Approximation-Aware Training for Efficient Neural Network Inference on MRAM Based CiM Architecture by Hemkant Nehete, Sandeep Soni, Tharun Kumar Reddy Bollu, Balasubramanian Raman, Brajesh Kumar Kaushik

“…The network is trained using backpropagation to minimize the loss function with respect to AFC matrix with linear and quadratic approximation functions preserving accuracy at high compression rates. …”
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Energy Efficiency and Mathematical Modeling of Shrimp Pond Oxygenation: A Multiple Regression Experimental Study by Yoisdel Castillo Alvarez, Yorlan González González, Reinier Jiménez Borges, Luis Angel Iturralde Carrera, José M. Álvarez-Alvarado, Juvenal Rodríguez-Reséndiz

“…This research proposes a multiple linear regression mathematical model to optimize oxygenation systems in intensive shrimp aquaculture by reducing energy consumption and minimizing water changes in ponds. …”
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Efficient Nyström-Based Unitary Single-Tone 2D DOA Estimation for URA Signals by Liping Yuan, Ke Wang, Fengkai Luan

“…We propose an efficient Nyström-based unitary subspace method for low-complexity two-dimensional (2D) direction-of-arrival (DOA) estimation in uniform rectangular array (URA) signal processing systems. …”
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How likely are you to observe non-locality with imperfect detection efficiency and random measurement settings? by Paweł Cieśliński, Tamás Vértesi, Mateusz Kowalczyk, Wiesław Laskowski

“…We derive analytical lower bounds on the violation probability for a two-qubit maximally entangled state, which is tight for correlation inequalities and perfect detection efficiencies. We further investigate it numerically for more qubits and settings using two detection efficiency models and an original method based on the linear programming. …”
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Fast TILs—A pipeline for efficient TILs estimation in non-small cell lung cancer by Nikita Shvetsov, Anders Sildnes, Masoud Tafavvoghi, Lill-Tove Rasmussen Busund, Stig Manfred Dalen, Kajsa Møllersen, Lars Ailo Bongo, Thomas Karsten Kilvær

“…Further, only 5% of eligible patches are necessary to retain the pipeline's prognostic accuracy (c-index = 0.65), resulting in a linear reduction of the total computational time compared to the filtered patch subset analysis. …”
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Developing the optimal model for correct use of environmental resources in chelgerd watershed by Moslem Heydari, Afshin Honarbakhsh, Mahdi Pajoohesh, Maryam Zangiabadi

“…For this purpose, a single objective linear programming model with environmental approach was used to land use optimization and a multi objective optimization model for optimal allocation of resources. …”
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EST-STFM: An Efficient Deep-Learning-Based Spatiotemporal Fusion Method for Remote Sensing Images by Qiyuan Zhang, Xiaodan Zhang, Chen Quan, Tong Zhao, Wei Huo, Yuanchen Huang

“…To overcome these limitations, we propose an efficient hierarchical Transformer-based spatiotemporal fusion method, named the efficient sparse Transformer spatiotemporal fusion model (EST-STFM). …”
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Methods for Extracting Fractional Vegetation Cover from Differentiated Scenarios Based on Unmanned Aerial Vehicle Imagery by Changning Sun, Yonggang Ma, Heng Pan, Qingxue Wang, Jiali Guo, Na Li, Hong Ran

“…This study facilitates accurate, efficient extraction of vegetation information in differentiated scenarios within arid and semiarid regions, providing key technical references for FVC estimation in similar arid areas.…”
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Enhanced coordination interaction with multi-site binding ligands for efficient and stable perovskite solar cells by Riming Nie, Peikun Zhang, Jiaxing Gao, Cheng Wang, Weicun Chu, Luyao Li, Kaiyu Wang, Dongmin Qian, Fanrong Lin, Xuefeng Xia, Yong Wu, Lingfeng Chao, Chunyang Miao, Xiaoming Zhao, Wanlin Guo, Zhuhua Zhang

