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Preprint ARTICLE | doi:10.20944/preprints202405.0047.v1

The “Galenic Question”: A solution Based on Historical Sources and Mathematical Analysis of Texts

Fernando La Greca, Liberato De Caro, Emilio Matricciani

Subject: Arts And Humanities, History Keywords: classical Greek; deep– language variables; Galen of Pergamum; history of medicine; statistical analysis; linguistics

Online: 1 May 2024 (07:20:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.1111.v1

Predicting Machine Failures From Multivariate Time Series: An Industrial Case Study

Nicolò Oreste Pinciroli Vago, Francesca Forbicini, Piero Fraternali

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Failure prediction; Machine Learning; Deep Learning; Predictive Maintenance; Compressor; Blood refrigerator; Nitrogen generator; Wrapping machine

Online: 17 April 2024 (11:41:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.1833.v1

ResECA-Unet: Enhancement of GI Tract Segmentation Using an Improved U-Net Framework

SM Nuruzzaman Nobel, Omar Faruque Sifat, MD Rajibul Islam, MD Shohel Sayeed, Md Amiruzzaman

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: U-Net; Deep learning; Transfer learning; ECA-Net; Computer vision; GI tract; Segmentation; Radiation therapy

Online: 29 March 2024 (13:51:41 CET)

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Preprint ARTICLE | doi:10.20944/preprints202403.1484.v1

Integrated Neuro-Symbolic Analysis Pipeline for Cerebral Aneurysm Rupture Diagnosis

Max Xiao

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Neuro-symbolic; Deep learning; Data fusion; 3D segmentation; Intracranial Aneurysms; MRA; Model Pipeline

Online: 25 March 2024 (12:50:51 CET)

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Preprint ARTICLE | doi:10.20944/preprints202402.1634.v1

Enhancing Legal Sentiment Analysis: A CNN-LSTM Document-Level Model

Bolanle Abimbola, Enrique De La Cal Marin, Qing Tan

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Convolutional neural networks; deep neural networks; long short-term memory; sentimental analysis; recurrent neural networks

Online: 28 February 2024 (13:48:43 CET)

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Preprint ARTICLE | doi:10.20944/preprints202402.0821.v1

Data Augmentation with Generative Adversarial Network for Solar Panel Segmentation from Remote Sensing Images

Justinas Lekavičius, Valentas Gružauskas

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: deep learning; solar panels; semantic segmentation; data augmentation; generative adversarial network; remote sensing; transfer learning

Online: 14 February 2024 (16:32:01 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0125.v1

Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis

Roberta Avanzato, Francesco Beritelli, Alfio Lombardo, Carmelo Ricci

Subject: Computer Science And Mathematics, Signal Processing Keywords: Digital twin; IoT sensors; image processing; lung healthcare; smart healthcare; convolutional neural network; deep learning

Online: 3 January 2024 (10:36:37 CET)

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The integration of Artificial Intelligence (AI) with Digital Twins (DTs) has emerged as a promising approach to revolutionize healthcare, particularly in the diagnosis and management of thoracic disorders. This study proposes a comprehensive framework, named Lung-DT, which leverages IoT sensors and AI algorithms to establish a digital representation of a patient’s respiratory health. Using the YOLOv8 neural network, the Lung-DT system accurately classifies chest X-Rays into five distinct categories of lung diseases, including "Normal," "Covid," "Lung Opacity," "Pneumonia," and "Tuberculosis". The system’s performance was evaluated on a chest X-Ray dataset, demonstrating an impressive average accuracy of 96.6% across all classes. Further tests (prediction) were conducted on the trained network using a third dataset available in the literature and completely unknown to the network, yielding an average accuracy of 98% across three classes. The proposed Lung-DT framework offers several advantages over conventional diagnostic methods. Firstly, it enables real-time monitoring of lung health through continuous data acquisition from IoT sensors, facilitating early diagnosis and intervention. Secondly, the AI-powered classification module provides automated and objective assessments of chest X-Rays, reducing dependence on subjective human interpretation. Thirdly, the twin digital representation of the patient’s respiratory health allows for comprehensive analysis and correlation of multiple data streams, providing valuable insights for personalized treatment plans. The integration of IoT sensors, AI algorithms, and DT technology within the Lung-DT system demonstrates a significant step towards improving thoracic healthcare. By enabling continuous monitoring, automated diagnosis, and comprehensive data analysis, the Lung-DT framework has enormous potential to enhance patient outcomes, reduce healthcare costs, and optimize resource allocation.

Preprint ARTICLE | doi:10.20944/preprints202310.0329.v1

Marine Cultural Target Detection for Underwater Robotics Based on Deep Aggregation Network with Deformation Convolution

Yutuo Yang, Wei Liang, Daoxian Zhou, Yinlong Zhang, Gaofei Xu

Subject: Computer Science And Mathematics, Robotics Keywords: autonomous underwater vehicle (AUV); underwater target detection; deformable convolution; multi-scale deep aggregation; attention mechanism

Online: 6 October 2023 (11:51:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.1788.v1

Characteristics and Research Significance of Micro-Nanoparticles in Geothermal Fluids in the Central Area of Shandong Province

Lei Zuo, Peng Zhang, Yaqin Wang, Rui Liu, Guangxi Ma

Subject: Environmental And Earth Sciences, Water Science And Technology Keywords: geothermal fluids; micro-nanoparticles; TEM; NTA; deep hidden geothermal resources; central area of Shandong Province

Online: 27 September 2023 (05:44:12 CEST)

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Preprint REVIEW | doi:10.20944/preprints202309.1715.v1

Percutaneous Deep Venous Arterialization for Limb Salvage of No Option Patients with Chronic Limb-Threatening Ischemia

Stavros Spiliopoulos, Efstathia Davoutis, Nikolaos-Achilleas Arkoudis, Kaji Sritharan, Symeon Lechareas

Subject: Medicine And Pharmacology, Cardiac And Cardiovascular Systems Keywords: chronic limb-threatening ischemia; peripheral arterial disease; endovascular treatment; tibial vessels; percutaneous deep venous arterialization

Online: 26 September 2023 (04:44:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.1675.v1

Dataset and System Design for Orthopedic Walker Fall Detection and Activity Logging Using Motion Classification

Antony Garcia, Maxwell Huang

Subject: Engineering, Electrical And Electronic Engineering Keywords: orthopedic walker; dataset; IoT; fall detection; activity logging; inertial measurement unit; machine learning; deep learning

Online: 25 September 2023 (10:07:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.1392.v1

Developing an Advanced Software Requirements Classification Model Using BERT: an Empirical Evaluation Study on Newly Generated Turkish Data

Fatih Yucalar

Subject: Computer Science And Mathematics, Computer Science Keywords: software requirements classification; transformer learning; deep neural networks; machine learning; functional requirements non-functional requirements.

