Metallic Artifacts’ Reduction in Microtomography Using the Bone- and Soft-Tissue Decomposition Method by Jan Juszczyk, Jakub Pałachniak, Ewa Piętka

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An Antenna Array Sidelobe Level Reduction Approach through Invasive Weed Optimization by Geng Sun, Yanheng Liu, Han Li, Shuang Liang, Aimin Wang, Boyu Li

“…The results show that IWO has a better performance in terms of the accuracy, the convergence rate, and the stability compared with other algorithms for the SLL reductions. Moreover, the electromagnetic simulation results also show that IWO achieves the best performance for the beam pattern synthesis of the antenna arrays in practical conditions.…”
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Long short-term memory (LSTM) networks for precision prediction of Schottky barrier photodiode behavior at different illumination levels by Gökalp Tulum, Sajjad Nematzadeh, İlke Taşçıoğlu, Şemsettin Altındal, Fahrettin Yakuphanoğlu

“…Abstract This study has focused on modeling and predicting the electrical properties and parameters of CdZnO interlayered Al/p-Si Schottky Diodes (SDs) using the Long Short-Term Memory (LSTM) algorithm. …”
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Adaptive dimensionality reduction for neural network-based online principal component analysis. by Nico Migenda, Ralf Möller, Wolfram Schenck

“…While the continuous update of the principal components is widely studied, the available algorithms for dimensionality adjustment are limited to an increment of one in neural network-based and incremental PCA. …”
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A Novel Efficient Feature Dimensionality Reduction Method and Its Application in Engineering by Zhun Cheng, Zhixiong Lu

“…To render feature dimensionality reduction more effective and faster, this paper proposes a new feature dimensionality reduction approach combining a sampling survey method with a heuristic intelligent optimization algorithm. …”
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Reduction of the Reconstruction Error With Lower and Upper Bounds in Synthetic Aperture Imaging Radiometers by Xiaocheng Yang, Zhenyi Yang, Jingye Yan, Lin Wu, Mingfeng Jiang, Wentao Lyu

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An Optimization Mechanism Intended for Static Power Reduction Using Dual-𝑉thTechnique by Rodolfo P. Santos, Gabriela S. Clemente, Abel Silva-Filho, Cristiano Araújo, Adriano Sarmento, Manoel Lima, Edna Barros

“…The fact that only some cells are replaced every iteration results in a reduction of the runtime of the algorithm. Additionally, results showed a reduction in static power up to 39.28%, when applying the proposed approach in the ISCAS85 benchmark circuits.…”
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Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography by Singanallur Venkatakrishnan, Obaidullah Rahman, Lynda Amichi, Jose D. Arregui-Mena, Haoran Yu, David A. Cullen, Amirkoushyar Ziabari

“…In this paper, we present a two-stage algorithm based on metal artifact reduction, utilizing model-based iterative reconstruction methods with adaptive adjustment of regularization parameters. …”
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Gaining transparency in Uber’s algorithmic management by Jessica Pidoux, Sofia Kypraiou, Paul-Olivier Dehaye

“…Nevertheless, this dependence and the resulting economic losses and gains are passed on to drivers individually as “algorithmic predictability risk”. Indeed, drivers’ data are controlled by Uber to make automated predictions of supply and demand for the benefit of the platform exclusively.…”
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ALGORITHM OF TECHNOLOGICAL FORECASTING IN THE RUSSIAN FEDERATION by Victor Mikhaylovich Averbukh

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Molecular Beacon Sequence Design Algorithm by W. Todd Monroe, Frederick R. Haselton

“…This analysis is carried out using mfold structural predictions along with other free Web-based tools. For smaller laboratories where molecular beacons are not the focus of research, the public domain algorithm described here may be usefully employed to aid in molecular beacon design.…”
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Algorithm profiling for architectures with dataflow accelerators by Nenad Korolija, Veljko Milutinović, Borko Furht

“…As a result, it is not always obvious whether programming dataflow architectures for certain algorithms is worth the effort needed. Therefore, there is a need for a programmer to be able to predict the outcome of programming for dataflow architectures in terms of accelerating program execution and power savings. …”
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openTSNE: A Modular Python Library for t-SNE Dimensionality Reduction and Embedding by Pavlin G. Poličar, Martin Stražar, Blaž Zupan

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Integrating proximal geophysical sensing and machine learning for digital soil mapping: Spatial prediction and model evaluation using a small dataset by Danilo César de Mello, Gustavo Vieira Veloso, Murilo Ferre de Mello, Marcos Guedes de Lana, Isabelle de Angeli Oliveira, Fellipe Alcantara de Oliveira Mello, Rafael Gomes Siqueira, Lucas Carvalho Gomes, Elpídio Inácio Fernandes-Filho, Carlos Ernesto Gonçalves Reynaud Schaefer, Márcio Rocha Francelino, Emilson Pereira Leite, Tiago Osório Ferreira, José Alexandre Melo Demattê

“…However, studies focusing the spatial prediction of geophysical data remain limited. In this research, we aimed to model and predict the spatial distribution of soil geophysical properties using parent material and terrain attributes with machine learning algorithms. …”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. …”
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A Game Theoretic Approach for Interuser Interference Reduction in Body Sensor Networks by Guowei Wu, Jiankang Ren, Feng Xia, Lin Yao, Zichuan Xu, Pengfei Shang

“…In this paper, a game theoretic decentralized interuser interference reduction scheme for BSN is proposed. The selection of the channel and transmission power is modeled as a noncooperative game between different BSNs congregating in the same area. …”
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Feedforward Control of a Light-Weight Device Casing for Active Noise Reduction by Stanislaw WRONA, Marek PAWELCZYK

“…An adaptive control strategy based on the Least Mean Square (LMS) algorithm is used to update control filter parameters. …”
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Performance Comparison of Data Reduction Techniques for Wireless Multimedia Sensor Network Applications by Pinar Sarisaray-Boluk, Kemal Akkaya

“…The results also indicate that data reduction techniques including BS algorithms and compression techniques can provide significant energy savings in terms of transmission energy costs.…”
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Divisive hierarchical clustering for energy saving and latency reduction in UAV-assisted WSANs by Xuan Zhang, Yong-Long Wang, Heejung Byun

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A Method for Service Function Chain Migration Based on Server Failure Prediction in Mobile Edge Computing Environment by Joelle Kabdjou, Norihiko Shinomiya

Subjects: “…Failure prediction…”
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