BBC Russian

Preprint ARTICLE | doi:10.20944/preprints202406.1279.v1

CWT-AM-CNN: A Lightweight Feature Extraction Network with Attention Mechanism Based on CWT Peak Seeking Method for Aero-Engine Hot Jet FT-IR Classification

Shuhan Du, Wei Han, Zhenping Kang, Xiangning Lu, Yurong Liao, Zhaoming Li

Subject: Engineering, Aerospace Engineering Keywords: Infrared Spectral detection; FT-IR; Aero-engine hot jet; deep learning; Attention Mechanism

Online: 20 June 2024 (12:51:20 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.1134.v1

The Mother's Day Solar Storm of 11 May 2024 and Its Effect on Earth's Radiation Belts

Viviane Pierrard, Alexandre Winant, Edith Botek, Maximilien Péters de Bonhome

Subject: Physical Sciences, Space Science Keywords: geomagnetic storm; solar energetic particles; solar event; radiation belts; energetic protons; relativistic electrons

Online: 14 September 2024 (10:38:34 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202403.0069.v1

An Attitude Adaptive Integral Sliding Mode Control Algorithm with Feedforward Compensation Disturbance Observer for Microsatellites to Track High-Speed Moving Targets

Xinyan Yang, Lei Li, Yurong Liao, Zhaoming Li

Subject: Engineering, Aerospace Engineering Keywords: Microsatellite; Attitude Control; Moving Target Tracking; Disturbance Observer; Sliding Mode Control

Online: 1 March 2024 (18:25:20 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202406.1287.v1

SE-CBAM-YOLOv7: An Improved Lightweight Attention Mechanism-Based YOLOv7 for Real-Time Detection of Small Aircraft Targets in Microsatellite Remote Sensing Imaging

Zhenping Kang, Yurong Liao, Shuhan Du, Haonan Li, Zhaoming Li

Subject: Engineering, Aerospace Engineering Keywords: aircraft detection; YOLOv7; CBAM; SENet; microsatellite

Online: 18 June 2024 (15:09:54 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.0113.v1

Geomagnetic Field Measurements based Adaptive Cubature H-infinity Filter for Microsatellite Autonomous Orbit Estimation

Zhaoming Li, Xinyan Yang, Lei Li, Yurong Liao

Subject: Engineering, Aerospace Engineering Keywords: autonomous orbit estimation; microsatellite; cubature Kalman filter; robust; geomagnetic field

Online: 1 July 2024 (13:54:09 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202405.1876.v1

Assessment of Particulate Organic Carbon in the Mediterranean Sea Based on Dual-Optimization Random Forest

Chao Li, Huisheng Wu, Chaojun Yang, Long Cui, Ziyue Ma, Lejie Wang

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: particle organic carbon; Mediterranean; machine learning; tuneRanger R package; geographic detector

Online: 28 May 2024 (14:28:22 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202309.1002.v6

Dark Energy and Dark Matter from Extra Dimensional Symmetry as Different Manifestations of Vacuum Energy

Kabir Umar

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: chirality; dark energy; dark matter; extra dimension; gravity; neutrino; vacuum energy

Online: 23 September 2024 (12:19:15 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201712.0057.v1

Relative Weighted Feature Space for Dimensionality Reduction and Classification of Hyperspectral Images

Seyyed Ali Ahmadi, Nasser Mehrshad, Seyyed Mohammad Razavi

Subject: Environmental And Earth Sciences, Other Keywords: dimension reduction; feature extraction; hyperspectral image; weighted feature space; low rank representation; spectral clustering

Online: 11 December 2017 (06:55:22 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201609.0088.v1

Multi-range Conditional Random Field for Classifying Railway Electrification System Objects

Jaewook Jung, Leihan Chen, Gunho Sohn, Chao Luo, Jong-Un Won

Subject: Engineering, Civil Engineering Keywords: classification; railway; power line; mobile laser scanning data; conditional random field; layout compatibility

Online: 26 September 2016 (09:33:05 CEST)

Show abstract| Download PDF| Share

Railway has been used as one of the most crucial means of transportation in public mobility and economic development. For efficiently operating railways, the electrification system in railway infrastructure, which supplies electric power to trains, is essential facilities for stable train operation. Due to its important role, the electrification system needs to be rigorously and regularly inspected and managed. This paper presents a supervised learning method to classify Mobile Laser Scanning (MLS) data into ten target classes representing overhead wires, movable brackets and poles, which are recognized key objects in the electrification system. In general, the layout of railway electrification system shows a strong regularity of spatial relations among object classes. The proposed classifier is developed based on Conditional Random Field (CRF), which characterizes not only labeling homogeneity at short range, but also the layout compatibility between different object classes at long range in the probabilistic graphical model. This multi-range CRF model consists of a unary term and three pairwise contextual terms. In order to gain computational efficiency, MLS point clouds is converted into a set of line segments where the labeling process is applied. Support Vector Machine (SVM) is used as a local classifier considering only node features for producing the unary potentials of CRF model. As the short-range pairwise contextual term, Potts model is applied to enforce a local smoothness in short-range graph. While, long-range pairwise potentials are designed to enhance spatial regularities of both horizontal and vertical layouts among railway objects. We formulate two long-range pairwise potentials as the log posterior probability obtained by Naïve Bayes classifier. The directional layout compatibilities are characterized in probability look-up tables which represent co-occurrence rate of spatial relations in horizontal and vertical directions. The likelihood function is formulated by multivariate Gaussian distributions. In the proposed multi-range CRF model, the weight parameters to balance four sub-terms are estimated by applying the Stochastic Gradient Descent (SGD). The results show that the proposed multi-range CRF can effectively classify detailed railway elements, representing the average recall of 97.66% and the average precision of 97.07% for all classes.

Preprint ARTICLE | doi:10.20944/preprints202402.0890.v1

Characterization of Industrial High-Strength Aluminum Alloys by Laser-Induced Breakdown Spectroscopy, With Special Emphasis on the Detection of Low Contents of Mg, Mn, Cr, Cu, Zn and Sensing of Molecular Diatomic Emission of AlO During Ablation

Svetlana Rytchkova, Luc Lévesque

Subject: Physical Sciences, Optics And Photonics Keywords: Laser-induced breakdown spectroscopy (LIBS); Aluminum (Al); Magnesium (Mg); Manganese (Mn); Chromium (Cr); Copper (Cu); Zinc (Zn); Aluminum Monoxide (AlO).

