Efficient spectral data reduction for accurate iodine quantification in multi-energy CT by Olivia F. Sandvold, Roland Proksa, Heiner Daerr, Amy E. Perkins, Kevin M. Brown, Thomas Koehler, Ravindra M. Manjeshwar, Peter B. Noël

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Optimizing Deep Learning Models for Resource‐Constrained Environments With Cluster‐Quantized Knowledge Distillation by Niaz Ashraf Khan, A. M. Saadman Rafat

“…To address these issues, we propose Cluster‐Quantized Knowledge Distillation (CQKD), a novel framework that integrates structured pruning with knowledge distillation, incorporating cluster‐based weight quantization directly into the training loop. …”
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Study of algorithmic approaches to digital signal filtering and the influence of input quantization on output accuracy by Shermuradova Malika, Gadoeva Mavlyuda, Rahmatov Shukhrat, Abdullaev Uktamjon, Aralov Dilshod

“…The research supports the broader integration of AI-driven technologies in modern automation systems, paving the way for more adaptive, efficient, and fault-tolerant control mechanisms in complex environments.…”
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Fully Quantized Matrix Arithmetic-Only BERT Model and Its FPGA-Based Accelerator by Hiroshi Fuketa, Toshihiro Katashita, Yohei Hori, Masakazu Hioki

“…In this paper, we propose a fully quantized matrix arithmetic-only BERT (FQ MA-BERT) model to enable efficient natural language processing. …”
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Development of the ELISA Test System for Quantitative Determination of IgG to the Varizella zoster virus in Human Serum and Assessment of its Diagnostic Efficiency by L. N. Lukhverchyk, G. L. Alatortseva, L. N. Nesterenko, V. Y. Kabargina, V. V. Dotsenko, I. I. Amiantova, O. B. Vylivannaya, A. V. Sidorov, A. V. Milovanova, O. S. Oksanich, S. Y. Konanykhina, V. V. Zverev

“…This problem can be solved using quantitative immunoassay methods. Aim. Development of an enzyme-linked immunosorbent assay for the concentration of class G immunoglobulins (AB) to Varicella zoster virus (VZV) determining and assessing its functional characteristics and diagnostic efficiency. …”
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Comparison of DNA and RNA extraction efficiency from blood by SU Xinglei, LU Ping, PENG Junjie, WANG Zimin, SONG Ping, HAN Da

“…Furthermore, this protocol was applied to extracting cfDNA from plasma samples of 100 colorectal cancer patients. Quantitative real-time PCR (qPCR) was used to quantify the extracted DNA and RNA, and the molecular yields were compared to evaluate the extraction efficiency. …”
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Research of channel quantization and feedback strategies based on multiuser diversity MIMO-OFDM systems by LIANG Xue-jun, ZHU Guang-xi, SU Gang, WANG De-sheng

“…Firstly, a quantization method was proposed by quantized value indicating the modulation level instead of the full values of channel quality information（CQI） and the achievable average spectrum efficiency showed no loss compared with perfect case.Secondly, employment of the integrated design that combined with opportunistic, best, and hybrid feedback scheme was considered and the close-form expression of average spectrum efficiency was deduced in various case.Finally, the calculation of optimal feedback parameters was confirmed from two aspects of feedback channel capacity and capacity relative loss.Extensive simulations were presented to evaluate these proposed strategies.The results match with the numeral analysis very well.The proposed partial feedback schemes can reduce the feedback load greatly with the same system capability, only if the feedback parameters be chosen properly.Wherein, the hybrid feedback combined with quantization performs best and provides the instruction to design the channel feedback of practical systems.…”
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Smoothed per-tensor weight quantization: a robust solution for neural network deployment by Xin Chang

“…This paper introduces a novel method to improve quantization outcomes for per-tensor weight quantization, focusing on enhancing computational efficiency and compatibility with resource-constrained hardware. …”
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Reducing Memory and Computational Cost for Deep Neural Network Training with Quantized Parameter Updates by Leo Buron, Andreas Erbslöh, Gregor Schiele