Online: 20 September 2023 (10:46:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.1174.v1

ENN: Hierarchical Image Classification Ensemble Neural Network for Large-Scale Automated Detection of Potential Design Infringement

Chan Jae Lee, Seong Ho Jeong, Young Yoon

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Design Right Infringement; Deep Learning; Ensemble Learning; Image Classification; Object Detection; Large-Scale Detection System

Online: 19 September 2023 (03:03:46 CEST)

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This paper presents a two-stage hierarchical neural network using image classification and object detection algorithms as key building blocks for a system that automatically detects a potential design right infringement. This neural network is trained to return the Top-N original design right records that highly resemble the input image of a counterfeit. Design rights specify the unique aesthetic characteristics of a product. Due to the rapid change of trends, new design rights are continuously generated. This work proposes an Ensemble Neural Network (ENN), an artificial neural network model that aims to deal with a large amount of counterfeit data and design right records that are frequently added and deleted. At first, we performed image classification and objection detection learning per design right using the existing models with a proven track record of high accuracy. The distributed models form the backbone of the ENN and yield intermediate results aggregated at a master neural network. This master neural network is a deep residual network paired with a fully connected network. This ensemble layer is trained to determine the sub-models that return the best result for a given input image of a product. In the final stage, the ENN model multiples the inferred similarity coefficients to the weighted input vectors produced by the individual sub-models to assess the similarity between the test input image and the existing product design rights to see any sign of violation. Given 84 design rights and the sample product images taken meticulously under various conditions, our ENN model achieved average Top-1 and Top-3 accuracies of 98.409% and 99.460%, respectively. Upon introducing new design rights data, a partial update of the inference model was done an order of magnitude faster than the single model. ENN maintained a high level of accuracy as it scaled out to handle more design rights. Therefore, the ENN model is expected to offer practical help to the inspectors in the field, such as the customs at the border that deal with a swarm of products.

Preprint ARTICLE | doi:10.20944/preprints202309.0702.v1

An Efficient Convolution Neural Network Based Novel Framework for Potato Leaf Diseases Classification and Identification

Sawrnali Khatun, Monishanker Halder, Md. Yasir Arafat, Mohammad Nowsin Amin Sheikh, Dr. Md. Nasim Adnan, Sk. Shalauddin Kabir

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Potato Leaf Diseases Detection; Classification; Transfer learning; Convolution Neural Network; Deep learning; Pre-trained Models

Online: 12 September 2023 (02:52:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.0642.v1

Combination of Physics-Informed Neural Networks and Single-Relaxation-Time Lattice Boltzmann Method for Solving Inverse Problems in Fluid Mechanics

Zhixiang Liu, Yuanji Chen, Ge Song, Wei Song, Jingxiang Xu

Subject: Computer Science And Mathematics, Mathematics Keywords: physics-informed neural networks; deep neural networks; lattice Boltzmann method; fluid mechanics; inverse problem; PDEs

Online: 11 September 2023 (07:35:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.0085.v1

The Promise of Semantic Segmentation in Detecting Actinic Keratosis Using Clinical Photography in the Wild

Panagiotis Derekas, Panagiota Spyridonos, Aristidis Likas, Athanasia Zampeta, George Gaitanis, Ioannis Bassukas

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; semantic segmentation; U‐Net; actinic keratosis; cutaneous cancerization field; skin lesions; clinical photography

Online: 4 September 2023 (04:23:19 CEST)

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Preprint REVIEW | doi:10.20944/preprints202307.0847.v1

Quorum Sensing: Unravelling the Intricacies of Microbial Communication for Biofilm Formation, Biogeochemical Cycling, and Biotechnological Applications

Edamkue Israel, Selvarajan Ramganesh, Akebe Luther King Abia, Chioma Blaise Chikere

Subject: Environmental And Earth Sciences, Environmental Science Keywords: quorum sensing; microbial communication; biofilm formation; biogeochemical cycling; biotechnological applications; marine environment; deep‐sea environment

Online: 13 July 2023 (05:26:58 CEST)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints202307.0705.v1

Technical Note: Using Computer Vision’s Pixel Segmentation to Detect Beef Cattle Feeding Behavior

Yalong Pi, Egleu Mendes, Luis Tedeschi, Jian Tao, Siddhanth Reddy, Nick Duffield

Subject: Biology And Life Sciences, Animal Science, Veterinary Science And Zoology Keywords: Computer Vision; Pixel Segmentation; Deep Learning; Convolutional Neural Network; Precision Livestock Farming; Feeding Behavior Analysis

Online: 11 July 2023 (11:52:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0830.v1

Wireless Device with Energy Management for Closed-Loop Deep Brain Stimulation (CLDBS)

Tiago Matheus Nordi, Gabriel Augusto Ginja, Rodrigo Gounella, Erich Talanoni Fonoff, Eduardo Colombari, Melkzedekue M. Alcântara Moreira, Jose A. Afonso, Vitor Monteiro, Joao L. Afonso, João Paulo Carmo

Subject: Engineering, Electrical And Electronic Engineering Keywords: closed-loop deep brain stimulation (CLDBS); neurostimulatio; implantable devices; internet of things (IoT); energy management

Online: 12 June 2023 (11:11:09 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.2180.v1

Deep Camera-Radar Fusion with Attention Framework for Autonomous Vehicle Vision in Foggy Weather Conditions

Isaac Oluwadunsin Ogunrinde, Shonda Bernadin

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Sensor fusion; object detection; deep learning; autonomous vehicles; camera-radar; adverse weather; fog; attention module

Online: 31 May 2023 (07:25:27 CEST)

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Preprint REVIEW | doi:10.20944/preprints202305.0376.v1

Monkeypox: Re-emerging Infectious Disease and One Health Strategy

Cheryl Ann Ann Alexander, Lidong Wang

Subject: Public Health And Healthcare, Public Health And Health Services Keywords: monkeypox; One Health; Big Data analytics; deep learning; blockchain; cybersecurity; vaccine; sexually transmitted diseases; HIV

Online: 6 May 2023 (04:50:56 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0007.v1

An Advanced Approach on Enhancing Accommodation Maintenance Via Text-Based Customer Review Analysis

Tharindu Wickramasinghe, Pumudu Fernando

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine Learning; Classification; Natural Language Processing; Text-based Customer Review Analysis; Sentiment Analysis; Deep Learning

Online: 1 May 2023 (03:21:05 CEST)

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Preprint REVIEW | doi:10.20944/preprints202304.1035.v1

A Review on Deriving Maintenance of Accommodations Via Text-based Feedback Analysis

Tharindu Wickramasinghe, Pumudu Fernando

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine Learning; Classification; Natural Language Processing; Text-based Customer Review Analysis; Sentiment Analysis; Deep Learning

Online: 27 April 2023 (04:30:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0645.v1

Automated Word-level Lip Reading using Convolutional Neural Networks with New Turkish Dataset

Nergis Pervan-Akman, Ali Berkol, Hamit Erdem

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Lip Reading; Multiclass Classification; Turkish Lip Reading Dataset; Deep Learning; Convolutional Neural Networks; Lip Detection

Online: 20 April 2023 (10:07:48 CEST)

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Preprint REVIEW | doi:10.20944/preprints202303.0203.v1

Liver Transplant in Patients With Hepatocarcinoma: Imaging Guidelines and Future Perspectives Using Artificial Intelligence

Mihai Dan Pomohaci, Mugur Cristian Grasu, Radu Lucian Dumitru, Mihai Toma, Ioana Gabriela Lupescu

Subject: Medicine And Pharmacology, Gastroenterology And Hepatology Keywords: Hepatocarcinoma; Cirrhosis; Liver transplantation; Liver transplant; Artificial intelligence; Machine learning; Radiomics; Deep learning; Neural networks

Online: 13 March 2023 (02:13:50 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0050.v1

A Concise Overview of the Vision-based Human Action Recognition Field

Fernando Camarena, Miguel Gonzalez-Mendoza, Leonardo Chang, Ricardo J Cuevas-Ascencio

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: video-based human action recognition; Action Recognition; Deep Learning Methods; handcrafted Methods; Human Action; Overview

Online: 3 February 2023 (01:17:56 CET)

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Preprint ARTICLE | doi:10.20944/preprints202206.0230.v1

How the First Year of the COVID-19 Pandemic Impacted Patients’ Care in the Vascular Surgery Divisions of the Southern Regions of the Italian Peninsula

