Mapping the most effective measures to optimize carrot slice tray drying using physics-based and Monte Carlo simulations by Jörg Schemminger, Sharvari Raut, Barbara Sturm, Thijs Defraeye

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Joint Identification and Sensing for Discrete Memoryless Channels by Wafa Labidi, Yaning Zhao, Christian Deppe, Holger Boche

“…In the identification (ID) scheme proposed by Ahlswede and Dueck, the receiver’s goal is simply to verify whether a specific message of interest was sent. …”
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Modal Parameter Identification of the Improved Random Decrement Technique-Stochastic Subspace Identification Method Under Non-Stationary Excitation by Jinzhi Wu, Jie Hu, Ming Ma, Chengfei Zhang, Zenan Ma, Chunjuan Zhou, Guojun Sun

“…This not only improves the signal-to-noise ratio of the signal, but also improves the computational efficiency significantly. A non-stationary excitation is applied to the spatial grid structure model, and the RDT-SSI method is used to identify the modal parameters. …”
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Enhancing DeepLabv3+ Convolutional Neural Network Model for Precise Apple Orchard Identification Using GF-6 Remote Sensing Images and PIE-Engine Cloud Platform by Guining Gao, Zhihan Chen, Yicheng Wei, Xicun Zhu, Xinyang Yu

“…This study enhanced the DeepLabv3+ model to achieve superior performance in apple orchard identification by incorporating ResNet, optimizing the algorithm, and adjusting hyperparameter configuration using the PIE-Engine cloud platform. …”
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YOLOv8 forestry pest recognition based on improved re-parametric convolution by Lina Zhang, Shengpeng Yu, Bo Yang, Shuai Zhao, Ziyi Huang, Zhiyin Yang, Helong Yu

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Identification of human-wildlife interaction hotspots near riparian reserves: A case study of Beas conservation reserve, A Ramsar site by Navdeep Sood, Rohan Kumar, Swati Sharma

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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…To address the challenges posed by class imbalance and temporal dependency in drilling condition data and enhance the accuracy of condition identification, this study proposes an integrated method combining feature engineering, data resampling, and deep learning model optimization. …”
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Damping Identification Sensitivity in Flutter Speed Estimation by Gabriele Dessena, Alessandro Pontillo, Marco Civera, Dmitry I. Ignatyev, James F. Whidborne, Luca Zanotti Fragonara

“…This study evaluates two frequency-domain system identification methods, Fast Relaxed Vector Fitting (FRVF) and the Loewner Framework (LF), for predicting the flutter onset speed of a flexible wing model. …”
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Security-centric node identification in complex networks by Lanying Liu, Ning Du, Duyong Sheng

“…To achieve this, we develop a mathematical model to compute SC, introduce efficient algorithms for identifying critical nodes, and implement an incremental update mechanism to enhance adaptability in real-time networks. …”
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FruVeg_MultiNet: A hybrid deep learning-enabled IoT system for fresh fruit and vegetable identification with web interface and customized blind glasses for visually impaired indivi... by Khondokar Oliullah, Md. Reazul Islam, Jahirul Islam Babar, M.A. Nur Quraishi, Md. Mahbubur Rahman, Md. Mahbub-Or-Rashid, T.M. Amir-Ul-Haque Bhuiyan

“…This research presents a pioneering approach for fresh fruit and vegetable identification through IoT and a hybrid deep learning model, combining EfficientNetB7 and ResNet50 architectures. …”
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Risks as an object of internal control: identification and assessment by М.М., I.I.

“…Identification and assessment of business risk, determining the level of its materiality and impact on the functioning of economic entities of various organizational and legal forms and forms of ownership, is possible with a properly organized system of internal control. …”
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Temperature-Dependent Kinetic Modeling of Nitrogen-Limited Batch Fermentation by Yeast Species by Artai R. Moimenta, Romain Minebois, David Henriques, Amparo Querol, Eva Balsa-Canto

“…The development of predictive models that accurately describe these effects is essential for automating and optimizing fermentation design, reducing trial-and-error experimentation, and improving process efficiency and product quality. …”
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Identification of Factors Affecting Project Financing Risk by Gholamreza Sharafi, Kiamars Fathi Hafashjani, Faegh Ahmadi

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Identification of Eye Diseases Through Deep Learning by Elena Acevedo, Dinora Orantes, Marco Acevedo, Ricardo Carreño

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Identification of quality problems staff vocational training by Vera V. Zhivaeva, Vadim A. Nikovaev, Svetlana N. Parfenova, Elena P. Tuponosova

“…Observation of the reaction of output quantities to changes in input influences allows us to construct an a posteriori model of the process, i.e. to identify the quality problem in the early stages of its inception.The purpose of this work is to investigate the possibility of ensuring the quality of personnel software by the identification method based on the results of evaluating the input and output signals of the OP as a control object. …”
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A distributionally robust machine learning model of simultaneous classification and feature selection under data uncertainty: Theory, methods, and application to the identification... by Q.Y. Huang, N.D. Dizon, N. Jeyakumar, V. Jeyakumar

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Contextualizing Innovation Investor Behaviour Through Structural Simulation Modelling of Influential Factors

“…This study aims to examine the interconnections between self-efficacy, self-determination, and intrinsic motivation among individual investors; to delineate the relationships between intrinsic and extrinsic motivation, investor attitudes, perceived risk, and loyalty; and to develop a conceptual model that synthesizes these relationships. The research methodology is based on interpretive structural modelling (ISM), ensuring a systematic exploration of factor interdependencies. …”
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Enhancing Urban Land Utilization Through SegFormer: A Vacant Land Analysis in Chengdu by Xi Cheng, Jieyu Yang, Bin Li, Bin Zhao, Deng Pan, Zhanfeng Shen, Qian Zhu, Miaomiao Liu

“…This framework provides the accurate and efficient tool for UVL identification, contributing to improved urban land utilization and offering valuable insights for future research and urban planning.…”
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Secure and load balanced routing model for wireless sensor networks by Gousia Thahniyath, M. Jayaprasad

“…The result attained shows SLBR model attains better performance than ECSO in terms of energy efficiency (i.e., network lifetime considering first sensor device death and total sensor device death), communication overhead, throughput, packet processing latency, malicious sensor device misclassification rate and identification.…”
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Detecting drug transfers via the drop-off method: A supervised model approach using AIS data by Britt van Leeuwen, Maike Nutzel

“…Unlike existing research, primarily employing unsupervised methods, we propose a supervised model specifically tailored to this illicit activity, with a particular emphasis on its application to fishing vessels.Our model significantly reduces the number of data points requiring classification by the observer by 70% , thereby enhancing the efficiency of the drop-off detection process. …”
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