• Title/Summary/Keyword: Evolving Algorithm

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A Study on Stowage Automation Algorithm for Cargo Stowage Optimization of Vehicle Carriers (차량 운반선의 화물 적재 최적화를 위한 적재 자동화 알고리즘 연구)

  • JI Yeon Kim;Young-Jin Kang;Jeong, Seok Chan;Hoon Lee
    • The Journal of Bigdata
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    • v.7 no.2
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    • pp.129-137
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    • 2022
  • With the development of the 4th industry, the logistics industry is evolving into a smart logistics system. However, ship work that transports vehicles is progressing slowly due to various problems. In this paper, we propose an stowage automation algorithm that can be used for cargo loading of vehicle carriers that shortens loading and unloading work time. The stowage automation algorithm returns the shortest distance by searching for a loading space and a movable path in the ship in consideration of the structure of the ship. The algorithm identifies walls, ramps and vehicles that have already been shipped, and can work even with randomly placed. In particular, it is expected to contribute to developing a smart logistics system for vehicle carriers by referring to the ship's master plan to search for vehicle loading and unloading space in each port and predict the shortest movable path.

An Algorithm of Welding Bead Detection and Evaluation Using and Multiple Filters Geodesic Active Contour (다중필터와 축지적 활성 윤곽선 알고리즘을 이용한 용접 비드 검출 및 판단 알고리즘)

  • Milyahilu, John;Kim, Young-Bong;Lee, Jae Eun;Kim, Jong-Nam
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.3
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    • pp.141-148
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    • 2021
  • In this paper, we propose an algorithm of welding bead detection and evaluation using geodesic active contour algorithm and high pass filter with image processing technique. The algorithm uses histogram equalization and high pass filter as gaussian filter to improve contrast. The image processing techniques smoothens the welding beads reduce the noise on an image. Then, the algorithm detects the welding bead area by applying the geodesic active contour algorithm and morphological ooperation. It also applies the balloon force that either inflates in, or deflates out the evolving contour for a better segmentation. After that, we propose a method for determining the quality of welding bead using effective length and width of the detected bead. In the experiments, our algorithm achieved the highest recall, precision, F-measure and IOU as 0.9894, 0.9668, 0.9780, and 0.8957 respectively. We compared the proposed algorithm with the conventional algorithms to evaluate the performance of the proposed algorithm. The proposed algorithm achieved better performance compared to the conventional ones with a maximum computational time of 0.6 seconds for segmenting and evaluating one welding bead.

Feature Selection Algorithm for Intrusions Detection System using Sequential Forward Search and Random Forest Classifier

  • Lee, Jinlee;Park, Dooho;Lee, Changhoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.5132-5148
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    • 2017
  • Cyber attacks are evolving commensurate with recent developments in information security technology. Intrusion detection systems collect various types of data from computers and networks to detect security threats and analyze the attack information. The large amount of data examined make the large number of computations and low detection rates problematic. Feature selection is expected to improve the classification performance and provide faster and more cost-effective results. Despite the various feature selection studies conducted for intrusion detection systems, it is difficult to automate feature selection because it is based on the knowledge of security experts. This paper proposes a feature selection technique to overcome the performance problems of intrusion detection systems. Focusing on feature selection, the first phase of the proposed system aims at constructing a feature subset using a sequential forward floating search (SFFS) to downsize the dimension of the variables. The second phase constructs a classification model with the selected feature subset using a random forest classifier (RFC) and evaluates the classification accuracy. Experiments were conducted with the NSL-KDD dataset using SFFS-RF, and the results indicated that feature selection techniques are a necessary preprocessing step to improve the overall system performance in systems that handle large datasets. They also verified that SFFS-RF could be used for data classification. In conclusion, SFFS-RF could be the key to improving the classification model performance in machine learning.

Co-Evolution of Fuzzy Rules and Membership Functions

  • Jun, Hyo-Byung;Joung, Chi-Sun;Sim, Kwee-Bo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.601-606
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    • 1998
  • In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. Futhermore proper fuzzy partitioning is not deterministic ad there is no unique solution. So we propose a co-evolutionary method finding optimal fuzzy rules and proper fuzzy membership functions at the same time. Predator-Prey co-evolution and symbiotic co-evolution algorithms, typical approaching methods to co-evolution, are reviewed, and dynamic fitness landscape associated with co-evolution is explained. Our algorithm is that after constructing two population groups made up of rule base and membership function, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the propose method to a path planning problem of autonomous mobile robots when moving objects applying the proposed method to a pa h planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

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Acceleration of Phase Measuring Profilometry using GPU (GPU를 이용한 위상 측정법의 가속화)

  • Kim, Ho-Joong;Cho, Tai-Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.12
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    • pp.2285-2290
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    • 2017
  • Automation systems are evolving in many areas of industry in recent years. At the same time, the necessity of the height inspection of the object by the 3D measurement is gradually increasing. Among the various 3D measurement methods, this paper discusses phase measuring profilometry(PMP). The PMP is a method of obtaining the height of an object using the phase value of the fringe pattern. Since the PMP is an algorithm requiring a large amount of computation, a method for efficiently solving the problem is needed. In this paper, we propose to use CUDA from NVIDIA to solve this problem. We also propose using pinned memory and streams provided by CUDA. This can greatly improve the measurement speed while maintaining accuracy. Finally, we demonstrate the performance of the proposed method through experiments.