Eugenio Martelli, Giovanni Sotgiu, Laura Saderi, Massimo Federici, Giuseppe Sangiorgi, Matilde Zamboni, Allegra Rosa Martelli, Giancarlo Accarino, Giuseppe Bianco, Francesco Bonanno, Umberto Marcello Bracale, Enrico Cappello, Giovanni Cioffi, Giovanni Colacchio, Adolfo Crinisio, Salvatore De Vivo, Carlo Patrizio Dionisi, Loris Flora, Giovanni Impedovo, Francesco Intrieri, Luca Iorio, Gabriele Maritati, Piero Modugno, Mario Monaco, Giuseppe Natalicchio, Vincenzo Palazzo, Fernando Petrosino, Francesco Pompeo, Raffaele Pulli, Davide Razzano, Maurizio Ruggero Ruggieri, Carlo Ruotolo, Paolo Sangiuolo, Gennaro Vigliotti, Pietro Volpe, Antonella Biello, Pietro Boggia, Michelangelo Boschetti, Enrico Maria Centritto, Flavia Condò, Lucia Cucciolillo, Amodio Salvatore D'Amodio, Mario De Laurentis, Claudio Desantis, Daniela Di Lella, Giovanni Di Nardo, Angelo Disabato, Ilaria Ficarelli, Angelo Gasparre, Antonio Nicola Giordano, Alessandro Luongo, Mafalda Massara, Vincenzo Molinari, Andrea Padricelli, Marco Panagrosso, Anna Petrone, Serena Pisanello, Roberto Prunella, Michele Tedesco, Alberto Maria Settembrini

Subject: Medicine And Pharmacology, Hematology Keywords: COVID-19; carotid stenosis; abdominal aortic aneurysm; chronic limb-threatening ischemia; amputation; deep venous thrombosis

Online: 16 June 2022 (04:40:54 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0166.v1

The Long-Term Efficacy, Prognostic Factors, Safety, and Hospitalization Costs following Denervation and Myotomy of the Affected Muscles and Deep Brain Stimulation in 94 Patients with Spasmodic Torticollis

Zhiqiang Cui, Tong Chen, Jian Wang, Zhiqi Mao, Longsheng Pan, Zhipei Ling, Jianning Zhang, Xuemei Li

Subject: Medicine And Pharmacology, Neuroscience And Neurology Keywords: spasmodic torticollis (ST); deep brain stimulation (DBS); denervation and myotomy (DAM); hospitalization cost; prognostic factors

Online: 13 June 2022 (04:12:34 CEST)

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Surgical methods for treating spasmodic torticollis include denervation and myotomy (DAM) of the affected muscles, and deep brain stimulation (DBS). This study reports on the long-term efficacy, prognostic factors, safety, and hospitalization costs following these two procedures. We collected data from 94 patients with spasmodic torticollis, of whom 41 and 53 were treated with DAM and DBS, respectively, from June 2008 to December 2020 at the Chinese People’s Liberation Army General Hospital. We used the Tsui scale and the global outcome score of the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) to evaluate the preoperative and postoperative clinical condition in all patients. We also determined the cost of hospitalization, prognostic factors, and serious adverse events following the two surgical procedures. The mean follow-up time was 68.83 months (range = 13–116). Both resection surgery and DBS showed good results in terms of Tsui (Z = -5.103, P = 0.000; Z = -6.210, P = 0.000) and TWSTRS scores (t = 8.762, P = 0.000; Z = -6.308, P = 0.000). Compared with the DAM group, the preoperative (47.71, range 24–67.25) and postoperative (18.57, range 0–53) TWSTRS scores in the DBS group were significantly higher (Z = -3.161, P = 0.002). We found no correlation between prognostic factors and the patient age, gender, or disease duration for either surgical procedure. However, prognostic factors were related to the length of the postoperative follow-up period in the DBS surgery group (Z = -2.068, P = 0.039; Z = -3.287, P = 0.001). The mean hospitalization cost in the DBS group was 6.85 times that found in the resection group (Z = -8.284, P = 0.000). The total complication rate was 4.26%. We found, both resection surgery and DBS, showed good results in the patients with spasmodic torticollis. Although DBS had a greater impact on the quality of life and the degree of pain relief, it was more expensive. Prognostic factors were related to the length of the postoperative follow-up period in patients who underwent DBS surgery.

Preprint ARTICLE | doi:10.20944/preprints202204.0279.v1

Exploiting Concepts of Instance Segmentation to Boost Detection in Challenging Environments

Khurram Azeem Hashmi, Alain Pagani, Marcus Liwicki, Didier Stricker, Muhammad Zeshan Afzal

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: object detection; challenging environments; low-light; image enhancement; complex environments; deep neural networks; computer vision

Online: 28 April 2022 (09:42:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202110.0237.v1

Deep Cross-Project Software Reliability Growth Model using Project Similarity Based Clustering

Kyawt Kyawt San, Hironori Washizaki, Yoshiaki Fukazawa, Kiyoshi Honda, Masahiro Taga, Akira Matsuzaki

Subject: Computer Science And Mathematics, Information Systems Keywords: Software reliability; deep learning; long short-term memory; project similarity and clustering; cross-project prediction

Online: 18 October 2021 (10:33:39 CEST)

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Working Paper ARTICLE

Sensor-fusion for Smartphone Location Tracking using Hybrid Multimodal Deep Neural Networks

Xijia Wei, Zhiqiang Wei, Valentin Radu

Subject: Computer Science And Mathematics, Computer Science Keywords: Indoor Localization; Sensor Fusion; Multimodal Deep Neural Network; Multimodal Sensing; WiFi Fingerprinting; Pedestrian Dead Reckoning

Online: 13 October 2021 (12:14:39 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0347.v1

A Comparative Study of Time Frequency Representation Techniques for Freeze of Gait Detection and Prediction

Tahjid Ashfaque Mostafa, Sara Soltaninejad, Tara L. McIsaac, Irene Cheng

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Parkinson’s Disease; Freeze of Gait; Deep Learning; Ensemble Learning; Wearable Sensor Data, Detection and Predication

Online: 16 August 2021 (16:48:14 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202106.0294.v1

Combining Business Model Innovation and Model-based Analysis to Tackle the Deep Uncertainty of Societal Transitions – A Case Study on Industrial Electrification and Power Grid Management

Juliana Zapata Riveros, Matthias Speich, Mirjam West, Silvia Ulli-Beer

Subject: Business, Economics And Management, Accounting And Taxation Keywords: Prosumer concepts; technology change; business strategies; system dynamics; decentralization; photovoltaic; deep uncertainty; low-carbon transitions

Online: 10 June 2021 (13:26:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202103.0165.v1

Combining Business Model Innovation and Model-Based Analysis to Tackle the Deep Uncertainty of Societal Transitions – a Case Study on Industrial Electrification and Power Grid Management

Juliana Zapata Riveros, Matthias Speich, Mirjam West, Silvia Ulli-Beer

Subject: Business, Economics And Management, Accounting And Taxation Keywords: Prosumer concepts; technology change; business strategies; system dynamics; decentralization; photovoltaic; deep uncertainty; low-carbon transitions

Online: 4 March 2021 (14:14:46 CET)

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Preprint ARTICLE | doi:10.20944/preprints202011.0591.v2

Constructing a Reliable Health Indicator for Bearings Using Convolutional Autoencoder and Continuous Wavelet Transform

Mohammadreza Kaji, Jamshid Parvizian, Hans Wernher van de Venn

Subject: Engineering, Automotive Engineering Keywords: health indicator; performance degradation assessment; deep learning; vibration monitoring; bearing; remaining useful life; digital twin

Online: 11 December 2020 (11:59:20 CET)

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Preprint ARTICLE | doi:10.20944/preprints202011.0039.v1

Generative Model for Skeletal Human Movements based on conditional DC-GAN applied to pseudo-images

Wang Xi, Guillaume Devineau, Fabien Moutarde, Jie Yang

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: generative model; human movement; conditional Deep Convolutional Generative Adversarial Network; GAN; spatio-temporal pseudo-image

Online: 2 November 2020 (12:55:22 CET)

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Preprint ARTICLE | doi:10.20944/preprints202009.0458.v1

High-Throughput Phenotyping of Soybean Maturity Using Time Series UAV Imagery and Convolutional Neural Networks

Rodrigo Trevisan, Osvaldo Pérez, Nathan Schmitz, Brian Diers, Nicolas Martin

Subject: Biology And Life Sciences, Agricultural Science And Agronomy Keywords: machine learning; deep leaning; physiological maturity; computer vision; plant breeding; Phenology; Glycine max (L.) Merr.