Online: 16 February 2024 (07:01:12 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202405.2089.v1

The Entropy of the Collapsing Molecular Cloud

Gemechu Muleta Kumssa

Subject: Physical Sciences, Space Science Keywords: Entropy; Gravity; Turbulence; Molecular cloud; Star formation

Online: 31 May 2024 (08:10:11 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.1383.v1

A Peak Finding Siamese Convolutional Neural Network (PF-SCNN) for Aero-engine Hot Jet FT-IR Spectrum Classification

Shuhan Du, Wei Han, Zhenping Kang, Fengkun Luo, Yurong Liao, Zhaoming Li

Subject: Engineering, Aerospace Engineering Keywords: infrared spectrum detection; FT-IR; aero-engine hot jet; siamese convolutional neural network networks; peak finding

Online: 17 July 2024 (13:41:29 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202406.0062.v1

Development and Testing of a Smart Ice Control System Using Machine Learning Models

Dario Farina, Hatim Machrafi, Patrick Queeckers, Patrice Desire Dongo, Carlo Saverio Iorio

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: aerospace icing prevention; risk mitigation in aviation; graphene-based sensors; dynamic ice sensing; de-icing; conductive polymer applications; smart sensors; pedot:pss polymers; 2D materials; micromachines

Online: 3 June 2024 (10:41:17 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202406.0839.v1

Lifetime of Long-Lived Sunspot Groups

Judit Muraközy

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: Solar physics; Sunspots; Sunspot groups; Sunspot cycle; Solar magnetic fields; Solar active region magnetic fields

Online: 12 June 2024 (12:21:17 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.2044.v1

Evaluation of Solid Phase Joining Using Friction Stir Welding Technique between Aluminum 6061 and Polymer-Based Composites

NOUMAN ALI, Zain ul Abadeen, Yumna Qureshi

Subject: Chemistry And Materials Science, Other Keywords: FSW (Friction Stir Welding); IMc (Intermetallic Compounds); UTM (Universal Testing Machine); RPM (Revolutions Per Minute); HAZ (Heat Affected Zone); WZ (Weld Zone); BM (Base Metal); CNC (Computer Numeric Control); EDM (Electrical Discharge Machine)

Online: 29 August 2024 (16:58:20 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.0030.v1

Surface Ages in the Vicinity of the Chang’e-6 Landing Site

Li Zhang, Jianzhong Liu, Gregory Michael, Ping Ge, Kaichang Di, Congzhe Wu, Kai Zhu, Xiaoxi Kang

Subject: Environmental And Earth Sciences, Geophysics And Geology Keywords: Chang’ e-6; CSFD measurements; absolute model age; Apollo basin

Online: 2 September 2024 (08:54:01 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202407.0928.v1

Transmission Spectroscopy Along the Transit of Venus: A Proxy for Exoplanets Atmospheric Characterization

Alexandre Baptista Branco, Pedro Machado, Olivier Demangeon, Sarah Amelia Jaeggli, Thomas Widemann, Paolo Tanga

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: Venus; Solar Transit; High-resolution transmission spectroscopy; Radiative transfer; Cross-correlation; Carbon dioxide; Carbon monoxide; Ozone; Venus-like exoplanets

Online: 11 July 2024 (08:37:43 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.1366.v1

Pore Characteristics of Hydrate-Bearing Sediments from Krishna-Godavari Basin, Offshore India

Wen Guan, Hailin Yang, Xindi Lu, Hailong Lu

Subject: Environmental And Earth Sciences, Oceanography Keywords: hydrate-bearing sediments; microporous structure; Krishna-Godavari Basin; pore characterization

Online: 20 August 2024 (03:39:46 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202405.0039.v1

Water Recuperation from Regolith at Martian, Lunar & Micro-gravity during Parabolic Flight

Dario Farina, Hatim Machrafi, Patrick Queeckers, Christophe Minetti, Carlo Saverio Iorio

Subject: Engineering, Aerospace Engineering Keywords: regolith hydration; water extraction technologies; parabolic flight simulation; ice-regolith interaction; substrate condensation efficiency; in-situ resource utilization (ISRU); thermal condensation processes; micro-gravity experiments; surface properties and water recovery; space resources; space mining

Online: 1 May 2024 (09:56:06 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202001.0375.v1

Exploring Geometric Feature Hyper-Space in Data to Learn Representations of Abstract Concepts

Rahul Sharma, Bernardete Ribeiro, Alexandre Miguel Pinto, Amilcar F cardoso

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: unsupervised machine learning; hierarchical learning; computational representation; computational cognitive modeling; contextual modeling; classification; IoT data modeling

Online: 31 January 2020 (04:38:51 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202406.1235.v1

Feature Distributions of Technologies

Jiannan Zhu, Chao Deng, Jiaofeng Pan, Fu Gu, Jianfeng Guo

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: 2D analytical space; commerciality; disruptiveness; representative keyword; search engine; significance; technological assessment; versatility

Online: 18 June 2024 (16:15:59 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202405.1792.v1

Unsupervised Characterization of Water Composition with UAV-based Hyperspectral Imaging and Generative Topographic Mapping

John Waczak, Adam Aker, Lakitha O. H. Wijeratne, Shawhin Talebi, Ashen Fernando, Prabuddha M. H. Dewage, Mazhar Iqbal, Matthew Lary, David Schaefer, Gokul Balagopal, And David J. Lary

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Hyperspectral Imaging; Remote Sensing; Unsupervised Classification; Endmember Extraction; Generative Topographic Mapping

Online: 3 June 2024 (17:09:23 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202403.1444.v1

Environmental Chamber Characterization of an Ice Detection Sensor for Aviation Using Graphene and PEDOT:PSS

Dario Farina, Marco Mazio, Hatim Machrafi, Patrick Queeckers, Carlo Saverio Iorio

Subject: Engineering, Aerospace Engineering Keywords: Ice Formation; Aircraft Ice Detection; Hazard Management; Graphene Sensors; In-Flight Safety Technology; Real-time Ice Monitoring; Resistance Signal Analysis; Pedot:PSS; Climatic chamber

Online: 25 March 2024 (08:47:38 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.1700.v1

Ionospheric Absorption Variation Based on Ionosonde and Riometer Data and the NOAA D-RAP Model over Europe During Intense Solar Flares in September, 2017

Veronika Barta, Tamás Bozóki, Dávid Péter Süle, Daniel Kouba, Jens Mielich, Tero Raita, Attila Buzás

Subject: Environmental And Earth Sciences, Space And Planetary Science Keywords: space weather; solar flare; ionosphere; ionospheric absorption; ionosonde data; HF radio wave absorption; radio fade-out; riometer; D-RAP model

Online: 23 September 2024 (12:16:33 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202404.1704.v1

Vision System for the Mars Sample Return Capture, Containment and Return System (CCRS)

Brent Jon Bos, David Donovan, John Capone, Chen Wang, Terra Hardwick, Dylan Bell, Yuqing Zhu, Robert Podgurski, Bashar Rizk, Ireneusz Orlowski, Rachel Edison, David Harvey, Brianna Dizzon, Lindsay Haseltine, Kristoffer Olsen, Chad Sheng, Robert Bousquet, Luan Vo, Georgi Georgiev, Kristen Washington, Michael Singer, Stefan Ioana, Anloc Le, Elena Georgieva, Michael Hackett, Michael Ravine, Michael Caplinger, Phillip Coulter, Erin Percy, Charles Torisky, Jean Lauenstein, Kaitlyn Ryder, Michael Campola, Dillon Johnstone, William J. Thomes, Richard G. Schnurr, John McCloskey, Eugenia DeMarco, Ellen Lee, Calinda Yew, Bo Yang, Mingyu Han, Bartosz Blonski

Subject: Engineering, Aerospace Engineering Keywords: Mars; cameras; sample return; space optics

Online: 26 April 2024 (09:33:12 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.2092.v1

