The Impact of Prediction Models on Energy-Aware Resource Management in FaaS Platforms by Shahrokh Vahabi, Francesca Righetti, Carlo Vallati, Nicola Tonellotto

“…Accurate time-series prediction models, which forecast the future number of function invocations, are crucial for energy-efficient function scheduling, enabling proactive resource allocation. In this work, we evaluate the impact of different neural time-series predictors based on Gaussian processes, recurrent neural networks, and transformer architectures in forecasting the number of function invocations. …”
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Growing Correspondence Seeds for Efficient and Accurate Satellite DSM Extraction by Amin Sedaghat, Nazila Mohammadi

“…The main property of the Sat-GCS method is the generation of a set of precise and dense tie-points in stage (2), used as initial correspondence seeds to improve the GCS algorithm in stage (4). The proposed method is evaluated on 12 different datasets from four different satellite sensors including ZY3-01, CartoSat-1, ZY3-02, and Worldview-3, and the results are compared with the CATALYST, SAT-MVSF, and SS-DSM methods. …”
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Potential G-quadruplexes and i-Motifs in the SARS-CoV-2. by Efres Belmonte-Reche, Israel Serrano-Chacón, Carlos Gonzalez, Juan Gallo, Manuel Bañobre-López

“…These sequences were evaluated by their in vitro formation probability, their position in the viral RNA, their uniqueness and their conservation rates (calculated in over seventeen thousand different COVID-19 clinical cases and sequenced at different times and locations during the ongoing pandemic). …”
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Filtering Techniques To Reduce Speckle Noise And Image Quality Enhancement Methods On Porous Silicon Images Layers by Tifouti Issam, Rahmouni Salah, Meriane Brahim

“…Recently, many studies have examined filters for reducing or removing speckle noise, which is inherent to different images types such as Porous Silicon (PS) images, in order to ameliorate the metrological evaluation of their applications. …”
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Unite and conquer approach for data clustering based on particle swarm optimization and moth flame optimization by E. Mosavi, S.A. Shahzadeh Fazeli, E. Abbasi, F. Kaveh-Yazdy

“…The  fficiency of the proposed approach is evaluated utilizing benchmark functions F1-F23. Its efficiency is evaluated with PSO and MFO algorithms on different datasets. …”
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Minimum Energy Demand Locomotion on Space Station by Wing Kwong Chung, Yangsheng Xu

“…To evaluate the performance of the proposed gaits and path planning algorithm, numerous simulations are performed. …”
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An intelligent stochastic optimization approach for air cargo order allocation under carbon emission constraints. by Zhenzhong Zhang, Ling Zhang, Deqiang Fu, Weichun Li

“…A new intelligent optimization method is introduced for addressing the order assignment problem under carbon emission constraints by combining the improved adaptive large-scale neighborhood search algorithm with the scenario generation technique. The method finds the optimal solution through an improved adaptive large-scale neighborhood search algorithm and uses a scenario generation technique to generate the scenarios required for evaluating candidate solutions to the high-dimensional stochastic optimization problem. …”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…However, the current multi-layer quantitative analysis model still exhibits some deviations in regard to different elements. In the future, a potential avenue is to consider integrating various algorithms to establish preliminary classification models, aiming for even better quantitative analysis outcomes.…”
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Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition by Erhan Bergil, Murat Yıldız

“…The generated feature matrices are applied to different classifiers as input. It is aimed to detect different epileptic stage. …”
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A machine learning-based approach for constructing a 3D apparent geological model using multi-resistivity data by Jordi Mahardika Puntu, Ping-Yu Chang, Haiyina Hasbia Amania, Ding-Jiun Lin, M. Syahdan Akbar Suryantara, Jui-Pin Tsai, Hwa-Lung Yu, Liang-Cheng Chang, Jun-Ru Zeng, Lingerew Nebere Kassie

