• Proceedings of the Korean Society of Computer Information Conference
• /
• 2009.01a
• /
• pp.211-214
• /
• 2009

Edge detection always influenced by noise belong to the original image, therefore need use some methods to sort this issue, mean shift algorithm has the smooth function which suit for the edge detection purpose, so adopted to fade out the unimportant information, and the sensitive noise portions. After this section, use the Canny algorithm to pick up the contour of the objects we focus on, meanwhile select the Soble operator that has the orientation attribute to support the method work well. In final, take experiment and get the perfect result we wanted, make sure this method make sense and better than the sole Edge detection algorithm,

• Journal of information and communication convergence engineering
• /
• v.13 no.2
• /
• pp.113-122
• /
• 2015

Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.

• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2435-2437
• /
• 2004

In this paper, an obstacle avoidance algorithm is proposed for a network-based robot considering network delay by distribution. The proposed algorithm is based on the VFH(Vector Field Histogram) algorithm, and for the network-based robot system, in which it is assumed robot localization information is transmitted through network communication. In this paper, target vector for the VFH algorithm is estimated through the robot localization information and the measurement of its delay by distribution. The delay measurement is performed by time-stamp method. To synchronize all local clocks of the nodes distributed on the network, a global clock synchronization method is adopted. With the delay measurement, the robot localization estimation is performed by calculating the kinematics of the robot. The validation of the proposed algorithm is performed through the performance comparison of the obstacle avoidance between the proposed algorithm and the existing VFH algorithm on the network-based autonomous mobile robot.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.6
• /
• pp.2925-2948
• /
• 2019

In order to improve the utilization of irrigation water resources of greenhouse tomatoes, a water-saving irrigation decision-making model based on genetic optimization T-S fuzzy neural network is proposed in this paper. The main work are as follows: Firstly, the traditional genetic algorithm is optimized by introducing the constraint operator and update operator of the Krill herd (KH) algorithm. Secondly, the weights and thresholds of T-S fuzzy neural network are optimized by using the improved genetic algorithm. Finally, on the basis of the real data set, the genetic optimization T-S fuzzy neural network is used to simulate and predict the irrigation volume for greenhouse tomatoes. The performance of the genetic algorithm improved T-S fuzzy neural network (GA-TSFNN), the traditional T-S fuzzy neural network algorithm (TSFNN), BP neural network algorithm(BPNN) and the genetic algorithm improved BP neural network algorithm (GA-BPNN) is compared by simulation. The simulation experiment results show that compared with the TSFNN, BPNN and the GA-BPNN, the error of the GA-TSFNN between the predicted value and the actual value of the irrigation volume is smaller, and the proposed method has a better prediction effect. This paper provides new ideas for the water-saving irrigation decision in greenhouse tomatoes.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.6B
• /
• pp.450-455
• /
• 2008

We analyze the tag identification procedure of conventional EPC Class 1 RFID system and propose the fast anti-collision algorithm for the performance improvement of the system. In the proposed algorithm, the reader uses information of tag collisions and reduces unnecessary procedures of the conventional algorithm. We evaluate the performance of the proposed anti-collision algorithm and the conventional algorithm using mathematical analysis and simulation. According to the results, the fast anti-collision algorithm shows greatly better performance than conventional algorithm.

• Journal of information and communication convergence engineering
• /
• v.2 no.2
• /
• pp.89-92
• /
• 2004

An adaptive algorithm for reducing the hardware complexity is presented. This paper proposes a modified LMS algorithm for the adaptive system and analyzes its convergence characteristics mathematically. An objective of the proposed algorithm is to reduce the hardware complexity. In order to test the performances, it is applied to the echo canceller, and a program is described. The results from simulations show that the echo canceller adopting the proposed algorithm achieves almost the same performances as one adopting the NLMS algorithm. If an echo canceller is implemented with this algorithm, its computation quantities are reduced to the one third as many as the one that is implemented with the NLMS algorithm, without so much degradation of performances.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.1
• /
• pp.343-364
• /
• 2021

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.8
• /
• pp.2881-2894
• /
• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• Journal of Information Processing Systems
• /
• v.19 no.1
• /
• pp.17-32
• /
• 2023

Centralized hierarchical routing protocols are often used to solve the problems of uneven energy consumption and short network life in wireless sensor networks (WSNs). Clustering and cluster head election have become the focuses of WSNs. In this paper, an energy balanced clustering routing algorithm optimized by sine cosine algorithm (SCA) is proposed. Firstly, optimal cluster head number per round is determined according to surviving node, and the candidate cluster head set is formed by selecting high-energy node. Secondly, a random population with a certain scale is constructed to represent a group of cluster head selection scheme, and fitness function is designed according to inter-cluster distance. Thirdly, the SCA algorithm is improved by using monotone decreasing convex function, and then a certain number of iterations are carried out to select a group of individuals with the minimum fitness function value. From simulation experiments, the process from the first death node to 80% only needs about 30 rounds. This improved algorithm balances the energy consumption among nodes and avoids premature death of some nodes. And it greatly improves the energy utilization and extends the effective life of the whole network.

• Journal of the Regional Association of Architectural Institute of Korea
• /
• v.21 no.4
• /
• pp.15-26
• /
• 2019

In recent years, researchers are increasingly trying to use BIM-based 3D models for BIM nD design such as 4D (3D + Time) and 5D (4D + Cost). However, there are still many problems in efficiently using process management based on the BIM information created at each design stage. Therefore, this study proposes a method to automate 4D and 5D design support in each design stage by using BIM-based Dynamo algorithm. To do this, I implemented an algorithm that can automatically input the process information needed for 4D and 5D by using Revit's Add-in program, Dynamo. In order to support the 4D design, the algorithm was created to enable automatic process simulation by synchronizing process simulation information (Excel file) through the Navisworks program, BIM software. The algorithm was created to automatically enable process simulation. And to support the 5D design, the algorithm was developed to enable automatic extraction of the information needed for mass production from the BIM model by utilizing the dynamo algorithm. Therefore, in order to verify the 4D and 5D design support algorithms, we verified the applicability through consultation with related workers and experts. As a result, it has been demonstrated that it is possible to manage information about process information and to quickly extract information from design and design changes. In addition, BIM data can be used to manage and input the necessary process information in 4D and 5D, which is advantageous for shortening construction time and cost. This study will make it easy to improve design quality and manage design information, and will be the foundation for future building automation research.