• Title/Summary/Keyword: Attention algorithm

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A Study of UWB Placement Optimization Based on Genetic Algorithm

  • Jung, Doyeon;Kim, Euiho
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.2
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    • pp.99-107
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    • 2022
  • Urban Air Mobility (UAM) such as a drone taxi is one of the future transportations that have recently been attracting attention. Along with the construction of an urban terminal, an accurate landing system for UAM is also essential. However, in urban environments, reliable Global Navigation Satellite Systems (GNSS) signals cannot be received due to obstacles such as high-rise buildings which causes multipath and non-line of sight signal. Thus, the positioning result in urban environments from the GNSS signal is unreliable. Consequently, we propose the Ultra-Wideband (UWB) network to assist the soft landing of UAM on a vertiport. Since the positioning performance of UWB network depends on the layout of UWB anchors, it is necessary to optimize the layout of UWB anchors. In this paper, we propose a two-steps genetic algorithm that consists of binary genetic algorithm involved multi objectives fitness function and integer genetic algorithm involved robust solution searching fitness function in order to optimize taking into account Fresnel hole effects.

SwiftQ: A Time-Efficient RFID Collision Arbitration Algorithm for Gen2-Based RFID Systems

  • Donghwan Lee;Wonjun Lee
    • Journal of Information Processing Systems
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    • v.20 no.3
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    • pp.307-316
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    • 2024
  • In the realm of large-scale identification deployments, the EPCglobal Class-1 Generation-2 (Gen2) standard serves as a cornerstone, facilitating rapid processing of numerous passive RFID tags. The Q-Algorithm has garnered considerable attention for its potential to markedly enhance the efficiency of Gen2-based RFID systems with minimal adjustments. This paper introduces a groundbreaking iteration of the Q-Algorithm, termed Time-Efficient Q-Algorithm (SwiftQ), specifically designed to push the boundaries of time efficiency within Gen2-based RFID systems. Through exhaustive simulations, our study substantiates that SwiftQ outperforms existing algorithms by a significant margin, demonstrating exceptional expediency that positions it as a formidable contender in the landscape of large-scale identification environments. By prioritizing time efficiency, SwiftQ offers a promising solution to meet the escalating demands of contemporary Internet of Things applications, underscoring its potential to catalyze advancements in RFID technology for diverse industrial and logistical contexts.

Directed Association Rules Mining and Classification (목표 속성을 고려한 연관규칙과 분류 기법)

  • 한경록;김재련
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.24 no.63
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    • pp.23-31
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    • 2001
  • Data mining can be either directed or undirected. One way of thinking about it is that we use undirected data mining to recognize relationship in the data and directed data mining to explain those relationships once they have been found. Several data mining techniques have received considerable research attention. In this paper, we propose an algorithm for discovering association rules as directed data mining and applying them to classification. In the first phase, we find frequent closed itemsets and association rules. After this phase, we construct the decision trees using discovered association rules. The algorithm can be applicable to customer relationship management.

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Sensorless Control for a Interior Permanent Magnet Synchronous Motor based on an Instantaneous Reactive Power (순시 무효전력을 이용한 IPM모터의 센서리스 제어)

  • Joung, Woo-Taik;Kang, Hyung-Seok;Kim, Young-Seok
    • Proceedings of the KIEE Conference
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    • 2005.07b
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    • pp.1447-1449
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    • 2005
  • An interior permanent magnet synchronous motor(IPMSM) is receiving increased attention for many industrial applications because of its high torque to inertia ratio, superior power density, and high efficiency. This paper presents algorithm for speed sensorless vector control based on an Instantaneous Reactive Power. Effectiveness or algorithm is confirmed by the experiments.

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Automatic collision avoidance algorithm based on improved artificial potential field method

  • Wang Zongkai;Im Namkyu
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2023.05a
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    • pp.265-266
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    • 2023
  • With the development of science and technology, various research on ship collision avoidance has also developed rapidly. The research and development of ship collision avoidance technology has also received high attention from many researchers. This paper proposes a new collision avoidance algorithm for ships based on the artificial force field collision avoidance method. Using the simulation platform, the simulation results show that ships can successfully avoid collision in open water under single ship and multi ship situations, and the research results are relatively ideal.

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PSO-SAPARB Algorithm applied to a VTOL Aircraft Longitudinal Dynamics Controller Design and a Study on the KASS (수직이착륙기 종축 제어기 설계에 적용된 입자군집 최적화 알고리즘과 KASS 시스템에 대한 고찰)

  • Lee, ByungSeok;Choi, Jong Yeoun;Heo, Moon-Beom;Nam, Gi-Wook;Lee, Joon Hwa
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.24 no.4
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    • pp.12-19
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    • 2016
  • In the case of hard problems to find solutions or complx combination problems, there are various optimization algorithms that are used to solve the problem. Among these optimization algorithms, the representative of the optimization algorithm created by imitating the behavior patterns of the organism is the PSO (Particle Swarm Optimization) algorithm. Since the PSO algorithm is easily implemented, and has superior performance, the PSO algorithm has been used in many fields, and has been applied. In particular, PSO-SAPARB (PSO with Swarm Arrangement, Parameter Adjustment and Reflective Boundary) algorithm is an advanced PSO algorithm created to complement the shortcomings of PSO algorithm. In this paper, this PSO-SAPARB algorithm was applied to the longitudinal controller design of a VTOL (Vertical Take-Off and Landing) aircraft that has the advantages of fixed-wing aircraft and rotorcraft among drones which has attracted attention in the field of UAVs. Also, through the introduction and performance of the Korean SBAS (Satellite Based Augmentation System) named KASS (Korea Augmentation Satellite System) which is being developed currently, this paper deals with the availability of algorithm such as the PSO-SAPARB.

