An Innovative Framework for Quality Assurance in Logistics Packaging by Henriett Matyi, Péter Tamás

“…<i>Background</i>: As a result of the effort to satisfy unique customer needs, the complexity of production and service processes is constantly increasing. …”
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Classification of power quality disturbances in microgrids using a multi-level global convolutional neural network and SDTransformer approach. by Junzhuo Jiang, Hao Wu, Changhua Zhong, Hong Song

“…The model effectively retains the signal's original one-dimensional temporal attributes while also delving into more complex features. This approach exhibits strong resistance to noise and enhanced generalization skills, markedly improving the detection accuracy of power quality issues within microgrids.…”
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Generation of Genuine Multipartite Entangled States via Indistinguishability of Identical Particles by Kobra Mahdavipour, Farzam Nosrati, Stefania Sciara, Roberto Morandotti, Rosario Lo Franco

“…We also show that this graph-theoretical approach allows for the optimization of the generation efficiency of specific multipartite entangled states by exploring a variety of generation schemes. …”
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Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies. by Mario Pannunzi, Thomas Nowotny

“…We find that NSIs improve mixture ratio detection and plume structure sensing and do so more efficiently than the traditionally considered mechanism of lateral inhibition in the antennal lobe. …”
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Structured Summarization of League of Legends Match Data Optimized for Large Language Model Input by Jooyoung Kim, Wonkyung Lee, Jungwoon Park

“…Large-scale match data from esports games like League of Legends are stored in complex JSON files that often exceed the input token limitations of large language models (LLMs), restricting advanced analysis and applications such as automated commentary and strategic insight generation. …”
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Enhanced Software Testing Model Under Software Warranty Policy Considering Debugger Learning and Time Postponement Factors by Wang Li, Chih-Chiang Fang

“…This allows for the selection of the most effective option. The model takes into account the learning curve, which can significantly impact the efficiency of the software testing process. …”
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Spectrum Allocation and Power Control Based on Newton’s Method for Weighted Sum Power Minimization in Overlay Spectrum Sharing by Yang Yu, Xiaoqing Tang, Guihui Xie

“…Maximizing weighted sum energy efficiency (WSEE) requires solving complex multiple-ratio fractional programming (FP) problems. …”
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Automated Extraction of Pipe Geometry Using SAM for Mixed Reality Inspection Tasks by S. Einizinab, S. Einizinab, K. Khoshelham, K. Khoshelham, S. Winter, P. Christopher, P. Christopher

“…Accurate detection and measurement of building elements are essential for efficient automated inspection and quality assessment in construction. …”
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Robust Radio Frequency Fingerprinting With Signal Denoising and Stacked Multivariate Ensemble Learning for Secure Wireless Communications by Syed Usman Ali Shah, Muhammad Usama Zahid, Syed Abuzar H Shah, Saeed Ur Rehman, Dan Komosny

“…Radio Frequency Fingerprinting (RFF) has gained significant attention in wireless communication and security research due to its potential for device authentication and intrusion detection. While deep learning-based approaches have shown promising results, existing methods suffer from critical limitations: high computational complexity hinders real-time deployment on resource-constrained hardware, poor robustness under low Signal-to-Noise Ratio (SNR) conditions, and inadequate generalization across different datasets. …”
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Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems by Xiangyong Liu, Zan Yang, Jiansheng Liu, Junxing Xiong, Jihui Huang, Shuiyuan Huang, Xuedong Fu

“…Traditional optimization algorithms often struggle to balance the efficiency of global and local searches, especially when dealing with high-dimensional and complex constraint conditions. …”
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Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants by Deise Cristina Dal’Ongaro, Cicero Cena, Bruno Spolon Marangoni, Daniele A. Soares-Marangoni

“…Abstract Congenital syphilis is a global public health issue, and its diagnostic complexity poses a challenge to early treatment. Fourier Transform Infrared Spectroscopy (FTIR) is a promising technological tool that facilitates the detection and diagnosis of various diseases by providing information on the biochemical composition of biofluids, including saliva. …”
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An Optimization Algorithm for Forward-Scatter Radar Network Node Deployment Based on BFGS and Improved NSGA-II by Yuqing Zheng, Xiaofeng Ai, Zhiming Xu, Jing Wu, Feng Zhao

“…A multi-objective optimization model was subsequently established with the objective functions of minimizing node cost and maximizing spatial detection area. Second, a method based on the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm was introduced to obtain the sub-optimal solution of node cost, thereby reducing the computational complexity of the optimization process. …”
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KEDM: Knowledge-Embedded Diffusion Model for Infrared Image Destriping by Lingxiao Li, Xin Wang, Dan Huang, Yunan He, Zhuqiang Zhong, Qingling Xia

“…Specifically, LDM leverages a pretrained variational autoencoder (VAE) to transform the input image into latent feature space for efficient diffusion propagation, reducing computational complexity while preserving image restoration quality. …”
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The Implementation of the Askisi-SD Neuropsychological Web-Based Screener: A Battery of Tasks for Screening Cognitive and Spelling Deficits of Children by Nikolaos C. Zygouris, Eugenia I. Toki, Filippos Vlachos, Stefanos K. Styliaras, Nikos Tziritas

“…The web-based nature of the screener enables scalable and standardized administration, making it a practical and efficient tool for the early identification of spelling difficulties in children.…”
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A comparison of statistical methods for deriving occupancy estimates from machine learning outputs by Lydia K. D. Katsis, Tessa A. Rhinehart, Elizabeth Dorgay, Emma E. Sanchez, Jake L. Snaddon, C. Patrick Doncaster, Justin Kitzes

“…The inability to determine stable parameter choices a priori, coupled with the increased computational complexity of several models (i.e. the detection-count and continuous-score models), limits the practical application of false-positive models. …”
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Exploring sustainable strategies for mitigating microplastic contamination in soil, water, and the food chain: A comprehensive analysis by Udaratta Bhattacharjee, Kamal Narayan Baruah, Maulin P. Shah

“…Further, the article suggests a cost effective, efficient, and sustainable strategy to intercept MPs infiltration in the food chain and establish practical data applicability in real-life scenarios.…”
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Comparative Analysis of Classifiers for the Assessment of Respiratory Disorders Using Speech Parameters by Poonam Shrivastava, Neeta Tripathi, Bikesh Kumar Singh, Bhupesh Kumar Dewangan

“…The conclusion was that the proposed classifiers may provide an aid in the simple assessment of respiratory disorders utilising speech parameters with high efficiency. In the future, the proposed approach can be evaluated for the detection of specific respiratory disorders such as asthma, COPD, etc.…”
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Multi-modal action recognition via advanced image fusion techniques for cyber-physical systems by Zaiyong Shou, Daoyu Zhu

“…IntroductionThe increasing complexity of cyber-physical systems (CPS) demands robust and efficient action recognition frameworks capable of seamlessly integrating multi-modal data. …”
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Implementation of MF block in CNN for advanced REB fault diagnosis by M. Pandiyan, Narendiranath Babu T.

“…Furthermore, computational complexity analysis, including FLOPs estimation, was performed to assess real-time applicability. …”
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Empowering sentiment analysis in social media: a comprehensive approach to enhance the classification of abusive Tamil comments using transformer models by Malliga Subramanian, Sathishkumar Veerappampalayam Easwaramoorthy, Nandhini Subbarayan, Usha Moorthy

“…Of the models explored, the adapter-based mDeBERTa achieved the highest accuracy of 75.393%, validating the effectiveness of parameter-efficient transfer learning for abusive language detection in low-resource, code-mixed contexts.…”
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