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Preprint ARTICLE | doi:10.20944/preprints201908.0073.v1

Self-Supervised Contextual Keyword and Keyphrase Retrieval with Self-Labelling

Prafull Sharma, Yingbo Li

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: contextual keyword extraction; BERT; word embedding; LSTM; transformers; Deep Learning

Online: 6 August 2019 (09:17:36 CEST)

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Preprint REVIEW | doi:10.20944/preprints201908.0152.v1

List of Deep Learning Models

Amir Mosavi, Sina Faizollahzadeh ardabili, Annamária R. Várkonyi-Kóczy

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; machine learning model; convolutional neural networks (CNN); recurrent neural networks (RNN); denoising autoencoder (DAE); deep belief networks (DBNs); long short-term memory (LSTM); review; survey; state of the art

Online: 13 August 2019 (09:32:09 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.0148.v1

GPT-4 Can't Reason

Konstantine Arkoudas

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: GPT-4; LLM; AI; reasoning; inference

Online: 2 August 2023 (04:10:57 CEST)

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Preprint REVIEW | doi:10.20944/preprints201908.0203.v1

Advances in Machine Learning Modeling Reviewing Hybrid and Ensemble Methods

Sina Ardabili, Amir Mosavi, Annamária R. Várkonyi-Kóczy

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; deep learning; ensemble models

Online: 20 August 2019 (08:41:28 CEST)

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Preprint BRIEF REPORT | doi:10.20944/preprints202303.0422.v1

GPT-4 vs. GPT-3.5: A Concise Showdown

Anis Koubaa

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ChatGPT; GPT-4; GPT-3.5; GPT performance; GPT limitations; OpenaAI; NLP

Online: 24 March 2023 (02:23:41 CET)

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Preprint ARTICLE | doi:10.20944/preprints202206.0428.v1

Machine Learning-based Algorithms for Weather Forecasting

ismaila oshodi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; weather forecast

Online: 30 June 2022 (11:30:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202002.0197.v1

Predict Arrival Time by Using Machine Learning Algorithm to Promote Utilization of Urban Smart Bus

Rafidah Md Noor, Ng Seong Yik, Raenu Kolandaisamy, Ismail Ahmedy, Mohammad Asif Hossain, Kok-Lim Alvin Yau, Wahidah Md Shah, Tarak Nandy

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Support Vector Machine; Support Vector Regression; Machine learning; Prediction; Urban Smart Bus

Online: 15 February 2020 (14:33:23 CET)

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Preprint ARTICLE | doi:10.20944/preprints201807.0119.v1

Implementation of Regional-CNN and SSD Machine Learning Object Detection Architectures for the Real Time Analysis of Blood Borne Pathogens in Dark Field Microscopy

Daniel Fleury, Angelica Fleury

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Convolutional Neural Network,Single Shot Detector, Regional Convolutional Neural Network, Machine Learning, Visualization-Localization

Online: 6 July 2018 (14:38:52 CEST)

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Preprint REVIEW | doi:10.20944/preprints201909.0326.v1

Recent Advances in Anomaly Detection Methods applied to Aviation

Luis Basora, Xavier Olive, Thomas Dubot

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: anomaly detection; aviation; trajectory; time series; machine learning; deep learning; predictive maintenance; prognostics and health management; condition monitoring; air traffic management

Online: 29 September 2019 (06:14:02 CEST)

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Preprint REVIEW | doi:10.20944/preprints202007.0230.v1

Machine Learning: A Review of Learning Types

Shagan Sah

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine Learning

Online: 11 July 2020 (04:46:12 CEST)

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Preprint REVIEW | doi:10.20944/preprints202303.0438.v1

Exploring ChatGPT Capabilities and Limitations: A Critical Review of the NLP Game Changer

Anis Koubaa, Wadii Boulila, Lahouari Ghouti, Ayyub Alzahem, Shahid Latif

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ChatGPT; Review; Technical Novelties; Taxon-omy; Applications

Online: 27 March 2023 (03:36:47 CEST)

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Preprint REVIEW | doi:10.20944/preprints202303.0344.v1

Strategies for the Management of Spike Protein-Related Pathology

Matthew T.J. Halma, Cristof Plothe, Theresa Lawrie

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Long Covid; Covid-19 vaccine; thrombosis; clots; inflammation; therapeutics

Online: 20 March 2023 (04:37:02 CET)

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Preprint ARTICLE | doi:10.20944/preprints201607.0064.v1

Modeling, Simulation and Optimization of agricultural greenhouse microclimate by the application of artificial intelligence and / or fuzzy logic

Didi Faouzi, Nacereddine Bibi-Triki

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Greenhouse , microclimate , Modelling , fuzzy controller , Optimization , Solar Energy , Energy saving , Climate Model ,Greenhouse effect , Temperature

Online: 21 July 2016 (09:44:16 CEST)