Design and On-Orbit Performance of Ku-Band Phase-Array SAR Payload System

Wei Yan, Xiaomin Tan, Jiang Wu, Mingze Yuan, Hongxing Dang, Wujun Chang

Subject: Engineering, Aerospace Engineering Keywords: Ku band; SAR system; payload; Taijing-4(03); on-orbit; application; micro-nano; satellite

Online: 29 August 2024 (07:14:22 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202404.1284.v1

Robust Wideband Interference Suppression Method for GNSS Array Antenna Receiver via Hybrid Beamforming Technique

Zhenxing Xu, Qijia Dong, Shenyang Li, Fuzhan Yue, Meng Wang, Zhenghuan Xia, Xiao Chen, Shuangna Zhang, Guoji Zou, Huizheng Wang

Subject: Engineering, Aerospace Engineering Keywords: wideband interference; anti-jamming; hybrid beamforming; hybrid array; digital array

Online: 18 April 2024 (15:42:11 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202405.2062.v1

IFU Spectroscopic Study of the Planetary Nebula Abell 30: Mapping the Ionization and Kinematic Structure of the Inner Complex

Kam Ling Chan, Quentin Andrew Parker, Andreas Ritter

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: Planetary nebulae; Abell 30; Integral spectroscopy; Kinematics; velocity maps; Binary system; born-again scenario; wolf rayet central star; hydrogen deficient CSPN

Online: 30 May 2024 (13:43:19 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202406.1264.v1

Microwave Corona Breakdown Suppression of Microstrip Coupled-Line Filter Using Lacquer Coating

Ming Ye, Shaoguang Hu, Rui Wang, Yong Zhang, Yongning He

Subject: Engineering, Electrical And Electronic Engineering Keywords: coupled-line filter; dielectric coating; microstrip circuits; microwave corona breakdown suppression ;

Online: 18 June 2024 (13:36:03 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202402.0545.v1

Global Generalized Mersenne Numbers: Definition, Decomposition, and Generalized Theorems

Vladimir Pletser

Subject: Computer Science And Mathematics, Algebra And Number Theory Keywords: Mersenne numbers; Generalized Mersenne numbers; divisibility and congruence properties

Online: 9 February 2024 (10:50:56 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201607.0008.v1

Spectral and Polarization Signatures of Relativistic Shocks in Blazars

Markus Boettcher

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: active galaxies; blazars; jets; polarization; shock acceleration

Online: 8 July 2016 (03:03:04 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202406.1725.v1

Ionosonde Measurements Comparison during an ICME- and a SIR/CIR-Driven Geomagnetic Storm over Europe

Kitti Alexandra Berényi, Loredana Perrone, Dario Sabbagh, Alessandro Ippolito, Carlo Scotto, Árpád Kis, Veronika Barta

Subject: Environmental And Earth Sciences, Space And Planetary Science Keywords: space weather; geomagnetic storms; ionosphere; ionospheric storm; ICME; SIR/CIR; ionosonde; Digisonde; rTEC; TIMED/GUVI

Online: 25 June 2024 (07:15:52 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ESSAY | doi:10.20944/preprints201801.0060.v1

Some Potentially Strategic Considerations for the Sex-Bot Industry

Glenn W. Smith

Subject: Social Sciences, Gender And Sexuality Studies Keywords: sexually-enable robot; sex-bot

Online: 8 January 2018 (09:56:06 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.1433.v1

Feature Coding and Graph via Transformer: Different Granularities Classification for Aircrafts

Jianghao Rao, Senlin Qin, Zongyan An, Jianlin Zhang, Qiliang Bao, Zhenming Peng

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: fine-grained; aircraft recognition; label divisions; swin-transformer

Online: 20 September 2024 (03:47:37 CEST)

Show abstract| Download PDF| Share

Against the background of the sky, imaging and perception of aircraft are cru- cial. Among these, the location of aircrafts is not a very difficult problem in general, because that deep learning algorithms and object detection models based on convolutional neural network(CNN) are ever-evolving. In order to have a better identification of various aircrafts, or to accurately locate different types of flying targets in the sky, it becomes significant to distinguish and recognize different types of aircrafts. One question is that, distinguishing and recognizing between sub-categories of aircrafts pose great challenges. Although fine-grained recognition focuses on exploring and studying such problems, aircrafts under different sub-categories and granularities lead us to rethink the application of features. We noticed that features in swin-transformer demonstrates the under- standing and processing of images, fully showcasing the encoding and indexing of information. Through this research and proposed approach, we discovered a better understanding of features encoding and use, which are inspired by the feature encoding and computation in swin-transformer. In our paper, our ap- proach has achieved effects on features encoded graphically, manifested from the architecture design and convolutional neural network computation, and outper- forms other famous fine-graiend classification models on this issue. Not only approach we proposed has demonstrated superior performance in fine-grained aicraft classification, but also the mechanisms of the feature encoding under different sample space partitions is revealed for this issue, which provides a re- search for the representation of aircraft fineness characteristics. The relationship between representation orientation of aircraft feature information under various grained divisions, shows that the recognition of different categories according to man-made, such as aircraft, can be achieved by means of the feature represen- tations studied in this paper, for more specific defined classification tasks and various man-made targets partition criteria, which may influences the princi- ple of design for calculation and feature extraction in fine-grained classification models.

Preprint ARTICLE | doi:10.20944/preprints202408.2013.v1

On the Ionisation Tolerance of C₂₀ Fullerene in Ground and Excited Electronic States in Planetary Nebulae

SeyedAbdolreza Sadjadi, Quentin Andrew Parker

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: astrochemistry; C₂₀ fullerene; Ionisation; excited state; DFT; planetary nebulae

Online: 28 August 2024 (05:16:53 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.1320.v1

Evaluating Feature Impact Prior to Phylogenetic Analysis Using Machine Learning Techniques

Osama A. Salman, Gábor Hosszú

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Feature Selection; Hyperparameters; Machine Learning; Phylogenetics; Scriptinformatics; Consistency Index (CI); False Rejection Rate (FRR); False Acceptance Rate (FAR); Classification

Online: 20 August 2024 (10:42:40 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202312.1044.v1

Improving Breast Tumor Multi-Classification from High-Resolution Histological Images with the Integration of Feature Space Data Augmentation

Nadia Brancati, Maria Frucci

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Deep Learning; Whole Slide Image; Augmentation; Classification; Feature Space

Online: 14 December 2023 (10:05:41 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201608.0178.v1

Bias Correction of Chinese Fengyun-3C Microwave Humidity and Temperature Sounder Measurements in Retrieval of Atmospheric Parameters

Qiurui He, Zhenzhan Wang, Jieying He

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: FY-3C/MWHTS; linear regression correction; neural networks correction; one-dimensional variational algorithm; atmospheric temperature and humidity profiles

Online: 19 August 2016 (09:22:31 CEST)

