• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.323-334
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• 2003

This paper presents a goal-programming (GP) model for management decision-making for sugarcane fertilizer mix problems. Sensitivity analysis on the priority structure of the goals has been performed to obtain all possible solutions. The study uses Euclidean distance function to measure distances of all possible solutions from the ideal solution. The optimum solution is determined from the minimum distance between the ideal solution and other possible solutions of the problem. The optimum solution corresponds to the appropriate priority structure of the problem in the decision-making context. furthermore, the results obtained from sensitivity analysis on the cost of combination of fertilizers confirm the priority structure.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.5
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• pp.591-596
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• 1986

A binary continuous phase frequency shift keying (CPFSK), whose phase is a continuous function of time and instantaneous frequency is constant, is a bandwidth efficient constant envelope signalling scheme. A transmitting signal is formed by combined coding of a convolutional encoder and a binary CPFSK modulator. The signal is transmitted throuth additive white Gaussian noise(AWGN) channel. If the received signal is detected by a coherent maximum likelihood(ML) receiver, error probability can be expressed approximately in terms of minimum Euclidean distance. We propose rate 2/4 codes for the improvement of error performance without increating the data rate per bandwidth and the receiver complexity. Its minimum Euclidean distances are compared with those of rate \ulcornercodes as a function of modulation index and observation interval.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.119-124
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• 2014

Blind adaptive systems based on the Euclidean distance (ED) between the distribution function of the output samples and that of a set of random symbols generated at the receiver matching with the distribution function of the transmitted symbol points estimate the ED at each iteration time to examine its convergence state or its minimum ED value. The problem is that this ED estimation obtained by block?data processing requires a heavy calculation burden. In this paper, a recursive ED estimation method is proposed that reduces the computational complexity by way of utilizing the relationship between the current and previous states of the datablock. The relationship provides a ground that the currently estimated ED value can be used for the estimation of the next ED without the need for processing the whole new data block. From the simulation results the proposed recursive ED estimation shows the same estimation values as that of the conventional method, and in the aspect of computational burden, the proposed method requires only O(N) at each iteration time while the conventional block?processing method does $O(N^2)$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.561-566
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• 2021

The optimum kernel size for error-distribution estimation with given error samples cannot be used in the weight adjustment of minimum Euclidean distance between error distributions (MED) algorithms. In this paper, a new adaptive kernel estimation method for convergence enhancement of MED algorithms is proposed. The proposed method uses the average rate of change in error power with respect to a small interval of the kernel width for weight adjustment of the MED learning algorithm. The proposed kernel adjustment method is applied to experiments in communication channel compensation, and performance improvement is demonstrated. Unlike the conventional method yielding a very small kernel calculated through optimum estimation of error distribution, the proposed method converges to an appropriate kernel size for weight adjustment of the MED algorithm. The experimental results confirm that the proposed kernel estimation method for MED can be considered a method that can solve the sensitivity problem from choosing an appropriate kernel size for the MED algorithm.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.2
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• pp.146-159
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• 2023

This paper proposes a hybrid algorithm combining K-means clustering and watershed algorithms for flower segmentation and counting. We use the K-means clustering algorithm to obtain the main colors in a complex background according to the cluster centers and then take a color space transformation to extract pixel values for the hue, saturation, and value of flower color. Next, we apply the threshold segmentation technique to segment flowers precisely and obtain the binary image of flowers. Based on this, we take the Euclidean distance transformation to obtain the distance map and apply it to find the local maxima of the connected components. Afterward, the proposed algorithm adaptively determines a minimum distance between each peak and apply it to label connected components using the watershed segmentation with eight-connectivity. On a dataset of 30 images, the test results reveal that the proposed method is more efficient and precise for the counting of overlapped flowers ignoring the degree of overlap, number of overlap, and relatively irregular shape.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.25-33
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• 1988

An efficient heuristic solution procedure is developed for the minimum location problems. The gradient direction method and modified gradient approach are developed due to the differentiability of the objective functions. Suboptimal step size is obtained analytically. A Modified Gradient Procedure (NGP) is presented and compared with the hyperboloid approximation procedure (HAP) which is one of the best known methods.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1531-1534
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• 2002

Shape description and its corresponding matching algorithm is one of the main concerns in MPEG-7. In this paper, a new method is proposed for shape registration of 2D objects for MPEG-7 Shapes are recognized using the Hu statistical moments in frequency domain. The Hu moments are moment-based descriptors of planar shapes, which are invariant under general translation, rotational, scaling, and reflection transformation. The image is transformed into frequency domain using Fourier Transform. Annular and radial wedge distributions fur the power spectra are extracted. Different statistical features (Hu moments) are found f3r the power spectrum of each selected transformed individual feature. The Euclidean distance of the extracted moment descriptors of the features are found with respect to the shapes in the database. The minimum Euclidean distance is the candidate for the matched shape. The simulation results are performed on the test shapes of MPEG-7.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.612-627
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• 2009

The high-level contribution of this paper is to illustrate the effectiveness of using graph theory tree traversal algorithms (pre-order, in-order and post-order traversals) to generate the chain of sensor nodes in the classical Power Efficient-Gathering in Sensor Information Systems (PEGASIS) data aggregation protocol for wireless sensor networks. We first construct an undirected minimum-weight spanning tree (ud-MST) on a complete sensor network graph, wherein the weight of each edge is the Euclidean distance between the constituent nodes of the edge. A Breadth-First-Search of the ud-MST, starting with the node located closest to the center of the network, is now conducted to iteratively construct a rooted directed minimum-weight spanning tree (rd-MST). The three tree traversal algorithms are then executed on the rd-MST and the node sequence resulting from each of the traversals is used as the chain of nodes for the PEGASIS protocol. Simulation studies on PEGASIS conducted for both TDMA and CDMA systems illustrate that using the chain of nodes generated from the tree traversal algorithms, the node lifetime can improve as large as by 19%-30% and at the same time, the energy loss per node can be 19%-35% lower than that obtained with the currently used distance-based greedy heuristic.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.715-720
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• 2016

In this paper, a method to design 3-dimensional (3-D) cross-lattice signal constellations with increased compactness is presented and analyzed. Here, the symbols located at the outermost sides in the conventional lattice constellation are moved symmetrically to fill in empty sides and sunken corners. While the minimum Euclidean distance (MED) among adjacent symbols remains unchanged, the presented cross-lattice constellations have 3~5% reduced average power and upto 25% reduced total volume as compared with the conventional ones. Due to the increase compactness, average power of the new 3-D constellations is lower than that of the conventional ones. As a result, computer simulation verifies that the presented cross-lattice constellations can improve symbol error performance of a digital transmission system about 0.4 [dB]. Hence, the proposed 3-D cross-lattice constellations are appropriate for low-power and high-quality digital communication systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2021-2026
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• 2016

In this paper, a system model for transmission of 3-dimensional (3-D) signals is presented and its performance is analyzed. Unlike 2-D signals, no quadrature form expression for the 3-D signals is available. Exploiting a set of orthogonal basis functions, the 3-D signals are transmitted. As a result of computer simulation using very higher-level signal constellations, the 3-D transmission system has significantly improved error performance as compared with the 2-D system. It is considered that the principal reason for such performance improvement is much increased minimum Euclidean distance (MED) of the 3-D lattice constellations compared with the corresponding 2-D ones. When the MEDs of 2-D and 3-D lattice constellation are compared to confirm the analysis, the MED of 3-D 1024-ary constellation is around 2.6 times larger than that of the quadrature amplitude modulation (QAM). Expanding the constellation size to 4096, the MED of 3-D lattice constellation is increased by 3.2 times of the QAM.