Hybrid deep learning architecture for scalable and high-quality image compression by Mustafa Al-Khafaji, Nehad T. A. Ramaha

“…The framework enables multiresolution decomposition, texture-aware feature extraction, and adaptive region-based compression. …”
Get full text

Vessel Trajectory Data Compression Algorithm considering Critical Region Identification by Xinliang Zhang, Shibo Zhou

“…It combines the feature nodes from the crucial regions in the vessel’s trajectory with the results obtained from the sliding window algorithm, effectively compressing the vessel’s trajectory. …”
Get full text

Compressed sensing transformer unfolding network for high resolution image denoising by Jie Zhang, Wenxiao Huang, Miaoxin Lu, Linwei Li, Yongpeng Shen, Yanfeng Wang, Jinsong Du

“…Abstract In recent years, compressive sensing (CS) theory has garnered significant attention due to its advantages in high-resolution image processing. …”
Get full text

Image Super-Resolution via Adaptive Regularization Term of Compressed Sensing by Yintao Liu, Chao Ren, Hongjuan Shao, Qirui Liu, Yan Zhang

“…This feature has shown effectiveness in image super-resolution. …”
Get full text

Loading rate effects on infrasound characterization of uniaxial compression damage in marble by Yanbo ZHANG, Bo WANG, Peng LIANG, Xulong YAO, Guangyuan YU, Zhigang TAO

“…The calm period following emergence of maximum infrasonic energy could be utilized as a precursor feature indicating marble instability and failure occurrence. …”
Get full text

Analysis of reticulated dome with universal connector by Oleksandr Gilodo, Andrii Arsirii, Yuliia Somina

“… In order to investigate the stress-strain state of a 4 m diameter reticulated dome model, four series of glued wooden rods were prepared for centric and eccentric compression tests. The tests were carried out in the laboratory of the Department of Metal Wood and Plastic Structures. …”
Get full text

Research on Clustering Based PWR pin-by-pin Homogenization Parameters Compression Method by LI Tianya1, 2, LUO Qi3, YAO Dong2, HE Caiyun1, CAI Yun2, WANG Dan1, DUAN Yongqiang1, LIAO Hongkuan1, XIAO Peng2

“…In response to the phenomenon that using only one clustering feature may lead to clustering pins of different material types into one cluster, based on the fact that the material of the pin-cell is the most important feature of clustering, a significant deviation was introduced, therefore, this paper proposed a multi-level clustering method of “classification first and then clustering”, and this method can significantly improve the stability of clustering; Secondly, based on the traditional homogenization theory, derived three different homogenization methods of clustering, and compared the accuracy and data compressing efficacy of the three methods, this paper derived the methods of clustering region super homogenization and clustering pin-by-pin super homogenization. …”

Deformation of Cavitation Bubbles Arranged in a Line during Their Strong Expansion-Compression by A.A. Aganin, A.I. Davletshin, D.Yu. Toporkov

“…The features of influence of hydrodynamic interaction between weakly nonspherical bubbles on their deformation during the process of their strong joint expansion-compression are investigated. …”
Get full text

Study of Structural and Compression Properties of Soft Soils in Kunming at Different Moisture Contents by Wei Guo, Shiguang Xu, Tuo Hong, Shaolei Hao, Gang Chen

“…Due to its high moisture content and lacustrine features, the soft soil in Kunming possessed obvious structural characteristics. …”
Get full text

Multi-source information transmission and classification algorithm for equipment based on compressed sensing by Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU

“…Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.…”
Get full text

Multi-source information transmission and classification algorithm for equipment based on compressed sensing by Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU

“…Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.…”
Get full text

Design Measurement and Analysis of Vapor Compression Heat Pump with Large Temperature Difference by Miao Qing, Li Minxia, Ma Yitai, Dang Chaobin, Wang Qifan, Zhang Shigang

“…This paper proposes a ''zero-carbon heating'' model that uses the technology of an electric-driven vapor compression heat pump unit with a large temperature difference that can be used for long-distance delivery of heating. …”
Get full text

Frequency-Aware Learned Image Compression Using Channel-Wise Attention and Restormer by Hanwen Zhang, Cheolkon Jung, Xu Liu

“…In recent years, learned image compression has leveraged convolutional neural networks (CNNs) and achieved notable advancements in coding efficiency. …”
Get full text

Efficient productivity prediction model based on edge data compression in smart farms by Peng Jin, Wenshuang Du, Wenquan Jin

“…This strategy integrates lightweight edge models and region-aware clippings and compression techniques to reduce data transmission while retaining key agronomic features. …”
Get full text

The impact of compression and confinement in tumor growth and progression: emerging concepts in cancer mechanobiology by Allison McKenzie Johnson, Charles Froman-Glover, Akshitkumar Mistry, Akshitkumar Mistry, Kavitha Yaddanapudi, Kavitha Yaddanapudi, Kavitha Yaddanapudi, Joseph Chen, Joseph Chen

“…With the advance of bioengineering platforms, deeper investigations into the impact of these biophysical features on cancer progression are being conducted with a growing appreciation of the intratumoral compression that underlie many of the biophysical changes. …”
Get full text

Numerical design of nonstationary wavelets: Enhanced filter design andapplications in image compression by A. Boussaad, Y. Fourar, K. Melkemi

“…This limitation results in suboptimal compression performance, particularly for images with varying statistical properties and localized features. …”
Get full text

Simultaneous Learning Knowledge Distillation for Image Restoration: Efficient Model Compression for Drones by Yongheng Zhang

“…To address this issue, we propose the <b>S</b>imultaneous <b>L</b>earning <b>K</b>nowledge <b>D</b>istillation (<b>SLKD</b>) framework, specifically designed to compress image restoration models for resource-constrained drones. …”
Get full text

Real-Time Compression Scheme for Urban Rail Transit Train Operation Data by LI Dexiang, WANG Linmei, WANG Shu

“…［Result & Conclusion］ The proposed multi-dimensional real-time data compression scheme features low complexity, strong compression ability and fast compression speed. …”
Get full text

Measurement of the Compressive Strength of Concrete Using Modeling of Deep Hybrid Forest Regression by J. Rajprasad, P. Priya Rachel, S. Arulselvan, D. Arul, G. Ramesh Kumar, H. J. Pallavi, M. Sivaraja, Vinay Kumar Singh, Getachew Gebreamlak

“…The paper proposes a deep hybrid forest regression-based modeling method for measuring the compressive strength (CS) of concrete. Then, the reduced feature vector is used as input to train multiple subforest models (SFM), the predicted values are selected from multiple subforests via the KNN (K-nearest neighbor) method to combine them to obtain the layer regression vector (LRV), and it is combined with the reduced feature vector to obtain the improved LRV, then the output of this layer is taken; second, the regression vector (RV) of the input layer enhancement layer is used as input to obtain the output of the second layer FM, and the steps are repeated until the output of the input layer FM is complete. …”
Get full text

QFCOI-Enhancing Objective Quality Assessment for Compressed Omnidirectional Images With Fusion of Measures by Marek Simka, Ladislav Polak, Adam Zizien, Karel Fliegel

“…This paper introduces Quality Fusion of Compressed Omnidirectional Images (QFCOI), an enhanced objective quality assessment method for compressed 360&#x00B0; images. …”
Get full text