Show abstract| Download PDF| Share

The Microwave Humidity and Temperature sounder (MWHTS) on board the Fengyun (FY)-3C satellite measure the outgoing radiance form the Earth surface and atmospheric constituents. MWHTS makes measurements in the isolated oxygen absorption line near 118 GHz and the vicinity of strong water vapor line around 183 GHz, can provide fine vertical distribution structure of both atmospheric humidity and temperature. However, in order to obtain the accurate soundings of humidity and temperature by the physical retrieval method, bias between the observed radiance and those simulated by radiative transfer model from the background or first guess profiles must be correct. In this study, two bias correction methods are developed through the correlation analysis between MWHTS measurements and air mass identified by the first guess profiles of the physical inversion, one is the linear regression correction (LRC) and the other is neural networks correction (NNC), representing the linear and nonlinear nature between MWHTS measurements and air mass, respectively. Both correction methods have been applied to MWHTS observed brightness temperatures over the geographic area (180° W-180° E, 60° S-60° N). The corrected results are evaluated by the probability density function of the difference between corrected observations and simulated values and the root mean square error (RMSE) with respect to simulated observations. The numerical results show that the NNC method perform better, especially in MWHTS channels 1 and 7-9 whose peak weight function heights are close to the surface. In order to assess the effects of bias correction methods proposed in this study on the retrieval accuracy, a one-dimensional variational system was built and applied to the MWHTS uncorrected and corrected brightness temperatures to estimated atmospheric temperature and humidity profiles, The retrieval results show that the NNC has better performance which is to be expected. An indication of the stability and robustness of NNC method is given which suggests that the NNC method has promising application perspectives in the physical retrieval.

Preprint ARTICLE | doi:10.20944/preprints202405.0433.v1

A Novel Algorithm for Classifying Vegetation and Non-Vegetation Using Red Edge Slope Coefficient with Hyperspectral LCTF Imaging

Bayarsaikhan Uudus, Bayartsetseg Oyungerel, Yukihiro Takahashi, Erdenebaatar Dashdondog, Turtogtokh Tumenjargal, Narangarvuu Dashdondog, Qinxue Wang, Hasi Bagan, Begzsuren Tumendemberel

Subject: Environmental And Earth Sciences, Ecology Keywords: Hyperspectral Imaging; Liquid Crystal Tunable Filter; Red Edge Slope Coefficient; Spectral Reflectance; Vegetation Classification; Remote Sensing Algorithms

Online: 8 May 2024 (15:28:55 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202405.2010.v1

Research on Underwater SLAM System Based on Visual Feature Enhancement

Haiyang Qiu, Yijie Tang, Hui Wang, Lei Wang, Dan Xiang, Mingming Xiao

Subject: Computer Science And Mathematics, Robotics Keywords: underwater SLAM; underwater image processing; visual feature point enhancement; association of acoustic and visual feature

Online: 30 May 2024 (11:03:03 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.0961.v1

Research on Short‐Term Forecasting Model of Global Atmospheric Temperature and Wind in the Near Space Based on Deep Learning

Xingxin Sun, Ting Lan, Yi Liu, Chen Zhou, Jian Feng, Huiyun Yang, Yuqiang Zhang, Zhou Chen, Tong Xu, Zhong-Xin Deng, Zhengyu Zhao

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: Global atmospheric temperature and wind in the near space; ConvGRU; ConvLSTM; MERRA‐2 reanalysis dataset

Online: 13 August 2024 (14:41:57 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.1674.v1

Augmented Feature Diffusion on Sparsely Sampled Subgraph

Xinyue Wu, Huilin Chen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: efficiency; scalability; subgraph; graph neural network

Online: 22 July 2024 (05:44:53 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202402.0543.v1

Random Forest Classifier for Cloud Clearing of the Operational TROPOMI XCH4 Product

Tobias Borsdorff, Mari Carmen Martinez-Velarte, Maarten Sneep, Mark ter Linden, Jochen Landgraf

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: TROPOMI; CH4; SUOMI NPP; VIIRS; CLOUDS; Machine Learning; Random Forest Classifier

Online: 9 February 2024 (10:52:15 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.2539.v1

Corrections of the Distribution of Nuclei Due to Neutron Degeneracy and Their Effects in the R-Process in Neutron Stars - Black Hole Mergers

Rita K. Y. Lau

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: nuclear astrophysics; nuclear reactions; neutron stars; black holes

Online: 31 July 2024 (14:04:38 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202406.1528.v1

Leveraging LDA Feature Extraction to Augment Human Activity Recognition Accuracy

Milad Vazan, Elaheh Sharifi, Hadi Farahani, Sadegh Madadi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Feature Extraction; Human Activity Recognition; Linear Discriminant Analysis

Online: 23 June 2024 (04:20:43 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202404.0038.v1

Weakly Supervised Semantic Segmentation of Point Cloud Scenes using Boundary-based Feature Aggregation

Yongwei Miao, Guoxiang Ren, Xudong Zhang, Haijian Liu, Fuchang Liu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Point cloud; Semantic segmentation; Weakly supervised learning; Boundary feature aggregation; Data augmentation

Online: 1 April 2024 (11:12:43 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.0478.v1

Gastric Cancer Image Classification: a Comparative Analysis and Feature Fusion Strategies

Andrea Loddo, Marco Usai, Cecilia Di Ruberto

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Computational Pathology; Histopathological Imaging; Gastric Cancer; Convolutional Neural Networks; Machine Learning; Deep Learning; Feature Extraction; Feature Combination

Online: 6 July 2024 (03:16:08 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201611.0002.v2

Small UAS-Based Wind Feature Identification System Part 1: Integration and Validation

Leopoldo Rodriguez Salazar, Jose A. Cobano, Anibal Ollero

Subject: Engineering, Control And Systems Engineering Keywords: wind prediction; wind estimation; UAS; wind shear; gust; multi-platform integration

Online: 18 January 2017 (09:44:54 CET)

Show abstract| Download PDF| Share

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s.

Preprint ARTICLE | doi:10.20944/preprints202406.0461.v1

Variations of VEGFR2 Chemical Space: Stimulator and Inhibitory Peptides

Claudiu N. Lungu, Ionel Mangalagiu, Gabriela Gurau, Mihaela Cezarina Hîncu

Subject: Medicine And Pharmacology, Cardiac And Cardiovascular Systems Keywords: peripheral artery disease; molecular modeling; docking; angiogenesis; vascular morphogenesis; chimeric protein

Online: 7 June 2024 (07:32:42 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.2285.v1

Comparative Study on the Interest of NURBS Representation Versus Polynomial Surface Description in Freeform TMA

Clément Freslier, Guillaume Druart, Alice Fontbonne, Thierry Lepine, Christophe Buisset, Tibor Agocs, Arnaud Hélière, Fanny Keller, Jean-Baptiste Volatier, Stéphane Beaussier, Paul Jougla

Subject: Physical Sciences, Optics And Photonics Keywords: optimization; freeform; NURBS; differential ray tracer; XY polynomials; TMA

Online: 29 July 2024 (10:14:59 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.0060.v1

PDAM-FAQ: Paraphrasing-based Data Augmentation and Mixed-Feature Semantic Matching for Low-Resource FAQs

Dongsheng Wang, Liming Wang, Kun Tang, Qile Bo, Bin Han

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Paraphrasing; Data Augmentation; Semantic Matching; FAQ; Low-Resource