“…For embedded devices, both memory and computational efficiency are essential due to their constrained resources. …”
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Precise Control of Lead Halide and Ammonium Salt Stoichiometric Ratios for Efficient Perovskite Solar Cells by Hengyi Jiang, Rui Yang, Ziqi Zhu, Chao Sun, Yongbin Jin, Lingfang Zheng, Lina Shen, Chengbo Tian, Liqiang Xie, Jinxin Yang, Zhanhua Wei

“…Conventional deposition techniques fail to establish a definitive structure‐performance relationship due to limitations in quantitative control, leading to inconsistent film quality and ambiguous reaction pathways. …”
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Efficient Explainable Models for Alzheimer’s Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning by Yogita Dubey, Aditya Bhongade, Prachi Palsodkar, Punit Fulzele

“…<b>Objective:</b> This paper aims to propose a computationally efficient, reliable, and transparent machine learning-based framework for the classification of Alzheimer’s disease patients. …”
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Quantitative Genetics of Feed-Efficiency-Related Traits for the Pacific Whiteleg Shrimp <i>Penaeus vannamei</i> in a Plant-Based Diet Environment by Ping Dai, Xiangyan Zhu, Sheng Luan, Juan Sui, Xianhong Meng, Jiawang Cao, Jian Tan, Jie Kong

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Generation of Phase-Only Fourier Hologram Based on Double Phase Method and Quantization Error Analysis by Yang Wu, Jun Wang, Chun Chen, Chan-Juan Liu, Feng-Ming Jin, Yu-Hen Hu

“…The double phase method is an efficient way to generate phase-only holograms with high reconstruction quality due to no addition of a random phase. …”
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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…This study introduces a novel method to optimize Post-Training Quantization (PTQ), a widely used technique for reducing model size, by integrating Vector Quantization (VQ) with incremental clustering. …”
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Optimising TinyML with quantization and distillation of transformer and mamba models for indoor localisation on edge devices by Thanaphon Suwannaphong, Ferdian Jovan, Ian Craddock, Ryan McConville

“…Abstract This paper proposes small and efficient machine learning models (TinyML) for resource-constrained edge devices, specifically for on-device indoor localisation. …”
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Enabling Flexible Link Capacity for eCPRI-Based Fronthaul With Load-Adaptive Quantization Resolution by Longsheng Li, Meihua Bi, Haiyun Xin, Yunhao Zhang, Yan Fu, Xin Miao, Ahmed Mohanmmed Mikaeil, Weisheng Hu

“…Bandwidth-efficient 5G optical fronthaul interfaces, such as the Ethernet-based common public radio interface (eCPRI), with novel low layer split (LLS) are being actively investigated. …”
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A Quantitative Methodology to evaluate the cost of Human Capital acquisition. BioPharma Industry Model by Jason BECKWITH, Stephen GOLDRICK, William NIXON, Stavros KOURTZIDIS

“…Purpose: - This study introduces a novel quantitative methodology to measure talent efficiency and its direct impact on business financial success, addressing a gap in traditional recruitment cost models. …”
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FPGA Acceleration With Hessian-Based Comprehensive Intra-Layer Mixed-Precision Quantization for Transformer Models by Woohong Byun, Jongseok Woo, Saibal Mukhopadhyay

“…Our concurrent quantization method balances the benefits of row-wise weight quantization and Query-Key coupled activation quantization while maximizing energy efficiency through multi-precision optimization. …”
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GENERATING OF OPTIMAL QUANTIZATION LEVELS OF CONTROL CURRENTS FOR LINEAR STEPPING DRIVES OF PRECISION MOTION SYSTEMS by I. V. Dainiak, V. P. Oger, D. S. Tsitko, D. G. Begun

“…The investigations have proved an efficiency of the proposed algorithm and methodology for forming coordinate discrete grid.…”
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Sliding Mode Control of Uncertain Switched Systems via Length-Limited Coding Dynamic Quantization by Qinqi Xu, Haijuan Zhao

“…To address these issues, a dynamic quantizer is introduced to efficiently encode the system state while minimizing quantization error under the constraint of the finite code length. …”
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