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Nanjing Youdian Xueyuan Xuebao/Journal of Nanjing Institute of Posts and Telecommunications 2005年第5期25卷 26-30+34页

作者： Wang, Mei Sha, Ai-Jun Yuan, Zhi-Feng College of Communication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing 210003 China

Based on TMS320C5402 DSPs, this paper implemented and promoted four repres + entative encryption algorithms, including DES (data encryption standard) algorithm, SHA-1 (secure hash standard algorithm), MD5 (message-digest) algorithm and RSA public key algorithm. The main goal is to provide a general platform for decryption to meet the real-time requirement in certain occasions.

关键词： algorithm optimization Date encryption standard algorithm Message digest RSA Secure hash algorithm

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Effects of hydration parameters on chemical properties of biocrudes based on machine learning and experiments

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BIORESOURCE TECHNOLOGY 2022年第0期350卷 126923-126923页

作者： Zhou, Xinxing Zhao, Jun Chen, Meizhu Wu, Shaopeng Zhao, Guangyuan Xu, Song Wuhan Univ Technol State Key Lab Silicate Mat Architectures Wuhan 430070 Peoples R China Shanxi Transportat Technol Res & Dev Co Ltd Key Lab Highway Construct & Maintenance Technol L Taiyuan 030032 Peoples R China Hong Kong Baptist Univ Inst Bioresource & Agr Dept Biol Hong Kong Peoples R China Univ Waterloo Dept Civil & Environm Engn Waterloo ON N2L 3G1 Canada Fuzhou Univ Coll Civil Engn Fuzhou 350103 Peoples R China McMaster Univ Dept Civil Engn Hamilton ON L8S 4L8 Canada

To investigate the effects of temperature and biomass concentration of Hydrothermal liquefaction (HTL) on chemical properties of biocrudes, machine learning (ML) was used to predict the weight of hydration parameters on the properties of biocrudes. The elemental compositions, molecular weights, functional groups, thermal degradation, molecular structure of biocrudes were studied. The optimum yield of biocrudes was 65% and the highest heat value reached up to 34.28 kJ/g, showing comparable fuel properties. It was found that the hydration temperature significantly affects the elemental components, functional groups and molecular weight and structures of biocrudes. In addition, biomass concentration also affect the functional groups and structures of biocrudes. ML results indicated that Support Vector Machine Linear Kernel method is suitable for heat value prediction.

关键词： Woody biocrude Hydrothermal liquefaction Machine learning Chemical property algorithm optimization

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The application of virtual reality technology in the teaching of clarinet music art under the mobile wireless network learning environment

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ENTERTAINMENT COMPUTING 2024年 49卷

作者： Gao, Hongjiao Li, Fan Xinzhou Normal Univ Dept Mus Xinzhou 034000 Shanxi Peoples R China Ningbo Univ Conservatory Mus Ningbo 315211 Zhejiang Peoples R China

The traditional education model is undergoing tremendous changes, and network education has gradually developed and matured. This paper first gives an overview of the development history of the clarinet and the structure of the clarinet and then starts with the performance of the clarinet. This paper analyses and solves the situations that students are prone to encounter in teaching and expresses some opinions on the teaching of performance methods;also gives a brief overview of the psychology of going on stage. Combined with the above, some discussions are made on the teaching of performance methods. Performance requires not only skills but also music. Performance summarizes the characteristics and styles of music in various periods from the classical period to the century, and then discusses how the performer forms his performance style;the performance style is the re-creation and re-creation of the performer based on being loyal to the author's intention. This article compares and studies the performance of the clarinet before the 20th century and the performance of the clarinet today, and deeply explores the reasons why the clarinet performance method has formed the current performance method after a long evolution. The experimental results prove that virtual reality technology has made positive attempts and breakthroughs in the field of clarinet music art teaching. It has created an environment of "self-learning", and the traditional learning method of "teaching to promote learning" has been replaced by learners through their learning. Interaction with the information environment to obtain a new learning method of knowledge and skills, the optimized local matrix decomposition recommendation algorithm can greatly improve problems such as expensive musical instruments and lessons, scarce teachers, and lack of facilities, making the traditional clarinet Music arts teaching more diverse.

