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作者： Li, Jianhui Aba Teachers College Sichuan Province Wenchuan623000 China

In the era of big data, the rapid advancements in information technology have made the excavation and analysis of data resources crucial for various industries. Within this context, physical education (PE) plays a pivotal role in fostering students’ physical fitness and resilient willpower. Establishing an effec-tive evaluation system and enhancing data analysis techniques hold significant importance in elevating teaching quality and fostering the holistic development of students. This article introduces a PE evaluation framework that leverages big data analysis. By developing a PE simulation evaluation system, it enables the comprehensive collection, purification, interpretation, and feedback of sports-related data. Utilizing visualization technology, the analysis outcomes are presented in a user-friendly manner, thereby aiding teachers in making informed teaching deci-sions and bolstering the optimization of sports teaching practices in universities. Experimental findings reveal that this system can significantly enhance the quality of PE instruction, assist students in gaining a deeper understanding of their PE learning progress, and spark their interest and motivation in learning. Addition-ally, it provides teachers with an expanded arsenal of teaching resources and tools, promoting personalized teaching and boosting teaching efficacy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： data processing methods Physical Education Simulation Evaluation System

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Switching data-processing methods in a control loop: Trade-off between delay and probability of data acquisition

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IFAC-PapersOnLine 2016年第22期49卷 274-279页

作者： van Horssen, E.P. Antunes, D. Heemels, W.P.M.H. Control System Technology Group Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands

Many control applications, such as vision-based control, require data-processing methods to distill sensor information. This data-processing introduces several undesired effects in the control loop, such as delays, the probability of not acquiring information, and measurement inaccuracies. Often, these effects obey a trade-off. For example, the probability of acquiring control-relevant information, related to the probability of data-loss, is typically higher if a larger delay is allowed. While a single processing method with a reasonable trade-off is typically selected, we propose instead a solution to switch between data-processing methods with different delays and corresponding data-loss probabilities. We prove that the proposed method achieves a better LQG-type performance when compared to the individual methods. A simulation considering a second-order system illustrates the advantages of the proposed method. © 2016

关键词： data handling data acquisition data processing Delay control systems Economic and social effects Probability Time delay Control applications data processing methods Information loss Optimal controls Second order systemss Self triggered controls Switched system Vision based control

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data analysis methods and applications of the eddy current diagnostic system in the Keda Torus eXperiment device

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JOURNAL OF INSTRUMENTATION 2024年第1期19卷 P01004页

作者： Chen, Zheng Tao, Zhen Yolbarsop, Adil Li, Hong Zhang, Yuan Yan, Wentan Rao, Xianhao Ren, Shunrong Tian, Furen Mao, Wenzhe Wei, Zian Liu, Zixi Zhou, Chu Liu, Adi Lan, Tao Xie, Jinlin Zhou, Haiyang Wen, Xiaohui Wang, Hai Zhuang, Ge Xiao, Chijin Ding, Weixing Liu, Wandong Univ Sci & Technol China KTX Lab 443 Huangshan Rd Hefei Anhui Peoples R China Univ Sci & Technol China Dept Plasma Phys & Fus Engn 443 Huangshan Rd Hefei Anhui Peoples R China Univ Saskatchewan Plasma Phys Lab Saskatoon SK Canada

Since the establishment of the eddy current diagnostic system within the Keda Torus eXperiment (KTX) device, it has unveiled many applications. Recent developments have introduced innovative data analysis techniques alongside compelling experimental results, underscoring the necessity for a comprehensive summary of the system's data analysis approaches and broad applications. Notable features of the system encompass exceptional precision, the ability to encompass shell currents on the entirety of the closed boundary, vector detection of shell currents, and measurement of diverse physical quantities. In terms of data analysis methodologies, meticulous scrutiny of the null field region is conducted, and we reveal a distinctive characteristic within the complex shell current signals, namely the asymmetry of the amplitudes of +/- n Fourier coefficients. Moreover, the Hodge decomposition emerges as a pivotal technique, allowing for the distinctive separation of shell currents into three orthogonal components based on their distinct spatial topological properties. With regard to practical applications, an in-depth examination of the vector potential and magnetic helicity flux densities are presented in detail, further highlighting the far-reaching utility of the system's capabilities.

关键词： data processing methods Plasma diagnostics - probes

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Energy calibration based on ridge lines in scatter plots

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JOURNAL OF INSTRUMENTATION 2025年第4期20卷

作者： Li, Shuo Lyu, Xudong Li, Xinyu Huazhong Univ Sci & Technol Dept Biomed Engn Wuhan Hubei Peoples R China Raycan Technol Co Ltd Suzhou Jiangsu Peoples R China

In applications such as PET and proton therapy monitoring, MVT and TOT methods have played a significant role. However, these methods face issues such as energy nonlinearity and inconsistent performance across different energy ranges. The challenge of investigating and resolving these issues has become urgent. This paper proposes a nonlinear calibration framework based on a 3D energy spectrum surface and diffusion equations, significantly improving the energy resolution and calibration accuracy of high-energy radiation detection systems. To address this challenge, this work establishes a foundation using the joint probability density surface of the acquisition system's input and output energies, along with the probability density and energy transfer equation. From this foundation, a transfer equation describing the energy input-output relationship is derived, and subsequently, a ridge line equation is developed for energy calibration. This approach results in an improvement in linearity from -5.11%, obtained via empirical scatter plot fitting, to -1.18%.