Online: 19 September 2020 (10:08:43 CEST)

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Preprint REVIEW | doi:10.20944/preprints202008.0320.v1

Data Science in Unveiling COVID-19 Pathogenesis and Diagnosis: Evolutionary Origin to Drug Repurposing

Jayanta Kumar Das, Giuseppe Tradigo, Pierangelo Veltri, Pietro H Guzzi, Swarup Roy

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Data Science; Machine Learning; Deep Learning; Genomics; COVID-19; Drug Discovery; Image Analysis; Interactomics; Epidemiology

Online: 14 August 2020 (11:01:56 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201811.0612.v1

A Deep Temporal Convolutional Neural Network for Regional and Teleseismic Detection

Joshua Dickey, Brett Borghetti, William Junek

Subject: Environmental And Earth Sciences, Geophysics And Geology Keywords: geophysical signal processing; pattern recognition; temporal convolutional neural networks; seismology; deep learning; nuclear treaty monitoring

Online: 29 November 2018 (03:37:48 CET)

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Preprint ARTICLE | doi:10.20944/preprints201811.0045.v1

Cyber-Physical Attack Detection and Recovery based on RNN in Automotive Brake Systems

Jongho Shin, Youngmi Baek, Jaeseong Lee, Seonghun Lee

Subject: Engineering, Electrical And Electronic Engineering Keywords: Cyber-Physical Systems; Automotive; Cyber-Physical Attack; Integrity; Sensor Attack Detection; Speed Estimation; Deep learning

Online: 2 November 2018 (10:16:50 CET)

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The violation of data integrity in automotive Cyber-Physical Systems (CPS) may lead to dangerous situations for drivers and pedestrians in terms of safety. In particular, cyber-attacks on the sensor could easily degrade data accuracy and consistency over any other attack, we investigate attack detection and identification based on a deep learning technology on wheel speed sensors of automotive CPS. For faster recovery of a physical system with detection of the cyber-attacks, estimation of a specific value is conducted to substitute false data. To the best of our knowledge, there has not been a case of joining sensor attack detection and vehicle speed estimation in existing literatures. In this work, we design a novel method to combine attack detection and identification, vehicle speed estimation of wheel speed sensors to improve the safety of CPS even under the attacks. First, we define states of the sensors based on the cases of attacks that can occur in the sensors. Second, Recurrent Neural Network (RNN) is applied to detect and identify wheel speed sensor attacks. Third, in order to estimate the vehicle speeds accurately, we employ Weighted Average (WA), as one of the fusion algorithms, in order to assign a different weight to each sensor. Since environment uncertainty while driving has an impact on different characteristics of vehicles and cause performance degradation, the recovery mechanism needs the ability adaptive to changing environments. Therefore, we estimate the vehicle speeds after assigning a different weight to each sensor depending on driving situations classified by analyzing driving data. Experiments including training, validation, and test are carried out with actual measurements obtained while driving on the real road. In case of the fault detection and identification, classification accuracy is evaluated. Mean Squared Error (MSE) is calculated to verify that the speed is estimated accurately. The classification accuracy about test additive attack data is 99.4978%. MSE of our proposed speed estimation algorithm is 1.7786. It is about 0.2 lower than MSEs of other algorithms. We demonstrate that our system maintains data integrity well and is safe relatively in comparison with systems which apply other algorithms.

Preprint ARTICLE | doi:10.20944/preprints201809.0481.v1

Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals

Zied Tayeb, Juri Fedjaev, Nejla Ghaboosi, Christoph Richter, Lukas Everding, Xingwei Qu, Yingyu Wu, Gordon Cheng, Jörg Conradt

Subject: Computer Science And Mathematics, Computer Science Keywords: Brain-Computer Interfaces, spectrogram-based convolutional neural network model(pCNN), Deep Learning, EEG, LSTM, RCNN

Online: 25 September 2018 (08:58:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202411.0139.v1

Hyperspectral Image Segmentation for Optimal Satellite Operations: In-orbit Deployment of 1D-CNN

Jon Alvarez Justo, Dennis D. Langer, Simen Berg, Jens Nieke, Radu Tudor Ionescu, Per Gunnar Kjeldsberg, Tor Arne Johansen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Earth Observation; Satellite Hyperspectral Imagery; Deep Learning; 1D-CNN; Inference; Satellite Operations; Satellite Automation; Optimal Downlink

Online: 4 November 2024 (10:52:53 CET)

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Preprint ARTICLE | doi:10.20944/preprints202411.0051.v1

Enhancing PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion Models

Jay Shah, Yiming Che, Javad Sohankar, Ji Luo, Baoxin Li, Yi Su, Teresa Wu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: partial volume correction (PVC); positron emission tomography; amyloid; deep learning; diffusion models; medical image super-resolution

Online: 1 November 2024 (11:10:41 CET)

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Preprint ARTICLE | doi:10.20944/preprints202410.1451.v1

Hybrid-3D-Convolutional-Transformer Model for Detecting Stereotypical Motor Movements in Autistic Children During Pre-Meltdown Crisis

Salma Kammoun Jarraya, Marwa Masmoudi

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Autism; Stereotypical Motor Movements; Pre-meltdown Crisis; Hybrid 3D Convolutional and Transformer Model; Deep Learning Approaches

Online: 18 October 2024 (09:20:39 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202410.0686.v1

ChatGPT: Transforming Healthcare with AI

Fnu Neha, Deepshikha Bhati, Deepak Kumar Shukla, Md Amiruzzaman

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ChatGPT; Large Language Models (LLM); Artificial intelligence (AI); Deep Learning; Digital Health; Healthcare; Health Literacy; Medicine

Online: 9 October 2024 (12:03:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202409.1861.v1

Physics-Informed Neural Network for Solving a 1-Dimensional Solid Mechanics Problem

Vishal Singh, Rajnish Mallick, Sahaj Saxena, Sharanjeet Dhawan, Manoj Sahni, Dineshkumar Harursampath

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Physics-informed Neural Network; Deep Neural Network; Artificial Neural Network; Computational Solid Mechanics; Partial Differential Equation

Online: 24 September 2024 (12:36:03 CEST)

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Preprint REVIEW | doi:10.20944/preprints202409.1217.v1

Assessing the Societal Risks of AI’s Rapid Advancement: Innovation or Threat to Safety?

