Crucial heat damage analysis and optimization of a mid-sized pickup truck based on a deep Gaussian process model by Zebin Zhang, Sisi Liu, Xianzong Meng, Tingting Wang, Shizhao Jing, Chuanrui Wang, Dongchen Qin

“…Based on simulation results, a multi-objective two-layer deep Gaussian process model predicted heat source temperatures. The positions of cooling components were optimized using a genetic algorithm with heat-sensitive locations as the objectives. …”
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A smart energy management system for surface unmanned vehicles for border surveillance missions by João F. P. Fernandes, Mário Assunção, Daniel Serrano, Pedro Afonso, Pedro Pinheiro, Hugo Marques, José Neves, Pedro Teodoro, Ricardo Póvoa, Rosa Marat-Mendes, P. J. Costa Branco

“…The developed SEMS is capable of planning a mission profile based on the predicted environmental conditions. To achieve this, one presents a new A-star algorithm with probabilistic behaviour to avoid local minimums and find alternative paths that would reduce the energy consumption in later hours of the mission. …”
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On differential privacy for federated learning in wireless systems with multiple base stations by Nima Tavangaran, Mingzhe Chen, Zhaohui Yang, José Mairton B. Da Silva Jr., H. Vincent Poor

“…The simulation results show that our proposed scheduler improves the average accuracy of the predictions compared with a random scheduler. In particular, the results show an improvement of over 6%. …”
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A zenith wet delay improved model in China based on GPT3 and random forest by Shaoni Chen, Chunhua Jiang, Xiang Gao, Huizhong Zhu, Shuaimin Wang, Guangsheng Liu

“…To more accurately capture and predict complicated variations in ZWD, this paper developed the CRZWD model by a combination of the GPT3 model and random forests (RF) algorithm using 5-year atmospheric profiles from 70 radiosonde (RS) stations across China. …”
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Continuous Real-Time Acoustic Monitoring of endangered bird species in Hawai‘i by Melissa Weidlich-Rau, Amanda K. Navine, Patrick T. Chaopricha, Felix Günther, Stefan Kahl, Thomas Wilhelm-Stein, Raymond C. Mack, Hendrik Reers, Aaron N. Rice, Maximilian Eibl, Patrick J. Hart, Patrick Wolff, Holger Klinck, Lena D. Schnell, Rogelio Doratt, Michael Loquet, Tiana Lackey

“…A novel web application allows immediate visualization of the predicted bird species, facilitating the implementation of conservation measures. …”
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Modeling the Influence of Disturbances in High-Speed Railway Systems by Ping Huang, Chao Wen, Qiyuan Peng, Chaozhe Jiang, Yuxiang Yang, Zhuan Fu

“…Specifically, the validation results show that the proposed models accurately revealed the characteristics of HSTD and that these models can be used in real-time dispatch to predict the NAT and TDT, once the basic features of disturbances are known.…”
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Improving spatiotemporal data fusion method in multiband images by distributing variates by Yihua Jin, Zhenhao Yin, Weihong Zhu, Dongkun Lee

“…Compared to existing methods, RDSFM offers several key advantages: (1) It accurately predicts seasonal variations in bands such as red and NIR, (2) It effectively handles heterogeneous landscapes and shifting land cover, and (3) It requires only one high-resolution reference image as input, minimizing data requirements. …”
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Identification of potential accident concentrations due to traffic violations by drivers, taking into account the human factor by I. E. Ilyina, E. E. Vitvitsky, K. A. Perekusikhina, V. I. Rassokha

“…The theoretical significance of the work lies in verifying the operability of the proposed algorithm for determining potential concentrations of accidents due to violations of traffic rules by the driver, taking into account the parameters of the human factor, which is also of practical interest from the point of view of predicting accident rates and developing scientifically based measures to improve road safety. …”
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Advanced Control Technique for Optimal Power Management of a Prosumer-Centric Residential Microgrid by Peter Anuoluwapo Gbadega, Yanxia Sun, Olufunke Abolaji Balogun

“…To solve the multi-objective power management optimization problem, the Teaching-Learning-Based Optimization (TLBO) algorithm was implemented. This algorithm optimizes day-ahead power scheduling by considering temperature forecasts, energy prices, solar irradiance, system constraints, and user preferences. …”
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Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification by Heba G. Mohamed, Fadwa Alrowais, Fahd N. Al-Wesabi, Mesfer Al Duhayyim, Anwer Mustafa Hilal, Abdelwahed Motwakel

