Levels of Representation of the Computing Process and Workload on LAN by O. M. Demidenko

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Bumelia Webworm Urodus parvula (Edwards 1881) (Insecta: Lepidoptera: Urodidae) by Donald W. Hall

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Présence du végétal dans The Golden Apples de Eudora Welty by Jean-Marc Victor

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Challenges in classifying human chromosomal heteromorphisms using banding cytogenetics: From controversial guidelines to the need for a universal scoring system by Sílvia Pires, Paula Jorge, Thomas Liehr, Natália Oliva-Teles

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Sleep Posture Detection via Embedded Machine Learning on a Reduced Set of Pressure Sensors by Giacomo Peruzzi, Alessandra Galli, Giada Giorgi, Alessandro Pozzebon

“…Our results demonstrate that this approach maintains high classification accuracy (i.e., 0.90 and 0.96 for the configurations with 6 and 15 sensors, respectively) while reducing both hardware and computational requirements.…”
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Vestimentary eponyms in contemporary Spanish language by Y. V. Slivchikova

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Novel Deep Learning Method in Hip Osteoarthritis Investigation Before and After Total Hip Arthroplasty by Roel Pantonial, Milan Simic

“…Our investigation aims to utilize Deep Learning (DL) methodologies and improve classification results for the kinematic parameters of healthy, HOA, and 6 months post-THA gait cycles. …”
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Fault Diagnosis Method for Rolling Bearing Based on Sparse Principal Subspace Discriminant Analysis by Hongdi Zhou, Lin Zhu, Xixing Li

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Pre-trained convolutional neural network with transfer learning by artificial illustrated images classify power Doppler ultrasound images of rheumatoid arthritis joints by Jun Fukae, Yoshiharu Amasaki, Yuichiro Fujieda, Yuki Sone, Ken Katagishi, Tatsunori Horie, Tamotsu Kamishima, Tatsuya Atsumi

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Enhanced thyroid disease prediction using ensemble machine learning: a high-accuracy approach with feature selection and class balancing by Md. Rezaul Islam, Aniruddha Islam Chowdhury, Sharmin Shama, Md. Masudul Hasan Lamyea

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Methodology fundamentals for investigating violations of the laws and customs of war by O. O. Khan, O. V. Manyk

“…Based on modern ideas on the concept of forensic methods of specific crimes investigation, their classification according to the level of generalisation of information contained therein and their structure, the article considers theoretical prerequisites for developing methods of investigation of violations of the laws and customs of war. …”
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Characteristics of Patients With Community‐Acquired Pressure Injuries by Midori Nagano, Yoshiko Kubo, Akiko Egawa, Masayo Kobayashi, Masami Sato

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Analysis of Multidimensional Clinical and Physiological Data with Synolitical Graph Neural Networks by Mikhail Krivonosov, Tatiana Nazarenko, Vadim Ushakov, Daniil Vlasenko, Denis Zakharov, Shangbin Chen, Oleg Blyus, Alexey Zaikin

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Incidence of syphilis in the Cienfuegos province. 2013-2017 by Yoelvis Castro Bruzón, José Andrés Fuentes Soto, Yaneisy Rodríguez Cabrera, Sahily de la Caridad Ortega Medina

“…The prevailing age group was 25 to 59 years, with a total of 477 patients (61.7%), the male sex predominated with 482 patients (62.3%) over the female with 291 patients (37.6%). According to diagnostic classification by type, 395 (51%) corresponded to early latent acquired syphilis and symptomatic acquired 378 (49%). …”
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Landslide Susceptibility Zonation Mapping Using Machine Learning Algorithms and Statistical Prediction at Hunza Watershed Basin, Pakistan by A. Khan, G. Khan, M. Minhas, S. A. Hussain Gardezi, J. Ahmed and N. Abbas

“…The results indicated that the SCAI (D-value) was 7.3 for U-Net, 10 for DeeplabV3+, 7.6 for IF-D, and 9.1 for FR. Overall, the findings revealed that DeeplabV3+ exhibited the highest prediction accuracy and classification ability, making it the most suitable choice for landslide susceptibility mapping in the relevant study area.…”
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Phlegmonous appendicitis as a variant of uncomplicated appendicitis by Tezcan Akın, Hüseyin Fahri Martlı, Eda Şahingöz, Birkan Birben, Sadettin Er, Ayşe Çiftçi, Hayriye Tatlı Doğan, Mesut Tez

“…The distribution of patients was as follows: Group A (normal appendix, 7.6%), Group B (uncomplicated appendicitis, 59.8%), Group C (phlegmonous appendicitis, 17.6%), and Group D (complicated appendicitis, 15%). …”
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Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network by Guimei Yin, Jie Yuan, Yanjun Chen, Guangxing Guo, Dongli Shi, Lin Wang, Zilong Zhao, Yanli Zhao, Manjie Zhang, Yuan Dong, Bin Wang, Shuping Tan

“…The trial results demonstrated that, when using a 6-second segment length and time-domain and frequency-domain features, patients with first-episode schizophrenia achieved the highest classification accuracy of 87.64% This method outperforms other feature selection and brain network modeling approaches, providing new insights and directions for the early diagnosis and recognition of schizophrenia.…”
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Liquefaction potential analysis using the Tsuchida method and correlation of Relative Density (Dr) − D50 at Padang Beach by Andriani, Afifa Mifta, Yoriadi Didi, Shubhi Nurul Hadie Muhammad, Ahmad Fauziah

“…The accelerations used in this test are 0.3g and 0.6g. Soil classification according to the AASHTO (American Association of State Highway and Transportation Officials) system, the type of sand on the beach is A-3 (fine sand), and according to the USCS (Unified Soil Classification System) system, all samples are classified as SP (Poorly-graded sand). …”
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Blind Spot in the Radar of MEST-C Score: Type and Severity of Tubulointerstitial Nephritis in IgA Nephropathy by Iram Asrar, Mudassar Hussain, Aurangzeb Afzal, Usman Hassan, Sheeba Ishtiaq

“…The mean age at the time of biopsy was 31.90 ± 12.48 with 63.6% in the age group between 21 and 40 years, and 69.6% were male. …”
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Prediction of Causative Genes in Inherited Retinal Disorders from Spectral-Domain Optical Coherence Tomography Utilizing Deep Learning Techniques by Yu Fujinami-Yokokawa, Nikolas Pontikos, Lizhu Yang, Kazushige Tsunoda, Kazutoshi Yoshitake, Takeshi Iwata, Hiroaki Miyata, Kaoru Fujinami, on behalf of Japan Eye Genetics Consortium

“…The mean training accuracy was 98.5%, ranging from 90.6 to 100.0. The mean overall test accuracy was 90.9% (82.0–97.6). …”
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