification techniques. This paper uses UPPAAL model checker to model the dynamic distributed algorithm for shared virtual memory given by K.Li and P.Hudak. We analyse the mechanism to keep the coherence of memory in every read and write operation by using a dynamic distributed algorithm. Our results show that the dynamic distributed algorithm for shared virtual memory partially fulfils its functional requirements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2381-2399
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• 2019

Traditional recommendation algorithms on Collaborative Filtering (CF) mainly focus on the rating prediction with explicit ratings, and cannot be applied to the top-N recommendation with implicit feedbacks. To tackle this problem, we propose a new collaborative filtering approach namely Maximize MAP with Matrix Factorization (MFMAP). In addition, in order to solve the problem of non-smoothing loss function in learning to rank (LTR) algorithm based on pairwise, we also propose a smooth MAP measure which can be easily implemented by standard optimization approaches. We perform experiments on three different datasets, and the experimental results show that the performance of MFMAP is significantly better than other recommendation approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1964-1981
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• 2014

An improved Mean-Shift (MS) tracker called joint CB-LBWH, which uses a combined weighted-histogram scheme of CBWH (Corrected Background-Weighted Histogram) and LBWH (likelihood-based Background-Weighted Histogram), is presented. Joint CB-LBWH is based on the notion that target representation employs both feature saliency and confidence to form a compound weighted histogram criterion. As the more prominent and confident features mean more significant for tracking the target, the tuned histogram by joint CB-LBWH can reduce the interference of background in target localization effectively. Comparative experimental results show that the proposed joint CB-LBWH scheme can significantly improve the efficiency and robustness of MS tracker when heavy occlusions and complex scenes exist.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.140-143
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• 2000

In this paper, forward error control coding in multicarrier direct sequence code division multiple access (DS/CDMA) systems is considered. In order to accommodate a number of coding rates easily and make the encoder and do-coder structure simple, we use the rate compatible punctured convolutional (RCPC) code. We obtain data throughputs at several coding rates and choose the coding rate which has the highest data throughput in the SINR sense. To achieve maximum data throughput, a rate adaptive system using channel state information (the SINR estimate) is proposed. The SINR estimate is obtain by the soft decision Viterbi decoding metric. We show that the proposed rate adaptive convolutionally coded multicarrier DS/CDMA system can enhance spectral efficiency and provide frequency diversity.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.238-240
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• 2007

A new ZVZCS Single-Stage Power-Factor-Correction(PFC) AC/DC converter with boost PFC cell is integrated with voltage doubler rectified asymmetrical half-bridge(VDRAHB) is proposed in this paper. The proposed converter features good power factor correction, low current harmonic distortions, tight output regulations and low voltage of link capacitor. An 85W prototype was implemented to show that it meets the harmonic requirements and standards satisfactorily with nearly unity power factor and high efficiency over universal input.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.241-249
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• 2022

The current research attempts to measure the level of the acceptance of the Blackboard System (BBS) during the Corona crisis, and whether this is one of the reasons for the low use of the BBS at Al-Jouf University. To achieve this, the technology accepting model in the time of crisis (TAMTC) has been proposed to measure the degree of acceptance by students, which was then applied to a random sample of 339 of such. The results show a high level of student acceptance, despite their lower use of the system. The research also highlights the importance of upgrading e-courses and that the discontinuation of exam disqualification of students is secondary to their poor course attendance.

• Honam Mathematical Journal
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• v.26 no.3
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• pp.331-339
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• 2004

The aim of this paper is to show the difference between the notion of digital continuity and that of computer continuity. More precisely, for digital images $(X,\;k_0){\subset}Z^{n_0}$ and $(Y,\;k_1){\subset}Z^{n_1}$, $if(k_0,\;k_1)=(3^{n_0}-1,\;3^{n_1}-1)$, then the equivalence between digital continuity and computer continuity is proved. Meanwhile, if $(k_0,\;k_1){\neq}(3^{n_0}-1,\;3^{n_1}-1)$, then the difference between them is shown in terms of the uniform continuity property.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2044-2059
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• 2022

Recent works have shown that the geometric constraint can be harnessed to boost the performance of CNN-based camera localization. However, the existing strategies are limited to imposing image-level constraint between pose pairs, which is weak and coarse-gained. In this paper, we introduce a pixel-level epipolar geometry constraint to vanilla localization framework without the ground-truth 3D information. Dubbed EpiLoc, our method establishes the geometric relationship between pixels in different images by utilizing the epipolar geometry thus forcing the network to regress more accurate poses. We also propose a variant called EpiSingle to cope with non-sequential training images, which can construct the epipolar geometry constraint based on a single image in a self-supervised manner. Extensive experiments on the public indoor 7Scenes and outdoor RobotCar datasets show that the proposed pixel-level constraint is valuable, and helps our EpiLoc achieve state-of-the-art results in the end-to-end camera localization task.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.404-409
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• 1998

In this paper, we propose a learning algorithm of fuzzy neural networks with trapezoidal fuzzy weights. This fuzzy neural networks can use fuzzy numbers as well as real numbers, and represent linguistic information better than standard neural networks. We construct trapezodal fuzzy weights by the composition of two triangles, and devise a learning algorithm using the two triangular membership functions, The results of computer simulations on numerical data show that the fuzzy neural networks have high fitting ability for target output.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.1-5
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• 2004

In this paper, we propose a novel approach for evolving the architecture of a multi-layer neural network. Our method uses combined ART1 algorithm and Max-Min neural network to self-generate nodes in the hidden layer. We have applied the. proposed method to the problem of recognizing ID number in student identity cards. Experimental results with a real database show that the proposed method has better performance than a conventional neural network.