Interdisciplinary approaches among the subjects Surveillance and Vector Control and History of America by Bárbara Cecilia Eguiguren Ferrer, Reina Ysabel Hernández Cedeño, Valia Caminero Chávez, Miriam Olano Rivalta, Enma de la Caridad Díaz Hernández

“…In this way, the interdisciplinary training of these future professionals, who will work on surveillance and vector control, is strengthened.…”
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An Adaptive Support Vector Regression Machine for the State Prognosis of Mechanical Systems by Qing Zhang, Fei Liu, Xiang Wan, Guanghua Xu

“…To model hidden trends and predict deterioration failure utilizing volatile state indicators, an adaptive support vector regression (ASVR) machine is proposed. In ASVR, the width of an error-insensitive tube, which is a constant in the traditional support vector regression, is set as a variable determined by the transient distribution boundary of local regions in the training time series. …”
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An Alternative Gene Editing Strategy Using a Single AAV Vector by Jamie Moffa, Vani Kalyanaraman, Bryan Copits

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On the generalisation capabilities of Fisher vector‐based face presentation attack detection by Lázaro J. González‐Soler, Marta Gomez‐Barrero, Christoph Busch

“…A feature space based on Fisher Vectors computed from compact binarised statistical image features histograms, which allows discovering semantic feature subsets from known samples to enhance the detection of unknown attacks is presented. …”
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Massive discovery of crystal structures across dimensionalities by leveraging vector quantization by ZiJie Qiu, Luozhijie Jin, Zijian Du, Hongyu Chen, Guanyao Mao, Yan Cen, Siqi Sun, Yongfeng Mei, Hao Zhang

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Static Pakistani Sign Language Classification using Support Vector Machine by Shaheer Mirza, Sheikh Muhammad Munaf, Shahid Ali, Muhammad Asif

“… In this study, a system is proposed that uses the Support Vector Machine (SVM) technique with Bag-of-Words (BoW) and recognizes static Pakistani Sign Language (PSL) alphabets. …”
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Advanced Defect Detection in Wrap Film Products: A Hybrid Approach with Convolutional Neural Networks and One-Class Support Vector Machines with Variational Autoencoder-Derived Cov... by Tatsuki Shimizu, Fusaomi Nagata, Maki K. Habib, Koki Arima, Akimasa Otsuka, Keigo Watanabe

“…These covariance vectors serve as feature vectors for training a specialized One-Class SVM (OCSVM), a key component of our approach. …”
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A Fault Diagnosis Method of Contactor Based on Support Vector Classifier by YANG Jiawei, ZENG Weizhang, ZHU Wenlong, XU Hailong, ZHANG Zhongjing

“…Based on this relationship, a fault diagnosis method of contactor based on support vector machine is proposed. Through this method, diagnosis and classification of four types of contactor common faults are realized, and the diagnostic accuracy is over 93%. …”
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Study on the Magnitude of Reservoir-Triggered Earthquake Based on Support Vector Machines by Hai Wei, Mingming Wang, Bingyue Song, Xin Wang, Danlei Chen

“…An effective approach is introduced to predict the magnitude of reservoir-triggered earthquake (RTE), based on support vector machines (SVM) and fuzzy support vector machines (FSVM) methods. …”
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JDroid: Android malware detection using hybrid opcode feature vector by Recep Sinan Arslan

“…For this purpose, opcodes are extracted from APK files by code analysis and directly converted into vectors as 0 and 1 according to their usage cases. …”
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Sistem Identifikasi Pembicara Berbahasa Indonesia Menggunakan X-Vector Embedding by Alim Misbullah, Muhammad Saifullah Sani, Husaini, Laina Farsiah, Zahnur, Kikye Martiwi Sukiakhy

“…Durasi ekstraksi x-vectors menggunakan model terbaik untuk dataset data train berdurasi 6 jam 42 menit 39 detik, VoxCeleb1 bagian test berdurasi 2 menit 24 detik, inf19_enroll berdurasi 18 detik, inf19_test_td berdurasi 25 detik, dan inf19_test_tid berdurasi 9 detik. …”
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Training, Competition & Health by Sauter L, Schellhorn P, Niess AM, Burgstahler C

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Effects of strength training and detraining considering maturity status in youth highly trained basketball players. by Oliver Gonzalo-Skok, Jorge Arede, Thomas Dos'Santos

“…Left horizontal jumping at post-test and detraining was significantly (p  <  0.05; ES  =  1.56 - 1.73) greater in post-PHV and mid-PHV than pre-PHV. The combined training had favorable outcomes for most unilateral jumps, particularly those with a horizontally oriented force vector, independent of maturity status. …”
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Attitude Determination Algorithms through Accelerometers, GNSS Sensors, and Gravity Vector Estimator by Raúl de Celis, Luis Cadarso

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Fault Diagnosis Research on Bearingof Motor Based on LMD And Support Vector Machine by YIN Zhao-jie, XU Tong-le, ZHENG Dian-kun

“…Finally，the energy feature vector is used as the training sample and test sample of SVM，and the fault information of motor bearing is trained and predicted. …”
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Talent identification in soccer using a one-class support vector machine by Jauhiainen S., Äyrämö S., Forsman H., Kauppi J-P.

“…Therefore, we approach talent identification as an anomaly detection problem. We trained a nonlinear one-class support vector machine (one-class SVM) on a dataset (N=951) collected from 14-year-old junior soccer players to detect potential future elite players. …”
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Performance Evaluation of Support Vector Machine and Stacked Autoencoder for Hyperspectral Image Analysis by Brahim Jabir, Bendaoud Nadif, Isabel De la Torre Diez, Helena Garay, Irene Delgado Noya

“…Our research dives into the performance comparison of two popular machine learning approaches: the support vector machine (SVM) and the more recent deep learning-based stacked autoencoder (SAE). …”
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Financial Risk Early-Warning of Neusoft Group Based on Support Vector Machine by Yuxuan Dai, Chenhui Yu

“…Nowadays, the advantages of support vector machine (SVM) have gradually appeared. The research on financial risk early-warning using SVM mostly stays in dichotomy. …”
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A novel ensemble support vector machine model for land cover classification by Ying Liu, Lihua Huang

“…Nowadays, support vector machines are widely applied to land cover classification although this method is sensitive to parameter selection and noise samples. …”
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Application of support vector machine system introducing multiple submodels in data mining by Weinan Tang

“…For large-scale data mining problems, a clustering-based kernel matrix inner product filtering method is introduced to decompose the original quadratic programming problem into multiple sub-problems to support parallel training. And a Spark-based multiple submodels parallel support vector machine is proposed. …”
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