Deep Residual Transfer Ensemble Model for mRNA Gene-Expression-Based Breast Cancer by Job Prasanth Kumar Chinta Kunta, Vijayalakshmi A. Lepakshi

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Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

“…In order to describe the characteristic information of the speech signal more comprehensively and improve the detection rate of camouflage, a spoofing speech detection method based on the combination of uniform local binary pattern texture feature and constant Q cepstrum coefficient acoustic feature was proposed, which used random forest as the classifier model.The texture feature vector in the speech signal spectrogram was extracted by using the uniform local binary mode, and the joint feature was formed with the constant Q cepstrum coefficient.Then, the obtained joint feature vector was used to train the random forest classifier, so as to realize the camouflage speech detection.In the experiment, the performances of several spoofing detection systems constructed by other feature parameters and the support vector machine classifier model were compared, and the results show that the proposed speech spoofing detection system combined with the joint feature and the random forest model has the best performance.…”
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Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

“…In order to describe the characteristic information of the speech signal more comprehensively and improve the detection rate of camouflage, a spoofing speech detection method based on the combination of uniform local binary pattern texture feature and constant Q cepstrum coefficient acoustic feature was proposed, which used random forest as the classifier model.The texture feature vector in the speech signal spectrogram was extracted by using the uniform local binary mode, and the joint feature was formed with the constant Q cepstrum coefficient.Then, the obtained joint feature vector was used to train the random forest classifier, so as to realize the camouflage speech detection.In the experiment, the performances of several spoofing detection systems constructed by other feature parameters and the support vector machine classifier model were compared, and the results show that the proposed speech spoofing detection system combined with the joint feature and the random forest model has the best performance.…”
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Assessing training needs and influencing factors among personnel at centers for disease control and prevention in northeast China: a cross-sectional study framed by SDT and TPB usi... by Kexin Wang, Peng Wang, Min Wei, Yanping Wang, Huan Liu, Ruiqian Zhuge, Qunkai Wang, Nan Meng, Yiran Gao, Yuxuan Wang, Lijun Gao, Jingjing Liu, Xin Zhang, Mingli Jiao, Qunhong Wu

“…SHapley Additive exPlanations (SHAP) were used to explain the output of the optimal machine learning model. Results This study identified the four subgroups of competency patterns, including novice (25.3%), public health experts (15.1%), potential expansion talents (24.7%), and versatile talents (34.9%). …”
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Tool Wear Monitoring Technology and Its Application in Heavy Cutting by CHENG Yao-nan, DING Ya, GAI Xiao-yu, GUAN Rui, MA Chun-jie

“…In the modern cutting system, the wear or damage of cutting tools will lead to the failure of the workpiece and even the damage of machine tools.Tool condition monitoring can effectively improve the adverse effects of wear and breakage on the cutting process, so it is of great significance to apply tool condition monitoring to the process of heavy cutting water chamber head to improve the cutting efficiency and machining quality of workpieces. …”
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PCA-GWO-KELM Optimization Gait Recognition Indoor Fusion Localization Method by Xiaoyu Ji, Xiaoyue Xu, Suqing Yan, Jianming Xiao, Qiang Fu, Kamarul Hawari Bin Ghazali

“…In this method, 30-dimensional motion features for different motion patterns are extracted from inertial measurement units. …”
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Direct scribing of metal microgratings using sawtoothed cemented carbide tools with Johnson-Cook model-based plastic deformation simulation by Minwook Kim, Dae Bo Sim, Yong Tae Kim, Bo Hyun Kim, Jong G. Ok

“…We demonstrate the DISCRIM (DIrect SCRIbing of Metals) process for the continuous and scalable precision machining of metal micrograting structures, which utilizes direct mechanical scribing of a sawtooth–patterned cemented carbide tool edge over a metal workpiece. …”
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Dementia Scale Score Classification Based on Daily Activities Using Multiple Sensors by Akira Minamisawa, Shogo Okada, Ken Inoue, Mami Noguchi

