Harmonizer: A Universal Signal Tokenization Framework for Multimodal Large Language Models by Amin Amiri, Alireza Ghaffarnia, Nafiseh Ghaffar Nia, Dalei Wu, Yu Liang

“…Harmonizer employs a unified approach to convert diverse, non-linguistic signals into discrete tokens via its FusionQuantizer architecture, built on FluxFormer, to efficiently capture essential signal features while minimizing complexity. …”
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Key Considerations for Real-Time Object Recognition on Edge Computing Devices by Nico Surantha, Nana Sutisna

“…This review paper introduces how artificial intelligence (AI) can be integrated with edge computing to enable efficient and scalable object recognition applications. …”
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Evaluating a Hybrid LLM Q-Learning/DQN Framework for Adaptive Obstacle Avoidance in Embedded Robotics by Rihem Farkh, Ghislain Oudinet, Thibaut Deleruyelle

“…A selective triggering mechanism ensures efficient LLM intervention, minimizing computational overhead. …”
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Nested Bi-level scheduling strategy for energy storage systems in hybrid microgrid considering uncertainties of battery dynamic performances by Jiazhi Lei, Zhao Liu

“…Firstly, the uncertainties in dynamic performances caused by fitting error including efficiencies, self-discharge rate, cycle life and capacity fading were modeled by interval method and probability distribution method. …”
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Discontinuity method for evaluating scattering amplitudes within the worldline formalism by Victor Miguel Banda Guzmán

“…As a result, a collection of worldline master integrals has been derived within this approach. However, efficient mathematical tools for evaluating these integrals remain limited. …”
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EMISSION PROCESSES OF QUANTUM WELL INTERACTION WITH DELTA-LAYER IN pHEMT-HETEROSTRUCTURES by Yana V. Ivanova, George E. Yakovlev, Vasily I. Zubkov

“…The optimum distance between QW and delta-layer providing the most efficient charge carrier delivery to quantum well is found. …”
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Predicting Overload Risk on Plasma-Facing Components at Wendelstein 7-X from IR Imaging Using Self-Organizing Maps by Giuliana Sias, Emanuele Corongiu, Enrico Aymerich, Barbara Cannas, Alessandra Fanni, Yu Gao, Bartłomiej Jabłoński, Marcin Jakubowski, Aleix Puig Sitjes, Fabio Pisano, W7-X Team

“…This study aims to thoroughly evaluate the capabilities of the SOM in recognizing overload risk levels, defined by quantizing the maximum criticality across different IR cameras. …”
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Research and optimization of a multilevel fire detection framework based on deep learning and classical pattern recognition techniques by Qi Liu, Hong Chen, Da Lin

“…Our objective is to further develop FFDNet into a robust, efficient, and widely applicable tool for flame detection, thereby providing significant technical support for fire prevention and response initiatives.…”
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Quantifying Shape and Texture Biases for Enhancing Transfer Learning in Convolutional Neural Networks by Akinori Iwata, Masahiro Okuda

“…Aligning the model’s bias with the dataset’s bias can significantly enhance performance in transfer learning, leading to more efficient learning. This study aims to quantitatively demonstrate that increasing shape bias within the network by varying kernel sizes and dilation rates improves accuracy on shape-dominant data and enables efficient learning with less data. …”
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Text-Guided Synthesis in Medical Multimedia Retrieval: A Framework for Enhanced Colonoscopy Image Classification and Segmentation by Ojonugwa Oluwafemi Ejiga Peter, Opeyemi Taiwo Adeniran, Adetokunbo MacGregor John-Otumu, Fahmi Khalifa, Md Mahmudur Rahman

“…The validation accuracy of various classification models Big Transfer (BiT), Fixed Resolution Residual Next Generation Network (FixResNeXt), and Efficient Neural Network (EfficientNet) were 92%, 91%, and 86%, respectively. …”
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Analysis of Mechanical Performance of Soil Solidification and Examination of Compatibility as Semi-Permanent House Material for Forcibly Displaced People by Dayoung Oh, Takafumi Noguchi, Ryoma Kitagaki

“…This study aims to investigate the suitability of earthen housing for refugees and establish a more efficient system for selecting and adjusting materials by quantitatively analyzing the influence of various factors affecting the mechanical performance of earthen housing. …”
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Analysis of Nonstationary Change of Annual Maximum Level Records in the Yangtze River Estuary by Guofang Li, Xinyi Xiang, Caixiu Guo