Online: 1 August 2024 (14:51:28 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202305.1866.v1

A Novel Approach for Reducing Feature Space Dimensionality and Develop a Universal Machine-Learning Model for Coated Tubes in Cross Flow Heat Exchangers

Mahyar Jahaninasab, Ehsan Taheran, S. Alireza Zarabadi, Mohammadreza Aghaei, Ali Rajabpour

Subject: Engineering, Mechanical Engineering Keywords: Computational heat transfer; Coating; Feature combination; Machine learning; Heat-exchangers

Online: 26 May 2023 (05:38:40 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202405.1257.v1

A New Alternating Suboptimal Dynamic Programming Algorithm with Applications for Feature Selection

David Podgorelec, Borut Žalik, Domen Mongus, Dino Vlahek

Subject: Computer Science And Mathematics, Computer Science Keywords: dynamic programming, suboptimal solution, feature selection, machine learning

Online: 20 May 2024 (09:40:02 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201610.0078.v1

Copernicus Sentinel-2 Calibration and Products Validation Status

Ferran Gascon, Olivier Thépaut, Mathieu Jung, Benjamin Francesconi, Jérôme Louis, Vincent Lonjou, Bruno Lafrance, Stéphane Massera, Angélique Gaudel-Vacaresse, Florie Languille, Bahjat Alhammoud, Françoise Viallefont, Jakub Bieniarz, Bringfried Pflug, Sébastien Clerc, Laëtitia Pessiot, Thierry Trémas, Enrico Cadau, Roberto De Bonis, Claudia Isola, Philippe Martimort, Valérie Fernandez

Subject: Environmental And Earth Sciences, Environmental Science Keywords: calibration; validation; optical; instrument; processing; imagery; spatial; operational

Online: 19 October 2016 (10:59:29 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.0199.v1

DCFF-Net: Deep Context Feature Fusion Network for High-Precision Classification of Hyperspectral Image

Chen Zhijie, Chen Yu, Wang Yuan, Wang Xiaoyan, Wang Xinsheng, Xiang Zhouru

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: deep learning; hyperspectral images; classification; hyperspectral feature map

Online: 2 July 2024 (11:21:06 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202404.1215.v1

Evaluating the VIIRS Imagery for Developing Near Real-Time Nationwide Vegetation Cover Monitoring in Indonesia

Yudi Setiawan, Kustiyo Kustiyo, Sahid Agustian Hudjimartsu, Judin Purwanto, Riva Rovani, Anna Tosiani, Basyiruddin Usman, Tatik Kartika, Novie Indriasari, Lilik Budi Prasetyo, Belinda Arunarwati Margono

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: change detection; temporal vegetation dynamics; open area index; multi temporal VIIRS

Online: 18 April 2024 (10:57:27 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202404.0122.v1

Landau Tidal Damping and Major-Body Clustering in Solar and Extrasolar Subsystems

Dimitris M. Christodoulou, Demosthenes Kazanas

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: Dynamical evolution of planets and satellites; Extrasolar planets; Gravitation; Landau damping; Mean tidal field

Online: 2 April 2024 (09:18:05 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.1914.v1

Estimates for Certain Rough Multiple Singular Integrals on Triebel-Lizorkin Space

Hussain Al-Qassem, Mohammed Ali

Subject: Computer Science And Mathematics, Analysis Keywords: Triebel-Lizorkin space; singular integrals; Rough kernels; product spaces

Online: 27 August 2024 (17:06:35 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202402.1364.v1

An Indoor 3D Positioning Method Using Terrain Feature Matching for PDR Error Calibration

Xintong Chen, Yuxin Xie, Zihan Zhou, Yingying He, Qianli Wang, Zhuming Chen

Subject: Engineering, Electrical And Electronic Engineering Keywords: indoor three-dimensional positioning; PDR; terrain features; feature matching; pattern recognition

Online: 23 February 2024 (09:46:35 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.1180.v1

Prediction of Environmental Parameters for Predatory Mite Cultivation Based on Temporal Feature Clustering

Ying Ma, Hongjie Lin, Wei Chen, Weijie Chen, Qianyan Wang

Subject: Engineering, Control And Systems Engineering Keywords: time series clustering, LSTNet, greenhouse environmental parameter modeling, temperature and humidity prediction

Online: 15 August 2024 (14:51:31 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202405.0441.v1

Investigating the Performance of a Novel Modified Binary Black Hole Optimization Algorithm for Enhancing Feature Selection

Mohammad Ryiad Al-Eiadeh, Raneem Qaddoura, Mustafa Abdallah

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Feature Selection; Wrapper Feature Selection; Black Hole Algorithm; Cuckoo Search Algorithm; Correlation Functions; Transfer Function; Data Mining

Online: 8 May 2024 (15:26:26 CEST)

Show abstract| Download PDF| Share

High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At the exploitation phase, a set of stars are modified based on some rule and according to some objective function, the best star is selected as the black hole which attracts other stars. Furthermore, when a star gets closer to the event horizon, it will be swallowed and a new one will be randomly generated in the search space which thus is the exploration phase. However, randomness may cause the algorithm to fall into the trap of local optima, and to overcome such complications, inversion mutation is used. Furthermore, we modify a widely utilized objective function in most of the proposed works for wrapper feature selection by combining two new terms that are based on the correlation among the selected subset of features and the features and the classification label. We also utilize a transfer function, known as the V2 transfer function, to convert continuous values into discrete ones to enhance search. We assess our approach via extensive evaluation experiments using fourteen benchmark datasets. We benchmark the performance of a wrapper FS approach called Binary Cuckoo Search (BCS), and three filter-based FS approaches (namely Mutual Information Maximisation (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Relevance (mRMR)). Our evaluation has shown that the proposed model is an effective approach for FS, in selecting better features that enhance the performance metrics on the classifiers. Thus, MBHO can be utilized as one alternative to the existing state-of-art-approaches. We release the source codes of our implementation for the community to build on with new methods and datasets.

Preprint ARTICLE | doi:10.20944/preprints202406.1593.v1

Evolution of Dew and Rain Water Resources in Gujarat (India) between 2005 and 2021

Rupal Budhbhatti, Anil Roy, Marc Muselli, Daniel Beysens

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: Water resources; dew and rain increase; dew/rain ratio; dew/rain correlation; dew/rain mapping; Gujarat (India); climate change.