Oma Zaib, Abbas Raza Ali

Subject: Computer Science And Mathematics, Computer Science Keywords: Artificial Intelligence (AI); Deep Fakes; Autonomous Vehicles (AV); Societal Safety; Cyber Security; Regulatory Frameworks

Online: 17 September 2024 (02:55:57 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202407.2352.v2

Meta-Connectivity in Urban Morphology: A Deep Generative Approach for Integrating Human-Wildlife Landscape Connectivity in Urban Design

Sheng-Yang Huang, Yuankai Wang, Enriqueta Llabres-Valls, Mochen Jiang, Fei Chen

Subject: Arts And Humanities, Architecture Keywords: urban design; deep generative models; cross-domain translation; landscape connectivity; progressive reasoning; urban ecology

Online: 22 August 2024 (09:13:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1178.v1

Achieving Real-time Prediction of Paroxysmal Atrial Fibrillation Onset by Convolutional Neural Network and Sliding Window on R-R Interval Sequences

Wenjing Chen, Peirong Zheng, Yuxiang Bu, Yuanning Xu, Dakun Lai

Subject: Engineering, Bioengineering Keywords: arrhythmias; paroxysmal atrial fibrillation; electrocardiogram; heart rate variability; deep learning; onset prediction; real-time; monitoring; algorithm

Online: 15 August 2024 (14:29:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202407.1095.v1

Impact of Image Size and Image Overlap on the Prediction Performance of Convolutional Neural Networks Trained for Road Classification

Calimanut-Ionut Cira, Miguel Angel Manso Callejo, Naoto Yokota, Tudor Sălăgean, Ana-Cornelia Badea

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: road classification; aerial orthoimagery; deep learning; image size; image overlap; convolutional neural networks; statistical performance evaluation

Online: 14 July 2024 (03:11:57 CEST)

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Popular geo-computer vision works make use of aerial imager with sizes ranging from 64 × 64 to 1024 × 1024 pixels without any overlap, although the learning process of deep learning models can be affected by the reduced semantic context or the lack of information near image boundaries. In this work, the impact of three image sizes (256 × 256, 512 × 512, and 1024 × 1024 pixels) and two image overlap levels (no overlap and 12.5% overlap) on the performance of road classification models was statistically evaluated. For this, two convolutional neural networks used in various tasks of geospatial object extraction were trained (using the same hyperparameters) on a large dataset (containing aerial image data covering 8650 km² of the Spanish territory that was labelled with binary road information) under twelve different scenarios, each scenario featuring a different combination of tile size and overlap. To assess their generalisation capacity, the performance of all resulting models was evaluated on a data from novel areas covering approximately 825 km². The performance metrics obtained were analysed using appropriate descriptive and inferential statistical techniques to evaluate the impact of the performance at distinct levels of the fixed factors (tile size, tile overlap, neural network architecture). Statistical tests were applied to study the main and interaction effects of the fixed factors on the performance. A significance level of 0.05 was applied to all the null hypothesis tests. The results were highly significant for the main effects (p-values lower than 0.001), while the two-way and three-way interaction effects among them had different levels of significance. The results indicate that the training of road classification models on images with a higher tile size (more semantic context) and tile overlap (additional border context and continuity) significantly impacts their performance. The best model was trained on a dataset featuring tiles with a size of 1024 × 1024 pixels and a 12.5% overlap and achieved a loss value of 0.0984, an F1 score of 0.8728, and an ROC-AUC score of 0.9766, together with an error rate of 3.5% on the test set.

Preprint ARTICLE | doi:10.20944/preprints202405.2022.v1

Comprehensive Neural Cryptanalysis on Block Ciphers Using Different Encryption Methods

Ongee Jeong, Ezat Ahmadzadeh, Inkyu Moon

Subject: Computer Science And Mathematics, Security Systems Keywords: artificial intelligence; cryptanalysis; block cipher; data encryption standard (DES); advanced encryption standard (AES); SPECK; deep learning

Online: 31 May 2024 (02:37:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202405.1971.v1

The Impact of AI on Metal Artifacts in CBCT Oral Cavity Imaging

Róża Wajer, Adrian Wajer, Natalia Kazimierczak, Justyna Wilamowska, Zbigniew Serafin

Subject: Medicine And Pharmacology, Other Keywords: Cone-Beam Computed Tomography; Deep Learning Model; Image Quality; Noise Reduction; Dental Imaging; Metal Artifact Reduction

Online: 29 May 2024 (11:53:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202405.0659.v1

Facial Pain Expression Detection System using TXQEDA-Deep for Pain Evaluation

Rachid Aliradi, Nidhaleddine Chenni, Mohammed Touami, Ridha Ejbali, Najib Benaoun

Subject: Computer Science And Mathematics, Computer Science Keywords: Accuracy; Pain Assessment; PSPI; SVC; SVM; Multilinear subspace learning; TXQEDA; CNN-Deep Learning; UNBC McMaster dataset

Online: 10 May 2024 (11:52:37 CEST)

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Preprint REVIEW | doi:10.20944/preprints202405.0377.v1

How AI and Robotics Will Advance Interventional Radiology: A Narrative Review and Future Perspectives

Jiaming Zhang, Jiayi Fang, Yanneng XU, Guangyan Si

Subject: Medicine And Pharmacology, Clinical Medicine Keywords: Artificial Intelligence; Robot; Deep Learn; Machine Learn; Convolutional Neural Networks; Interventional Oncology; Interventional Neuroradiology; Interventional Cardiology.

Online: 7 May 2024 (11:41:25 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202405.0021.v1

Turning Features Detection from Aerial Images: Model Development and Application on Florida’s Public Roadways

Richard Boadu Antwi, Michael Kimollo, Eren Erman Ozguven, Thobias Sando, Ren Moses, Maxim A. Dulebenets

Subject: Engineering, Transportation Science And Technology Keywords: Turning lanes; Deep Learning; Roadway Characteristic Index (RCI); Pavement Markings; Machine Learning (ML); Roadway Geometry Features

Online: 1 May 2024 (04:28:21 CEST)

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Preprint REVIEW | doi:10.20944/preprints202404.1084.v1

Plant Synthetic Promoters

Piotr Szymczyk, Małgorzata Majewska

Subject: Biology And Life Sciences, Biology And Biotechnology Keywords: plant synthetic promoter; enhancer; cis-element; trans-factor; orthogonal systems; bidirectional promoters; machine learning; deep learning

Online: 17 April 2024 (07:26:01 CEST)

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Preprint REVIEW | doi:10.20944/preprints202404.0188.v1

Neuromodulation and the Gut-Brain Axis: Therapeutic Mechanisms and Implications for Gastrointestinal and Neurological Disorders

Baha’ Aljeradat, Danisha Kumar, Suliman Abdulmuizz, Mrinmoy Kundu, Yasser F. Almealawy, Dima Ratib Batarseh, Oday Atallah, Michelle Ennabe, Muath Alsarafandi, Albert Alan, Martin Weinand

Subject: Medicine And Pharmacology, Neuroscience And Neurology Keywords: Gut-Brain-Axsis; Neuromodulation; Deep Brain stimulation; Vagus nerve Stimulation; Irritable Bowel Syndrome; Inflammatory Bowel Disease.

