Skin Cancer Image Classification Using Artificial Intelligence Strategies: A Systematic Review by Ricardo Vardasca, Joaquim Gabriel Mendes, Carolina Magalhaes

“…The increasing incidence of and resulting deaths associated with malignant skin tumors are a public health problem that can be minimized if detection strategies are improved. …”
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Breast cancer classification based on hybrid CNN with LSTM model by Mourad Kaddes, Yasser M. Ayid, Ahmed M. Elshewey, Yasser Fouad

“…Abstract Breast cancer (BC) is a global problem, largely due to a shortage of knowledge and early detection. …”
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Comparative study of soft neurological signs in patients of schizophrenia and bipolar disorder at a tertiary care center by Ravi Kishore Sadula, Aparna Meda, Sudharani Kesavareddy, Umashankar Molanguri

“…Background: The study of neurological soft signs (NSSs) is a simple, clinical, inexpensive, and direct method of investigation for schizophrenia and bipolar disorders which are the major mental health problems that require early detection and treatment. …”
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Fault diagnosis model of rolling bearings based on the M-YOLO network by NING Shaohui, ZHANG Shaopeng, WU Yukun, DU Yue, FAN Xiaoning

“…Finally, the traditional Dropout structure was replaced by Dropblock, and more refined optimization was carried out from the spatial and temporal levels to improve the robustness and diagnostic accuracy of the model.ResultsThe test results show that the diagnosis results of the M-YOLO diagnostic model are significantly higher than those of the traditional fault diagnosis methods, and the frequency-domain conversion feature image has better robustness than the time-domain image, which is more suitable for the training and classification of the object detection model.…”
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Text classification by CEFR levels using machine learning methods and BERT language model by Nadezhda S. Lagutina, Ksenia V. Lagutina, Anastasya M. Brederman, Natalia N. Kasatkina

“…Determining the level of text in natural language is an important component of assessing students knowledge, including checking open tasks in e-learning systems. To solve this problem, vector text models were considered based on stylometric numerical features of the character, word, sentence structure levels. …”
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Forensic Assistance in the Investigation of Crimes against Tigers by Georgii G. Omel'yanyuk, Shamil' N. Khaziev, Viktoriya V. Gulevskaya

“…The article deals with the problem of providing forensic assistance in the investigation of crimes against tigers, and the work of international organizations and foreign forensic science institutions involved in tiger conservation. …”
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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The low or unstable yield caused by unstable flowering is a prominent problem in litchi production, and the flowering time affects not only the maturity of fruit, but also the flowering rate and yield of litchi. …”
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Sociological Aspects of Risk in Marketing Management by Alexander Sergeyevih Korezin, Sergey Borisovih Murashov

“…In an article in the aspect of the sociology of risk, examines the problem of the risks associated with the management of marketing activities. …”
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Progress in Root Cause and Fault Propagation Analysis of Large-Scale Industrial Processes by Fan Yang, Deyun Xiao

“…In large-scale industrial processes, a fault can easily propagate between process units due to the interconnections of material and information flows. Thus the problem of fault detection and isolation for these processes is more concerned about the root cause and fault propagation before applying quantitative methods in local models. …”
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An Intelligent Weed Recognition Method Based on Optical Patrol Image by Guoliang YUE, Yanqiao LU, Hao CHANG, Cuiying SUN

“…In this paper, a method for intelligent recognition of weeds is proposed for power patrol inspection based on optical patrol images. Based on the feature of weeds in the optical images, and combined with the convolutional neural network method, the problem of weed recognition near the power equipment in optical patrol images is solved. …”
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Mining Potential Spammers from Mobile Call Logs by Zhipeng Liu, Dechang Pi, Yunfang Chen

“…These applications combine manual and automatic methods to detect spammers. Although the results of these client-based solutions are quite satisfying, it is extremely unfortunate that many people still use feature phones, which can not be equipped with third party applications. …”
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Towards Explainable Graph Embeddings for Gait Assessment Using Per-Cluster Dimensional Weighting by Chris Lochhead, Robert B. Fisher

