Speech emotion recognition using long-term average spectrum by Huerta-Hernández Luis David, Meléndez-Acosta Nayeli Joaquinita, Troncoso-Romero David Ernesto, Ramírez-Pacheco Julio César, León-Borges Jose Antonio

“…The main contribution of this work is to demonstrate that the new framework using LTAS significantly reduces the number of parameters down to 87.5 values per s (approximately), as opposed to the 1,200 values used in the best-performing state-of-the-art alternatives; this means that the process of feature extraction is significantly reduced and the performance in terms of correct classification is improved.…”
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Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption by Fei Guo, Shiyu Miao, Sheng Xu, Mingxuan Luo, Jing Dong, Hongchi Zhang

“…Performance parameters and generative design applications have redefined the human–machine collaborative relationship, challenging traditional architectural design paradigms and guiding the architectural design process toward a performance-based design transformation. …”
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Nanomechanical Systems for Reservoir Computing Applications by Enise Kartal, Yunus Selcuk, Humayun Ahmed, Batuhan E. Kaynak, M. Taha Yildiz, Ramazan Tufan Erdogan, Cenk Yanik, Mehmet Selim Hanay

“…Reservoir computing (RC) provides a route to use physical systems for computation and machine learning. Owing to their inherent nonlinearity, nanomechanical systems constitute an interesting technology to serve as reservoir. …”
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Robotic Motion Intelligence Using Vector Symbolic Architectures and Blockchain-Based Smart Contracts by Daswin De Silva, Sudheera Withanage, Vidura Sumanasena, Lakshitha Gunasekara, Harsha Moraliyage, Nishan Mills, Milos Manic

“…The current AI landscape is dominated by machine learning techniques, specifically deep learning algorithms, that have been effective in addressing some of these challenges. …”
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Carbon dots: Review of recent applications and perspectives in bio-sensing and biomarker detection by Xeniya Terzapulo, Aiym Kassenova, Alissa Loskutova, Rostislav Bukasov

“…There are 4 types of CD-based sensors or detection (CD-only, CD-based Enzymatic, CD-based Antigen-Antibody modified, CD-based Nucleic acid biosensors) that will be described and compared in this review. Such analytical parameters as Limit of Detection (LOD), linear range, Relative Standard Deviation (RSD) are compared and discussed in this review. …”
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A survey on exploring the challenges and applications of wireless body area networks (WBANs) by Arun Sekar Rajasekaran, L. Sowmiya, Azees Maria, R. Kannadasan

“…Due to the arrival of the Micro Electromechanical System (MEMS) and several intelligent sensors, collaboration with WBAN makes accurate predictions of parameters in the human body. WBAN has numerous applications in medical and non-medical fields. …”
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Mechanical Properties of Biodegradable Fibers and Fibrous Mats: A Comprehensive Review by Ehsan Niknejad, Reza Jafari, Naser Valipour Motlagh

“…In addition, mechanical testing techniques such as tensile test machine, atomic force microscopy, and dynamic mechanical analysis are examined to show how fabrication parameters influence fiber performance. …”
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Multi-strategy enhanced marine predator algorithm: performance investigation and application in intrusion detection by Zhongmin Wang, Yujun Zhang, Jun Yu, YuanYuan Gao, Guangwei Zhao, Essam H. Houssein, Rui Zhong

“…Finally, we extend the proposed MEMPA to optimize the hyper-parameters of the Extreme Learning Machine (ELM) for intrusion detection, and the performance of MEMPA-ELM increases the average accuracy by 0.79% than the second-best model. …”
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Design and Optimization of Optical NAND and NOR Gates Using Photonic Crystals and the ML-FOLD Algorithm by Alireza Mohammadi, Fariborz Parandin, Pouya Karami, Saeed Olyaee

“…To optimize the phase parameters efficiently, we employ the ML-FOLD (Meta-Learning and Formula Optimization for Logic Design) optimization formula, which outperforms traditional methods and machine learning approaches in terms of computational efficiency and data requirements. …”
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A Yarn Quality Prediction Method Based on M-ESTIMATOR Robust Broad Learning System With Tightly Cascaded Feature Layers by Baowei Zhang, Zhilin Guo, Yonghua Wang

“…First, the feature mapping groups of the BLS were connected in a tightly cascaded manner to improve the model’s ability to express the features of the parameters of raw cotton and machine operation. Second, five M-ESTIMATOR regression loss functions, such as the Tukey function with robust characteristics, were proposed to replace the L2 norm squared loss function of the BLS. …”
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Design and Experiment of a Single-Disk Silage Corn Harvester by Wenxuan Wang, Wei Sun, Hui Li, Xiaokang Li, Yongwei Yuan

“…At that time, the machine productivity was 38 t·h⁻¹, the average standard grass length rate was 82.15%, and the stubble qualification rate was 91.95%. …”
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Critical Damage Analysis of WC-Co Tip of Conical Pick due to Coal Excavation in Mines by Saurabh Dewangan, Somnath Chattopadhyaya, Sergej Hloch

“…As a result the tools wear out during the process. Other parameters like cutting techniques, tool orientation, and environmental conditions also affect the tool significantly. …”
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Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person by Mustufa Haider Abidi

“…However, more complications are increased in the human–machine-based interaction techniques, creating more scope for personalized assistance for the human motion intention prediction system. …”
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Establishment and Test Effect of Artificial Intelligence Optimization Model Based on Convolutional Neural Network by Chunrong Zhou, Zhenghong Jiang

“…Furthermore, artificial intelligence (AI) and machine learning (ML) are related technologies, which are considered a branch of computer science, which are used to simulate and enhance human intelligence. …”
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First Main Problem of the Theory of Elasticity for a Layer with Two Thick-Walled Pipes and One Cylindrical Cavity by Oleksandr Yu. Denshchykov

“…The obtained numerical results can be used in the prediction of geometric parameters during design.…”

Analysis of Electromagnetic and Thermal Processes of an Induction Motor Using 3D Modeling by A. N. Pekhota, V. N. Galushko, B. M. Khrustalev, D. V. Mirosh

“…Information is presented on the creation of a design model of an auxiliary induction motor with various parameters according to the Goldberg method and the procedure for selecting the option with the best electromechanical characteristics is described. …”
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Bilateral co-transfer for unsupervised domain adaptation by Fuxiang Huang, Jingru Fu, Lei Zhang

“…Labeled data scarcity of an interested domain is often a serious problem in machine learning. Leveraging the labeled data from other semantic-related yet co-variate shifted source domain to facilitate the interested domain is a consensus. …”
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Enhanced SVM-based model for predicting cyberspace vulnerabilities: Analyzing the role of user group dynamics and capital influx. by Yicheng Long

“…To address the limited adaptability of traditional support vector machine (SVM) models in identifying nonlinear attacks, this study introduces a distribution-driven, dynamically adaptive kernel optimization approach. …”
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Dynamic Rock-Breaking Process of TBM Disc Cutters and Response Mechanism of Rock Mass Based on Discrete Element by Qinglong Zhang, Yanwen Zhu, Canxun Du, Sanlin Du, Kun Shao, Zhihao Jin

“…Rock-breaking efficiency of full-face rock tunnel boring machine (TBM) is closely related to the performance of the disc cutter and the characteristics of the rock mass. …”
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Learning Transferable Convolutional Proxy by SMI-Based Matching Technique by Wei Jin, Nan Jia

“…Domain-transfer learning is a machine learning task to explore a source domain data set to help the learning problem in a target domain. …”
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