Challenges and Prospects of Deploying AI and Machine Learning for Clinical Diagnosis in African Healthcare by Edmund Terem Ugar

“…This stems from the inherent nature of the data used to develop these technologies, primarily sourced from healthcare experiences in designing nations, coupled with the pervasive algorithmic biases prevalent in contemporary ML systems. …”
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Fraud Detection in Cryptocurrency Networks—An Exploration Using Anomaly Detection and Heterogeneous Graph Transformers by Víctor Pérez-Cano, Francisco Jurado

“…On the one hand, anomaly detection algorithms were applied to determine whether fraudulent activities tend to show anomalous behaviour without resorting to manually obtained labels. …”
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Phase Change Memory: A Review on Electrical Behavior and Use in Analog In‐Memory‐Computing (A‐IMC) Applications by Mattia Boniardi, Matteo Baldo, Mario Allegra, Andrea Redaelli

“…Abstract Recent development and progress of Artificial Intelligence (AI) algorithms made clear that this topic is a paradigm shift with respect to the past. …”
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Predicting Pulsars from Imbalanced Dataset with Hybrid Resampling Approach by Ernesto Lee, Furqan Rustam, Wajdi Aljedaani, Abid Ishaq, Vaibhav Rupapara, Imran Ashraf

“…Experiments are performed with imbalanced and balanced datasets using well-known machine learning algorithms. Results demonstrate that the proposed hybrid resampling approach proves highly influential to avoid model overfitting and increase the prediction accuracy. …”
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Event-Based Consensus for General Linear Multiagent Systems under Switching Topologies by Yinshuang Sun, Zhijian Ji, Kaien Liu

“…Obviously, compared with the continuous time control algorithms, the event-triggered control strategies can reduce the communication frequency among agents effectively. …”
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High-Precision Target Detection of Remote Sensing Image Based on Feature Enhancement with 6G Technology by Haiyan Chen

“…Military and civilian use: at present, many advanced object detection algorithms have achieved success in natural imaging, but their development is limited by two factors: large variation in object size and low detection accuracy, the scale, rotation direction, and distribution density of remote sensing images. …”
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Solving Integral Equations by Means of Fixed Point Theory by E. Karapinar, A. Fulga, N. Shahzad, A. F. Roldán López de Hierro

“…Its iterative procedures are applicable to a great variety of contexts in which other algorithms fail. In this paper, we study a very general class of integral equations by means of a novel family of contractions in the setting of metric spaces. …”
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Efficiency Optimization of the Main Operating Points of an EV Traction Motor by Gi-haeng Lee, Yong-min You

“…Subsequently, the selected metamodel was integrated with four optimization algorithms to optimize the design.…”
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Convergence and Quantum Advantage of Trotterized MERA for Strongly-Correlated Systems by Qiang Miao, Thomas Barthel

“…Here, we determine the scaling of computation costs for various critical spin chains which substantiates a polynomial quantum advantage in comparison to classical MERA simulations based on exact energy gradients or variational Monte Carlo. Algorithmic phase diagrams suggest an even greater separation for higher-dimensional systems. …”
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Enhancing fingerprint identification using Fuzzy-ANN minutiae matching by S.P. Singh, Dinesh Kumar Nishad, Saifullah Khalid

“…Utilizing a combination of minutiae-based matching and neural network algorithms, the system is designed to overcome the limitations of traditional methods, which often fail under less-than-ideal conditions. …”
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Computational thinking on concept pattern number: A study learning style Kolb by Ratni Purwasih, Turmudi Turmudi, Jarnawi Afgani Dahlan, Naufal Ishartono

“…Computational thinking students with an assimilator learning style in solving mathematical problems of number patterns can solve issues by involving decomposition, pattern identification, abstraction and generalization, and algorithms. They can generalize patterns using accurate, thorough, complete, and systematic problem-solving strategies.…”
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The Political Economy of the Gifts on Tiktok by Cristina-Oana Cristea

“…It is a multifaceted object of study, allowing research on various topics such as security and surveillance, algorithms and addiction, and communication and online interactions. …”
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Evaluation of Liver Fibrosis through Noninvasive Tests in Steatotic Liver Disease by Yuri Cho

“…Magnetic resonance elastography, with superior diagnostic accuracy and operator independence, is a promising method, but its high cost and limited availability restrict its widespread use. Emerging algorithms, such as NIS4, FAST, or MAST score, have strong potential in identifying high-risk metabolic dysfunction-associated steatohepatitis patients. …”
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On Facial Expression Recognition Benchmarks by Ebenezer Owusu, Jacqueline Asor Kumi, Justice Kwame Appati

“…This study, as a result, aims to review selected published works in the domain of study and conduct valuable analysis to determine the most common and useful algorithms employed in the study. We selected published works from 2010 to 2021 and extracted, analyzed, and summarized the findings based on the most used techniques in feature extraction, feature selection, validation, databases, and classification. …”
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On Vibration Joint Time-Frequency Investigations of CNC Milling Machines for Tool Trajectory Task Conformity Estimation by Silviu Nastac

“…It was used short time fast Fourier transform (STFFT) and Hough transform (HT) algorithms, along with stochastic evaluation of signal parameters, within time and frequency domains. …”
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Hyperbolic Metric Spaces and Stochastic Embeddings by Chris Gartland

“…Stochastic embeddings of finite metric spaces into graph-theoretic trees have proven to be a vital tool for constructing approximation algorithms in theoretical computer science. In the present work, we build out some of the basic theory of stochastic embeddings in the infinite setting with an aim toward applications to Lipschitz free space theory. …”
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N2GNet tracks gait performance from subthalamic neural signals in Parkinson’s disease by Jin Woo Choi, Chuyi Cui, Kevin B. Wilkins, Helen M. Bronte-Stewart

“…Abstract Adaptive deep brain stimulation (DBS) provides individualized therapy for people with Parkinson’s disease (PWP) by adjusting the stimulation in real-time using neural signals that reflect their motor state. Current algorithms, however, utilize condensed and manually selected neural features which may result in a less robust and biased therapy. …”
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Experimental Study to Determine the Failure Criteria of Concrete at Its Early-Age by Hongyan Ding, Lei Zhang, Puyang Zhang

“…The delay of theoretical advancement in this field resulted into a mismatch between the rough theories and the advanced algorithms, which were adopted for the estimation and analysis of early-age concrete structures. …”
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Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

“…The findings illustrate that RFR is achieving better performance than the other two algorithms, as the predicted magnitudes are close to the actual magnitudes. …”
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A Novel Approach to Word Sense Disambiguation Based on Topical and Semantic Association by Xin Wang, Wanli Zuo, Ying Wang

“…Although WSD has been researched over the years, the performance of existing algorithms in terms of accuracy and recall is still unsatisfactory. …”
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