Online: 2 April 2024 (10:40:18 CEST)

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Preprint REVIEW | doi:10.20944/preprints202404.0055.v1

Optimizing Lead Compounds: The Role of Artificial Intelligence in Drug Discovery

Sarfaraz K. Niazi, Zamara Mariam, Matthias Magoola

Subject: Computer Science And Mathematics, Mathematical And Computational Biology Keywords: Lead optimization; drug discovery; artificial intelligence; machine learning; deep neural networks; cheminformatics; chemical modifications; drug development

Online: 1 April 2024 (13:35:22 CEST)

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Preprint CASE REPORT | doi:10.20944/preprints202403.1073.v1

Improved Brain Function with Deep Spectrum Biotherapeutics

Iain Strickland, David S Oakley, Anna Parievsky

Subject: Medicine And Pharmacology, Neuroscience And Neurology Keywords: Electroencephalogram (EEG); Event Related Potential (ERP); Advanced &; Deep Biotherapeutics; Photobiomodulation (PBM); Mild Cognitive Impairment (MCI)

Online: 19 March 2024 (05:13:05 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.1817.v1

Hybrid Neural Networks for Enhanced Prediction of Remaining Useful Life in Lithium-Ion Batteries

Alireza Rastegarparnah, Mohammed Eesa Asif, Rustam Stolkin

Subject: Engineering, Other Keywords: Deep Learning; Remaining Useful Life; Lithium-Ion Batteries; Battery Management Systems; Recycling and Reuse; Battery Degradation

Online: 25 January 2024 (10:40:34 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.1249.v1

MODEAS – a Counter-UAV System with Optical and Radar Sensors

Alina Lindner, Thomas Müller, Lars Wilko Sommer, Thomas Emter, Angelika Zube, Alexander Kröker

Subject: Engineering, Electrical And Electronic Engineering Keywords: counter-UAV; UAV detection; UAV classification; UAV tracking; optical sensors; radar; artificial intelligence (AI); deep learning

Online: 16 January 2024 (15:31:27 CET)

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Preprint REVIEW | doi:10.20944/preprints202312.2293.v1

Potential of Deep Eutectic Solvents in the Extraction of Organic Compounds From Food Industry By-Products and Agro-Industrial Waste

Maja Molnar, Dajana Gašo Sokač, Mario Komar, Martina Jakovljević Kovač, Valentina Bušić

Subject: Chemistry And Materials Science, Applied Chemistry Keywords: deep eutectic solvents; bioactive organic compounds; food industry by-products; greener sol-vents; agro-industrial waste

Online: 3 January 2024 (09:55:33 CET)

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Preprint REVIEW | doi:10.20944/preprints202312.1362.v1

A Comprehensive Review on Deep Eutectic Solvents and Its Use to Extract Bioactive Compounds of Pharmaceutical Interest

Cátia Ferreira, And Mafalda Sarraguça

Subject: Chemistry And Materials Science, Other Keywords: Green Chemistry; Sustainability; Neoteric Solvents; Deep Eutectic Solvents; Bioactive Compounds; Extraction techniques; Natural products; Pharmaceutical Industry

Online: 19 December 2023 (07:23:48 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.1299.v1

A Deep Sequencing Strategy for Investigation of Virus Variants Within African Swine Fever Virus-infected Pigs

Camille Melissa Johnston, Ann Sofie Olesen, Louise Lohse, Agnete le Maire Madsen, Anette Bøtner, Graham J. Belsham, Thomas Bruun Rasmussen

Subject: Biology And Life Sciences, Virology Keywords: African swine fever virus (ASFV); next-generation sequencing (NGS); deep sequencing; Nanopore sequencing; minority variant analysis

Online: 18 December 2023 (09:08:56 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.0011.v1

Enhancing Fingerprint Forensics: A Comprehensive Study of Gender Classification Based on Advanced Data-Centric AI Approaches and Multi-Database Analysis

Assaf Spanier, Dor Steiner, Navon Sahalo, Yoel Abecassis, Dan Ziv, Ido Hefetz, Shimon Kimchi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; fingerprint; Gender classification; Data-Centric AI (DCAI); forensic science; Partial or low-quality fingerprint

Online: 1 December 2023 (08:15:23 CET)

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Preprint ARTICLE | doi:10.20944/preprints202311.1888.v1

SkinLesNet: Classification of Skin Lesions Using a Multi-Layer Deep Convolutional Neural Network in Dermoscopy Images

Muhammad Azeem, Kaveh Kiani, Taha Mansouri

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; convolutional neural networks; image analysis; machine learning; ResNetV50; skin lesions; VGG16; cancer; computer vision

Online: 29 November 2023 (11:33:49 CET)

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Preprint ARTICLE | doi:10.20944/preprints202310.1519.v1

Continuous Super-Resolution of Climate Data Using Time-aware Implicit Neural Representation

Yang Wang, Hassan A. Karimi, Xiaowei Jia

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Deep Learning; Implicit Neural Representation; Sea Surface Temperature; Super Resolution; Satellite Retrieval Climate Data; Temporal Information

Online: 24 October 2023 (13:26:54 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202310.0467.v1

Extruder Machine Gear Fault Detection Using Autoencoder LSTM via Senor Fusion Approach

Joon-Hyuk Lee, Chibuzo Nwabufo Okwuosa, Jang-Wook Hur

Subject: Engineering, Industrial And Manufacturing Engineering Keywords: Anomaly detection; autoencoder; long short-term memory; deep learning; discrete wavelet transform, feature extraction, outlier detection.)

Online: 9 October 2023 (07:34:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.2105.v1

Precision in Dermatology: Developing an Optimal Feature Selection Framework for Skin Lesion Classification

Tallha Akram, Riaz Junejo, Anas Alsuhaibani, Muhammad Rafiullah, Adeel Akram, Nouf Abdullah Almujally

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: convolutional neural networks; feature selection; transfer learning; feature fusion; gray wolf optimization; deep learning; skin lesion

Online: 31 August 2023 (10:24:52 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.0555.v1

Postural instability and risk of falls in patients with Parkinson’s disease treated with deep brain stimulation: a stabilometric platform study

Giorgio Leodori, Marco Santilli, Nicola Modugno, Michele D’Avino, Maria Ilenia De Bartolo, Andre Fabbrini, Lorenzo Rocchi, Antonella Conte, Giovanni Fabbrini, Daniele Belvisi

Subject: Medicine And Pharmacology, Neuroscience And Neurology Keywords: deep brain stimulation; fall risk; falls; parkinson’s disease; postural instability; stabilometric platform; movement disorders; postural control.

Online: 7 August 2023 (12:03:46 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.0258.v1

Autonomously Steering Vehicles Along Unmarked Roads Using Low-Cost Sensing and Computational Systems

Giuseppe DeRose, Austin Ramsey, Justin Dombecki, Nicholas Paul, Chan-Jin Chung

Subject: Computer Science And Mathematics, Robotics Keywords: Autonomous vehicles; self-drive vehicles; deep learning; convolutional neural networks; recurrent neural networks; image histogram matching

Online: 3 August 2023 (08:20:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.1510.v1

Advancing Pig Welfare Assessment: Introducing the SSPD-PER Method for Objective and Reliable Pig Emotion Recognition

Jung Hwan Kim, Savina Jassica Colaco, Alwin Poulose, Suresh Neethirajan, Dong Seog Han

Subject: Biology And Life Sciences, Aquatic Science Keywords: Pig emotion recognition (PER); convolution neural network (CNN); Xception; ResNet; deep neural network; domestic livestock; pigs

Online: 21 July 2023 (11:15:43 CEST)

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Preprint REVIEW | doi:10.20944/preprints202305.1637.v2

Computational Advancements in Cancer Combination Therapy Prediction

Victoria L. Flanary, Jennifer L. Fisher, Elizabeth J. Wilk, Timothy C. Howton, Brittany N. Lasseigne

Subject: Medicine And Pharmacology, Oncology And Oncogenics Keywords: computational; drug repurposing; drug repositioning; cancer; combination therapy; network biology; machine learning; deep learning; precision oncology

Online: 20 July 2023 (05:02:16 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.0219.v1

Joint Latency-Oriented, Energy Consumption, and Carbon Emission for Space-Air-Ground Integrated Network with New Designed Power Technology

Yonghao Wang, Bo Li, Jiahao He, Jiaxing Dai, Yuxin Yang, Yidong Liu

Subject: Computer Science And Mathematics, Other Keywords: space-air-ground integrated network; renewable energy; twin delayed deep deterministic policy gradient; latency; energy consumption

Online: 4 July 2023 (11:24:56 CEST)

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Preprint REVIEW | doi:10.20944/preprints202306.2225.v1

A Review of Brain Tumor Diagnosis and Segmentation

Reham Kaifi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Brain tumors; magnetic resonance imaging; computed tomography; computer-aided diagnostic and detection; Deep learning; Machine learning

Online: 30 June 2023 (14:56:31 CEST)

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Preprint REVIEW | doi:10.20944/preprints202306.1124.v1

Redefining Radiology: A Review of Artificial Intelligence Integration in Medical Imaging

Reabal Najjar

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Medical imaging; radiology; artificial intelligence; machine learning; deep learning; convolutional neural networks; computer-aided diagnosis; radiomics.