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Agricultural greenhouse is largely answered in the agricultural sphere, despite the shortcomings it has, including overheating during the day and night cooling which sometimes results in the thermal inversion mainly due to its low inertia. The glasshouse dressed chapel is relatively more efficient than the conventional tunnel greenhouse. Its proliferation on the ground is more or less timid because of its relatively high cost[14-22]. Agricultural greenhouse aims to create a favorable microclimate to the requirements of growth and development of culture, from the surrounding weather conditions, produce according to the cropping calendars fruits, vegetables and flower species out of season and widely available along the year. It is defined by its structural and functional architecture, the quality thermal, mechanical and optical of its wall, with its sealing level and the technical and technological accompanying[12-13]. The greenhouse is a very confined environment, where multiple components are exchanged between key stakeholders and them factors are light, temperature and relative humidity[8]. This state of thermal evolution is the level sealing of the cover of its physical characteristics to be transparent to solar, absorbent and reflective of infrared radiation emitted by the enclosure where the solar radiation trapping effect otherwise called "greenhouse effect" and its technical and technological means of air that accompany. The socio-economic analysis of populations in the world leaves appear especially the last two decades of rapid and profound transformations These changes are accompanied by changes in eating habits, mainly characterized by rising consumption spread along the year[14]. To effectively meet this demand, greenhouse-systems have evolved, particularly towards greater control of production conditions (climate, irrigation, ventilation techniques, CO2 supply, etc ...). Technological progress has allowed the development of greenhouses so that they become increasingly sophisticated and of an industrial nature (heating, air conditioning, control, computer, regulation, etc ...). New climate driving techniques have emerged, including the use of control devices from the classic to the use of artificial intelligence[10-11] such as neural networks and / or fuzzy logic, etc... As a result, the greenhouse growers prefer these new technologies while optimizing the investment in the field to effectively meet the supply and demand of these fresh products cheaply and widely available throughout the year.

Preprint ARTICLE | doi:10.20944/preprints201607.0085.v1

Garments Texture Design Class Identification Using Deep Convolutional Neural Network

S.M. Sofiqul Islam, Emon Kumar Dey, Md. Nurul Ahad Tawhid, B. M. Mainul Hossain

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: CNN; Deep Learning; AlexNet; VGGNet; Texture Descriptor; Garment Categories; 13 Garment Trend Identification; Design Classification for Garments.

Online: 27 July 2016 (15:39:53 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201811.0546.v4

An Overview of Convolutional Neural Network: Its Architecture and Applications

Shadman Sakib, Nazib Ahmed, Ahmed Jawad Kabir, Hridon Ahmed

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Convolutional Neural Network (CNN), Deep learning, Architecture, Applications

Online: 14 February 2019 (10:01:31 CET)

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Preprint ARTICLE | doi:10.20944/preprints201912.0351.v1

Simulation of Turbulent Flow around a Generic High-Speed Train Using Hybrid Models of RANS Numerical Method with Machine Learning

Alireza Hajipour, Arash Mirabdolah Lavasani, Mohammad Eftekhari Yazdi, Amir Mosavi, Shahaboddin Shamshirband, Kwok-Wing Chau

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; aerodynamics; high-speed train; hybrid machine learning; Prediction Turbulence model; deep learning

Online: 26 December 2019 (05:23:14 CET)

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Preprint ARTICLE | doi:10.20944/preprints202002.0181.v1

Evaluation of Electrical Efficiency of Photovoltaic Thermal Solar Collector

Mohammad Hossein Ahmadi, Alireza Baghban, Milad Sadeghzadeh, Mohammad Zamen, Amir Mosavi, Shahaboddin Shamshirband, Ravinder Kumar, Mohammad Mohammadi-Khanaposhtani

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: renewable energy; neural networks (NNs); adaptive neuro-fuzzy inference system (ANFIS); least square support vector machine (LSSVM); photovoltaic-thermal (PV/T); hybrid machine learning model

Online: 14 February 2020 (02:53:47 CET)

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Preprint REVIEW | doi:10.20944/preprints201908.0166.v1

Deep Learning and Machine Learning in Hydrological Processes, Climate Change and Earth Systems: A Systematic Review

Sina Faizollahzadeh ardabili, Amir Mosavi, Majid Dehghani, Annamária R. Várkonyi-Kóczy

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; deep learning; big data; hydrology; climate change; global warming; hydrological model; earth systems

Online: 15 August 2019 (05:50:48 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201912.0154.v1

Weighting the Key Features Affecting Supplier Selection using Machine Learning Techniques

Ahmad Abdulla, George Baryannis, Ibrahim Badi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: supplier selection; machine learning; decision tree

Online: 11 December 2019 (12:21:26 CET)

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Preprint ARTICLE | doi:10.20944/preprints202307.2142.v2

Llama 2: Early Adopters' Utilization of Meta's New Open-Source Pretrained Model

Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios K. Nasiopoulos

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: llama 2; llama2; llama 2 projects; llama 2 model architecture; llama 2 fine-tuning

Online: 2 August 2023 (04:30:51 CEST)

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Preprint SHORT NOTE | doi:10.20944/preprints202207.0302.v1

Machine Learning Application in G.I.S. and Remote Sensing: An Overview

Anjeel Upreti

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; artificial intelligence; pattern; models; classification; regression; GIS; remote sensing

Online: 20 July 2022 (10:58:15 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202004.0257.v1

Predictive Analytics of COVID-19 Using Information, Communication and Technologies

Parikshit N. Mahalle, Nilesh P. Sable, Namita P. Mahalle, Gitanjali R. Shinde

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: COVID-19; predictive analytics; forecasting models; Machine Learning Method; prediction; epidemic; pandemic

Online: 16 April 2020 (05:54:13 CEST)

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Preprint REVIEW | doi:10.20944/preprints201911.0278.v1

Machine Learning for Clinical Decision-Making: Challenges and Opportunities

Sergio Sanchez-Martinez, Oscar Camara, Gemma Piella, Maja Cikes, Miguel Angel Gonzalez Ballester, Marius Miron, Alfredo Vellido, Emilia Gomez, Alan Fraser, Bart Bijnens

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine learning; clinical decision-making; personalized medicine; digital health

Online: 24 November 2019 (13:26:16 CET)

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Preprint ARTICLE | doi:10.20944/preprints202308.0148.v2

GPT-4 Can't Reason

Konstantine Arkoudas

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: GPT-4; LLM; AI; reasoning; inference

Online: 7 August 2023 (07:13:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202301.0521.v1