关键词： data processing methods Performance of High Energy Physics Detectors data acquisition concepts Electronic detector readout concepts (solid-state)

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Nanosecond hardware regression trees in FPGA at the LHC

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NUCLEAR INSTRUMENTS & methods IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2025年 1072卷

作者： Serhiayenka, Pavel Roche, Stephen T. Carlson, Benjamin T. Hong, Tae Min Univ Pittsburgh Dept Phys & Astron Pittsburgh PA 15260 USA St Louis Univ Sch Med St Louis MO USA Westmont Coll Dept Phys & Engn Santa Barbara CA USA

We present a generic parallel implementation of the decision tree-based machine learning (ML) method in hardware description language (HDL) on field programmable gate arrays (FPGA). A regression problem in high energy physics at the Large Hadron Collider (LHC) is considered: the estimation of the magnitude of missing transverse momentum using boosted decision trees (BDT). A forest of twenty decision trees each with a maximum depth often using eight input variables of 16-bit precision is executed with a latency of less than 10 ns using O(0.1%) resources on Xilinx UltraScale+ VU9P - approximately ten times faster and five times smaller compared to similar designs using high level synthesis (HLS) - without the use of digital signal processors (DSP) while eliminating the use of block RAM (BRAM). We also demonstrate a potential application in the estimation of muon momentum for ATLAS RPC at the High-Luminosity LHC (HL-LHC).

关键词： data processing methods data reduction methods Digital electronic circuits Trigger algorithms Trigger concepts and systems (hardware and software)

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Edge detection and depth evaluation of CFRP internal delamination defects based on differential image frequency domain preprocessing

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JOURNAL OF INSTRUMENTATION 2025年第1期20卷

作者： Zhou, Guangyu Fu, Yu Zhang, Zhijie Yin, Wuliang North Univ China Sch Instrument & Elect 3 Xueyuan Rd Taiyuan Peoples R China Shanxi Open Univ Inst Technol 108 Qianfeng north Rd Taiyuan Peoples R China Univ Manchester Sch Elect & Elect Engn Oxford Rd Manchester M13 9PL England

Carbon fiber reinforced polymers (CFRP) are widely used in fields such as aviation and aerospace. However, subtle defects can significantly impact the material's service life, making defect detection a critical priority. This paper presents a method for detecting delamination defects in carbon fiber reinforced composites (CFRP) using line laser infrared thermography. A preprocessing approach combining differential thermography and frequency-domain filtering is proposed to effectively eliminate the trailing artifacts caused by line laser scanning, resulting in defect feature images with an improved signal-to-noise ratio. Utilizing the preprocessed frequency-domain magnitude image data, an improved Fuzzy C-Means clustering segmentation algorithm is developed, achieving high-precision edge detection of layered defects with an average accuracy of 95.0%. Furthermore, defect depth classification based on the frequency-domain magnitude data is performed using the K-Nearest Neighbor (KNN) algorithm, yielding an average accuracy of 98.8%. These results validate the effectiveness of the proposed algorithms for defect edge detection and depth assessment.

关键词： data processing methods Detection of defects Image processing Lasers

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Spectrum analysis for identification of nuclides at radiological crime scene

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JOURNAL OF INSTRUMENTATION 2025年第3期20卷 C03004-C03004页

作者： Kaissas, I. Themistokleous, I. Karafasoulis, K. Xanthos, S. Kyriakis, A. Aristotle Univ Thessaloniki Fac Engn Sch Elect & Comp Engn Thessaloniki 54124 Greece Hellen Army Acad Div Nat Sci & Applicat Vari Attikis 16673 Greece Int Hellen Univ Dept Ind Engn & Management Thessaloniki 57400 Greece Natl Ctr Sci Res Demokritos Inst Nucl & Particle Phys Aghia Paraskevi 15341 Greece

Gamma-ray spectroscopy is an essential technique for identifying the composition of radioactive materials. This work presents a detailed algorithm for analysing gamma-ray spectra, focusing on peak detection, energy calibration, efficiency calibration and nuclide identification. The algorithm includes a systematic approach to match observed peaks with known nuclides, following a peak detection method, efficiency and energy calibration methods. The algorithm attempts to provide spectral analysis and nuclides identification on-site with portable spectroscopic devices. Therefore, it is tested with portable HPGe and CZT detectors demonstrating its ability to reliably identify isotopes in complex spectra, derived by multi radioactive sources identification scenarios. A conventional energy calibration is performed on the spectrum data to convert channels to energy values. Additional calibration is performed to adjust the height of the photopeaks, considering the efficiency curve of each detector. The algorithm identifies possible nuclides associated with each peak by searching for nuclides within a specified range of energy interval, minimum half-life, and minimum fraction yield of the photopeak. The matching process involves comparing photopeaks of the spectrum under investigation with a complete dataset of energies of gamma-rays and their emitters. To exclude false positive identifications of nuclides, a criterion considers a certain number of the most intense gamma-ray energies that each possible nuclide emits and investigates whether these energies are correlated with the photopeaks. In addition, another criterion checks the height of the photopeaks based on their fraction yield. The algorithm attempts to offer a solution for field applications, enhancing radiological crime-scene investigations and environmental monitoring.