“…There is a “black box” problem with existing machine learning models, where healthcare professionals are expected to “trust” the model making diagnoses without understanding its underlying reasoning. …”
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Implementasi Metode Naive Bayes untuk Mendeteksi Stres Siswa Berdasarkan Tweet pada Sistem Monitoring Stres by Diva Fardiana Risa, Fajar Pradana, Fitra Abdurrachman Bachtiar

“…Therefore, this research will build a feature to detect stress levels via tweet on a twitter account using the Naïve Bayes method which will be able to classify students' stress levels based on student tweets into three classes, namely light stress, moderate stress and severe stress classes. …”
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Aircraft Sensor Fault Diagnosis Based on GraphSage and Attention Mechanism by Zhongzhi Li, Jinyi Ma, Rong Fan, Yunmei Zhao, Jianliang Ai, Yiqun Dong

“…Traditional deep learning-based fault diagnosis methods often face challenges, such as limited data representation and insufficient feature extraction. To address these problems, this paper proposes an enhanced GraphSage-based fault diagnosis method that incorporates attention mechanisms. …”
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An Ensemble Classification Method Based on a Stacking Strategy for Ship Type Classification with AIS Data by Lei Deng, Shichen Yang, Limin Jia, Danyang Geng

“…Traditional ship type classification methods with AIS data are often plagued by problems such as data imbalance, insufficient feature extraction, reliance on single-model approaches, or unscientific model combination methods, which reduce the accuracy of classification. …”
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RRBM-YOLO: Research on Efficient and Lightweight Convolutional Neural Networks for Underground Coal Gangue Identification by Yutong Wang, Ziming Kou, Cong Han, Yuchen Qin

“…Coal gangue identification is the primary step in coal flow initial screening, which mainly faces problems such as low identification efficiency, complex algorithms, and high hardware requirements. …”
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LDMP-RENet: Reducing intra-class differences for metal surface defect few-shot semantic segmentation. by Jiyan Zhang, Hanze Ding, Zhangkai Wu, Ming Peng, Yanfang Liu

“…Given their fast generalization capability for unseen classes and segmentation ability at pixel scale, models based on few-shot segmentation perform well in solving data insufficiency problems during metal defect detection and in delineating refined objects under industrial scenarios. …”
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APT attack threat-hunting network model based on hypergraph Transformer by Yuancheng LI, Yukun LIN

“…To solve the problem that advanced persistent threat (APT) in the Internet of things (IoT) environment had the characteristics of strong concealment, long duration, and fast update iterations, it was difficult for traditional passive detection models to quickly search, a hypergraph Transformer threat-hunting network (HTTN) was proposed.The HTTN model had the function of quickly locating and discovering APT attack traces in IoT systems with long time spans and complicated information concealment.The input cyber threat intelligence (CTI) log graph and IoT system kernel audit log graph were encoded into hypergraphs by the model, and the global information and node features of the log graph were calculated through the hypergraph neural network (HGNN) layer, and then they were extracted for hyperedge position features by the Transformer encoder, and finally the similarity score was calculated by the hyperedge, thus the threat-hunting of APT was realized in the network environment of the Internet of things system.It is shown by the experimental results in the simulation environment of the Internet of things that the mean square error is reduced by about 20% compared to mainstream graph matching neural networks, the Spearman level correlation coefficient is improved by about 0.8%, and improved precision@10 is improved by about 1.2% by the proposed HTTN model.…”
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A Transfer Learning Approach for Toe Walking Recognition Using Surface Electromyography on Leg Muscles by Andrea Manni, Gabriele Rescio, Anna Maria Carluccio, Andrea Caroppo, Alessandro Leone

“…This study proposes a new approach to detect toe walking using surface Electromyography (sEMG) on lower limbs. sEMG sensors, by measuring the electrical activity of muscles, can see signals before the movement corresponding to muscle activation, contributing to an early detection of a possible problem. …”
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Analyzing social psychological impact on emotional expression through peer communication using crayfish optimization algorithm with deep learning model by Umkalthoom Alzubaidi

“…Emotional recognition in the text document is primarily a content-based classification problem containing ideas from natural language processing (NLP). …”
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