关键词： Virtual reality technology Network learning Clarinet music art teaching Local matrix factorization recommendation algorithm optimization

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Optimizing the Vegetation Health Index for Agricultural Drought Monitoring: Evaluation and Application in the Yellow River Basin

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REMOTE SENSING 2024年第23期16卷 4507-4507页

作者： Hang, Qinghou Guo, Hao Meng, Xiangchen Wang, Wei Cao, Ying Liu, Rui De Maeyer, Philippe Wang, Yunqian Qufu Normal Univ Sch Geog & Tourism Rizhao 276826 Peoples R China Sino Belgian Joint Lab Geoinformat Rizhao 276826 Peoples R China Sino Belgian Joint Lab Geoinformat B-9000 Ghent Belgium Univ Ghent Dept Geog B-9000 Ghent Belgium

The ecological environment of the Yellow River Basin in China is characterized by drought, which has been exacerbated by global warming. It is critical to keep accurate track of the region's agricultural drought conditions. To enhance the vegetation health index (VHI), the optimal time scale for the standardized precipitation evapotranspiration index (SPEI) was determined by using the maximum correlation coefficient method, and the calculation method for VHI was optimized. The contributions of the vegetation condition index (VCI) and the temperature condition index (TCI) to the VHI were scientifically optimized, leading to the development of the optimal VHI (VHIopt). Soil moisture anomaly (SMA) and the SPEI were employed for assessing the performance of VHIopt. Furthermore, the temporal and spatial evolution of agricultural drought in the Yellow River Basin (YRB) was analyzed using VHIopt. The results indicate the following: (1) In the YRB, the optimal contribution of the VCI to the VHI is lower than that of the TCI. (2) The drought monitoring accuracy of VHIopt in forests, grasslands, croplands, and other vegetation types exceeds that of the original VHI (VHIori). Additionally, it demonstrates a high level of consistency with the SMA and the SPEI03 regarding spatial and temporal characteristics. (3) Agricultural drought in the YRB is gradually diminishing;however, significant regional differences remain. Generally, the findings of this study highlight that VHIopt is better suited to the specific climate and vegetation conditions of the Yellow River Basin, enhancing its effectiveness for agricultural drought monitoring in this region.

关键词： vegetation health index yellow river basin algorithm optimization drought monitoring

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Estimation of Leaf Nitrogen Content in Wheat Using New Hyperspectral Indices and a Random Forest Regression algorithm

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REMOTE SENSING 2018年第12期10卷 1940-1940页

作者： Liang, Liang Di, Liping Huang, Ting Wang, Jiahui Lin, Li Wang, Lijuan Yang, Minhua Jiangsu Normal Univ Sch Geog Geomat & Planning Xuzhou 221116 Jiangsu Peoples R China George Mason Univ Ctr Spatial Informat Sci & Syst Fairfax VA 22030 USA Cent South Univ Sch Geosci & Infophys Changsha 410083 Hunan Peoples R China

Novel hyperspectral indices, which are the first derivative normalized difference nitrogen index (FD-NDNI) and the first derivative ratio nitrogen vegetation index (FD-SRNI), were developed to estimate the leaf nitrogen content (LNC) of wheat. The field stress experiments were conducted with different nitrogen and water application rates across the growing season of wheat and 190 measurements were collected on canopy spectra and LNC under various treatments. The inversion models were constructed based on the dataset to evaluate the ability of various spectral indices to estimate LNC. A comparative analysis showed that the model accuracies of FD-NDNI and FD-SRNI were higher than those of other commonly used hyperspectral indices including mNDVI(705), mSR, and NDVI705, which was indicated by higher R-2 and lower root mean square error (RMSE) values. The least squares support vector regression (LS-SVR) and random forest regression (RFR) algorithms were then used to optimize the models constructed by FD-NDNI and FD-SRNI. The p-R-2 values of the FD-NDNI_RFR and FD-SRNI_RFR models reached 0.874 and 0.872, respectively, which were higher than those of the exponential and SVR model and indicated that the RFR model was accurate. Using the RFR inversion model, remote sensing mapping for the Operative Modular Imaging Spectrometer (OMIS) image was accomplished. The remote sensing mapping of the OMIS image yielded an accuracy of R-2 = 0.721 and RMSE = 0.540 for FD-NDNI and R-2 = 0.720 and RMSE = 0.495 for FD-SRNI, which indicates that the similarity between the inversion value and the measured value was high. The results show that the new hyperspectral indices, i.e., FD-NDNI and FD-SRNI, are the optimal hyperspectral indices for estimating LNC and that the RFR algorithm is the preferred modeling method.