Feasibility Study on Utilization of the Artificial Intelligence GPT-3 in Public Health

David Jungwirth, Daniela Haluza

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ChatGPT; GPT-3; OpenAI; chatbots; digital health; artificial intelligence; automation; technological advancement; human-AI interaction; collaboration; open science

Online: 28 January 2023 (07:56:35 CET)

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Preprint ARTICLE | doi:10.20944/preprints201805.0102.v2

What Do We Learn from Word Associations? Evaluating Machine Learning Algorithms for the Extraction of Contextual Word Meaning in Natural Language Processing

Epaminondas Kapetanios, Saad Alshahrani, Anastasia Angelopoulou, Mark Baldwin

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; algorithms; natural language processing, deep learning, vector space models, semantic similarity, distributional semantics, latent semantic analysis, word2vec

Online: 10 May 2018 (05:56:56 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202004.0257.v2

Data Analytics: COVID-19 Prediction Using Multimodal Data

Parikshit N. Mahalle, Nilesh P. Sable, Namita P. Mahalle, Gitanjali R. Shinde

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: COVID-19; Predictive Analytics; Machine Learning; Prediction; Pandemic

Online: 14 May 2020 (09:03:52 CEST)

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Preprint REVIEW | doi:10.20944/preprints201908.0154.v1

State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability

Saeed Nosratabadi, Amir Mosavi, Ramin Keivani, Sina Faizollahzadeh ardabili, Farshid Aram

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; machine learning; smart cities; urban sustainability; cities of future; internet of things (IoT); data science; big data

Online: 13 August 2019 (10:00:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201912.0028.v1

Diversity-Generated Image Inpainting with Style Extraction

Weiwei Cai, Zhanguo Wei

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; generative adversarial networks; image inpainting; diversity inpainting

Online: 3 December 2019 (12:04:01 CET)

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Preprint ARTICLE | doi:10.20944/preprints202107.0138.v2

Study on Temperature (τ) Variation for SimCLR based Activity Recognition

Pranjal Kumar

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Contrastive learning; activity recognition; healthcare

Online: 9 July 2021 (15:46:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.1723.v1

Truth-O-Meter: Collaborating with LLM in Fighting its Hallucinations

Boris A. Galitsky

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Large Language Model; hallucination; fact-checking; multiple inconsistent sources

Online: 25 July 2023 (13:09:30 CEST)

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Preprint REVIEW | doi:10.20944/preprints201911.0338.v1

Sentiment Analysis on Indian Indigenous Languages: A Review on Multilingual Opinion Mining

Sonali Rajesh Shah, Abhishek Kaushik

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Indian; Sentiment Analysis; Indigenous Languages; Machine Learning; Deep learning; Data; Opinion Mining; Languages.

Online: 27 November 2019 (09:30:07 CET)

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Preprint ARTICLE | doi:10.20944/preprints202005.0171.v1

COVID19: A Natural Language Processing and Ontology Oriented Temporal Case-Based Framework for Early Detection and Diagnosis of Novel Coronavirus

Olaide Nathaniel Oyelade, Absalom E. Ezugwu

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Coronavirus; case-based reasoning; ontology; natural language processing

Online: 10 May 2020 (15:29:43 CEST)

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Coronavirus, also known as COVID-19, has been declared a pandemic by the World Health Organization (WHO). At the time of conducting this study, it had recorded over 1.6million cases while more than 105,000 have died due to it, with these figures rising on a daily basis across the globe. The burden of this highly contagious respiratory disease is that it presents itself in both symptomatic and asymptomatic patterns in those already infected, thereby leading to an exponential rise in the number of contractions of the disease and fatalities. It is therefore crucial to expedite the process of early detection and diagnosis of the disease across the world. The case-based reasoning (CBR) model is an effective paradigm that allows for the utilization of cases’ specific knowledge previously experienced, concrete problem situations or specific patient cases for solving new cases. This study therefore aims to leverage the very rich database of cases of COVID-19 to interpret and solve new cases even at their early stage to the advanced stage. The approach adopted in this study employs a natural language processing (NLP) technique to parse records of cases and thereafter formalize each case which is represented as a mini-ontology file. The formalized case is therefore parsed into a CBR model to allow for classification of the case into positive or negative to COVID-19. Meanwhile, feature extraction for each case is done by classifying tokens extracted by the NLP approach into special, temporal and thematic classes before encoding them using an ontology modeling method. The CBR model therefore leverages on the formalized features to compute the similarity of the new case with extracted similar cases from the archive of the CBR model. The proposed framework was populated with 68 cases obtained from the Italian Society of Medical and Interventional Radiology (SIRM) repository. Results obtained revealed that the proposed approach leverages on locations (spatial) and time (temporal) of contagion to successfully detect cases even in their early stages of two days onward before the incubation period of fourteen days. The proposed framework achieved an accuracy of 97.10%, sensitivity of 0.98 and specificity of .066. The study found that the proposed model can assist physicians to easily diagnose and isolate cases, thereby minimizing the rate of contagion and reducing false diagnosis as observed in some parts of the globe.

