Effect Analysis of Machining Errors of the Axle Wheel Hub Planet Carrier on Function and Durability-Related Parameters by Adam Fiausch

“…This paper introduces a real case study that analyzes the calculated and experimental effects of planet carrier machining quality from a functional property and service life point of view, and compares two parts, which represent the original and the developed status of the pin hole drilling process.…”
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Modeling of Systematic Errors and Precision Optimization Methods for Workpiece Clamping and Alignment System in Aeroengine Gearbox Automated Line Machining by DU Xueming, XIANG Yang, LIU Shun, JIN Sun

“…In the upgrading and automation of aeroengine gearbox assembly line, the introduction of new equipment such as zero-point positioning systems and auxiliary alignment systems has significantly improved production efficiency. …”
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Investigating the Impact of Drill Point Angles on the Drilling Behavior of Date Palm Biocomposites: Experimental, ANN, and Taguchi Modeling by Riyadh Benyettou, Salah Amroune, Mohamed Slamani, Mohammad Jawaid, Alain Dufresne, Hassan Fouad, Tarek Bidi

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CALCULATION OF OPTIMAL TEMPERATURE OF AIR HEATING IN RECUPERATOR AT THE EXAMPLE OF OPERATING THERMAL FURNACE OF THE MODERN MACHINE-BUILDING PLANT FROM TECHNICAL-ECONOMICAL POINT OF... by V. I. Timoshpolskij, D. V. Mendeleev, M. L. German, I. A. Trusova, S. V. Korneev

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Sendotypes predict worsening renal function in chronic kidney disease patients by Thomas McLarnon, Steven Watterson, Sean McCallion, Eamonn Cooper, Andrew R. English, Ying Kuan, David S. Gibson, Elaine K. Murray, Frank McCarroll, Shu‐Dong Zhang, Anthony J. Bjourson, Taranjit Singh Rai

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Developing Machine Learning-based Control Charts for Monitoring Different GLM-type Profiles With Different Link Functions by Patrik Hric, Hamed Sabahno

“…In this paper, we propose an innovative approach that uses different machine-learning (ML) techniques for constructing control charts and monitoring generalized linear model (GLM) profiles with three different GLM-type response distributions of Binomial, Poisson, and Gamma, and by examining different link functions for each response distribution. …”
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Machine Learning for Predicting Postoperative Functional Disability and Mortality Among Older Patients With Cancer: Retrospective Cohort Study by Yuki Hashimoto, Norihiko Inoue, Takuaki Tani, Shinobu Imai

“…ObjectiveWe aimed to develop and validate machine-learning models to predict postoperative functional disability (≥5-point decrease in the Barthel Index) or in-hospital death in patients with cancer aged ≥ 65 years. …”
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Measurement of the Functional Size of Web Analytics Implementation: A COSMIC-Based Case Study Using Machine Learning by Ammar Abdallah, Alain Abran, Munthir Qasaimeh, Malik Qasaimeh, Bashar Abdallah

“…Next, a set of 50 web analytics projects were sized in COSMIC Function Points and used as inputs to various machine learning (ML) effort estimation models. …”
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Predicting rapid decline in kidney function among type 2 diabetes patients: A machine learning approach by Eri Nakahara, Kayo Waki, Hisashi Kurasawa, Imari Mimura, Tomohisa Seki, Akinori Fujino, Nagisa Shiomi, Masaomi Nangaku, Kazuhiko Ohe

“…Background: Diabetic kidney disease (DKD) is one of the typical complications of type 2 diabetes (T2D), with approximately 10 % of DKD patients experiencing a Rapid decline (RD) in kidney function. RD leads to an increased risk of poor outcomes such as the need for dialysis. …”
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Contagious infection-free medical interaction system with machine vision controlled by remote hand gesture during an operation by Van Doi Truong, Hyun-Kyo Lim, Seongje Kim, Than Trong Khanh Dat, Jonghun Yoon

