A Fault Diagnosis Model Based on LCD-SVD-ANN-MIV and VPMCD for Rotating Machinery by Songrong Luo, Junsheng Cheng, Kexiang Wei

“…The fault diagnosis process is essentially a class discrimination problem. …”
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A Novel Approach for Tomato Leaf Disease Classification with Deep Convolutional Neural Networks by Gizem Irmak, Ahmet Saygılı

“…Specifically, classical learning methods employed the local binary pattern (LBP) technique for feature extraction, while classification tasks were carried out using extreme learning machines, k-nearest neighborhood (kNN), and support vector machines (SVM). In contrast, a novel convolutional neural network (CNN) framework, complete with unique parameters and layers, was utilized for deep learning. …”
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Word Embedding for Semantically Relative Words: an Experimental Study by Maria S. Karyaeva, Pavel I. Braslavski, Valery A. Sokolov

“…Each word can be represented as a vector, so the closest coordinates of vectors can be interpreted as similar words. …”
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Application of Fuzzy-RBF-CNN Ensemble Model for Short-Term Load Forecasting by Mohini Yadav, Majid Jamil, Mohammad Rizwan, Richa Kapoor

“…Its results are validated while comparing with four benchmark models like multiple linear regression (MLR), support vector machine (SVM), ML-SVM, and fuzzy-RBFNN in terms of accuracy. …”
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Accuracy Prediction of Compressive Strength of Concrete Incorporating Recycled Aggregate Using Ensemble Learning Algorithms: Multinational Dataset by Menghay Phoeuk, Minho Kwon

“…The CatBoost model performed the best, exhibiting an R2 of 0.938 and low mean absolute error and root mean squared error values of 2.639 and 3.885, respectively, in the blind evaluation process. Although the random forest regression algorithm performed the least well among the four models, it still outperformed conventional machine learning algorithms such as support vector machines and artificial neural networks. …”
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A Comprehensive Survey on AI in Counter-Terrorism and Cybersecurity: Challenges and Ethical Dimensions by Ioannis Syllaidopoulos, Klimis S. Ntalianis, Ioannis Salmon

“…This paper provides a comprehensive overview of AI methodologies, such as predictive analytics, Natural Language Processing (NLP), and machine learning architectures (e.g., Support Vector Machines – SVM and Long Short-Term Memory – LSTM), and optimization algorithms (e.g., Particle Swarm Optimization – PSO), assessing their effectiveness in security applications. …”
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Pedagogical assistance as a mechanism of socio-pedagogical adaptation of cadets of military universities by S. Yartsev

“…We also analyze the components of pedagogical assistance: personal, cognitive, process, vector, adaptive. Conclusion. According to the results of the study, it can be concluded that the combination of all components gives a kind of integral education, which includes the desire for success at various personal levels, awareness in the development of new knowledge, the search for personal meanings, the productive implementation of personal choice, the preparation of a specific plan and its implementation of joint activities with subsequent reflection, an adaptive response the student. …”
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On the ground among the beasts, under the whisper of the stars: contributions to a zoopoetic reading of franz kafka’s work by Ricardo Gil Soeiro

“…Anchoring myself in conceptual approaches with a post-anthropocentric approach (Deleuze/Guattari, 2003; Derrida, 2006; Geier, 2016; Harel, 2020), I will examine a set of Zoopoetics mechanisms that Kafka sets in motion in Die Verwandlung, alluding to other of his stories about animals (the so-called Tiergeschichten), seeking to understand how a posthumanist prism proves capable of illuminating some of the meanings that Kafka's texts reveal, promoting, in a broadly nuanced way, a process of decentering of the human – a strategic vector for the posthumanist forma mentis.…”
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A Hybrid Forecasting System Based on Comprehensive Feature Selection and Intelligent Optimization for Stock Price Index Forecasting by Xuecheng He, Jujie Wang

