Improving detection of Parkinson’s disease with acoustic feature optimization using particle swarm optimization and machine learning by Elmoundher Hadjaidji, Mohamed Cherif Amara Korba, Khaled Khelil

“…Leveraging voice analysis and classification techniques, numerous studies explore the feasibility of early PD detection through automated systems. While several databases offer acoustic features for this purpose, their effectiveness largely depends on the classification methodology employed. …”
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Gas Leak Real-Time Detection and Volume Flow Quantification Based on Infrared Imaging and Advanced Algorithms by Man Yan, Zhou Li, Zheng Dong, Yiming Liun, Liyun Chen, Xiaosong Wu, Lijun Wu

“…In this paper, we present a strategy for automating real-time identification and quantification of gases in the mid-infrared band by combining an infrared camera combined with a series optimized algorithms. …”
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Dense-ShuffleGCANet: An Attention-Driven Deep Learning Approach for Diabetic Foot Ulcer Classification Using Refined Spatio-Dimensional Features by Armaano Ajay, Akshaj Singh Bisht, R. Karthik

“…Deep learning provides an efficient solution to the challenge by automating the process of DFU detection, thereby alleviating the burden on the healthcare industry. …”
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Towards Transparent Diabetes Prediction: Combining AutoML and Explainable AI for Improved Clinical Insights by Raza Hasan, Vishal Dattana, Salman Mahmood, Saqib Hussain

“…This study integrates Automated Machine Learning (AutoML) with Explainable Artificial Intelligence (XAI) to improve diabetes risk prediction and enhance model interpretability for healthcare professionals. …”
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Research on Mandatory Lane-Changing Behavior in Highway Weaving Sections by Wei Hao, Zhaolei Zhang, Zhibo Gao, Kefu Yi, Li Liu, Jie Wang

“…As the accident-prone sections and bottlenecks, highway weaving sections will become more complicated when it comes to the mixed-traffic environments with connected and automated vehicles (CAVs) and human-driven vehicles (HVs). …”
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Empirical case study of a digitally enabled energy community with prosumers and P2P trading by Philipp Staudt, Bent Richter

“…One direction to make energy communities more attractive to regulators and utilities is the conceptualization, design, and empirical evaluation of systems that lead to low perceived complexity for participants while enabling high levels of external automated control.…”
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Enhancing Real-Time Embedded System Education With Self-Driving Car Models by Dheya Mustafa, Safaa Mahmoud Khabour, Intisar Ghazi Mustafeh

“…Using the proposed models, real-world autodrive features exposed to automated vehicles were implemented and validated.…”
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Evolving techniques in sentiment analysis: a comprehensive review by Mahander Kumar, Lal Khan, Hsien-Tsung Chang

“…Sentiment analysis, a specialized field within natural language processing, has evolved to meet these challenges by automating the detection and categorization of opinions and emotions in text. …”
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Emerging technologies and language learning: mining the past to transform the future by Hubbard Philip

“…Today’s emerging technologies—artificial intelligence, machine learning, conversational robots, virtual worlds, virtual reality, augmented reality, automated assessment, and so on—are full of promise and seem poised to revolutionize language teaching and learning over the next decade. …”
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Partition Learning for Multiagent Planning by Jared Wood, J. Karl Hedrick

“…Automated surveillance of large geographic areas and target tracking by a team of autonomous agents is a topic that has received significant research and development effort. …”
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Analysis of The Role of Deep Learning Models in Image Classification Applications by Li Xiang

“…The integration of deep learning models, particularly Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs), has revolutionized this process, enabling the development of automated, fast, and practical systems. These advanced models are now employed in diverse areas, including biomedical science, remote sensing, and business management, thanks to their ability to achieve high accuracy across a broad spectrum of scenarios. …”
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A shallow convolutional neural network for cerebral neoplasm detection from magnetic resonance imaging by Hossein Sadr, Zeinab Khodaverdian, Mojdeh Nazari, Mohammad Yamaghani

