• Title/Summary/Keyword: system-identification methods

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A Study of PCI (Physical Cell Identification) Assignment in LTE (Long Term Evolution) SON (Self-Organization Network) (LTE 자가 구성 네트워크망에서 물리적 셀 ID할당 방법 연구)

  • Yang, Mochan
    • Journal of IKEEE
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    • v.23 no.3
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    • pp.941-946
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    • 2019
  • In this paper, the author analyzed the PCI (Physical Cell Identification) allocation methods in the LTE (Long Term Evolution) SON (Self Organization Network) environment. A variety of techniques have been proposed for how to allocate PCI, and the LTE standard fundamentally explained that collision between a cell and neighbor cells arise while a cell assign the PCI. Therefore, in this paper, the author examined the scenarios of PCI collision, weak collision, and confusion proposed by LTE specification. In addition, the cell central approach and the distributed approach were discussed as solutions for each scenario. In this paper, the author reviewed the approach of graphic coloring technique which was studied recently and explained the strategy of central approach.

Optimal sensor placements for system identification of concrete arch dams

  • Altunisik, Ahmet Can;Sevim, Baris;Sunca, Fezayil;Okur, Fatih Yesevi
    • Advances in concrete construction
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    • v.11 no.5
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    • pp.397-407
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    • 2021
  • This paper investigates the optimal sensor placements and capabilities of this procedure for dynamic characteristics identification of arch dams. For this purpose, a prototype arch dam is constructed in laboratory conditions. Berke arch dam located on the Ceyhan River in city of Osmaniye is one of the highest arch dam constructed in Turkey is selected for field verification. The ambient vibration tests are conducted using initial candidate sensor locations at the beginning of the study. Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification methods are used to extract experimental dynamic characteristics. Then, measurements are repeated according to optimal sensor locations of the dams. These locations are specified using the Effective Independence Method. To determine the optimal sensor locations, the target mode shape matrices which are obtained from ambient vibration tests of the selected dam with a large number of accelerometers are used. The dynamic characteristics obtained from each ambient vibrations tests are compared with each other. It is concluded that the dynamic characteristics obtained from initial measurements and those obtained from a limited number of sensors are compatible with each other. This situation indicates that optimal sensor placements determined by the Effective Independence Method are useful for dynamic characteristics identification of arch dams.

A study on Improving the Performance of Anti - Drone Systems using AI (인공지능(AI)을 활용한 드론방어체계 성능향상 방안에 관한 연구)

  • Hae Chul Ma;Jong Chan Moon;Jae Yong Park;Su Han Lee;Hyuk Jin Kwon
    • Journal of the Korean Society of Systems Engineering
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    • v.19 no.2
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    • pp.126-134
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    • 2023
  • Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.

A combined spline chirplet transform and local maximum synchrosqueezing technique for structural instantaneous frequency identification

  • Ping-Ping Yuan;Zhou-Jie Zhao;Ya Liu;Zhong-Xiang Shen
    • Smart Structures and Systems
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    • v.33 no.3
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    • pp.201-215
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    • 2024
  • Spline chirplet transform and local maximum synchrosqueezing are introduced to present a novel structural instantaneous frequency (IF) identification method named local maximum synchrosqueezing spline chirplet transform (LMSSSCT). Namely spline chirplet transform (SCT), a transform is firstly introduced based on classic chirplet transform and spline interpolated kernel function. Applying SCT in association with local maximum synchrosqueezing, the LMSSSCT is then proposed. The index of accuracy and Rényi entropy show that LMSSSCT outperforms the other time-frequency analysis (TFA) methods in processing analytical signals, especially in the presence of noise. Numerical examples of a Duffing nonlinear system with single degree of freedom and a two-layer shear frame structure with time-varying stiffness are used to verify the effectiveness of structural IF identification. Moreover, a nonlinear supported beam structure test is conducted and the LMSSSCT is utilized for structural IF identification. Numerical simulation and experimental results demonstrate that the presented LMSSSCT can effectively identify the IFs of nonlinear structures and time-varying structures with good accuracy and stability.