Online: 24 June 2024 (11:36:33 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202402.1670.v1

Understanding Microplastics Retention Efficiency and Sorption Dynamics in Porous Media

Hande Okutan, Çağdaş Sağır, Bedri Kurtuluş, Hasan Burak Özmen, Emrah Pekkan, Moumtaz Razack, Philippe Le Coustumer

Subject: Environmental And Earth Sciences, Environmental Science Keywords: microplastics; porous media; retention; transport; polyethylene; retention efficiency; numerical model; MT3DMS; MODFLOW

Online: 29 February 2024 (11:41:01 CET)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints201608.0002.v1

Results of Long-Duration Simulation of Distant Retrograde Orbits

Gary Turner

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: Distant Retrograde Orbit; DRO; orbits–stability; radiation pressure; orbits–resonance; dynamics

Online: 1 August 2016 (09:00:06 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202402.0697.v1

Quantifying Inhaled Concentrations of Particulate Matter, Carbon Dioxide, Nitrogen Dioxide, and Nitric Oxide Using Observed Biometric Responses with Machine Learning

Shisir Ruwali, Shawhin Talebi, Bharana Fernando, Lakitha O. H. Wijeratne, John Waczak, Prabuddha Madusanka Hathurusinghe Dewage, David J. Lary, John Sadler, Tatiana Lary, Matthew Lary, Adam Aker

Subject: Public Health And Healthcare, Public, Environmental And Occupational Health Keywords: Autonomic Response; Exposome; Micoenvironment; Air Quality; Biometric Observations; Machine Learning; Particulate Matter; CO2; NO2; NO

Online: 14 February 2024 (03:38:19 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202401.2197.v2

Bayesian Feature Extraction for Two-Part Latent Variable Model with Polytomous Manifestations

Qi Zhang, Yi-Hui Zhang, And Yemao Xia

Subject: Business, Economics And Management, Econometrics And Statistics Keywords: Two-part latent variable model; spike and slab prior; Bayesian lasso; MCMC sampling; CHFS

Online: 1 February 2024 (08:47:59 CET)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202404.0008.v1

An Automatic Near-Duplicate Video Data Cleaning Method Based on a Consistent Feature Hash Ring

Yi Qin, Ou Ye, Yan Fu

Subject: Computer Science And Mathematics, Analysis Keywords: Video cleaning; consistent feature hash ring; feature distance means; mountain peak function; multi-head attention mechanism; near-duplicate videos

Online: 1 April 2024 (09:49:59 CEST)

Show abstract| Download PDF| Share

In recent decades, with the ever-growing scale of video data, near-duplicate videos continue to emerge. Data quality issue caused by near-duplicate videos is becoming more and more prominent, which has affected the application of normal videos. Although current studies on near-duplicate video detection can be helpful to uncover data quality issues for videos, they still lack a process of automatic merging for the video data represented by high-dimensional features, which are difficult to automatically clean the near-duplicate videos to improve data quality for video datasets. At present, there are few studies on near-duplicate video data cleaning. The existing studies have the sensitive problems of video data orderliness and clustering initial center under a condition that prior distribution is unknown, which seriously affect the accuracy of near-duplicate video data cleaning. To address the above issues, an automatic near-duplicate video data cleaning method based on a consistent feature hash ring is proposed in this paper. First, a residual network with convolutional block attention modules, a long short-term memory deep network, and an attention model are integrated to construct an RCLA deep network with the multi-headed attention mechanism to extract spatiotemporal features of video data. Then, a consistent feature hash ring is constructed, which can effectively alleviate the sensitivity of video data orderliness while providing a condition of near-duplicate video merging. To reduce the sensitivity of the initial cluster centers to results of near-duplicate video cleansing, an optimized feature distance-means clustering algorithm is constructed by utilizing a mountain peak function on a consistent feature hash ring, which can implement automatic cleaning of near-duplicate video data. Finally, experiments are conducted based on a commonly used dataset named CC_WEB_VIDEO and a coal mining video dataset. Compared with some existing works, simulation results demonstrate that the performance of the proposed method.

Preprint REVIEW | doi:10.20944/preprints202406.0104.v1

Cereal-Derived Water-Unextractable Arabinoxylans: Structure Feature, Effects on Baking Products and Human Health

Manchun Huang, Juan Baia, Daniele Giuseppe Buccato, JiaYan Zhang, Yufeng He, Ying Zhu, Zihan Yang, Xiao Xiang, Maria Daglia

Subject: Biology And Life Sciences, Food Science And Technology Keywords: water-unextractable arabinoxylans; chemical properties human; health properties; gut microbiota; fermentation

Online: 3 June 2024 (13:47:42 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202403.0743.v1

PointNet++ Network with Contextual Feature and Mutual Learning for Point Sets

Xi Hu, Xiaolan Xie

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: point cloud; part segmentation; deep learning; self-attention; object classification

Online: 13 March 2024 (10:18:11 CET)

Show abstract| Download PDF| Share

Preprint REVIEW | doi:10.20944/preprints202208.0347.v1

The Uncertainty Principle and the Minimal Space-Time Length Element

David Escors, And Grazyna Kochan

Subject: Physical Sciences, Quantum Science And Technology Keywords: General relativity; uncertainty principle; geodesics; black hole singularity; quantum gravity; Planck star; Lorentz invariance violations.

Online: 18 August 2022 (11:06:06 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202403.1861.v1

Stability Analysis and Dynamic Simulations for Gravity Gradient of a Large Rigid Space Structure

Chenglei Tang, Jialiang Sun, Dongping Jin

Subject: Engineering, Aerospace Engineering Keywords: Stability analysis; Gravity gradient; Large rigid space structure; Orbit dynamics; Natural coordinate formulation

Online: 29 March 2024 (13:45:30 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202405.0755.v1

Combined Response of Ocular Cyclotorsion and Head Tilt during Body Tilt

Se Joon Woo, Sang-Ho Hwang, Ki Young Chung, Hee Kyung Yang, Sang Beom Han, Jeong-Min Hwang

Subject: Biology And Life Sciences, Life Sciences Keywords: cyclotorsion; tilt; vestibulo-ocular reflex; cervico-ocular reflex; optokinetic reflex

Online: 13 May 2024 (12:15:38 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202406.0082.v2

A Field-Theory Approach for Modeling Dissipative Relativistic Fluids

Nils Andersson, Thomas Celora, Gregory Comer, Ian Hawke

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: relativistic fluids; dissipation; field theory

Online: 16 July 2024 (05:26:47 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.1751.v1

CP Violation: Differing Binding Energy Levels of Quarks and Antiquarks, and their Transitions in Λ-baryons and B-mesons

Dimitris M Christodoulou, Demosthenes Kazanas

Subject: Physical Sciences, Particle And Field Physics Keywords: CP Violation; Flavor Symmetries; Properties of Hadrons; Quark Masses; Quark-Gluon Plasma

Online: 22 July 2024 (14:44:53 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202405.0018.v1

Improved YOLOv8-seg Based on Multi-scale Feature Fusion and Deformable Convolution for Weed Precision Segmentation

Zhuxi Lyu, Anjiang Lu, Yinglong Ma

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: YOLOv8; Weed Segmentation; Bi-directional Feature Pyramid Network; Dynamic Snake Convolution; Laser Weeding

Online: 1 May 2024 (04:22:08 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202402.0704.v1

Rapid Visual Screening Feature Importance for Seismic Vulnerability Ranking via Machine Learning and SHAP values

Ioannis Karampinis, Lazaros Iliadis, Athanasios Karabinis

Subject: Engineering, Civil Engineering Keywords: Rapid Visual Screening; Explainable AI; Feature Importance; SHAP

Online: 12 February 2024 (14:53:17 CET)

Show abstract| Download PDF| Share

Preprint HYPOTHESIS | doi:10.20944/preprints202402.1074.v1

A New Theory of Tree Sap Flow

András Török, Domokos Máthé, Imre Hegedus

Subject: Biology And Life Sciences, Forestry Keywords: plant water transport, suction-pressure pipe, pulsating system, different time-phase cycle, aquaporin