“…The result of this study not only enables healthcare professionals to quickly and accurately identify brain malignancies but also automates the diagnostic process and minimizes dependence on manual interpretation. …”
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Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features by Emmanuel Adetiba, Oludayo O. Olugbara

“…The result of the ANN ensemble and HOG genomic features is promising for automated screening and early detection of lung cancer. …”
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Hematological Changes in Sudanese Patients with Falciparum Malaria Attending Elnihoud Teaching Hospital by Abdelnassir M. Ahamed, Hafiz Ahmed Hobiel, Gad Allah Modawe, Mohammed Saeed Elsammani

“…Questionnaire was filled by every participant and thick and thin blood films for malaria were prepared and stained by giemsa stain and the CBC was done by sysmex automated hematological analyzer. Results: Thrombocytopenia, leucopenia, microcytic hypochromic red blood cells and relative lymphocytosis have significant association with falciparum malaria with Pvalues 0.008, 0.001, 0.008, and 0.004, respectively. …”
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Sensitivity and Resolution Capacity of Electrode Configurations by Cyril Chibueze Okpoli

“…The parameters appreciate the effectiveness of automated multichannel system which has evolved several electrode arrays that are cost effective, reduction in survey time, high sensitivity, and resolution capacity in 2D and 3D resistivity tomographies. …”
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Hematoxylin and Eosin-stained whole slide image dataset annotated for skin tissue segmentationMendeley Data by Anum Abdul Salam, Muhammad Zeeshan Asaf, Muhammad Usman Akram, Noah Musolff, Samavia Khan, Bassem Rafiq, Babar Rao

“…With the advent of Artificial Intelligence (AI) and technology, the use of automated disease diagnosis systems has increased significantly. …”
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User Behavior Traffi c Replay Technology for Space-IntegratedGround Information Network Based on Profi le Analyzing by Qingsong XUE, Xiaofeng WANG

“…Faced the needs of user behavior emulation of the space-integrated-ground information network with complex behaviors and diverse protocols, an architecture based on cloud computing and virtualization technologies for replaying user behavior traffi c in the spaceintegrated-ground information network was designed.Furthermore, a user behavior traffi c automatic analysis and traffi c profi le generation technology based on deep packet inspection, and a user behavior traffi c replay technology of the space-integrated-ground information network based on traffi c profi le were researched, to achieve unifi ed, automated, and realistic simulation of miscellaneous kinds of user behavior traffi c.An emulation scenario of a space-integrated-ground information network with 6 space-based backbone network satellites and 66 space-based access network satellites was constructed.The experimental verifi cation of protocol traffi c profi le generation and traffi c replay of the broadband user behavior and narrow-band user behavior showed that the emulation of diversifi ed user interaction behaviors could provide eff ective support for the emulation of the space-integrated-ground information network.…”
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A multicenter study of neurofibromatosis type 1 utilizing deep learning for whole body tumor identification by Cheng-Jiang Wei, Yan Tang, Yang-Bai Sun, Tie-Long Yang, Cheng Yan, Hui Liu, Jun Liu, Jing-Ning Huang, Ming-Han Wang, Zhen-Wei Yao, Ji-Long Yang, Zhi-Chao Wang, Qing-Feng Li

“…Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background. …”
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Vibration Based Diagnosis for Planetary Gearboxes Using an Analytical Model by Liu Hong, Yongzhi Qu, Yuegang Tan, Mingyao Liu, Zude Zhou

“…This analytical model is easy to implement because the only prerequisite information is the basic geometry of the planetary gear-set. Afterwards, an automated diagnostic scheme is proposed to cope with the challenges associated with the characteristic configuration of planetary gearboxes. …”
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Holistic Framework for Blockchain-Based Halal Compliance in Supply Chains Enabled by Artificial Intelligence by Funlade Sunmola, George Baryannis, Albert Tan, Kenneth Co, Emmanuel Papadakis

“…This paper proposes a holistic framework for halal certification and compliance, addressing these challenges through the integration of artificial intelligence (AI) and blockchain technologies. AI can automate halal compliance checks, identify potential irregularities in sourcing and composition, and facilitate risk management. …”
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