Online: 16 June 2023 (03:22:26 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0262.v1

Improved DeepSORT-Based Object Tracking in Foggy Weather for AVs Using Sematic Labels and Fused Appearance Feature Network

Isaac Oluwadunsin Ogunrinde, Shonda Bernadin

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Multi-object tracking; DeepSORT; object detection; sensor fusion; deep learning, autonomous vehicles; radars; adverse weather; fog

Online: 5 June 2023 (08:09:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0156.v1

Three-Dimensional Cranio-Facial Landmark Detection in Series of CT Slices, Using Multi-Phased Regression Networks

Soh Nishimoto, Takuya Saito, Hisako Ishise, Toshihiro Fujiwara, Kenichiro Kawai, Masao Kakibuchi

Subject: Medicine And Pharmacology, Dentistry And Oral Surgery Keywords: Multi-phased deep learning; Regression neural network; Coordinate value; Computer assisted tomography (CT); Cranio-facial bone

Online: 10 April 2023 (07:59:58 CEST)

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Preprint REVIEW | doi:10.20944/preprints202303.0116.v1

Explainable Artificial Intelligence (XAI) in Healthcare

Tim Hulsen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: XAI; AI; artificial intelligence; explainable; explainability; machine learning; deep learning; data science; big data; healthcare; medicine

Online: 7 March 2023 (01:43:13 CET)

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Preprint ARTICLE | doi:10.20944/preprints202302.0299.v1

Using Ensemble Convolutional Neural Network to Detect Deepfakes Using Periocular Data

David Johnson, Xiaohonh Yuan, Kaushik Roy

Subject: Computer Science And Mathematics, Computer Science Keywords: deepfake detection; CNN; deep neural network; computer vision; scale invariant feature transform; histogram of oriented gradients

Online: 17 February 2023 (06:51:37 CET)

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Preprint DATA DESCRIPTOR | doi:10.20944/preprints202301.0473.v1

Prognosease: A Data Generator for Health Deterioration Prognosis

Tarek BERGHOUT, Mohamed Benbouzid

Subject: Computer Science And Mathematics, Applied Mathematics Keywords: Data generator; dataset; deep learning; health index; machine learning; prognosis and health management; remaining useful life

Online: 26 January 2023 (08:37:30 CET)

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Preprint ARTICLE | doi:10.20944/preprints202210.0477.v1

FlowerPhenoNet: Automated Flower Detection from Multi-view Image Sequences using Deep Neural Networks for Temporal Plant Phenotyping Analysis

Sruti Das Choudhury, Samarpan Guha, Aankit Das, Amit Kumar Das, Ashok Samal, Tala Awada

Subject: Computer Science And Mathematics, Analysis Keywords: High Throughput Plant Phenotyping; Deep Neural Network; Flower Detection; Temporal Phenotypes; Benchmark Dataset; Flower Status Report

Online: 31 October 2022 (10:00:24 CET)

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Preprint ARTICLE | doi:10.20944/preprints202210.0448.v1

Leveraging Computer Vision Application in Visual Arts: A Case Study on the Use of Residual Neural Network to Classify and Analyze Baroque Paintings

Daniel Kvak

Subject: Arts And Humanities, Art Keywords: computational creativity; deep learning; feature extraction; image analysis; machine perception; painting classification; residual networks; transfer learning

Online: 28 October 2022 (09:37:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0197.v1

An Ontological Knowledge Base of Poisoning Attacks on Deep Neural Networks

Majed Altoub, Fahad AlQurashi, Tan Yigitcanlar, Juan Corchado, Rashid Mehmood

Subject: Computer Science And Mathematics, Computer Science Keywords: Deep neural networks; Adversarial Attacks; Poisoning; Backdoors; Trojans; Taxonomy; Ontology; Knowledge Base; Explainable AI; Green AI

Online: 10 August 2022 (09:39:07 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202204.0163.v1

Jointly Optimized Deep Neural Networks to Synthesize Monoenergetic Images from Single-Energy CT Angiography for Improving Classification of Pulmonary Embolism

Matthias A Fink, Constantin Seibold, Hans-Ulrich Kauczor, Rainer Stiefelhagen, Jens Kleesiek

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: artificial intelligence; deep learning; image-to-image translation; dual-energy computed tomography; pulmonary embolism; emergency radiology

Online: 18 April 2022 (09:45:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0149.v1

HPV DeepSeq: Ultra-Fast Method of NGS Data Analysis and Visualization Using Automated Workflows and a Customized Papillomavirus Database in CLC Genomics Workbench

Jane Shen-Gunther, Qingqing Xia, Hong Cai, Yufeng Wang

Subject: Biology And Life Sciences, Biochemistry And Molecular Biology Keywords: Bioinformatics; Cervical cancer; Deep Sequencing; Human papillomavirus; HPV genotyping; Metagenome; Next generation sequencing; Taxonomic classification; Virome

Online: 6 August 2021 (08:00:00 CEST)

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Preprint REVIEW | doi:10.20944/preprints202106.0609.v1

Treatment-Free Remission in Chronic Myeloid Leukaemia: Can We Identify Prognostic Factors?

Hilbeen Hisham Saifullah, Claire Marie Lucas

Subject: Medicine And Pharmacology, Immunology And Allergy Keywords: Chronic myeloid leukaemia; chronic phase; Tyrosine kinase inhibitor; Treatment free remission; deep molecular response; BCR-ABL.

Online: 25 June 2021 (08:13:40 CEST)

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Preprint REVIEW | doi:10.20944/preprints202106.0448.v1

Current Knowledge on the Background, Pathophysiology, and Treatment of Levodopa-Induced Dyskinesia – Literature Review.

Michał Jan Hutny, Jagoda Maria Hofman, Aleksandra Klimkowicz-Mrowiec, Agnieszka Gorzkowska

Subject: Medicine And Pharmacology, Immunology And Allergy Keywords: Parkinson’s disease; abnormal involuntary movements; dopaminergic signaling; basal ganglia; spiny projection neurons; neurotransmission; deep brain stimulation

Online: 16 June 2021 (14:17:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202106.0053.v1

Sentiment Analysis Techniques Applied to Raw-Text Data from a CSQ-8 Questionnaire About Mindfulness in Times of Covid-19 to Improve Strategy Generation

Mario Jojoa, Gema Castillo-Sánchez, Begonya Garcia-Zapirain, Isabel De la Torre Diez, Manuel Franco-Martín

Subject: Engineering, Automotive Engineering Keywords: Mindfulness; stress; COVID-1; CSQ-8; Natural Language Processing; Deep Learning; Embedding; IMDB; Swivel; Neural Networks.

