A Design of CP-MIMO System with Elements of a Diamond-Ring Slot for 5G Mobile-Phone by Alyaa Sami Abdullah, Seham A. Hashem, Mahmood F . Mosleh

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DQN-based energy-efficient routing algorithm in software-defined data centers by Zan Yao, Ying Wang, Xuesong Qiu

“…For the scenario of in-band control mode of software-defined data centers, we formulate the dual optimal objective of energy-saving and the load balancing between controllers. …”
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QeMFi: A Multifidelity Dataset of Quantum Chemical Properties of Diverse Molecules by Vivin Vinod, Peter Zaspel

“…Multifidelity ML (MFML) methods, where models are trained on data from more than one fidelity, have shown to be effective over single fidelity methods. …”
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Color Standardization Method and System for Whole Slide Imaging Based on Spectral Sensing by Shinsuke Tani, Yasuhiro Fukunaga, Saori Shimizu, Munenori Fukunishi, Kensuke Ishii, Kosei Tamiya

“…And we can conduct without training data set which is needed in conventional method, 2) We can get detection performance of H&E component equivalent to conventional method (60 bands). …”
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Continuous Wavelet Transform and CNN for Fault Detection in a Helical Gearbox by Iulian Lupea, Mihaiela Lupea

“…Through CWT, the vibration signal is decomposed into 2D time-frequency grayscale images, with a filter bank of ten voices per octave in the frequency band of interest. Three 2D-CNN-based models trained on the CWT-based representation of the vibration signals measured on individual accelerometer axes (<i>X</i>, <i>Y</i>, and <i>Z</i>) are proposed to detect the four health states (one normal and three faulty) of the helical gearbox, regardless of the selected load level or speed on the test rig. …”
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Unsteady Aerodynamic Modeling Based on POD-ARX by Xiaopeng Wang, Chen’an Zhang, Wen Liu, Famin Wang, Zhengyin Ye

“…In addition, this method also shows good wide-band characteristics by using the “3211” multistep signal as the training signal.…”
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Predicting and synthesizing terahertz spoof surface plasmon polariton devices with a convolutional neural network model by Vahid Najafy, Bijan Abbasi-Arand, Maryam Hesari-Shermeh

“…Three examples are provided for inversely designing several sensor devices and absorbers in the terahertz band using the proposed CNN and the genetic optimization algorithm.…”
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Lighting Spectrum Optimization With Deep Learning for Moss Species Classification by Kenichi Ito, Pauli Falt, Markku Hauta-Kasari, Shigeki Nakauchi

“…Hence, we propose a method for obtaining spectral information on moss in the forest using a deep learning model to train convolutional neural network models while optimizing a suitable light source for moss identification. …”
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SVDD: SAR Vehicle Dataset Construction and Detection by Dan Gao, Xiaofang Wu, Zhijin Wen, Yue Xu, Zhengchao Chen

“…First, we constructed a multi-band SAR vehicle detection dataset (SVDD) with annotations as the training dataset of the object detection model. …”
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Short-term load forecasting based on multi-frequency sequence feature analysis and multi-point modified FEDformer by Kaiyuan Hou, Xiaotian Zhang, Junjie Yang, Jiyun Hu, Guangzhi Yao, Jiannan Zhang

“…Subsequently, for each frequency band of the load sequence, the LightGBM algorithm quantifies the correlation between the load and various influencing factors. …”
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Precision Imaging for Early Detection of Esophageal Cancer by Po-Chun Yang, Chien-Wei Huang, Riya Karmakar, Arvind Mukundan, Tsung-Hsien Chen, Chu-Kuang Chou, Kai-Yao Yang, Hsiang-Chen Wang

“…The dataset was divided into two subsets: RGB-WLIs and NBIs, and four distinct models were trained using these datasets. The experimental results revealed that the prediction performance of the training model was notably enhanced when using HSI compared to general NBI training. …”
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A Lightweight Human Activity Recognition Method for Ultra-wideband Radar Based on Spatiotemporal Features of Point Clouds by Yongkun SONG, Tianxing YAN, Ke ZHANG, Xian LIU, Yongpeng DAI, Tian JIN

“…Low-frequency Ultra-WideBand (UWB) radar offers significant advantages in the field of human activity recognition owing to its excellent penetration and resolution. …”
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Intelligent Turning Tool Monitoring with Neural Network Adaptive Learning by Maohua Du, Peixin Wang, Junhua Wang, Zheng Cheng, Shensong Wang

“…The results show that the correct recognition rate of BP network model after samples training is 92.59%, which can more accurately and intelligently monitor the tool wear state.…”
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Dynamic Functional Ability in Lacrosse Players in Relation to Development of Sport-Related Onset of Musculoskeletal Pain by Zane Thompson, Joseph G. Wasser, Kevin R. Vincent, Heather K. Vincent

“…Thomas test (hip flexibility), Ober's test (iliotibial band tightness), and Ely's test (rectus femoris tightness) were performed. …”
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Multi-Temporal Image Fusion-Based Shallow-Water Bathymetry Inversion Method Using Active and Passive Satellite Remote Sensing Data by Jie Li, Zhipeng Dong, Lubin Chen, Qiuhua Tang, Jiaoyu Hao, Yujie Zhang

“…A backpropagation (BP) neural network model is then used to incorporate the initial multispectral information of Sentinel-2 data at each bathymetric point and its surrounding area during the training process. Bathymetric maps of the study areas are generated based on the trained model. …”
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Portal Hypertensive Polyps as Gastroscopic Finding in Liver Cirrhosis by Firdevs Topal, Sabiye Akbulut, Cengiz Karahanlı, Süleyman Günay, Elif Sarıtaş Yüksel, Fatih Esad Topal

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Generalisation of EEG-Based Pain Biomarker Classification for Predicting Central Neuropathic Pain in Subacute Spinal Cord Injury by Keri Anderson, Sebastian Stein, Ho Suen, Mariel Purcell, Maurizio Belci, Euan McCaughey, Ronali McLean, Aye Khine, Aleksandra Vuckovic

“…EEG features were extracted based on either band power or Higuchi fractal dimension (HFD). Three levels of generalisability were tested: (1) classification PDP vs. …”
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Application of Machine Learning Techniques to Distinguish between Mare, Cryptomare, and Light Plains in Central Lunar South Pole−Aitken Basin by Frank C. Chuang, Matthew D. Richardson, Jennifer L. Whitten, Daniel P. Moriarty, Deborah L. Domingue

“…From the training area values, the MLC unit map showed a distinction between the two prior indistinguishable K-Means units. …”
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Exploring Machine Learning Classification of Movement Phases in Hemiparetic Stroke Patients: A Controlled EEG-tDCS Study by Rishishankar E. Suresh, M S Zobaer, Matthew J. Triano, Brian F. Saway, Parneet Grewal, Nathan C. Rowland

“…Data preprocessing included z-score normalization and frequency band power binning. Results: In chronic stroke participants who received active tDCS, the classification accuracy for hold vs. reach phases increased from pre-stimulation to the late intra-stimulation period (72.2% to 75.2%, <i>p</i> < 0.0001). …”
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The role of partial splenic artery embolization in the management of refractory esophageal variceal bleeding due to portal vein thrombosis by Büşra Tetik Dinçer, Nafiye Urgancı, Aylin Hasanefendioğlu Bayrak, Özlem Durmaz, İlgin Özden

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