A Global Revolutionary Class Will Ride the Tiger of Alienation by Hardy Hanappi

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Representative Model of Economic Development for an Agricultural Enterprise in the Context of Socioeconomic Rural Space Formation by Vasyl D. Zalizko, Igor L. Fedun, Valentyn I. Martynenkov

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Multi-criteria decision analysis for regional-scale flood susceptibility mapping in Kerala state, India by M. S. Kendagannaswamy, C. K. Roopa, B. S. Harish, M. S. Mukesh

“…Despite Kerala's flood vulnerability and due to its intense annual rainfall, existing flood prediction approaches often fail to provide accurate and localized risk assessments. Various Machine Learning (ML) approaches offer promising results but there is a critical gap in applying these advanced ML algorithms along with systematized decision-making frameworks that would work well for Kerala's specific geographical and climatic conditions. …”
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Mine cable partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold by Jiyuan CAO, Yanwen WANG, Peng CHEN, Xuan ZHOU, Weixiong ZHU, Yihe ZHANG, Le WANG

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Error Analysis and Compensation of 3‒PTT Parallel Robot by CHEN Mingfang, LIANG Hongjian, WEI Songpo, HE Chaoyin

“…Thus, the algorithm is more feasible. In addition, to improve the efficiency of the aforementioned error compensation algorithm, the standard particle swarm optimization algorithm is further enhanced by integrating the dynamic inertia weight value and dynamic learning factor, thus overcoming the problems of precocious convergence to a local optimum and slow convergence in the later iteration of the standard particle swarm optimization algorithm. …”
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Robust Bi-CBMSegNet framework for advancing breast mass segmentation in mammography with a dual module encoder-decoder approach by Yu Wang, Mudassar Ali, Tariq Mahmood, Amjad Rehman, Tanzila Saba

“…Current target detection algorithms have limited applications and low accuracy. …”
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Prevalence of COVID-19-associated pneumonia signs on chest computed tomography in cancer patients: the ARILUS study by A. A. Dyachenko, A. M. Grjibovski, M. A. Bogdanov, D. V. Bogdanov, E. A. Nazarova, A. A. Meldo, V. Yu. Chernina, M. G. Belyaev, V. A. Gombolevsky, M. Yu. Valkov

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Evaluating Spatial Patterns of Ecosystem Services based on a Comparative Approach on Spatial Statistics in the Central Part of Isfahan Province by Sedighe Abdollahi, Alireza Ildoromi, Abdolrassoul Salmanmahini, Sima Fakheran

“…Accordingly, the spatial variation of three ecosystem services, aesthetics value, recreation value and noise pollution reduction in the central part of Isfahan province was investigated applying statistical approaches of Local Moran’s I, and Getis-Ord Gi analysis. Then, spatial accuracy of the investigated algorithms was evaluated and compared using the Receiving Operator Characteristic method. …”
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Impact of summer heat and mitigation strategies on apple (Cosmic Crisp®) fruit color dynamics quantified using crop physiology sensing system by Basavaraj R. Amogi, Lav R. Khot, Bernardita V. Sallato

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Hybrid optimized data aggregation for fog computing devices in internet of things by M. Jalasri, S. Manikandan, Arthur Davis Nicholas, S. Gobimohan, Naarisetti Srinivasa Rao

“…In this work, a new and novel hybrid optimization technique based on TABU Search (TS), Particle Swarm Optimization (PSO), and River Formation Dynamics (RFD) algorithms were proposed. The Hybrid RFD-TS, along with a hybrid RFD-PSO technique, was in the solution space search used for the local optimum, which is avoided. …”
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Assessment of flood vulnerability in a coastal metropolitan city for sustainable environmental using machine learning methods by Rana Alabdan, C. Sharmila, Nuha Alruwais, Haya Mesfer Alshahrani, S. Anbukkarasi, M. Sujatha, S. Vivek

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Enhancing Attendance Management Through Face Recognition Technology: A Case Study at Rugarama School of Nursing and Midwifery. by Taremwa, Benjamin

“…This study, titled "Enhancing Attendance Management through Face Recognition Technology: A Case Study at Rugarama School of Nursing and Midwifery," aimed to develop a more accurate and efficient solution using Local Binary Pattern Histogram and Convolutional Neural Networks algorithms to automate attendance tracking.A mixed-method approach was employed, combining system testing with user feedback from administrators, staff, and students. …”
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Design of Ricker Wavelet Neural Networks for Heat and Mass Transport in Magnetohydrodynamic Williamson Nanofluid Boundary-Layer Porous Medium Flow with Multiple Slips by Zeeshan Ikram Butt, Muhammad Asif Zahoor Raja, Iftikhar Ahmad, Muhammad Shoaib, Rajesh Kumar, Syed Ibrar Hussain

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Multi-UAV assisted air-to-ground data collection for ground sensors with unknown positions by Cheng Yiran, Dong Yangrui

“…However, due to the increasing miniaturization of wireless sensors, obtaining precise locations for deploying such sensors simultaneously in large areas is challenging or costly. While sensor localization techniques have been widely explored, including collaborative localization in sensor networks and received signal strength-based positioning, previous research has not addressed scenarios where sensor positions are completely unknown. …”
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Influence of Absorbing Material Distribution on Double Slope Sound Decay in L-Shaped Room by Mirosław MEISSNER

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A parameter centric service discovery framework for social digital twins in smart City by Farhan Amin, Salabat Khan, Gyu Sang Choi, Muhammad Ali Abid, Isabel de la Torre, Elisabeth Caro Montero, Irene Delgado Noya

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Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

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Graph-Theoretic Detection of Anomalies in Supply Chains: A PoR-Based Approach Using Laplacian Flow and Sheaf Theory by Hsiao-Chun Han, Der-Chen Huang

“…Based on Graph Balancing Theory, this study proposes an anomaly detection algorithm, the Supply Chain Proof of Relation (PoR), applied to enterprise procurement networks formalized as weighted directed graphs. …”
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Beyond boundaries: AI-optimized global landslide susceptibility mapping by Mahdi Panahi, Fatemeh Rezaie, Khabat Khosravi, Zahra Kalantari, Sayed M. Bateni, Jeong-A Lee

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A comparative study of convolutional neural networks and traditional feature extraction techniques for adulteration detection in ground beef by Leila Bahmani, Saied Minaei, Alireza Mahdavian, Ahmad Banakar, Mahmoud Soltani Firouz

“…In order to identify the most appropriate feature extraction algorithm and classify samples having various levels of adulteration, Local Binary Pattern (LBP), Gray Level Co-occurrence Matrixes (GLCM) and Gabor filter were compared. …”
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