Preprint ARTICLE | doi:10.20944/preprints202109.0199.v1

Big Five Personality Detection Using Deep Convolutional Neural Networks

Waiel Tinwala, Shristi Rauniyar

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Big Five; Natural Language Processing; Personality Detection; Artificial Intelligence

Online: 13 September 2021 (09:59:25 CEST)

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Working Paper ARTICLE

Reach on Waste Classification and Identification by Transfer Learning and Lightweight Neural Network

Xiujie Xu, Xuehai Qi, Xingjian Diao

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: waste classification; transfer learning; deep learning; recognition classification

Online: 23 February 2020 (14:01:01 CET)

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Preprint ARTICLE | doi:10.20944/preprints201701.0097.v1

Physical Intelligence and Thermodynamic Computing

Robert L. Fry

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Carnot cycle; causality; distinguishability; entropy; intelligent processes; questions

Online: 22 January 2017 (05:23:08 CET)

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Preprint ARTICLE | doi:10.20944/preprints202003.0096.v1

Temporal Convolutional Networks Applied to Energy-related Time Series Forecasting

Pedro Lara-Benítez, Manuel Carranza-García, José M. Luna-Romera, José C. Riquelme

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Deep learning; Energy demand; Temporal convolutional network; Time series forecasting

Online: 5 March 2020 (15:02:37 CET)

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Preprint REVIEW | doi:10.20944/preprints202003.0309.v1

Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

Amir Mosavi, Pedram Ghamisi, Yaser Faghan, Puhong Duan, Shahab Shamshirband

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: economics; deep reinforcement learning; deep learning; machine learning

Online: 20 March 2020 (07:13:42 CET)

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Preprint ARTICLE | doi:10.20944/preprints202304.0827.v3

ROSGPT: Next-Generation Human-Robot Interaction with ChatGPT and ROS

Anis Koubaa

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Human-Robot Interaction; ROS; ROS2; ChatGPT; Large Language Model; Robot Operating System

Online: 26 April 2023 (03:54:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201812.0114.v1

Simultaneous Recognition of Horizontal and Vertical Text in Natural Images

Chankyu Choi, Youngmin Yoon, Junsu Lee, Junseok Kim

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: directional encoding mask; selective attention network; supervised learning; horizontal and vertical text recognition

Online: 11 December 2018 (07:24:04 CET)

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Preprint ARTICLE | doi:10.20944/preprints202305.1519.v1

Crop Prediction Model using Machine Learning Algorithms

Ersin Elbasi, Chamseddine ZAKI, Ahmet E. Topcu, Wiem Abdelbaki, Aymen I Zreikat, Elda Cina, Ahmed Younes Shdefat, Louai Saker

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: crop prediction; machine learning; feature selection; artificial intelligent; smart farming

Online: 22 May 2023 (11:24:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202004.0311.v1

COVID-19 Outbreak Prediction with Machine Learning

Sina F. Ardabili, Amir Mosavi, Pedram Ghamisi, Filip Ferdinand, Annamaria R. Varkonyi-Koczy, Uwe Reuter, Timon Rabczuk, Peter M. Atkinson

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: COVID-19; coronavirus disease; coronavirus; SARS-CoV-2; model; prediction; machine learning

Online: 19 April 2020 (01:47:10 CEST)

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Working Paper ARTICLE

Software Quality Assurance Testing Methodologies in IoT

Mehreen Sirshar, Komal Naeem, Mahnoor Khan, Tanzeela Akbar

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Internet of Things (IoT); Quality Assurance; Testing; Artificial Intelligence (AI)

Online: 9 December 2019 (07:39:47 CET)

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Preprint REVIEW | doi:10.20944/preprints202005.0234.v1

Epidemiological Challenges in Pandemic Coronavirus Disease (COVID-19): Role of Artificial Intelligence

Abhijit Dasgupta, Abhisek Bakshi, Srijani Mukherjee, Kuntal Das, Soumyajeet Talukdar, Pratyayee Chatterjee, Sagnik Mondal, Puspita Das, Subhrojit Ghosh, Archisman Som, Pritha Roy, Rima Kundu, Akash Sarkar, Arnab Biswas, Karnelia Paul, Sujit Basak, Krishnendu Manna, Chinmay Saha, Satinath Mukhopadhyay, Nitai P. Bhattacharyya, Rajat K. De

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: SIRD; Twitter; GHSI; Pre-symptomatic; EHR; Contact tracing; On-line survey; qRT-PCR; X-ray; CT/HRCT; CNN; Autoencoder; Drug affinity; CPI; and Inflation.

Online: 14 May 2020 (11:25:57 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.0827.v2

ROSGPT: Next-Generation Human-Robot Interaction with ChatGPT and ROS

Anis Koubaa

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Human-Robot Interaction; ROS; ROS2; ChatGPT; Large Language Model; Robot Operating System

Online: 25 April 2023 (03:42:52 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202005.0151.v1

COVID-DenseNet: A Deep Learning Architecture to Detect COVID-19 from Chest Radiology Images

Laboni Sarker, Md. Mohaiminul Islam, Tanveer Hannan, Zakaria Ahmed

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; CNN; DenseNet; COVID-19; transfer learning

Online: 9 May 2020 (04:54:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201901.0281.v1

Wind Turbine Maintenance Cost Reduction by Deep Learning Aided Drone Inspection Analysis

ASM Shihavuddin, Xiao Chen, Vladimir Fedorov, Nicolai Andre Brogaard Riis, Anders Nymark Christensen, Kim Branner, Anders Bjorholm Dahl, Rasmus Reinhold Paulsen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Wind Energy; Wind Turbine; Drone Inspection; Damage Detection; Deep Learning; Convolutional Neural Network (CNN)

Online: 28 January 2019 (15:50:04 CET)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints202103.0194.v1

scikit-activeml: A Library and Toolbox for Active Learning Algorithms

Daniel Kottke, Marek Herde, Tuan Pham Minh, Alexander Benz, Pascal Mergard, Atal Roghman, Christoph Sandrock, Bernhard Sick

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Active Learning, Classification, Machine Learning, Python, Github, Repository, Open Source

Online: 5 March 2021 (21:14:20 CET)

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Preprint REVIEW | doi:10.20944/preprints202011.0043.v1

Machine Learning for Stress Detection from Electrodermal Activity: A Scoping Review

