Optimization of Transformation Coefficients Using Direct Search and Swarm Intelligence by Manusov V.Z., Matrenin P.V., Orlov D.V.

“…Such algorithms include Swarm Intelligence algorithms. Their main features are self-organization, which allows them to automatically adapt to conditions of tasks, and the ability to efficiently exit from local extremes. …”
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Better Cone-Beam CT Artifact Correction via Spatial and Channel Reconstruction Convolution Based on Unsupervised Adversarial Diffusion Models by Guoya Dong, Yutong He, Xuan Liu, Jingjing Dai, Yaoqin Xie, Xiaokun Liang

“…The obtained results can reduce artifacts while preserving the anatomical structure of CBCT images. …”
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Numerical Prediction of Solid Particle Erosion in Jet Pumps Based on a Calibrated Model by Xuanchen Wan, Mengxue Dong, Maosen Xu, Chuanhao Fan, Jiegang Mou, Shuai Han

“…The Grey Wolf Optimization algorithm was applied to calibrate model coefficients. …”
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Land use land cover change as a casual factor for climate variability and trends in the Bilate River Basin, Ethiopia. by Samuel Shibeshi Bikeko, Dr E Venkatesham

“…Concurrently, agricultural land expanded at an annual rate of approximately 1,141 hectares, while urban areas grew by 24.3 hectares annually in recent years. …”
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A Novel Method Based on Particle Flow Filters for Stellar Gyroscope Parameter Estimations by Erol Duymaz

“…Inertial sensors are commonly used in many applications for a while. They provide important information about the orientation but are prone to structural errors, which makes it impossible to use their raw data. …”
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nPPoS: Non-interactive practical proof-of-storage for blockchain by Jun Wook Heo, Gowri Ramachandran, Raja Jurdak

“…The intentional resource-intensive encoding deters attacks, while faster decoding minimises performance overhead. …”
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Comparison of elastic properties of periodic and aperiodic porous structures produced by additive methods by Radosław Grabiec, Jacek Tarasiuk, Sebasatian Wroński, Gianpaolo Pillon

“…These structures, generated using an algorithm, featured three types of lattices: octet, cubic, and Voronoi diagram-based, with different porosities (40 %, 60 %, 80 %) and beam sizes (0.45 mm, 0.66 mm). …”
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Semantic RF Waveform Adaptation in Flying Ad Hoc Networks via Hybrid Knowledge Bases and Deep Reinforcement Learning by Weiqiang Lyu, Linsheng He, Jiamiao Zhao, Fei Hu

“…We propose a framework that jointly optimizes modulation order and cyclic prefix length while considering the semantic importance of transmitted data. …”
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Residual-conditioned sparse transformer for photoacoustic image artifact reduction by Xiaoxue Wang, Jinzhuang Xu, Chenglong Zhang, Moritz Wildgruber, Wenjing Jiang, Lili Wang, Xiaopeng Ma

“…By introducing residual prior information, our algorithm encodes and embeds it into local enhancement and detail recovery stages. …”
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Enhanced bearing health indicator extraction using slope adaptive signal decomposition for predictive maintenance by Dev Bhanushali, Pooja Kamat, Harsh Dhiman

“…This study introduces the Slope Adaptive Signal Decomposition (SASD) algorithm, a novel method for extracting enhanced intrinsic machine health indicators from vibration data. …”
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An Analysis of the Movement Trajectories of the Endangered <i>Acipenser gueldenstaedtii</i> in Ammonia-Supplemented Environments Using Image Processing Methods by Beytullah Ahmet Balci, Güray Tonguç, Muhammed Nurullah Arslan, İlker Zeki Kurtoğlu, Tuba Sari

“…For image processing operations, the optical flow Farneback object-tracking algorithm and necessary image development algorithms were implemented using Python 3.9.13 Programming language codes in the Visual Studio Code software 1.98.2 development environment. …”
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Collaborative Relay Beamforming Based on Minimum Power for M2M Devices in Multicell Systems by Xiaoning Zhang, Da Wang, Lin Bai, Chen Chen

