• Smart Media Journal
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• v.10 no.4
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• pp.15-20
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• 2021

The distributed trigger counting problem is to notify the user when the total number of triggers received from a distributed system consisting of n nodes reaches a predefined value w. The distributed trigger counting problem is used for monitoring and global snapshots in various distributed systems. In this paper, we propose a simple and efficient algorithm for the distributed trigger counting problem. The proposed algorithm operates based on a tree structure of degree $\sqrt{n}$ and height 2. The proposed algorithm operates in three different phases based on the remaining number of triggers. Experimental results show that the proposed algorithm has a smaller message complexity than CoinRand, and MaxRcv also performed better when the number of nodes is not large.

• Nuclear Engineering and Technology
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• v.27 no.5
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• pp.784-791
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• 1995

This paper describes the counting-loss problem for radiation measurement Multi-channel analyzers and spectrometers adopt various techniques for compensation for counting-losses in process-ing the radiation pulses from a detector. Researchers hate tried to seek the best solution for the problem. However, any absolute solution has not been reached and vendors of radiation instruments use their own algorithms individually. This survey explains the various compensation algorithms with electronic implementation approach. Shortcomings and merits of each algorithm are also reviewed and a direction is suggested of the recommendable development strategy for counting-loss compensation.

• Research in Mathematical Education
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• v.12 no.2
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• pp.127-142
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• 2008

The most important aim of mathematics education is to promote mathematical thinking. In the Hong Kong primary school, mathematical thinking is usually conducted through the use of formula and working on "application problem" or "word problems". However, there are many other ways that can promote mathematical thinking, and investigation on mathematical structure by using counting is one important source for promoting mathematical thinking for primary school children, as every children can count and hence a well designed question that can be solved by counting can enable children of different abilities to work together and obtain different results.

• School Mathematics
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• v.7 no.4
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• pp.353-373
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• 2005

The purpose of this paper is to analysis the basic network problem which can be applied to the mathematically gifted students in elementary school. Mainly, we discuss didactic transpositions of the double counting principle, the game of sprouts, Eulerian graph problem, and the minimum connector problem. Here the double counting principle is related to the handshaking lemma; in any graph, the sum of all the vertex-degree is equal to the number of edges. The selection of these subjects are based on the viewpoint; to familiar to graph theory, to raise algorithmic thinking, to apply to the real-world problem. The theoretical background of didactic transpositions of these subjects are based on the Polya's mathematical heuristics and Lakatos's philosophy of mathematics; quasi-empirical, proofs and refutations as a logic of mathematical discovery.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.113-119
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• 2020

This study proposed the structure of the cluster's cell counting algorithm for cell analysis. The image required for cell count is taken under a microscope. At present, the cell counting algorithm is reported to have a problem of low accuracy of results due to uneven shape and size clusters. To solve these problems, the proposed algorithm has a feature of calculating the number of cells in a cluster by applying a radius change analysis to the existing distance conversion and watershed algorithm. Later, cell counting algorithms are expected to yield reliable results if applied to the required field.

• The Mathematical Education
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• v.45 no.1 s.112
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• pp.123-138
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• 2006

In this paper, we confirm through surveys and interviews that it helps students in solving a problem counting the number of combinations to find a structural isomorphism between the given problem and a typical problem with the same mathematical structure. Then we suggest that a problem of distributing balls into boxes might be a good candidate for a typical problem. This approach is coherent to the viewpoint given by English(2004) that it is educationally important to see the connection and relationship between problems with different context but with similar mathematical structure.

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.493-505
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• 2016

Among modern computer vision and video surveillance systems, the pedestrian counting system is a one of important systems in terms of security, scheduling and advertising. In the field of, pedestrian counting remains a variety of challenges such as changes in illumination, partial occlusion, overlap and people detection. During pedestrian counting process, the biggest problem is occlusion effect in crowded environment. Occlusion and overlap must be resolved for accurate people counting. In this paper, we propose a novel pedestrian counting system which improves existing pedestrian tracking method. Unlike existing pedestrian tracking method, proposed method shows that average filter tracking method can improve tracking performance. Also proposed method improves tracking performance through frame compensation and outlier removal. At the same time, we keep various information of tracking objects. The proposed method improves counting accuracy and reduces error rate about S6 dataset and S7 dataset. Also our system provides real time detection at the rate of 80 fps.

• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.149-157
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• 2008

Since wireless sensor networks consist of nodes with the constrained battery, energy efficient MAC operation is one of the important issues. Low duty cycle operation is critical to conserve energy in wireless sensor network MAC protocol. Some paper proposed a new approach to low power listening, which employs a short preamble to further reduce energy consumption and to reduce latency. But short preamble suffers from unfair channel access problem since there was no consideration for contention between transmission nodes. Preamble counting proposes a solution to each of these problems by employing node selection information. Simulation results show that the preamble counting provides an improved energy efficiency and fairness of packet delivery.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.64-69
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• 2008

This paper discusses low resolution face recognition using the photon-counting linear discriminant analysis (LDA). The photon-counting LDA asymptotically realizes the Fisher criterion without dimensionality reduction since it does not suffer from the singularity problem of the fisher LDA. The linear discriminant function for optimal projection is determined in high dimensional space to classify unknown objects, thus, it is more efficient in dealing with low resolution facial images as well as conventional face distortions. The simulation results show that the proposed method is superior to Eigen face and Fisher face in terms of the accuracy and false alarm rates.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.3
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• pp.250-255
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• 2012

Face recognition has wide applications in security and surveillance systems as well as in robot vision and machine interfaces. Conventional challenges in face recognition include pose, illumination, and expression, and face recognition at a distance involves additional challenges because long-distance images are often degraded due to poor focusing and motion blurring. This study investigates the effectiveness of applying photon-counting linear discriminant analysis (Pc-LDA) to face recognition in harsh environments. A related technique, Fisher linear discriminant analysis, has been found to be optimal, but it often suffers from the singularity problem because the number of available training images is generally much smaller than the number of pixels. Pc-LDA, on the other hand, realizes the Fisher criterion in high-dimensional space without any dimensionality reduction. Therefore, it provides more invariant solutions to image recognition under distortion and degradation. Two decision rules are employed: one is based on Euclidean distance; the other, on normalized correlation. In the experiments, the asymptotic equivalence of the photon-counting method to the Fisher method is verified with simulated data. Degraded facial images are employed to demonstrate the robustness of the photon-counting classifier in harsh environments. Four types of blurring point spread functions are applied to the test images in order to simulate long-distance acquisition. The results are compared with those of conventional Eigen face and Fisher face methods. The results indicate that Pc-LDA is better than conventional facial recognition techniques.