关键词： data processing methods Spectrometers gamma-spectroscopy Nuclide identification Nuclear security

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Simulated near-field radioactive source localization in 3D with Coded Aperture and Convolutional Neural Networks

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JOURNAL OF INSTRUMENTATION 2025年第1期20卷

作者： Karafasoulis, K. Kaissas, I. Papadimitropoulos, C. Potiriadis, K. Lambropoulos, C. P. Hellen Army Acad Dept Nat Sci & Applicat Evelpidon Ave Vari Attikis 16673 Greece Aristotle Univ Thessaloniki Fac Engn Dept Elect & Comp Engn Egnatia 54124 Thessaloniki Greece Natl & Kapodistrian Univ Athens Dept Aerosp Sci & Technol Psachna Evia 34400 Greece Greek Atom Energy Commiss Patriarxou Grigoriou & Neapoleos Aghia Paraskevi Greece

Coded Aperture 7-cameras have been extensively used in applications ranging from astrophysics to nuclear medicine for imaging radioactive source distributions. These devices allow the identification of the direction of 7-emitters by analyzing the shadow patterns projected onto pixelated detectors. In this work, we propose a novel approach based on Convolutional Neural Networks (CNNs) for accurately localizing radioactive sources in 3D using one coded aperture gamma camera. The CNN is trained using simulated shadowgrams generated by a custom simulation tool, with sources placed at various positions within the near-field, ranging from 20 cm to 120 cm from the detector. Unlike previous methods that focused on estimating angular coordinates, our model also accurately estimates the distance of the source, achieving a distance estimation accuracy of 10 mm, in addition to determining the polar and azimuthal angles. This capability is particularly relevant for medical imaging applications, where precise localization of radioactive sources is crucial. The results of our study demonstrate the potential of CNN-based algorithms in improving the accuracy and reliability of single-detector systems in near-field radioactive source localization.

关键词： data processing methods Gamma camera, SPECT, PET PET/CT, coronary CT angiography (CTA) Image reconstruction in medical imaging Medical-image reconstruction methods and algorithms, computer-aided software

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Feature extraction on the TRD readout FPGA with HLS in the mCBM experiment

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JOURNAL OF INSTRUMENTATION 2025年第3期20卷 C03047-C03047页

作者： Schledt, D. Blume, C. Kebschull, U. Goethe Univ Frankfurt Max Von Laue Str 1 D-60438 Frankfurt Germany

The CBM experiment uses a free streaming DAQ with interaction rates up to 10MHz resulting in data rates, which exceed storage capabilities, necessitating online processing. The SPADIC ASIC of the CBM-TRD provides hit messages with oscilloscope-like sampling of the detector data, encoding valuable information. To speed up data unpacking and computing time, feature extraction is moved to the readout FPGA. In the mCBM experiment this approach is tested, demonstrating the benefits of HLS and C++ template programming for algorithm development. Results show resolution improvements and significant reductions in data volume and unpacking speed at the computing cluster.

关键词： data processing methods data acquisition concepts Digital signal processing (DSP) Pattern recognition, cluster finding, calibration and fitting methods

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Residual analysis based neutron-gamma pulses segregation of liquid scintillator detector

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JOURNAL OF INSTRUMENTATION 2025年第1期20卷

作者： Paul, R. K. Bhattacherjee, R. Bitragunta, S. Das, A. Banerjee, A. Dhara, P. Samanta, T. Pal, S. Variable Energy Cyclotron Ctr 1-AF-Bidhannagar Kolkata 700064 W Bengal India Homi Bhabha Natl Inst Training Sch Complex Mumbai 400094 India BITS Pilani Dept Elect & Elect Engn Pilani 333031 Rajasthan India Jadavpur Univ Bidhannagar LB BlockSect 3 Kolkata 700106 W Bengal India

An innovative residual analysis based method is proposed for pulse shape discrimination and segregation of neutron and gamma pulses of liquid scintillator-based detector (BC501A). This study develops a simple and efficient algorithm for discrimination of neutrons and gammas from mixed environment and then segregate the neutron and gamma pulses into two label datasets. This method involves analyzing the residuals between the measured pulse and the reference gamma pulse in normalized scale. By examining these residuals, users can identify characteristics unique to each type of radiation. The pulse shape discrimination performance obtained for a 5 inches by 5 inches (length by diameter) liquid scintillator detector using this residual method is found to be 20% better compared to that obtained using traditional charge comparison method.

关键词： data processing methods Digital signal processing (DSP) Particle identification methods Scintillators, scintillation and light emission processes (solid, gas and liquid scintillators)

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