“…Following evaluation via confusion matrix analysis, evaluation metrics, and examination of receiver operating characteristics curve, it emerged that the RF algorithm exhibits superior performance when applied to our multi-resistivity data set. …”
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Numerical Analysis of Digital Twin System Modeling Methods Aided by Graph-Theoretic Combinatorial Optimization by Sujing Zhou

“…Secondly, a scheduling technology framework for capacity simulation evaluation and optimization is established, and batching optimization, outsourcing decision, and rolling scheduling techniques are thus proposed to form a batching optimization algorithm based on priority rules, which realizes batching processing, outsourcing decision, and rolling scheduling of production orders to optimize equipment utilization and capacity. …”
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Individual tree segmentation of airborne and UAV LiDAR point clouds based on the watershed and optimized connection center evolution clustering by Yi Li, Donghui Xie, Yingjie Wang, Shuangna Jin, Kun Zhou, Zhixiang Zhang, Weihua Li, Wuming Zhang, Xihan Mu, Guangjian Yan

“…Our method outperforms the other methods especially in the broadleaf forests plot on slopes, where the five evaluation metrics for tree top detection outperformed the other algorithms by at least 11% on average. …”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…Extensive simulations are conducted to evaluate the performance of the proposed method against state-of-the-art algorithms in terms of coverage quality and node count. …”
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Self-organized cyber physical power system blockchain architecture and protocol by Ting Yang, Feng Zhai, Jialin Liu, Meng Wang, Haibo Pen

“…Different scales of IEEE standard bus systems are employed as experimental examples to evaluate the algorithm’s performance. …”
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Multistage Threshold Segmentation Method Based on Improved Electric Eel Foraging Optimization by Yunlong Hu, Liangkuan Zhu, Hongyang Zhao

“…To evaluate the segmentation performance of the proposed MIEEFO, 15 benchmark functions are used, and comparisons are made with seven other algorithms. …”
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Influence maximization under imbalanced heterogeneous networks via lightweight reinforcement learning with prior knowledge by Kehong You, Sanyang Liu, Yiguang Bai

“…We also analyze the effect of different graph embedding algorithms and prior knowledge on algorithmic results. …”
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Research on the On-Line Identification of Ship Maneuvering Motion Model Parameters and Adaptive Control by Jinlai Liu, Lubin Chang, Luping Xu, Fang He, Yixiong He

“…Data for identification are obtained via a maneuvering simulator and the impact of different forgetting factors on the identification process is evaluated. …”
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Performance of segmentation (watershed and meanshift) and image transformation (MNF-laplacian filter) methods for extracting complex coastlines from Pleiades images: the case of th... by Luc Simirore Diatta, Katia Schörle, Zahra Akacha, Semah Bettaieb, Ali Drine, Ameur Oueslati, Luc Lapierre

“…This evaluation of the performance of the automatic extraction methods was carried out by comparison with manually Digitized coastlines across different types of coastlines, a methodology that could be applied to other study areas with similar characteristics. …”
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Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population. by John T Murchison, Gillian Ritchie, David Senyszak, Jeroen H Nijwening, Gerben van Veenendaal, Joris Wakkie, Edwin J R van Beek

“…<h4>Materials and methods</h4>In total, a number of 337 scans of 314 different subjects with reported nodules of 3-30 mm in size were included into the evaluation. …”
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Breaking Through GNSS Outage: Advanced Stochastic Model for MEMS IMU in Navigation by Ahmed Shahrawy, Mahmoud A. Shawky, Adel M. Soliman, Wali Ullah Khan, Ahmad Almogren, Ahmed G. Abdellatif, Syed Tariq Shah

“…This article employs three techniques for modeling stochastic errors: the autocorrelation function (ACF), the Allan variance (AV), and the generalized method of wavelet moments (GMWM). Two different-grade inertial measurement units (IMUs) evaluate the effectiveness of ACF, AV, and GMWM in modeling inertial sensor noise: The ADIS low-cost microelectromechanical systems (MEMS) grade IMU and the Spatial MEMS tactical-grade IMU. …”
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