Evolutionary Design of Image Filter Using The Celoxica Rc1000 Board

  • Wang, Jin;Jung, Je-Kyo;Lee, Chong-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1355-1360
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    • 2005
  • In this paper, we approach the problem of image filter design automation using a kind of intrinsic evolvable hardware architecture. For the purpose of implementing the intrinsic evolution process in a common FPGA chip and evolving a complicated digital circuit system-image filter, the design automation system employs the reconfigurable circuit architecture as the reconfigurable component of the EHW. The reconfigurable circuit architecture is inspired by the Cartesian Genetic Programming and the functional level evolution. To increase the speed of the hardware evolution, the whole evolvable hardware system which consists of evolution algorithm unit, fitness value calculation unit and reconfigurable unit are implemented by a commercial FPGA chip. The Celoxica RC1000 card which is fitted with a Xilinx Virtex xcv2000E FPGA chip is employed as the experiment platform. As the result, we conclude the terms of the synthesis report of the image filter design automation system and hardware evolution speed in the Celoxica RC1000 card. The evolved image filter is also compared with the conventional image filter form the point of filtered image quality.

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The Study of Criminal Lingo Analysis on Cyberspace and Management Used in Artificial Intelligence and Block-chain Technology

  • Yoon, Cheolhee;Lee, Bong Gyou
    • International Journal of Advanced Culture Technology
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    • v.8 no.3
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    • pp.54-60
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    • 2020
  • Online cybercrime has various causes. The criminal guilty language, Criminal lingo is active in the shaded area with the bilateral aspect of the word on cyber. It has been continuously producing massive risk factors in cyberspace. Criminals are shared and disseminated online. It has been linked with fake news and aids to suicide that has recently become an issue. Thus the criminal lingo has become a real danger factor on cyber interface. Recently, Criminal lingo is shared and distributed as cyber hazard information. It is transformed that damaging to the youth and ordinary people through the internet and social networks. In order to take action, it is necessary to construct an expert system based on AI to implement a smart management architecture with block-chain technology. In this paper, we study technically a new smart management architecture which uses artificial intelligence based decision algorithm and block-chain tracking technology to prevent the spread of criminal lingo factors in the evolving cyber world. In addition, through the off-line regular patrol program of police units, we proposed the conversion of online regular patrol program for "cyber harem area".

An optimal codebook design for multistage gain-shape vector quantizer using genetic algorithms (유전알고리즘에 의한 다단 gain-shape 양자화기의 최적 코드북 설계)

  • 김대진;안선하
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.1
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    • pp.80-93
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    • 1997
  • This paper proposes a new technique of optimal codebook design in multistage gain-shape vector quantization (MS-GS VQ) for wireless image communication. An original image is divided into a smany blocks as possible in order to get strong robustness to channel transmission errors: the original image is decomposed into a number of subband images, each of which contains a sperate spatial frequency information and is obtained by the biorthogonal wavlet transform; each subband is separated into several consecutive VQ stages, where each stage has a residual information of the previous stage; one vector in each stage is divided into two components-gain and shape. But, this decomposition genrates too many blocks and it thus makes the determination of optimal codebooks difficult. We overcome this difficulty by evolving each block's codebook independently with different genetic algorithm that uses each stage's individual training vectors. Th eimpact of th eproposed VQ technique on the channel transmission errors is compared with that of other VQ techniques. Simulation results show that the proposed VQ technique (MS-GS VQ) with the optimal codebook designe dy genetic algorithms is very robust to channel transmission errors even under the bursty and high BER conditions.

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Requirements Analysis and System Design for the Implementation of the Gut Microbiome Analysis Platform (장내미생물 분석 플랫폼 구현을 위한 요구사항 분석 및 시스템 설계)

  • Lim, Wiseman;Ma, Sanghyuk;Ma, Sangbae;Choi, Hyoungmin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.6
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    • pp.487-496
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    • 2021
  • The analysis method of the microbiome has been evolving for a very long time, and the industrial field has grown rapidly with the start of human genome analysis 20 years ago. As continuous research continues, related industries have grown together, and among them, Illumina of the US has been leading the popularization of DNA analysis by developing innovative equipment and analysis methods since its establishment in 1998. In this paper, 'AiB Index', 'AiB Chart' using statistical process control and log-scale technique to analyze the gut microbiome analysis methodology and implement an algorithm that can analyze minute changes in the minor strains that can be overlooked in the existing analysis methods. want to implement. From the data analysis point of view, we proposed a platform for analyzing gut microbes that can collect fecal data, match and process gut microbes, and store and visualize the results.

Implementing Firewall to Mitigate YOYO Attack on Multi Master Cluster Nodes Using Fail2Ban

  • Muhammad Faraz Hyder;Muhammad Umer Farooq;Mustafa Latif;Faizan Razi Khan;Abdul Hameed;Noor Qayyum Khan;M. Ahsan Siddiqui
    • International Journal of Computer Science & Network Security
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    • v.23 no.2
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    • pp.126-132
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    • 2023
  • Web technology is evolving with the passage of time, from a single node server to high availability and then in the form of Kubernetes. In recent years, the research community have been trying to provide high availability in the form of multi master cluster with a solid election algorithm. This is helpful in increasing the resources in the form of pods inside the worker node. There are new impact of known DDoS attack, which is utilizing the resources at its peak, known as Yoyo attack. It is kind of burst attack that can utilize CPU and memory to its limit and provide legit visitors with a bad experience. In this research, we tried to mitigate the Yoyo attack by introducing a firewall at load-balancer level to prevent the attack from going to the cluster network.