“…The experimental results show that a maximum accuracy of 0.871 was obtained with a linear support vector machine (SVM) model by fusing the door, location, and sleep features and by clustering activity patterns using the X-means algorithm.…”
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A Data-Driven Approach to Mitigate Evolving Volumetric Attacks in Programmable Networks by Muhammad Saqib, Halima Elbiaze, Roch H. Glitho

“…In-network machine learning (ML) offers a cutting-edge approach for promptly detecting malicious traffic. …”
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A structured-illumination reflectance imaging dataset for woody breast assessment of broiler meatZenodo by Yuzhen Lu, Hamed Sardari

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Time Series Modelling and Predictive Analytics for Sustainable Environmental Management—A Case Study in El Mar Menor (Spain) by Rosa Martínez, Ivan Felis, Mercedes Navarro, J. Carlos Sanz-González

“…In this study on data science and machine learning, time series analysis plays a key role in predicting evolving data patterns. …”
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BCAST IDS: A Novel Network Intrusion Detection System for Broadcast Networks by Javier Gombao

“…A modern approach to enhancing the capabilities of NIDSs is the use of machine learning (ML) algorithms that predict attacks based on data. …”
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Development of an artificial intelligence system for the forecasting of infectious diseases by A. A. Kuzin, R. I. Glushakov, S. A. Parfenov, K. V. Sapozhnikov, A. A. Lazarev

“…Evolution of data science have led to the emergence of promising artificial intelligence (AI) algorithms and tools for the forecasting of infectious diseases. Employing machine learning algorithms, AI systems can rapidly analyze a large amount of data, extract specific disease patterns, and screen for the most efficient AI instruments in relation to specific tasks, thus contributing to prevention, diagnostics, and treatment of infectious diseases in the context of personalized medicine. …”
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Predicting individual traits from models of brain dynamics accurately and reliably using the Fisher kernel by Christine Ahrends, Mark W Woolrich, Diego Vidaurre

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Towards precision agriculture tea leaf disease detection using CNNs and image processing by Irfan Sadiq Rahat, Hritwik Ghosh, Suresh Dara, Shashi Kant

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Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization by Hua Huang, Haiyan Shao, Yifan Wang, Lili Ge

“…By integrating data from TCGA and GEO cohorts, we developed a Disulfide-Related Prognostic Signature (DRPS) using ten machine learning algorithms. Single-cell RNA sequencing (scRNA-seq) elucidated the cell subtype-specific expression patterns of disulfide bond regulatory genes, while immune microenvironment and drug sensitivity analyses validated its clinical translational potential. qRT-PCR experiments confirmed differential expression patterns of core genes in bladder cancer cell lines. …”
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Unsupervised learning analysis on the proteomes of Zika virus by Edgar E. Lara-Ramírez, Gildardo Rivera, Amanda Alejandra Oliva-Hernández, Virgilio Bocanegra-Garcia, Jesús Adrián López, Xianwu Guo

“…Unsupervised learning (UL), a form of machine learning algorithm, can be applied on the datasets without the need of known information for training. …”
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A two-stage model for enhanced mango leaf disease detection using an innovative handcrafted spatial feature extraction method and knowledge distillation process by Mohammad Manzurul Islam, Mst. Nasrat Jahan Niva, Abdullahi Chowdhury, Saleh Masum, Rifat Ara Shams, Taskeed Jabid, Md. Sawkat Ali, Md. Mostofa Kamal Rasel, Muhammad Firoz Mridha

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INTEGRATING ARTIFICIAL NEURAL NETWORKS FOR DEVELOPING TELEMEDICINE SOLUTION by Mihaela GHEORGHE

“…These can be used for assisting physicians or other clinical staff in the process of taking decisions under uncertainty. Thus, machine learning methods which are specific to this technology are offering an approach for prediction based on pattern classification. …”
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Extinction Risk Assessment and Conservation of the Pachypodium Under Climate Change by Yu Chen, Qisong Wan, Shenglan Du, Hillary Otieno Otieno, Haingotiana Johary Andrianjatovo, Maxwell Njoroge Njenga, Yuvenalis Morara Mbuni, Neng Wei, Jitao Li, Shengwei Wang

“…Additionally, machine learning methods have been applied to assess the extinction risk of these species. …”
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