Roberto Sánchez-Reolid, María T. López, Antonio Fernández-Caballero

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Electrodermal activity; Stress detection; Machine learning; Scoping review

Online: 2 November 2020 (13:37:08 CET)

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Preprint ARTICLE | doi:10.20944/preprints201912.0086.v1

Semi-CNN Architecture for Effective Spatio-Temporal Learning in Action Recognition

Mei Chee Leong, Dilip K. Prasad, Yong Tsui Lee, Feng Lin

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: action recognition; spatio-temporal features; convolution network; transfer learning

Online: 7 December 2019 (00:57:34 CET)

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Preprint REVIEW | doi:10.20944/preprints201908.0179.v1

Systematic Review of Deep Learning and Machine Learning Models in Biofuels Research

Sina Faizollahzadeh Ardabili, Amir Mosavi, Annamária R. Várkonyi-Kóczy

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: biofuels; deep learning; big data; machine learning models; biodiesel

Online: 17 August 2019 (03:48:28 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202307.0563.v1

ChatGPT and the Generation of Digitally Born “Knowledge”: How Does a Generative AI Language Model Interpret Cultural Heritage Values?

Dirk H.R. Spennemann

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: artificial intelligence; ChatGPT; construction of values; cultural heritage; cultural relativism; digitally born content; heritage management; falsified references; language model; machine learning

Online: 10 July 2023 (09:41:40 CEST)

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Preprint REVIEW | doi:10.20944/preprints201909.0019.v1

Trends in Virtual and Augmented Reality Research: A Review of Latest Eye Tracking Research Papers and Beyond

Jicheng Li, Roghayeh Barmaki

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Virtual Reality; Augmented Reality; eye tracking; deep learning; gaze estimation; collaborative computing

Online: 2 September 2019 (09:18:08 CEST)

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Preprint REVIEW | doi:10.20944/preprints202007.0479.v1

Past, Present, and Future of Face Recognition: A Review

Insaf Adjabi, Abdeldjalil Ouahabi, Amir Benzaoui, Abdelmalik Taleb-Ahmed

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Face Recognition; Face Analysis; Face Database; Deep Learning

Online: 21 July 2020 (11:13:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.1271.v1

Exploring Ethical Boundaries: Can ChatGPT Be Prompted to Give Advice on How to Cheat in University Assignments?

Dirk H.R. Spennemann

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: academic misconduct; artificial intelligence; ChatGPT; ethics; language model; machine learning

Online: 17 August 2023 (10:32:04 CEST)

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Working Paper ARTICLE

Within the Lack of Chest COVID-19 X-ray Dataset: A Novel Detection Model Based on GAN and Deep Transfer Learning

Mohamed Loey, Florentin Smarandache, Nour Eldeen M. Khalifa

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: 2019 novel coronavirus; COVID-19; SARS-CoV-2; Deep Transfer Learning; Convolutional Neural Network; Machine Learning; GAN

Online: 7 April 2020 (10:59:04 CEST)

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The coronavirus (covid-19) pandemic is putting healthcare systems across the world under unprecedented and increasing pressure according to the World Health Organization (WHO). With the advances in computer algorithms and especially Artificial Intelligence, the detection of this type of virus in the early stages will help in fast recovery and help in releasing the pressure off healthcare systems. In this paper, a GAN with deep transfer learning for coronavirus detection in chest x-ray images is presented. The lack of benchmark datasets for covid-19 especially in chest x-rays images is the main motivation of this research. The main idea is to collect all the possible images for covid-19 that exists until the writing of this research and use the GAN network to generate more images to help in the detection of the virus from the available x-rays images with the highest accuracy possible. The dataset used in this research was collected from different sources and it is available for researchers to download and use it. The number of images in the collected dataset is 307 images for four different types of classes. The classes are the covid-19, normal, pneumonia bacterial, and pneumonia virus. The dataset is divided into 90% for the GAN and the training and the validation phase, while 10% used in the testing phase. The GAN helps in generating more images from the original dataset to be 30 times larger than the originally collected dataset. The GAN also help in overcoming the overfitting problem and made the proposed model more robust. Three deep transfer models are selected in this research for investigation. The models are the Alexnet, Googlenet, and Restnet18. Those models are selected based on their small number of layers on their architectures, which will reflect in reducing the complexity of the models and the consumed memory and time. Using a combination of GAN and deep transfer models prove it is efficiency according to validation, testing accuracy, and performance measurements such as precision, recall, and F1 score. Three case scenarios are tested through the paper, the first scenario which includes 4 classes from the dataset, while the second scenario includes 3 classes and the third scenario includes 2 classes. All the scenarios include the covid-19 class as it is the main target of this research to be detected. In the first scenario, the Googlenet is selected to be the main deep transfer model as it achieves 80.6% in testing accuracy. In the second scenario, the Alexnet is selected to be the main deep transfer model as it achieves 85.2% in testing accuracy, while in the third scenario which includes 2 classes(covid-19, and normal), Googlenet is selected to be the main deep transfer model as it achieves 100% in testing accuracy and 99.9% in the validation accuracy. All the performance measurement strengthen the obtained results through the research. Finally, this research may be considered one of the first trails to use GAN and deep transfer models together to help in detecting coronaviruses (covid-19) within the absence of a benchmark dataset around the world, especially in x-rays chest images.