“…We minimize the transmit power of the base stations (BSs) and relays to save the power of M2M devices, while guaranteeing the receive signal-to-interference-and-noise ratio (SINR) of the destination devices. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…However, as cross-domain data evolves, the discrepancies between domains grow increasingly intricate and difficult to manage, rendering effective knowledge transfer across multiple domains a persistent challenge. While existing methods concentrate on minimizing domain discrepancies, they frequently encounter difficulties in maintaining effectiveness when confronted with high data complexity. …”
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Bytecode-based approach for Ethereum smart contract classification by Dan LIN, Kaixin LIN, Jiajing WU, Zibin ZHENG

“…In recent years, blockchain technology has been widely used and concerned in many fields, including finance, medical care and government affairs.However, due to the immutability of smart contracts and the particularity of the operating environment, various security issues occur frequently.On the one hand, the code security problems of contract developers when writing contracts, on the other hand, there are many high-risk smart contracts in Ethereum, and ordinary users are easily attracted by the high returns provided by high-risk contracts, but they have no way to know the risks of the contracts.However, the research on smart contract security mainly focuses on code security, and there is relatively little research on the identification of contract functions.If the smart contract function can be accurately classified, it will help people better understand the behavior of smart contracts, while ensuring the ecological security of smart contracts and reducing or recovering user losses.Existing smart contract classification methods often rely on the analysis of the source code of smart contracts, but contracts released on Ethereum only mandate the deployment of bytecode, and only a very small number of contracts publish their source code.Therefore, an Ethereum smart contract classification method based on bytecode was proposed.Collect the Ethereum smart contract bytecode and the corresponding category label, and then extract the opcode frequency characteristics and control flow graph characteristics.The characteristic importance is analyzed experimentally to obtain the appropriate graph vector dimension and optimal classification model, and finally the multi-classification task of smart contract in five categories of exchange, finance, gambling, game and high risk is experimentally verified, and the F1 score of the XGBoost classifier reaches 0.913 8.Experimental results show that the algorithm can better complete the classification task of Ethereum smart contracts, and can be applied to the prediction of smart contract categories in reality.…”
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A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions by Bing Yang, Kaiwei Wu, Zhe Guo, Yanbin Liang, Shijun Hao, Zhonghua Huang

“…To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. …”
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Verifiable secure aggregation scheme for privacy protection in federated learning networks by Wujun Yao, Tanping Zhou, Yiliang Han, Xiaolin Wang

“…Initially, we construct a functional reuse private key ring generation algorithm, enabling clients to encrypt and protect their private gradients using the private key ring. …”
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Distributionally robust optimal scheduling of flexible distribution networks considering dynamic spatio-temporal correlation of renewable energy by Shunxiang Yu, Xiaoming Dong, Chengfu Wang, Tianguang Lu

“…By utilizing the 1-norm and ∞-norm to characterize the uncertainty sets between sources and loads, this strategy effectively minimizes operational costs while ensuring robust performance. The proposed model is linearized and relaxed through second-order cone programming and solved using the column and constraint generation (C&CG) algorithm. …”
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Pathways to 30 × 30: Evidence-Based Lessons from Global Case Studies in Biodiversity Conservation by Susmita Dasgupta, David Wheeler, Brian Blankespoor

“…A spatial prioritization algorithm is employed to pinpoint areas where new protected regions can address biodiversity gaps, with a particular focus on endemic and unprotected species. …”
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EVOLUTION OF THE AGRICULTURAL LABOUR MARKET IN THE EUROPEAN UNION BETWEEN 2011-2020 by Cristina Vasilica ICOCIU, Ana-Maria IFRIM, Cătălin Ionuț SILVESTRU, Marius-Mihai MICU

“…Applying Lewis's model of development, governments must strive to increase agricultural productivity while stimulating capital accumulation and in the other sectors of the economy.…”
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From Tweets to Threats: A Survey of Cybersecurity Threat Detection Challenges, AI-Based Solutions and Potential Opportunities in X by Omar Alsodi, Xujuan Zhou, Raj Gururajan, Anup Shrestha, Eyad Btoush

“…DeepNN consistently outperforms competing methods in terms of overall and average figure of merit. While character-level feature extraction methods are abundant, we contend that a semantic focus is more beneficial for this stage of the process. …”
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