“…At last, an enhanced least squares support vector machine (LSSVM) algorithm is established to obtain high-precision point prediction results, and the Gaussian process regression (GPR) algorithm is used to obtain reasonable interval prediction results. …”
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Regulatory aspects of optogenetic research and therapy for retinitis pigmentosa under EU law by Johannes Freise

“…In view of the ongoing translational process, this paper examines regulatory aspects of preclinical and clinical research as well as a therapeutic application of optogenetics in ophthalmology. …”
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Dual Polarization Optical Slicing for C-RAN in 5G Networks based on Radio-over-Fiber by Gustavo Puerto-Leguizamón, Carlos Arturo Suárez-Fajardo

“…Experimental results focus on the Error Vector Magnitude (EVM) measurements for 0.1 nm, 0.5 nm, and 1 nm dual polarized optical slices. …”
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Optimization of Acceleration and Driving Force for Double-Toggle Stephenson-Chain Mold Clamping Mechanisms by Tzu-Hsia Chen, Po-Cheng Lai

“…In this paper, Stephenson-chain mechanisms were selected and subjected to a comprehensive analysis of their kinematic characteristics using vector loop and finite difference methods. The optimal design process included defining the objective function and evaluating the maximum acceleration and force ratio. …”
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Automated Classification Model for Elementary Mathematics Diagnostic Assessment Data Based on TF-IDF and XGBoost by Seonghyun Park, Seungmin Oh, Woncheol Park

“…To validate the model’s performance, comparative experiments were conducted with Logistic Regression, Support Vector Machine (SVM), LightGBM, BERT, and DistilBERT. …”
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Real-Time Traffic Data Analysis and Deep Learning-based Traffic Volume Classification for Congestion Mitigation at Urban Intersections by Omar Abdullah Hasan, Duraid Y. Mohammed

“…The collected data underwent analysis through signal processing techniques, followed by detection using machine learning models: Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), Long Short-Term Memory (LSTM). …”
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Self-Supervised Sensor Learning and Its Application: Building 3D Semantic Maps Using Terrain Classification by Chuho Yi, Donghui Song, Jungwon Cho

“…It learns about the surrounding environment using a support vector machine with the stored data, which is divided into terrains where people or vehicles have moved and other regions. …”
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Forecast Model of TV Show Rating Based on Convolutional Neural Network by Lingfeng Wang

“…At present, convolutional neural networks have become a research hotspot in speech recognition, image recognition and classification, natural language processing, and other fields and have been widely and successfully applied in these fields. …”
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Current harmonic minimum PWM strategy for traction inverter based on three-level topology by JIANG Wei, LI Zhaoyang, YIN Zhenhuan, QIU Tengfei, WANG Chenchen

“…Further exploration in this study delved into the pulse generation method of CHMPWM and the modulation mode switching method based on the flux linkage deviation vector of stators. In addition, experimental research was carried out on a small-power experimental platform, to verify the three-level inverter CHMPWM and modulation mode switching strategy. …”
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BanglaNewsClassifier: A machine learning approach for news classification in Bangla Newspapers using hybrid stacking classifiers. by Tanzir Hossain, Ar-Rafi Islam, Md Humaion Kabir Mehedi, Annajiat Alim Rasel, M Abdullah-Al-Wadud, Jia Uddin

“…This study utilized a dataset of 118,404 Bangla news articles, applying rigorous feature extraction techniques including TF-IDF vectorization and word2Vec embeddings. Our best-performing model, a stacking meta-classifier combining bidirectional long short-term memory and support vector machine, achieved a remarkable 94% accuracy, leaving all basic models' performance behind. …”
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Heterologous expression of the Stellaria media plant defensin SmD1 in Escherichia coli by Yiyi Qiu, Qiaozhi Song

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Machine learning via DARTS-Optimized MobileViT models for pancreatic Cancer diagnosis with graph-based deep learning by Yusuf Alaca

“…To further enhance classification accuracy, advanced machine learning algorithms, including K-Nearest Neighbours (KNN), Support Vector Machines (SVM), Random Forest (RF), and XGBoost, were applied. …”
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