Preprint ARTICLE | doi:10.20944/preprints201611.0017.v1

Empirical Prediction of Turnovers in NFL Football

Joel Bock

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; unbalanced data; predicting rare events; NFL football; sports analytics

Online: 2 November 2016 (07:07:06 CET)

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Preprint REVIEW | doi:10.20944/preprints202202.0083.v1

Machine Learning and Internet of Medical Things for Handling COVID-19: Meta-Analysis

Shahab Band, Sina Ardabili, Atefeh Yarahmadi, Bahareh Pahlevanzadeh, Adiqa Kausar Kiani, Amin Beheshti, Hamid Alinejad Rokny, Iman Dehzangi, Amir Mosavi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine Learning; COVID-19; Internet of Things (IoT); Deep Learning; Big Data

Online: 7 February 2022 (11:59:05 CET)

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Preprint REVIEW | doi:10.20944/preprints201903.0033.v1

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Speech Disabled Individuals

Yasmin Elsahar, Sijung Hu, Kaddour Bouazza-Marouf, David Kerr, Annysa Mansor

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: augmentative and alternative communication; assistive technologies; sensing modalities; signal processing; voice communication; machine learning; mobile health; speech disability

Online: 4 March 2019 (10:14:44 CET)

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Preprint ARTICLE | doi:10.20944/preprints202103.0644.v1

Stress Classification of ECG-Derived HRV Features Extracted from Wearable Devices

Kayisan Mary Dalmeida, Giovanni Luca Masala

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: stress; wearable device; machine learning; smart watch; heart rate variability; electrocardiogram

Online: 25 March 2021 (16:24:00 CET)

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Preprint ARTICLE | doi:10.20944/preprints202007.0517.v1

Experimental Analysis of Time Complexity and Solution Quality of Swarm Intelligence Algorithm

Mohammed Ajuji, Aliyu Abubakar, Datti, Useni Emmanuel

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: artificial bee colony; bat; particle swarm; optimization and Opytimizer

Online: 22 July 2020 (11:04:45 CEST)

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Preprint REVIEW | doi:10.20944/preprints202102.0349.v1

Human Activity Recognition with Deep Learning: Overview, Challenges & Possibilities

Pranjal Kumar

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Learning (artificial intelligence); Neural networks; Activity recognition; Multimodal sensors

Online: 17 February 2021 (09:26:44 CET)

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Preprint HYPOTHESIS | doi:10.20944/preprints202102.0349.v4

Human Activity Recognition with Deep Learning: Methods, Progress & Possibilities

Pranjal Kumar

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Learning (artificial intelligence); Neural networks; Activity recognition

Online: 7 June 2021 (13:04:11 CEST)

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Preprint REVIEW | doi:10.20944/preprints201708.0003.v1

De-Anonymizing Authors of Electronic Texts: A Survey on Electronic Text Stylometry

Mahmoud Khonji, Youssef Iraqi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: stylometry; author identification; author verification; authorprofiling; stylistic inconsistency; text analysis; supervised learning; unsupervised learning; classification; forensics

Online: 2 August 2017 (12:38:17 CEST)

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Electronic text stylometry is a collection of forensics methods that analyze the writing styles of input electronic texts in order to extract information about authors of the input electronic texts. Such extracted information could be the identity of the authors, or aspects of the authors, such as their gender, age group, ethnicity, etc. This survey paper presents the following contributions: 1) A description of all stylometry problems in probability terms, under a unified notation. To the best of our knowledge, this is the most comprehensive definition to date. 2) A survey of key methods, with a particular attention to data representation (or feature extraction) methods. 3) An evaluation of 23,760 feature extraction methods, which is the most comprehensive evaluation of feature extraction methods in the literature of stylometry to date. The importance of this evaluation is two fold. First, identifying the relative effectiveness of the features (since, currently, many are not evaluated jointly; e.g. syntactic n-grams are not evaluated against k-skip n-grams, and so forth). Second, thanks to our generalizations, we could evaluate novel grams, such as what we name compound grams. 4) The release of our associated Python feature extraction library, namely Fextractor. Essentially, the library generalizes all existing n-gram based feature extraction methods under the "at least l-frequent, dir-directed, k-skipped n-grams'', and allows grams to be diversely defined, including definitions that are based on high-level grammatical aspects, such as POS tags, as well as lower-level ones, such as distribution of function words, word shapes, etc. This makes the library, by far, the most extensive in this domain to date. 5) The construction, evaluation, and release of the first dataset for Emirati social media text. This evaluation represents the first evaluation of author identification against Emirati social media texts. Interestingly, we find that, when using our models and feature extraction library (Fextractor), authors could be identified significantly more accurately than what is reported with similarly sized datasets. The dataset also contains sub-datasets that represent other languages (Dutch, English, Greek and Spanish), and our findings are consistent across them.

Preprint ARTICLE | doi:10.20944/preprints201811.0509.v1

Recognition of Urban Sound Events using Deep Context-Aware Feature Extractors and Handcrafted Features

Theodoros Giannakopoulos, Stavros Perantonis

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: audio recognition; context-aware; deep learning

Online: 20 November 2018 (16:32:16 CET)

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Preprint ARTICLE | doi:10.20944/preprints202005.0106.v1

Benchmark Synthetic Training Data for Artificial Intelligence-based Li-ion Diagnosis and Prognosis

Matthieu Dubarry, David Beck

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Machine Learning; Training Data; alawa; AI

Online: 7 May 2020 (06:20:09 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201908.0029.v1

Multi-Label Classification for Fault Diagnosis of Rotating Electrical Machines

Adrienn Dineva, Amir Mosavi, Mate Gyimesi, Istvan Vajda

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: multiple fault detection; rotating electrical machines; drive systems; multi-label classification; machine learning; fault severity; fault classifiers

Online: 2 August 2019 (10:44:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201807.0488.v1

Heartbeat Abnormality Detection using Machine Learning Models and Rate Variability (HRV) Data

Pratik Vyas, Diptangshu Pandit

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: heart rate variability; machine learning; abnormality detection; window shifting; high accuracy prediction