Application of a Neuro-Fuzzy System Trained by Evolution Strategy to Nonlinear System Identification (진화전략으로 학습되는 뉴로퍼지 시스템의 비선형 시스템 동정에의 응용)

  • Jeong, Seong-Hun
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.39 no.1
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    • pp.23-34
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    • 2002
  • This paper proposes a new neuro-fuzzy system that is fast trained by evolution strategy and describes application results of the proposed system to nonlinear system identification to show its usefulness. As training methods of neuro-fuzzy systems, modified error back-propagation algorithms and genetic algorithms have been used so far. However, the former has some drawbacks such as long training time, falling to local optimum, and experimental selecting of learning rates and the latter has difficulty in precise searching solutions because genetic algorithms represents solutions as genotype individuals. The evolution strategy we used can do precise search because its individuals are represented as phenotype real values, it seldom falls into a local optimum, and its training speed is faster than error back-propagation algorithms. We apply our neuro-fuzzy systems to nonlinear system identification. It was found from experiments that training speed is fast and the training results were considerably good.

Analysis of Pattern Identification and Related Symptoms on Idiopathic Short Stature -Focusing on Traditional Chinese Medicine Literature- (특발성 저신장의 변증 유형 및 변증별 증상 분석 -중의학 논문을 중심으로-)

  • Lee, Boram;Kwon, Chan-Young;Jang, Soobin
    • The Journal of Pediatrics of Korean Medicine
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    • v.35 no.1
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    • pp.1-17
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    • 2021
  • Objectives We aimed to analyze traditional Chinese medicine (TCM) literatures in regards to the pattern identification and related symptoms of idiopathic short stature (ISS). Methods We searched relevant literatures published up to September 29, 2020 through three Chinese electronic databases. We performed frequency analysis of the selected studies by extracting information on pattern identification, clinical symptoms, and TCM treatments presenting pattern identification of ISS. Results Sixteen studies were included. Spleen deficiency, kidney deficiency, dual deficiency of spleen-kidney, and liver-kidney yin deficiency were frequently reported. Clinical symptoms of the spleen deficiency include sallow complexion, body constituent weakness, anorexia, lack of qi and no desire to speak, and loose stools. Herbal medicines (HMs) such as Sijunzi-tang were frequently reported. Clinical symptoms of the kidney deficiency include cold limb and fear of cold, soreness and weakness of waist and knees, and clear and long urine. HMs such as Bishendihuang-wan were frequently reported. Clinical symptoms of the dual deficiency of spleen-kidney include body constituent weakness, spirit lassitude and lack of strength, anorexia, soreness and weakness of waist and knees, and cold limb and fear of cold. HMs such as Sijunzi-tang plus Bishendihuang-wan were frequently reported. Clinical symptoms of the liver-kidney yin deficiency include tidal fever and night sweating, heat in the palms and soles, dizziness, and dry throat. HMs such as Liuweidihuang-wan were frequently reported. Conclusions This was the first study to analyze the frequency of pattern identification and related symptoms on ISS. In the future, a standardized Korean medicine pattern identification system should be established.

Operational modal analysis of reinforced concrete bridges using autoregressive model

  • Park, Kyeongtaek;Kim, Sehwan;Torbol, Marco
    • Smart Structures and Systems
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    • v.17 no.6
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    • pp.1017-1030
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    • 2016
  • This study focuses on the system identification of reinforced concrete bridges using vector autoregressive model (VAR). First, the time series output response from a bridge establishes the autoregressive (AR) models. AR models are one of the most accurate methods for stationary time series. Burg's algorithm estimates the autoregressive coefficients (ARCs) at p-lag by reducing the sum of the forward and the backward errors. The computed ARCs are assembled in the state system matrix and the eigen-system realization algorithm (ERA) computes: the eigenvector matrix that contains the vectors of the mode shapes, and the eigenvalue matrix that contains the associated natural frequencies. By taking advantage of the characteristic of the AR model with ERA (ARMERA), civil engineering can address problems related to damage detection. Operational modal analysis using ARMERA is applied to three experiments. One experiment is coupled with an artificial neural network algorithm and it can detect damage locations and extension. The neural network uses a specific number of ARCs as input and multiple submatrix scaling factors of the structural stiffness matrix as output to represent the damage.