Online: 2 June 2021 (08:40:48 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202105.0605.v1

COVID-19 Diagnosis from chest CT Scans: A Weakly Supervised CNN-LSTM Approach

Mustafa Kara, Zeynep Öztürk, Sergin Akpek, Ayşegül Turupcu

Subject: Computer Science And Mathematics, Algebra And Number Theory Keywords: deep learning; computed tomography; image classification; COVID-19; medical image analysis; pneumonia; CNN, LSTM, medical diagnosis

Online: 25 May 2021 (10:32:29 CEST)

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Working Paper ARTICLE

Hydrodynamic Forces Exerted on an Oscillating Cylinder at Its Translational Motion in Water Covered by a Compressed Ice

Yury Stepanyants, Izolda Sturova

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: Ideal fluid; deep water; ice cover; moving cylinder; hydrodynamic load; added mass; wave resistance; damping coefficient

Online: 21 January 2021 (15:21:49 CET)

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Preprint ARTICLE | doi:10.20944/preprints202006.0104.v1

Can Biochar Save Lives? The Impact of Surficial Biochar Treatment on Acute H₂S and NH₃ Emissions During Swine Manure Agitation Before Pump-out

Baitong Chen, Jacek A. Koziel, Myeongseong Lee, Hantian Ma, Zhanibek Meiirkhanuly, Peiyang Li, Andrzej Białowiec, Robert C. Brown

Subject: Environmental And Earth Sciences, Environmental Science Keywords: biochar; hydrogen sulfide; ammonia; livestock manure; agricultural safety; deep pit storage; waste management; air pollution; odor

Online: 7 June 2020 (15:54:48 CEST)

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Hydrogen sulfide and ammonia are always a concern in the livestock industries, especially when farmers try to clear their manure storage pits. Agitation of manure can cause dangerously high concentrations of harmful agents such as H₂S and NH₃ to be emitted into the air. Biochar has the ability to sorb these gases. We hypothesized that applying biochar on top of manure can create an effective barrier to protect farmers and animals from exposure to NH₃ and H₂S. In this study, two kinds of biochar were tested, highly alkaline, and porous (HAP, pH 9.2) biochar made from corn stover and red oak biochar (RO, pH 7.5). Two scenarios of (6 mm) 0.25” and (12 mm) 0.5” thick layers of biochar treatments were topically applied to the manure and tested on a pilot-scale setup, simulating a deep pit storage. Each setup experienced 3-min of agitation using a transfer pump, and measurements of the concentrations of NH₃ and H₂S were taken in real-time and measured until the concentration stabilized after the sharp increase in concentration due to agitation. The results were compared with the control in the following 3 situations: 1. The maximum (peak) flux 2. Total emission from the start of agitation until the concentration stabilized, and 3. The total emission during the 3 min of agitation. For NH₃, 0.5” HAP biochar treatment significantly (p<0.05) reduced maximum flux by 63.3%, overall total emission by 70%, and total emissions during the 3-min agitation by 85.2%; 0.25” HAP biochar treatment significantly (p<0.05) reduced maximum flux by 75.7%, overall, total emission by 74.5%, and total emissions during the 3-min agitation by 77.8%. 0.5” RO biochar treatment significantly reduced max by 8.8%, overall total emission by 52.9%, and total emission during 3-min agitation by 56.8%; 0.25” RO biochar treatment significantly reduced max by 61.3%, overall total emission by 86.1%, and total emission during 3-min agitation by 62.7%. For H₂S, 0.5” HAP biochar treatment reduced the max by 42.5% (p=0.125), overall total emission by 17.9% (p=0.290), and significantly reduced the total emission during 3-min agitation by 70.4%; 0.25” HAP treatment reduced max by 60.6% (p=0.058), and significantly reduced overall and 3-min agitation’s total emission by 64.4% and 66.6%, respectively. 0.5” RO biochar treatment reduce the max flux by 23.6% (p=0.145), and significantly reduced overall and 3-min total emission by 39.3% and 62.4%, respectively; 0.25” RO treatment significantly reduced the max flux by 63%, overall total emission by 84.7%, and total emission during 3-min agitation by 67.4%.

Preprint REVIEW | doi:10.20944/preprints202004.0325.v1

Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-like Epidemics: A Survey

Dinh C. Nguyen, Ming Dinh, Pubudu N. Pathirana, Aruna Seneviratne

Subject: Medicine And Pharmacology, Epidemiology And Infectious Diseases Keywords: COVID-19; artificial intelligence; AI; blockchain; epidemic; pandemic; machine learning; deep learning; coronavirus; SARS-CoV-2

Online: 19 April 2020 (04:44:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201905.0244.v1

Ensemble of Deep Convolutional Neural Networks for Classification of Early Barrett's Neoplasia Using Volumetric Laser Endomicroscopy

Roger Fonollà, Thom Scheeve, Maarten R. Struyvenberg, Wouter L. Curvers, Albert J. de Groof, Fons van der Sommen, Erik J. Schoon, Jacques J.G.H.M. Bergman, Peter H.N. de With

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Barrett's esophagus; deep learning; volumetric laser endomicroscopy; optical coherence tomography; classification; esophageal adenocarcinoma; glands; machine learning

Online: 20 May 2019 (11:50:09 CEST)

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Preprint REVIEW | doi:10.20944/preprints201805.0011.v1

Changing Trends in Computational Drug Repositioning

Jaswanth K. Yella, Suryanarayana Yaddanapudi, Yunguan Wang, Anil G. Jegga

Subject: Medicine And Pharmacology, Pharmacology And Toxicology Keywords: computational drug repositioning; drug repositioning; drug repurposing; machine learning; deep learning; crowdsourcing; open innovation; drug discovery

Online: 1 May 2018 (12:27:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201706.0012.v3

Road Segmentation on Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields

Teerapong Panboonyuen, Peerapon Vateekul, Kulsawasd Jitkajornwanich, Siam Lawawirojwong, Panu Srestasathiern

Subject: Engineering, Control And Systems Engineering Keywords: deep convolutional neural networks; road segmentation; conditional random fields; landscape metrics; satellite images; aerial images; THEOS

Online: 5 June 2017 (06:39:54 CEST)

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Preprint REVIEW | doi:10.20944/preprints202105.0254.v1

AI-enabled Efficient and Safe Food Supply Chain

Ilianna Kollia, Jack Stevenson, Stefanos Kollias

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; deep neural networks; recurrent LSTM models; attention layers; latent variable extraction; domain adaptation; yield and growth prediction in greenhouses; energy optimization in retail refrigerator systems; verification and recognition of expiry date in retail food packaging.

Online: 11 May 2021 (15:46:14 CEST)

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Preprint REVIEW | doi:10.20944/preprints202410.1058.v1

Advances and Challenges in Automated Drowning Detection and Prevention Systems

Maad Shatnawi, Frdoos Ali Albreiki, Ashwaq Alkhoori, Mariam Alhebshi, Anas Shatnawi

Subject: Engineering, Control And Systems Engineering Keywords: Drowning detection; prevention; rescue; Swimming pool safety; IoT; artificial intelligence: AI; deep learning; machine learning; surveillance technology

Online: 14 October 2024 (13:25:50 CEST)

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Preprint REVIEW | doi:10.20944/preprints202410.0792.v1

State-of-the-Art DC-DC Converters for Satellite Applications: A Comprehensive Review

Reshma Ravindran, Ahmed M. Massoud

Subject: Engineering, Electrical And Electronic Engineering Keywords: aerospace; DC-DC converters; deep space missions; high power electric propulsion; modular interleaved converters; satellite power system

Online: 10 October 2024 (12:56:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.1852.v1

A Novel Two-Stage Hybrid Model Optimization with FS-FCRBM-GWDO for Accurate and Stable STLF

Eustache Uwimana, Yatong Zhou

Subject: Engineering, Electrical And Electronic Engineering Keywords: Genetic wind-driven optimization algorithm; Short-term load forecasting; Factored conditional deep belief network; Efficiency energy consumption

Online: 26 August 2024 (15:35:31 CEST)

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