关键词： hyperspectral remote sensing crop parameter inversion spectral index design derivative algorithm optimization

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A novel measurement strategy for explosion temperature field towards enhancing the fire process safety

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FIRE SAFETY JOURNAL 2024年 145卷

作者： Yu, Hao Sun, Yaru Liu, Yan Wang, Xiaofeng Huang, Fenglei Liu, Haipeng Beijing Inst Technol State Key Lab Explos Sci & Technol Beijing 100081 Peoples R China Beijing Inst Technol Chongqing Innovat Ctr Chongqing 401120 Peoples R China

Chemical explosives such as TNT are widely used in special scenarios, such as civil explosives, due to their simple preparation and high energy density. However, the temperature of the fireball produced by the explosion of these explosives is extremely high. Moreover, this approach may cause many casualties and economic losses if not prevented. To accurately measure the temperature of a transient explosion field and study its space-time distribution, a two-dimensional high-speed temperature measurement system was built based on blackbody radiation theory, high-speed photography, image Bayer array and improved interpolation algorithm. The explosive fireball produced in a static explosion test of 10 kg of TNT was measured within the shooting range. TNT was added with an auxiliary blackbody (tungsten). Compared to traditional explosion temperature measurement methods, the experimental results showed that the colorimetric temperature measurement method based on the improved interpolation algorithm and the addition of tungsten powder could more accurately measure the temporal and spatial distributions of the temperature field. This work can aid in the prevention in the accidents during the transportation, storage, and manufacturing of chemicals relevant to process industries.

关键词： Process safety Space-time distribution algorithm optimization Explosion temperature field

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Efficient federated learning algorithm using sparse ternary compression based on layer variation classification

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COMPUTER NETWORKS 2024年 247卷

作者： Liu, Yuanyuan Chen, Kexin Zhu, Lu East China Jiaotong Univ Inst Informat Engn Nanchang Peoples R China

Federated learning is a distributed machine learning technique that ensures user privacy and enables multiple clients to jointly train a shared global model without transmitting local data. However, the frequent exchange of model parameters between numerous clients and the server results in heavy network delay and bandwidth limitation in federated learning. In view of that, we propose an efficient algorithm for federated learning using sparse ternary compression based on layer variation classification(LVC). First, use layer variation as a metric to assess the significance of each layer of the model parameters, and after client training, categorize the model parameters into different levels by the layer variation and sensitivity analysis. Then, during the upstream and downstream transmission of model parameters, we assign corresponding sparse and ternary quantization ratios for different levels to maximize compression efficiency while preserving crucial parameters. Finally, on the server side, a majority-layer aggregation strategy is adopted to further reduce the communication cost. Experimental results from image classification tasks conducted on MNIST and Fashion-MNIST datasets demonstrate that proposed LVC algorithm achieves high accuracy with minimal communication cost, thereby striking an optimal balance between communication efficiency and accuracy.