An Analytical Investigation on the Dancheong Pigments by Hyperspectral Technique: Focusing on Green Colors

  • Jung, Cham Hee;Lee, Han Hyoung;Song, You Na;Min, Kyeong Jin;Chung, Yong Jae
    • Journal of Conservation Science
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    • v.35 no.4
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    • pp.345-361
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    • 2019
  • This study demonstrates the application of hyperspectral analysis as a pigment identification method for modern and contemporary Dancheong, the polychrome surface on traditional Korean wooden buildings. In particular, green pigments are the focus of this study. Green pigments in modern and contemporary Dancheong have the largest variation of materials and show a noticeable timeline. Thus, they are most suitable for estimating the manufacture or restoration period of Dancheong. Hyperspectral analysis is a noncontact, long-distance measurement technique that has advantages in the field of Dancheong analysis. It is capable of identifying both organic and inorganic pigments, unlike existing analysis methods. For this experiment, green and other pigments used during the modern and contemporary era were selected and made into painted samples under various mixing conditions that reflect their actual uses. Through hyperspectral analysis, their reflectance characteristics were observed, which enables the derivation of four main features that can distinguish the type of pigments used for color mixture. Based on these, a pigment identification system was designed in the form of a flowchart, and its utility was confirmed through site application. Despite some limitations at this stage, the technique can be complemented by considering proper measurement methods or the continuous accumulation of samples and data. If a database on various materials, mixing ratios, painting techniques, and other external interference factors is developed in future research, it would provide the foundation for a faster and safer analysis environment of Dancheong sites.

An Automatic Identification System of Biological Resources based on 2D Barcode and UCC/EAN-128 (2차원 바코드와 UCC/EAN-128을 이용한 생물자원 자동인식시스템)

  • Chu, Min-Seok;Ryu, Keun-Ho;Kim, Jun-Woo;Kim, Hung-Tae;Han, Bok-Ghee
    • The KIPS Transactions:PartD
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    • v.15D no.6
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    • pp.861-872
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    • 2008
  • As rapid development of computing environment, field of automatic identification research which interoperates with various physical objects and digital information is making active progress. Although the automatic identification system is widely used in various industries, application of automatic identification system in the field of medical health doesn't reach other industry. Therefore research in medical health supplies such as medical equipment, blood, human tissues and etc is on progress. This paper suggests the application of automatic identification technology for biological resources which is core research material in human genome research. First of all, user environment requirements for the introduction of automatic identification technology are defined and through the experiments and research, barcode is selected as a suitable tag interface. Data Matrix which is 2D barcode symbology is chosen and data schema is designed based on UCC/EAN-128 for international defecto standard. To showapplicability of proposed method when applied to actual environment, we developed, tested and evaluated application as following methods. Experiments of barcode read time at 196 and 75 below zero which is actual temperature where biological resources are preserved resulted read speed of average of 1.6 second and the data schema satisfies requirements for the biological resources application. Therefore suggested method can provide data reliability as well as rapid input of data in biological resources information processing.

Structural System Parameter Estimation using Strain Output Feedback (스트레인 출력 되먹임을 이용한 구조 시스템 계수 추정)

  • Ha, Jae-Hoon;Park, Youn-Sik;Park, Young-Jin
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.124-127
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    • 2005
  • As computer capability and test skill become more and more advanced, finite element method and modal test are being widely applied in engineering design. In order to correlate and reconcile the inevitable discrepancies between the analytical and experimental models, many techniques have been developed. Among these methods, multiple-system methods are known as the effective tools in that they can supply the rich modal data available which are experimentally obtained. These abundant modal data can help structural system parameters estimated well. Multiple-system methods can be classified into the structural modification methods and feedback controller methods. The structural modification methods need the physical attachment of structures and their concept may limit the application of them. To overcome this drawback, the feedback controller methods are addressed which enable us to get more modal data without the structural change. Mode decoupling controller(MDC), one of them, is to use acceleration out)ut feedback to perturb an open-loop system. The output feedback controller generally cannot guarantee the stability of a closed-loop system. However, MDC can solve this problem under the certain constraints. So far, MDC utilizes accelerations as the sensor signals. In this research, strain sensors are going to be picked up to apply to the MDC. Strain output is recently used for structural system identification due to the drastically improved and miniaturized strain sensor. In this paper, we show that the MDC using strain output has differences compared with acceleration output in estimating the structural system parameters. The associated simulation is performed to demonstrate the above mentioned characteristics.

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