Online: 25 July 2018 (14:22:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0186.v1

Pilot Support System: A Machine Learning Approach

David Watkins, Guillermo Gallardo, Savio Chau

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: avionics systems; machine learning; big data; deep learning; pilot behavior analysis; eye tracking; automatic training system

Online: 16 April 2018 (05:22:22 CEST)

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Preprint REVIEW | doi:10.20944/preprints201912.0149.v1

Structural Damage Diagnosis and Prediction Using Machine Learning and Deep Learning Models: Comprehensive Review of Advances

Amir Mosavi

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: damage detection; machine learning; principal component analysis; composites; micromechanics of damage; continuum damage mechanics

Online: 11 December 2019 (04:50:48 CET)

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Preprint REVIEW | doi:10.20944/preprints202304.0158.v1

ChatGPT: A Brief Narrative Review

Bulbul Gupta, Tabish Mufti, Shahab Saquib Sohail, Dag Øivind Madsen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: ChatGPT; OpenAI; Artificial Intelligence (AI); Machine Learning (ML); Large Language Models (LLM)

Online: 10 April 2023 (08:40:13 CEST)

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Working Paper COMMUNICATION

Mineral Identification based on Deep Learning that Combines Image and Mohs Hardness

Xiang Zeng, Xiaohui Ji, Yancong Xiao, Gongwen Wang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: mineral identification; deep learning; convolutional neural network; image; Mohs hardness

Online: 6 August 2020 (10:14:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201902.0233.v1

A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends

Saptarshi Sengupta, Sanchita Basak, Pallabi Saikia, Sayak Paul, Vasilios Tsalavoutis, Frederick Ditliac Atiah, Vadlamani Ravi, Richard Alan Peters II

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep neural network architectures; supervised learning; unsupervised learning; testing neural networks; applications of deep learning; evolutionary computation

Online: 26 February 2019 (04:02:00 CET)

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Preprint ARTICLE | doi:10.20944/preprints201908.0202.v1

Prediction of Combine Harvester Performance Using Hybrid Machine Learning Modeling and Response Surface Methodology

Tarahom Mesri Gundoshmian, Sina Ardabili, Amir Mosavi, Annamária R. Várkonyi-Kóczy

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: combine harvester; hybrid machine learning; ANFIS; response surface methodology (RSM); artificial intelligence in agriculture; radial basis function (RBF)

Online: 20 August 2019 (08:03:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201802.0023.v1

HIVEC: A Hierarchical Approach for Vector Representation Learning of Graphs

Ayushi Patel, Ramakrishna R Mathiraj, Mausam Jai, Krishnakant Singh, Naveen Sivadasan, Vineeth N Balasubramanian

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep learning; graph kernels; unsupervised learning

Online: 4 February 2018 (10:52:50 CET)

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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 REVIEW | doi:10.20944/preprints202111.0044.v1

Deep Reinforcement Learning For Trading - A Critical Survey

Adrian Millea

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: deep reinforcement learning; model-based RL; hierarchy; trading; cryptocurrency; foreign exchange; stock market; risk; prediction; reward shaping

Online: 2 November 2021 (10:57:23 CET)

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Preprint ARTICLE | doi:10.20944/preprints201905.0090.v1

A new Deductive Method with Intelligence Using Pseudorandom Number for Solving Coin-Weighing Puzzles: Review of Inductive and Deductive Methods

Yoshiyasu Takefuji, Ren Yamada

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: intelligence; inductive methods; deductive methods; pseudorandom number; artificial intelligence; Prolog; Otter; Z3; deep learning; ensemble methods; automated reasoning; coin-weighing puzzles

Online: 8 May 2019 (10:03:46 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201810.0494.v1

Unsupervised Feature Learning in Time Series Prediction Using Continuous Deep Belief Network

Qili Chen, Guangyuan Pan, Ming Yu, Jiuhe Wang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: unsupervised training; features learning; deep learning; time series forecasting

Online: 22 October 2018 (12:24:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0808.v1

Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success

Ting Wang, Brady D. Lund, Agostino Marengo, Alessandro Pagano, Nishith Reddy Mannuru, Zoë A. Teel, Jenny Pange

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: artificial intelligence; AI; education; international students; personalized learning; adaptive learning; predictive analytics; chatbots

Online: 11 May 2023 (05:57:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0195.v1

LLMs and AI: Understanding Its Reach and Impact

Anand Gokul

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: llm; impact; society; ai; large-language-model; transformer; natural language processing; nlp

Online: 4 May 2023 (05:15:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0103.v1

PDF Malware Detection Based on Optimizable Decision Trees

Qasem Abu Al-Haija, Ammar Odeh, Hazem Qattous

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Portable Document Format (PDF); machine learning; detection; optimizable decision tree; Ada-Boost; PDF malware; evasion attacks; cybersecurity

Online: 7 September 2022 (05:33:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202009.0524.v1

Automatic Classification Approach for Detecting COVID-19 using Deep Convolutional Neural Networks

Sajib Sarker, Ling Tan, Ma Wen Jie, Rong Shan Shan, Md. Arfan Ali, Muhammad Bilal, Zhongfeng Qiu, Sanjit Kumar Mondal, Pravash Tiwari

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: COVID-19; chest X-ray images; deep convolutional neural network; COV-MCNet; deep learning

Online: 23 September 2020 (03:31:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201807.0570.v1

Towards End-to-End Acoustic Localization Using Deep Learning: From Audio Signal to Source Position Coordinates

Juan Manuel Vera-Diaz, Daniel Pizarro, Javier Macias-Guarasa

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: acoustic source localization; microphone arrays; deep learning; convolutional neural networks