Online: 19 February 2024 (16:46:00 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202311.1147.v1

Enhanced Ransomware Identification via Feature Extraction with Class Feature Weighting

Fang Wang

Subject: Computer Science And Mathematics, Computer Science Keywords: ransomware detection; machine learning; dynamic analysis; n-grams; Class Feature Weighting (CFW)

Online: 20 November 2023 (11:06:27 CET)

Show abstract| Download PDF| Supplementary Files| Share

Preprint ARTICLE | doi:10.20944/preprints202408.0942.v1

Spectral-Based Fault Diagnosis Methodology for Industrial Shot Blast Machinery Leveraging XGBoost and Feature Importance

Joon-Hyuk Lee, Chibuzo Nwabufo Okwuosa, Beak Cheon Shin, And Jang-Wook Hur

Subject: Engineering, Safety, Risk, Reliability And Quality Keywords: Fast Fourier Transform; Peak Detection; Feature Importance; Fault Detection and Isolation; Extreme Gradient Boosting; Machine Learning; Discriminative Features

Online: 13 August 2024 (13:05:48 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202404.1554.v1

Exogenous Cytokinin 4-PU-30 Modulates the Response of Wheat and Einkorn Seedlings to UV-B Radiation

Elisaveta Kirova, Irina Moskova, Vasilissa Manova, Yana Koycheva, Zoia Tsekova, Denitsa Borisova, Hristo Nikolov, Ventzeslav Dimitrov, Iskren Sergiev, Konstantina Kocheva

Subject: Biology And Life Sciences, Plant Sciences Keywords: antioxidant gene expression; flavonoids; oxidative stress; phenolic compounds; phenylurea-cytokinin; proline; remote sensing; ROS; spectral reflectance

Online: 24 April 2024 (08:58:18 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.1350.v1

Comparation of CALPUFF and CFD Modeling of Toxic Gas Dispersion in Mountainous Environments

Mei Li, ChoHo Lo, Dongou Yang, Yuanchen Li, Zhe Li

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: Mountainous Environment; High Sulphur Gas; CALPUFF; CFD; Atmospheric Dispersion Model

Online: 18 September 2024 (12:11:14 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.2384.v1

CJE-PCHF: Chinese Joint Entity and Relation Extraction Model based on Progressive Contrastive Learning and Heterogeneous Feature Fusion

Meng He, Yunli Bai, Dongye Wei

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: joint extraction; contrastive learning; heterogeneous features; interactive fusion; semantic association

Online: 30 July 2024 (05:26:48 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201611.0052.v1

Feature Extraction of Ship Radiated Noise Based on Permutation Entropy of the Intrinsic Mode Function with the Highest Energy

Yu-Xing Li, Ya-An Li, Zhe Chen, Xiao Chen

Subject: Physical Sciences, Acoustics Keywords: empirical mode decomposition; intrinsic mode function; permutation entropy; multi-scale permutation entropy; feature extraction

Online: 9 November 2016 (10:24:35 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.1302.v1

DFLM-YOLO: A Lightweight YOLO Model with Multiscale Feature Fusion Capabilities for Open Water Aerial Imagery

Chen Sun, Yihong Zhang, Shuai Ma

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: lightweight; multiscale feature fusion; data augmentation; UAV; object detection

Online: 16 July 2024 (12:57:33 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.2121.v1

Optimizing Unsupervised Feature Engineering and Predictive Models for Thyroid Cancer Recurrence Prediction

Emmanuel Onah, Uche Jude Eze, Abdullahi Salahudeen Abdulraheem, Ugochukwu Gabriel Ezigbo, Kosisochi Chinwendu Amorha

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Well-differentiated thyroid cancer; Recurrence prediction; Unsupervised Data Engineering Methods; Dimensionality Reduction Techniques; Machine learning; Clustering; Principal Component Analysis; Truncated Singular Value Decomposition; Logistic Regression

Online: 26 September 2024 (14:45:33 CEST)

Show abstract| Download PDF| Supplementary Files| Share

Background/Objectives: Thyroid cancer, particularly well-differentiated thyroid cancer, is one of the most prevalent endocrine malignancies, with a rising incidence. Although it generally has a favorable prognosis, recurrence is common. Accurate prediction of recurrence is crucial for optimizing treatment plans and improving patient outcomes. This study aimed to advance the state-of-the-art in thyroid cancer recurrence prediction by refining feature engineering techniques and exploring a diverse ensemble of machine learning algorithms and an artificial neural network, using the differentiated thyroid cancer dataset from the UCI Machine Learning Repository; Methods: Various unsupervised data engineering methods, such as dimensionality reduction and clustering, were employed to enhance feature quality and mitigate noise, using stratified 10-fold cross-validation. The best-performing dimensionality reduction techniques were used to build classification model pipelines employing each of several machine learning models and an artificial neural network. The performance of these classification pipelines were assessed using metrics sensitive to class imbalance; Results: Principal Component Analysis and Truncated Singular Value Decomposition achieved superior clustering performance and moderate variances in their first principal components. Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbors, and Feedforward Neural Network models all achieved high performance, with Logistic Regression pipelines demonstrating balanced accuracy, F1 score, AUC, sensitivity, specificity, and precision—all greater than 0.93 on the test set and slightly lower in 10-fold cross-validation. Gradient Boosting classification pipelines performed the lowest, though still with respectable metrics; Conclusions: This study shows that employing feature engineering techniques like Principal Component Analysis or Truncated Singular Value Decomposition in Logistic Regression, Random Forest, Feedforward Neural Networks, Support Vector Machine, and K-Nearest Neighbors classification pipelines can improve thyroid cancer recurrence prediction accuracy and reliability, supporting more personalized treatment strategies in post-treatment patients.

Preprint ARTICLE | doi:10.20944/preprints202407.0385.v1

SDF2Net: Shallow to Deep Feature Fusion Network for PolSAR Image Classification

Mohammed Q. Alkhatib, M. Sami Zitouni, Mina Al-Saad, Nour Abura’ed, Hussain Al-Ahmad

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Complex-Valued Convolutional Neural Network (CV-CNN); Polarimetric Synthetic Aperture Radar (PolSAR) Image Classification, Attention Mechanism; Feature Fusion

Online: 4 July 2024 (14:46:48 CEST)

Show abstract| Download PDF| Share

Preprint CASE REPORT | doi:10.20944/preprints202403.1325.v2

Deep Learning-based Approach for Optimizing Urban Commercial Space Expansion Using Artificial Neural Networks

Dawei Yang, Jiahui Zhao, Ping Xu

Subject: Business, Economics And Management, Economics Keywords: Commercial space; Points of interest; Deep learning; BP Neural Network

Online: 7 April 2024 (13:58:27 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201712.0090.v1

Analyze PFG Anomalous Diffusion via Real Space and Phase Space Approaches

Guoxing Lin

Subject: Computer Science And Mathematics, Probability And Statistics Keywords: PFG anomalous diffusion; fractional derivative; NMR; MRI

Online: 14 December 2017 (11:27:15 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.1033.v1