“…Remarkably, unencapsulated cells exhibited linear extrapolated T 80 lifetimes of 23,325 h during dark shelf storage. …”
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Impact of dietary forage proportion and crossbreeding on feed efficiency and methane emissions in lactating dairy cows by Sabrina Ormston, Tianhai Yan, Xianjiang Chen, Alan W. Gordon, Katerina Theodoridou, Sharon Huws, Sokratis Stergiadis

“…Diets consisted of varying proportions of forage and concentrate dependent on the experimental protocols of each experiment. A linear mixed model was used to investigate the effect of low (LFP; 10% to 30%), medium (MFP; 30% to 59%), high (HFP; 60% to 87%) and pure (FOR; 100%) FP (dry matter [DM] basis) and breed on feed efficiency, and CH4 emission parameters and multivariate redundancy analysis identified associations between animal and dietary drivers on the same variables. …”
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Resource-Efficient Context-Aware Dynamical Decoupling Embedding for Arbitrary Large-Scale Quantum Algorithms by Paul Coote, Roman Dimov, Smarak Maity, Gavin S. Hartnett, Michael J. Biercuk, Yuval Baum

“…The method relies on a graph representation of the embedding problem, where the optimal decoupling sequence can be efficiently calculated using an algebraic computation that scales linearly with the number of idles. …”
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Extraction Efficiency of Different Solvents and LC-UV Determination of Biogenic Amines in Tea Leaves and Infusions by U. Gianfranco Spizzirri, Nevio Picci, Donatella Restuccia

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A new iterative multi-step method for solving nonlinear equation by Muhammad Usman, Javed Iqbal, Alamgir Khan, Ikram Ullah, Hasib Khan, Jehad Alzabut, Hisham Mohammad Alkhawar

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An application of modified systematic sampling in auto-correlated populations

“…This study explores the efficiency of modified systematic sampling (MSS) in the context of auto-correlated populations. …”
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Driving behavior recognition and prediction based on Bayesian model by Xinsheng WANG, Zhen BIAN

“…Since the existing intelligent driving systems are lack of efficiency and accuracy when processing huge number of driving data,a brand new approach of processing driving data was developed to identify and predicate human driving behavior based on Bayesian model.The approach was proposed to take two steps to deduce the specific driving behavior from driving data correspondingly without any supervision,the first step being using Bayesian model segmentation algorithm to divide driving data that inertial sensor collected into near-linear segments with the help of Bayesian model segmentation algorithm,and the second step being using extended LDA model to aggregate those linear segments into specific driving behavior (such as braking,turning,acceleration and coasting).Both offline and online experiments are conducted to verify this approach and it turns out that approach has higher efficiency and recognition accuracy when dealing with numerous driving data.…”
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Transformerless Step-Up Inverter Based On Switched-Capacitor Converter Technology by Neilor Colombo Dal Pont, Gierri Waltrich, Telles Brunelli Lazzarin

“…The novel structure (VSI-SCC) is designed as a transformerless step-up inverter with linear gain. VSI and SCC models are individually characterized to integrate both structures in only one model. …”
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Artificial neural networks for predicting first-lactation 305-day milk yield in crossbred cattle by SM Usman, A Kumar, A Sherasiya, IM Youssef, MM Abo Ghanima, J Chandrakar, R Tiwari, NP Singh, QS Sahib, T Dutt, AA Swelum

“… This study was conducted using the first-lactation records of 1092 Vrindavani crossbred cattle to compare the relative efficiency of an artificial neural network (ANN) versus multiple linear regression for predicting the first-lactation 305-day milk yield (FL305DMY). …”
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Algorithm of Assessing Dynamic Correlation between Time Series Connected by TVP-Regression Model by N. A. Moiseev, G. V. Aivazian

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Enhancing Agricultural Productivity through Machine Learning: A Model for Accurate Crop Yield Prediction by adlin jebaumari, jayanthila devi

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Value chain optimization in large scale gas network considering elevation and transmission direction by Xifeng Ning, Jinfeng Qiu, Dejun Yu

“…We propose an algorithm based on sequential linear programming, which we test on the company’s network. …”
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