“…In this study, the efficiencies of trend test methods such as Spearman rank correlation test and Mann-Kendall test, as well as the efficiencies of change-point test methods such as moving T test, moving rank sum test, Pettitt test, and sequential Mann-Kendall test were analyzed quantitatively through Monte Carlo simulation. …”
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Anomalous entropy-driven kinetics of dislocation nucleation by Soumendu Bagchi, Danny Perez

“…These unusual kinetics are quantitatively rationalized using a variational transition state theory approach coupled with an efficient numerical scheme for the estimation of vibrational entropy changes. …”
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Mechanochemical Halogenations and Rearrangement of Sydnones: Insight into Reaction Conditions and Mechanism by Dr. Florian Luttringer, Dr. Nicolas Pétry, Dr. Eric Clot, Prof. Dr. Xavier Bantreil, Dr. Frédéric Lamaty

“…Abstract New mechanochemical methods for sydnone halogenation and insights into an efficient ring rearrangement yielding 1,3,4‐oxadiazolin‐2‐ones by heated ball‐milling are reported herein. …”
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Leveraging edge computing and deep learning for the real-time identification of bean plant pathologiesBean Plant Pathologies Dataset for Deep Learning Tasks by Andrew Katumba, Wayne Steven Okello, Sudi Murindanyi, Joyce Nakatumba-Nabende, Moses Bomera, Ben Wycliff Mugalu, Amos Acur

“…The custom CNN model and YOLO v8 model were quantized and deployed across two (2) edge platforms: a smartphone (through a mobile application) and a Raspberry Pi 4B to facilitate in-field disease detection. …”
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Ultrasound-based Eigenfrequency Analysis to Determine Material Parameters of Tissue Mimicking Phantoms by Heim Christian, Huber Christian M., Ullmann Ingrid, Lyer Stefan, Rupitsch Stefan J.

“…However, the spatial distribution of SPIONs cannot be quantitatively determined applying basic MMUS algorithms. …”
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New indicators of health among adolescent drug users and evaluation of drug policies comparing countries by Elena Ventura, Harrison Wagner, Carla Rossi

“…</p><p>We conclude that it is the correct balance between a drug policy aimed at prevention, rehabilitation, and a less restrictive legislation, that, on the basis of what we have analyzed and measured, has a positive effect on drug consumption and that indicators are efficient and should be applied regularly to compare quantitatively country policies to identify best practices.…”
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Spectrum decomposition in Gaussian scale space for uneven illumination image binarization. by JianWu Long, ZeRan Yan, HongFa Chen, XinLei Song

“…Although most images in industrial applications have fewer targets and simple image backgrounds, binarization is still a challenging task, and the corresponding results are usually unsatisfactory because of uneven illumination interference. In order to efficiently threshold images with nonuniform illumination, this paper proposes an efficient global binarization algorithm that estimates the inhomogeneous background surface of the original image constructed from the first k leading principal components in the Gaussian scale space (GSS). …”
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Ergonomic Framework to Enhance Sustainable Cost-Effective Process in A Fashion and Designed Industry by Kenneth Ugo Udeze, Gracious Amarachukwu Nwafor

“…The research employs established tools like RULA and REBA and diverse methods, including observations, interviews, and questionnaires, to quantitatively and qualitatively assess ergonomic risks. …”
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Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study by Sudeshna Das, Yao Ge, Yuting Guo, Swati Rajwal, JaMor Hairston, Jeanne Powell, Drew Walker, Snigdha Peddireddy, Sahithi Lakamana, Selen Bozkurt, Matthew Reyna, Reza Sameni, Yunyu Xiao, Sangmi Kim, Rasheeta Chandler, Natalie Hernandez, Danielle Mowery, Rachel Wightman, Jennifer Love, Anthony Spadaro, Jeanmarie Perrone, Abeed Sarker

“…Our modular framework generates individual summaries followed by an aggregated summary to answer medical queries from large amounts of user-generated social media data in an efficient manner. We compared the performance of a quantized large language model (Nous-Hermes-2-7B-DPO), deployable in low-resource settings, with GPT-4. …”
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