关键词： Federated learning Communication efficiency Model sparsity Parameter quantization algorithm optimization

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Censored distributed space-time coding for wireless sensor networks

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2008年第unknown期2008卷 127689-1-127689-9-0页

作者： Yiu, S. Schober, R. Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada

We consider the application of distributed space-time coding in wireless sensor networks (WSNs). In particular, sensors use a common noncoherent distributed space-time block code (DSTBC) to forward their local decisions to the fusion center (FC) which makes the final decision. We show that the performance of distributed space-time coding is negatively affected by erroneous sensor decisions caused by observation noise. To overcome this problem of error propagation, we introduce censored distributed space-time coding where only reliable decisions are forwarded to the FC. The optimum noncoherent maximum-likelihood and a low-complexity, suboptimum generalized likelihood ratio test (GLRT) FC decision rules are derived and the performance of the GLRT decision rule is analyzed. Based on this performance analysis we derive a gradient algorithm for optimization of the local decision/censoring threshold. Numerical and simulation results show the effectiveness of the proposed censoring scheme making distributed space-time coding a prime candidate for signaling in WSNs. Copyright (C) 2008.

关键词： time coding algorithm optimization noncoherent Error propagation decision rule Distribute differential space-time coding space-time coding

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Optimized CT-TDLAS reconstruction performance evaluation of least squares with the polynomial-fitting method

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FRONTIERS IN PHYSICS 2022年 10卷

作者： Zhou, Wangzheng Xu, Zhekai Cui, Wei Wang, Zhenzhen Chong, Daotong Yan, Junjie Xi An Jiao Tong Univ Sch Energy & Power Engn State Key Lab Multiphase Flow Power Engn Xian Peoples R China AF Engn Univ Sci & Technol Plasma Dynam Lab Xian Peoples R China

Computed tomography-tunable diode laser absorption spectroscopy (CT-TDLAS) has been widely used in the diagnosis of the combustion flow field. Several optimized CT reconstruction algorithms such as iteration methods, transformation methods, and nonlinear least squares were applied. Considering the industrial application background, the performances of algebraic iteration reconstruction with the simultaneous algebra reconstruction technique (SART), Tikhonov regularization, and least squares with the polynomial fitting method were discussed in this study. For the mentioned algorithm, identical simulated reconstruction parameters that contained 32-path laser structures, assumed temperature distribution, and absorption databases were adopted to evaluate the reconstruction performance including accuracy, efficiency, and measurement of environment applicability. In this study, different CT reconstruction algorithms were also used to calculate the temperature distribution of the Bunsen burner flame. The different reconstruction results were compared with thermocouple detection data. With the theoretically simulated and experimental analysis, the least squares with the polynomial fitting technique has advantages in reconstruction accuracy, calculation efficiency, and laser path applicability for the measurement condition. It will be helpful in enhancing CT-TDLAS technique development.

关键词： CT-TDLAS SART Tikhonov regularization the polynomial fitting method algorithm optimization

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Volumetric flame reconstructions in an optical engine cylinder involving refraction and blockage

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MEASUREMENT SCIENCE AND TECHNOLOGY 2023年第7期34卷 074007-074007页

作者： Gao, Yu Ling, Chen Wu, Yue Wu, Haifeng Men, Wenqi Beijing Inst Technol Sch Mech Engn Beijing 100081 Peoples R China

Practical applications of computed tomography (CT) in optical engines require an advanced algorithm that can correct the light refraction via optical windows and reconstruct the 3D signal field partially blocked by structural obstacles. In this work, an advanced CT algorithm is designed for optical engines to simultaneously eliminate the imaging distortion by refraction and diminish the reconstruction errors using partial signal blocking. By combining the pinhole model and Snell's law, the ray tracings from discretized 3D voxels in the measurement domain to 2D pixels in the imaging planes are accurately calculated, thus restoring the distortion in recorded projections. Besides, by deciding the locations and numbers of voxels that actually participate in iterative CT calculation, the iterative update process of voxel intensity becomes independent of the blocked rays, reducing the reconstruction errors. The algorithm is then numerically validated by reconstructing a simulated signal phantom inside an optical cylinder with a lightproof obstacle between the phantom and a recording camera, which imitates the refraction and blocking conditions in practical optical engines. Moreover, experimental demonstration is performed by reconstructing practical premixed flames inside optical engines. Both the simulation and the experiment present significantly enhanced flame chemiluminescence reconstruction by applying the optimized CT algorithm compared to the original algorithm utilized in open space applications.

关键词： computed tomography refraction blockage algorithm optimization

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