Online: 30 July 2018 (09:37:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202303.0025.v1

Artificial Intelligence and the Sustainable Development Goals: GPT-3`s Reflections on the Society Domain

David Jungwirth, Daniela Haluza

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: OpenAI; ChatGPT; GPT-3; text-davinci-003; chatbots; artificial intelligence; human-AI interface; collaboration; sustainability; social development; human development

Online: 1 March 2023 (14:17:24 CET)

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Preprint ARTICLE | doi:10.20944/preprints201801.0160.v1

A Lightweight Video Detection Framework Based on Information Theory and Machine Learning

Qi Liu, Guangtai Ding

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: target detection; dynamic background; information theory; feature matrix; computing resources

Online: 17 January 2018 (12:45:29 CET)

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Preprint ARTICLE | doi:10.20944/preprints201808.0350.v1

Personalized E-Learning System Architecture Using Data Mining Approach

Samina Kausar, Huahu Xu, Iftikhar Hussain, Wenhau Zhu, Misha Zahid

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: big data; clustering; data mining; educational data mining; e-learning; profile learning

Online: 20 August 2018 (10:38:27 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202008.0265.v2

Mining Stack Overflow: a Recommender Systems-Based Model

Fouzi Harrag, Mokdad Khamliche

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Ecommender system; learning to rank; Mining software repositories; Text Mining; Deep learning; Stack Overflow

Online: 4 September 2020 (11:20:33 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/preprints202212.0188.v1

Bitcoin Price Prediction using Machine Learning and Technical Indicators

Abdelatif Hafid, Abdelhakim Senhaji Hafid, Dimitrios Makrakis

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Bitcoin price movement; machine learning; crypto price prediction

Online: 12 December 2022 (03:36:10 CET)

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Preprint ARTICLE | doi:10.20944/preprints202309.1528.v1

Will the Age of Generative Artificial Intelligence Become an Age of Public Ignorance?

Dirk H.R. Spennemann

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: artificial intelligence; ChatGPT; ethics; knowledge generation; language models; machine learning; strategic foresight

Online: 22 September 2023 (08:20:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201611.0092.v2

A Semi-Formal Multi-Policy Secure Model for Semantic Spatial Trajectories

Xingang Wang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: semantic spatial trajectory; role based access control; Bell-Lapadula model; multi-policy; Web Ontology Language

Online: 17 November 2016 (15:19:51 CET)

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Preprint ARTICLE | doi:10.20944/preprints201901.0311.v1

Machine Learning Techniques to Detecting and Preventing Jamming Attacks in Optical Networks

Mounir Bensalem, Sandeep Kumar Singh, Admela Jukan

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning

Online: 30 January 2019 (10:16:14 CET)

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Preprint ARTICLE | doi:10.20944/preprints202005.0031.v1

COVID-19 Pandemic Prediction for Hungary: A Hybrid Machine Learning Approach

Gergo Pinter, Imre Felde, Amir Mosavi, Pedram Ghamisi, Richard Gloaguen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: COVID-19; Coronavirus disease; Coronavirus; SARS-CoV-2; model; prediction; machine learning

Online: 3 May 2020 (07:44:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202112.0481.v1

Machine Learning Schemes for Anomaly Detection in Solar Power Plants

Mariam Ibrahim, Ahmad Alsheikh, Feras M. Awaysheh, Mohammad Dahman Alshehri

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: anomaly detection; machine learning; comparison analysis; renewable energy; Solar Power plants

Online: 30 December 2021 (11:51:18 CET)

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Preprint ARTICLE | doi:10.20944/preprints202110.0020.v1

Artificial Intelligence in News Media: Current Perceptions and Future Outlook

Mathias-Felipe de-Lima-Santos, Wilson Ceron

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: journalism; artificial intelligence; computer science; machine learning; computer vision; NLP.

Online: 1 October 2021 (13:33:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202201.0258.v1

Hybrid Feature Fusion and Machine Learning Approaches for Melanoma Skin Cancer Detection

Md. Mahbubur Rahman, Mostofa Kamal Nasir, Nur A-Alam, Saikat Islam Khan, Shahab Band, Iman Dehzangi, Amin Beheshti, Hamid Alinejad Rokny

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Skin cancer; Deep learning; Hybrid feature extractor; Local binary pattern; Feature extraction

Online: 18 January 2022 (12:43:50 CET)

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Preprint ARTICLE | doi:10.20944/preprints202402.1299.v1

Advancements in Quantum Computing and AI May Impact PQC Migration Timelines

Dr. Robert Campbell, Dr. Whitfield Diffie, Charles Robinson

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Post-quantum cryptography (PQC), PQC transition timelines, hybrid quantum-classical computing, artificial intelligence, machine learning, deep learning, Grover's Adaptive Search (GAS), Harrow-Hassidim-Lloyd (HHL) Algorithm

Online: 22 February 2024 (11:54:49 CET)

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Preprint ARTICLE | doi:10.20944/preprints202008.0265.v1

Mining Stack Overflow: a Recommender Systems-Based Model

Fouzi Harrag, Mokdad Khamliche

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Ecommender system; learning to rank; Mining software repositories; Text Mining; Deep learning; Stack Overflow

Online: 11 August 2020 (10:16:33 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201711.0193.v1

A Quantum Hybrid PSO Combined with Fuzzy K-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

Abdullah M. Iliyasu, Chastine Fatichah

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: computational intelligence; quantum hybrid intelligent systems; quantum machine learning; medical image processing; disease diagnosis; Fuzzy k-NN; Quantum-behaved PSO; cervical smear images; cancer detection

Online: 30 November 2017 (07:21:00 CET)

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Computer Science and Mathematics