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Mean Field Initialization of the Annealed Importance Sampling Algorithm for an Efficient Evaluation of the Partition Function Using Restricted Boltzmann Machines by Arnau Prat Pou, Enrique Romero, Jordi Martí, Ferran Mazzanti

“…We conclude that these are good starting points to estimate the partition function with AIS with a relatively low computational cost. …”
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A novel measure for characterizing ultrasound device use and wear by Hamid Shokoohi, Andrew Goldsmith, Kay Negishi, Jeffrey R. Herrala, Eden Diamond, Sigmund Kharasch, Michael Blaivas, Andrew S. Liteplo

“…Once fully developed, the ULTrA score could be deployed in EDs and other clinical settings where POCUS is used to help streamline resources to maintain a functional and state‐of‐the‐art fleet of ultrasound machines over time.…”
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Investigating the Effects of Spectroscopic Method in Estimating Soluble Solid Content Values and Firmness of Cherries from an Environmental Point of View: Prediction of Environment... by Shirzad Naim, Shahgholi Gholamhossein, Ardabili Sina, Szymanek Mariusz

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Mean-Variance optimal portfolio selection integrated with support vector and fuzzy support vector machines by Simrandeep Kaur, Arti Singh, Abha Aggarwal

“…To mitigate the influence of noise, a new fuzzy support vector machine (NFSVM) is employed to select assets. Here, each sample point is assigned a membership value using a fuzzy membership function, as documented in existing literature [1]. …”
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Optimal design of hollow conductor for high‐speed synchronous motor exploiting adaptive‐sampling radial basis function algorithm by Ruiye Li, Peng Cheng, Hai Lan

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Optimizing Access Point Placement in Industrial IoT: A Deep Reinforcement Learning Approach With Q-Learning Verification and Signal Heatmap Visualization by Manash Mahanta, Attaphongse Taparugssanagorn, Kenta Umebayashi

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DESIGN AND STUDY OF DRIVE SWIVEL JOINTS FOR HYDRAULIC MANIPULATION SYSTEMS OF MOBILE TRANSPORT-TECHNOLOGICAL MACHINES by Lagerev A.V., Lagerev I.A.

“…Their design allows to combine the function of ensuring the continuity of the kinematic chain and the function of providing rotary movement adjacent units and without the use of additional external devices. …”
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Point-SPV: end-to-end enhancement of object recognition in simulated prosthetic vision using synthetic viewing points by Ashkan Nejad, Ashkan Nejad, Ashkan Nejad, Burcu Küçükoǧlu, Jaap de Ruyter van Steveninck, Sandra Bedrossian, Joost Heutink, Joost Heutink, Gera A. de Haan, Gera A. de Haan, Frans W. Cornelissen, Marcel van Gerven

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A machine learning model for predicting worsening renal function using one‐year time series data in patients with type 2 diabetes by Mari Watanabe, Shu Meguro, Kaiken Kimura, Michiaki Furukoshi, Tsuyoshi Masuda, Makoto Enomoto, Hiroshi Itoh

“…ABSTRACT Background and Aims To prevent end‐stage renal disease caused by diabetic kidney disease, we created a predictive model for high‐risk patients using machine learning. Methods and Results The reference point was the time at which each patient's estimated glomerular filtration rate (eGFR) first fell below 60 mL/min/1.73 m2. …”
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Prediction of the Gross Motor Function Measure-66 in Ambulant Children with Cerebral Palsy Based on Instrumental Gait Analysis Using Machine-Learning Algorithms by Stephanie Gross, Karoline Spiess, Stefanie Steven, Maja Zimmermann, Eckhard Schoenau, Ibrahim Duran

“…The Gross Motor Function Measure-66 (GMFM-66, range of values: 0 to 100 points) is one of the most widely used clinical tests to quantify motor function in children with cerebral palsy (CP). …”
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