Bi-dimensional Empirical Mode Decomposition Algorithm Based on Particle Swarm-Fractal Interpolation

  • An, Feng-Ping;He, Xin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.5955-5977
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    • 2018
  • Performance of the interpolation algorithm used in the technique of bi-dimensional empirical mode decomposition directly affects its popularization and application, so that the researchers pay more attention to the algorithm reasonable, accurate and fast. However, it has been a lack of an adaptive interpolation algorithm that is relatively satisfactory for the bi-dimensional empirical mode decomposition (BEMD) and is derived from the image characteristics. In view of this, this paper proposes an image interpolation algorithm based on the particle swarm and fractal. Its procedure includes: to analyze the given image by using the fractal brown function, to pick up the feature quantity from the image, and then to operate the adaptive image interpolation in terms of the obtained feature quantity. All parameters involved in the interpolation process are determined by using the particle swarm optimization algorithm. The presented interpolation algorithm can solve those problems of low efficiency and poor precision in the interpolation operation of bi-dimensional empirical mode decomposition and can also result in accurate and reliable bi-dimensional intrinsic modal functions with higher speed in the decomposition of the image. It lays the foundation for the further popularization and application of the bi-dimensional empirical mode decomposition algorithm.

Assesment and Diagnosis of Attention Deficit Hyperactivity Disorder(ADHD) - Focusing on Behavior Rating Scales - (주의력결핍과잉행동장애의 진단 및 평가 - 행동평정척도들을 중심으로 -)

  • Chang, Gyu-Tae;Han, Yun-Jeong
    • The Journal of Pediatrics of Korean Medicine
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    • v.20 no.2
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    • pp.147-175
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    • 2006
  • Objective : This study is to investigate the method for assesment and diagnosis of ADHD, especially focusing on behavior rating scales. Methods : We searched the recent date of the publication and paper in ADHD. Results : For Assesment and Diagnosis of ADHD, various method such as interview with parents, child and teacher, behavior observation, behavior rating scales and neuropsychological test are used. The structured interview consists of the restrictive questions and response, and then have diagnostic algorithm, consequently can be used by untrained clinicians. Of the structured interview, standardization of K-SADS in Korean version is finished. Behavior rating scales, the form of parent, teacher and self-report questionnaires, are used as diagnosis and treatment evaluation of ADHD. Behavior rating scales consist of both ADHD-specific scales and broad-band scales designed to screen for various symptoms (including ADHD symptoms). ADHD-specific scales are useful in differential diagnosis, discrimination of subtype, treatment evaluation, However, broad-band scales are useful in preliminary examination. The neuropsychological tests can evaluate attention deficit and effect of attention deficit on cognitive function and academic performance. The neuropsychological tests also used in diagnosis and treatment evaluation of ADHD. Conclusion : For Assesment and Diagnosis of ADHD, various method are used, especially behavior rating scales are both useful and simple tool for diagnosis and treatment evaluation.

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A Verification about the Formation Process of Filter Bubble with Personalization Algorithm (개인화 알고리즘으로 필터 버블이 형성되는 과정에 대한 검증)

  • Jun, Junyong;Hwang, Soyoun;Yoon, Youngmi
    • Journal of Korea Multimedia Society
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    • v.21 no.3
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    • pp.369-381
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    • 2018
  • Nowadays a personalization algorithm is gaining huge attention. It gives users selective information which is helpful and interesting in a deluge of information based on their past behavior on the internet. However there is also a fatal side effect that the user can only get restricted information on restricted topics selected by the algorithm. Basically, the personalization algorithm makes users have a narrower perspective and even stronger bias because users have less chances to get views of opponent. Eli Pariser called this problem the 'filter bubble' in his book. It is important to understand exactly what a filter bubble is to solve the problem. Therefore, this paper shows how much Google's personalized search algorithm influences search result through an experiment with deep neural networks acting like users. At the beginning of the experiment, two Google accounts are newly created, not to be influenced by the Google's personalized search algorithm. Then the two pure accounts get politically biased by two methods. We periodically calculate the numerical score depending on the character of links and it shows how biased the account is. In conclusion, this paper shows the formation process of filter bubble by a personalization algorithm through the experiment.

Harmonic Elimination and Optimization of Stepped Voltage of Multilevel Inverter by Bacterial Foraging Algorithm

  • Salehi, Reza;Vahidi, Behrooz;Farokhnia, Naeem;Abedi, Mehrdad
    • Journal of Electrical Engineering and Technology
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    • v.5 no.4
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    • pp.545-551
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    • 2010
  • A new family of DC to AC converters, referred to as multilevel inverter, has received much attention from industries and researchers for its high power and voltage applications. One of the conventional techniques for implementing the switching algorithm in these inverters is optimized harmonic stepped waveform (OHSW). However, the major problem in using this technique is eliminating low order harmonics by solving the nonlinear and complex equations. In this paper, a new approach called the "bacterial foraging algorithm" (BFA) is employed. This algorithm eliminates and optimizes the harmonics in a multilevel inverter. This method has higher speed, precision, and convergence power compared with the genetic algorithm (GA), a famous evolutionary algorithm. The proposed technique can be expanded in any number of levels. The purpose of optimization is to remove some low order harmonics, as well as to ensure the fundamental harmonic retained at the desired value. As a case study, a 13-level inverter is chosen. The comparison results by MATLAB software between the two optimization methods (BFA and GA) have shown the effectiveness and superiority of BFA over GA where convergence is desired to achieve global optimum.