“…One of the key benefits of the healthcare system is the ability to predict diseases early. Recently, the progress of artificial intelligence (AI) in the healthcare system has been a high priority. …”
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Performance Analysis of Superposition M-ary QAM Modulation in Coded Protograph LDPC MIMO Communication Systems With Low-Resolution ADCs by Duc A. Hoang, Hieu T. Nguyen, Thang N. Le

“…This modified PEXIT accurately predicts the iterative decoding thresholds under varying antenna dimensions, ADC resolutions, and superposition weighting schemes, thus facilitating a systematic code and modulation design process. …”
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An ImmunoSignature test distinguishes Trypanosoma cruzi, hepatitis B, hepatitis C and West Nile virus seropositivity among asymptomatic blood donors. by Michael Rowe, Jonathan Melnick, Robert Gerwien, Joseph B Legutki, Jessica Pfeilsticker, Theodore M Tarasow, Kathryn F Sykes

“…As a binary test, the accuracy of predicting T. cruzi seropositivity by IST was similar, perhaps modestly reduced, relative to conventional ELISAs. …”
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Aerodynamic model identification of supersonic aircraft using Bayesian approach-based Box–Jenkins structure by Muhammad Fawad Mazhar, Muhammad Wasim, Manzar Abbas, Imran Shafi, Jamshed Riaz, Tae-hoon Kim, Imran Ashraf

“…Results show good agreement between model predictions and simulated flight data with an accuracy of 82.42%. …”
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Factors associated with engagement in HIV care for young people living with perinatally acquired HIV in England: An exploratory observational cohort study. by Marthe Le Prevost, Ali Judd, Siobhan Crichton, Caroline Foster, Alasdair Bamford, Deborah Ford, Adolescents; Adults Living with Perinatal HIV (AALPHI) Steering Committee

“…We applied it to data from young people with PHIV in the Adolescents and Adults Living with Perinatal HIV (AALPHI) cohort. The algorithm predicts the timing of the next scheduled clinic visit, within 1-6 months of current visit, based on routine clinical data. …”
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Selection of features for modeling the risk of fatal outcomes in patients after myocardial infarction or unstable angina by D. A. Shvets, S. V. Povetkin

“…There were 8 following most significant parameters for predicting a fatal outcome according to machine selection results: age, LVEF, BSA, creatinine level, systolic blood pressure, HF, comorbidity, nosological unit.…”
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Coupled Elastic–Plastic Damage Modeling of Rock Based on Irreversible Thermodynamics by Xin Jin, Yufei Ding, Keke Qiao, Jiamin Wang, Cheng Fang, Ruihan Hu

“…This proves that the model can effectively predict the failure behavior of shale under different confining pressures and bedding angles. …”
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The neutrophil extracellular trap-related gene FPR1 (formyl peptide receptor 1) as a potential prognostic and therapeutic target in osteosarcoma by Shihao Li, Qiong Yuan, Yuanyuan Zhang, Haiyang Zhang

“…Results A signature NET score, comprising four NET-related genes (TNFRSF10C, FPR1, BST1 and SELPLG), was constructed to predict the prognosis of OS. The survival outcomes for patients in high-NET score group were markedly worse than that in the low-NET score group. …”
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GNSS-RTK-Based Navigation with Real-Time Obstacle Avoidance for Low-Speed Micro Electric Vehicles by Nuksit Noomwongs, Kanin Kiataramgul, Sunhapos Chantranuwathana, Gridsada Phanomchoeng

“…The system employs a scored predicted trajectory algorithm that simultaneously optimizes path-following accuracy and obstacle evasion. …”
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Multi-scale adversarial diffusion network for image super-resolution by Yanli Shi, Xianhe Zhang, Yi Jia, Jinxing Zhao

“…This ensures that the predicted images exhibit more realistic texture details. …”
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Automated recognition and segmentation of lung cancer cytological images based on deep learning. by Qingyang Wang, Yazhi Luo, Ying Zhao, Shuhao Wang, Yiru Niu, Jinxi Di, Jia Guo, Guorong Lan, Lei Yang, Yu Shan Mao, Yuan Tu, Dingrong Zhong, Pei Zhang

“…In addition, the model was deemed suitable for diagnosing pleural fluid cytology and bronchoalveolar lavage fluid cytology images. The model predictions were strongly correlated with pathologist diagnoses and the gold standard, indicating the model's ability to make clinical-level decisions during initial diagnosis. …”
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