Improved Urban Impervious Surface Mapping Using Multi-Sensor Feature Fusion: A Cross-City Analysis

Muhammad Nasar Ahmad, Fahad Almutlaq, Md. Enamul Huq, George D. Bathrellos, Akib Javed, Fakhrul Islam, Hariklia D. Skilodimou

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Data Fusion; Impervious surface; Landsat 8; LST; Sentinel-1

Online: 12 September 2024 (15:48:22 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202407.1155.v1

Belgrade’s Sustainable Transition: Reflections by Urban Planners on Change in Planning Urban Green Space

Sladana Milovanovic, Ivan Cvitković, Katarina Stojanović, Ante Klečina

Subject: Engineering, Architecture, Building And Construction Keywords: urban green space; urban planner; urban governance; sustainable transition; Belgrade

Online: 15 July 2024 (12:09:04 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201609.0055.v1

Cultural Heritage Sites in Danger—Towards Automatic Damage Detection from Space

Daniele Cerra, Simon Plank, Vasiliki Lysandrou, Jiaojiao Tian

Subject: Arts And Humanities, Archaeology Keywords: change detection; Cultural Heritage; texture analysis

Online: 18 September 2016 (08:38:10 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202403.0117.v2

Emergence of Time from Primordial Space and Expansion of Space with Time

Eckhard Rebhan

Subject: Physical Sciences, Astronomy And Astrophysics Keywords: space-time; generic space expansion; emergence of time; dark energy; quantum grav-ity; Wheeler-de Witt-equation; volume quantisation; friction by information transfer; information quantum

Online: 28 May 2024 (14:26:25 CEST)

Show abstract| Download PDF| Share

A model of space-time is presented, whose origin is set before the appearance of any universe. It uses concepts of previous work, a central one being that the information about the laws of nature is stored locally everywhere in space such that all physical processes obey them. Since information storage is bound to matter or energy, space is assumed to consist of dark energy (DE), which thus assumes an importance far beyond its function as a stopgap for an energy deficit in our universe ( U ). The primordial state (PS) is a timeless and relatively large space of 3 dimensions described by a Wheeler DeWitt (WDW) equation, whose solution is interpreted as an arrangement of very many space quanta and possesses properties that remind of the time-honored concept of the unmoved mover. The comparison of WDW solutions belonging to different mass densities of the DE favors one in which the space quanta are mini black holes. This allows the space quanta to be imagined as mass points which are kept at a distance compatible with the quantum volume by the Pauli principle or something equivalent. Triggered by a dramatic increase in probability, the PS is followed by a time-controlled sequence of quantized expansion states (ES i ). The concomitant emergence of time occurs in a lightning huge crash, consuming almost all DE of the PS. The subsequent quantized ES i emerge from a WDW equation, novelly derived from a solution of the modified cosmic momentum equation, which classically describes an exponential space expansion (CS). The huge volme of the ES i is also used as size of the PS. Information is assumed to be geometrically stored in arrangements of space quanta similar to how genetic information is stored in DNA molecules. During the CS information must be transferred from already existing "information quanta" to new ones. This requires time, slows down the expansion and is taken into account by a friction term in the cosmological momentum equation thus modified. Since the Friedmann-Lemaître (FL) equation remains fully valid, the model is widely based on recognized equations, so that some results may be understood as interpretations.

Preprint ARTICLE | doi:10.20944/preprints202404.0057.v1

Numerical Analysis of the Influence of Typical Perturbation Forces on LEO Satellites Orbit Prediction at Different Altitudes

Yang Zhang, Shengmao He, Chao Peng, Yuchang Xu, Deyong Xian, Ran Li, Guang Yang, Hong Yuan

Subject: Engineering, Aerospace Engineering Keywords: LEO constellations; Perturbation force; Gravitational field order; orbit prediction; Atmospheric density model

Online: 1 April 2024 (13:30:31 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.0841.v1

Research on Large Scene Adaptive Feature Extraction Based on Deep Learning

Yahe Yang, Iris Li, Ningjing Sang, Lipeng Liu, Xirui Tang, Qiyuan Tian

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: computing methodologies; artificial intelligence; computer vision; computer vision tasks; scene understanding

Online: 11 September 2024 (10:23:23 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202404.1919.v1

Outlier Detection by Energy Minimization in Quantized Residual Preference Space for Geometric Model Fitting

Zhang Yun, Yang Bin, Zhao Xi, Shiqian Wu, Luo Bin, Liangpei Zhang

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: geometric model fitting; outlier detection; quantized residual; energy minimization

Online: 30 April 2024 (03:47:50 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201703.0134.v1

Automatic Object-Oriented, Spectral-Spatial Feature Extraction Driven by Tobler’s First Law of Geography for Very High Resolution Aerial Imagery Classification

Zhiyong Lv, Penglin Zhang, Jón Atli Benediktsson

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: spatial-spectral feature; very high spatial resolution image; classification; Tobler’s First Law of Geography

Online: 17 March 2017 (05:06:12 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints201609.0104.v1

Icing Forecasting of High Voltage Transmission Line Using Weighted Least Square Support Vector Machine with Fireworks Algorithm for Feature Selection

Tiannan Ma, Dongxiao Niu

Subject: Computer Science And Mathematics, Computer Science Keywords: icing forecasting; fireworks algorithm; least square support vector machine; feature selection

Online: 27 September 2016 (11:16:44 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202409.2138.v1

Remote Sensing in Space Analog Missions for Future Life Support Systems

Agata Maria Kołodziejczyk, Mateusz Matt Harasymczuk

Subject: Public Health And Healthcare, Public, Environmental And Occupational Health Keywords: space analog missions; isolation; sensors network; biofeedback; monitoring

Online: 27 September 2024 (00:09:50 CEST)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202403.1635.v1

On Feature Selection Techniques for Detecting DoS Attacks with a Multi-class Classifier

Iuri A. Mundstock, Yuri Santo, Thiago L. T. da Silveira, Roger Immich, André Riker, Bruno L. Dalmazo

Subject: Computer Science And Mathematics, Computer Networks And Communications Keywords: Network Security; Feature Selection; Denial of Service Attacks; Systematic Review; Smart City; Anomaly Detection

Online: 27 March 2024 (00:16:15 CET)

Show abstract| Download PDF| Share

Preprint ARTICLE | doi:10.20944/preprints202408.1620.v1

MFGFF-BiLSTM-EGP: A Chinese Nested Named Entity Recognition Model for Chicken Disease Based on Multiple Fine-Grained Feature Fusion and Efficient Global Pointer

Xiajun Wang, Cheng Peng, Qifeng Li, Qinyang Yu, Liqun Lin, Pingping Li, Ronghua Gao, Wenbiao Wu, Ruixiang Jiang, Ligen Yu, Luyu Ding, Lei Zhu

Subject: Biology And Life Sciences, Animal Science, Veterinary Science And Zoology Keywords: nested named entity recognition; chicken disease; multiple fine-grained feature fusion; RoBERTa; efficient global pointer

Online: 22 August 2024 (07:41:02 CEST)

Show abstract| Download PDF| Share

Search Results

38756 articles found