Deep learning-driven approach for cataract management: towards precise identification and predictive analytics by Shuaixin Lu, Lingling Ba, Jie Wang, Min Zhou, Peiyao Huang, Xiaohua Zhang, Simo Pan, Xinmiao Zhou, Kai Wen, Jing Sun

“…Deep learning (DL) technology has shown significant potential in the whole process of cataract diagnosis and treatment through algorithms such as convolutional neural network (CNN). …”
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Bayesian adaptation in Poisson cognitive systems by Aleksander A. Solodov

“…In particular, to describe the stochastic properties of cognitive systems and the possibility of creating an optimal algorithm, the Bayesian approach recognized in a number of philosophical works is applied.The optimal estimate by the criterion of the minimum standard error is, as is known, a posteriori mathematical expectation of a random estimated value, which is applied in this work. …”
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Energy Efficiency Maximization through Cooperative Transmit and Receive Antenna Selection for Multicell MU-MIMO System by Yanjie Dong, Yinghai Zhang, Weidong Wang, Gaofeng Cui, Yang Yu

“…With this function, we can transform the whole system optimization problem to a sectional optimization problem and obtain a suboptimal antenna set using a heuristic algorithm. …”
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Configuring adaptive PID-controllers of the automatic speed control system of the GTE by K. E. Chertilin, V. D. Ivchenko

“…This is conditioned by two factors: the complexity of solving the problem as a whole and the presence of a large number of technically diverse situations that need to be adapted and optimized. …”
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A LIFE EVALUATION METHED FOR FRONT AXLE BASED ON FRONT AXLE DYNAMICS MODEL by FENG Jinzhi, SANG Wuzhuang, ZHANG Dongdong, LI Liangliang, LIU Xinrong, ZHAO Lihui

“…Then, with the goal of minimizing the difference between the damage/life of the front axle and the reference value under each working condition, the adjustment coefficient of the amplitude of the three-way forces at the wheel center was optimized by combining the response surface method and genetic algorithm. …”
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Modeling the Stability of the Housing and Construction Complex Based on Organizational and Economic Interaction of Entities by N. N. Shelomentseva, O. V. Grushina

“…A genetic algorithm in MATLAB was used for this purpose. Acceptable options for all participants were selected from a set of Pareto-optimal alternatives based on the preferences of the decision-maker. …”
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Development and Practice of Cloud Collaborative Platform for Downhole Measurement Tools by Che Yang, Yuan Guangjie, Qian Hongyu, Du Weiqiang, Wang Chenlong, Ding Jiping

“…In the paper， based on the remote operation requirements of coreless magnetic steering tool， a platform architecture of five modules， including simulation rehearsal， virtual training， remote operation， smart tool and intelligent decision， was designed in detail， achieving a whole process digitization from predrilling risk assessment and in-drilling acquisition and processing to post-drilling feedback and optimization， and a visual interface was developed. …”
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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…On the whole, the accuracy rate of 93% is achieved in defect detection of test sets.…”
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Software pipeline for predicting and analyzing the structure of the receptor–ligand by A.S. Kozlova, A.R. Mukhametgalieva, A.N. Fattakhova, N.I. Akberova

“…Possible interactions of the receptor–ligand complex are studied based on certain parameters: the energy of the affinity of the ligand for the receptor; the length and energy of the bond between the receptor and the ligand, both in the whole complex and between individual atoms. All characteristics can be automatically calculated by default under the specified optimal parameters. …”
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Advanced machine learning techniques reveal multidimensional EEG abnormalities in children with ADHD: a framework for automatic diagnosis by Ying Mao, Ying Mao, Xuchen Qi, Xuchen Qi, Xuchen Qi, Lingyan He, Shan Wang, Zhaowei Wang, Fang Wang, Fang Wang

“…Then, four widely-employed machine learning algorithms (including random forest (RF), XGBoost, CatBoost, and LightGBM) were used for classification calculations, and the SHAP algorithm was then used to assess the importance of the contributing features to interpret the model’s decision process.ResultsThe results showed that the highest classification accuracy of 99.58% for pediatric ADHD detection was obtained with the CatBoost model based on the optimal feature subset of 206 features (PSD/FuzEn/MI = 53/5/148). …”
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Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL by Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang

“…This paper uses Xilinx SDAccel to realize the parallel acceleration of CNN task, and it also proposes an optimizing strategy of single convolutional layer to accelerate CNN. …”
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Research on Energy-Saving Control Strategy of Nonlinear Thermal Management System for Electric Tractor Power Battery Under Plowing Conditions by Xiaoshuang Guo, Ruiliang Xu, Junjiang Zhang, Xianghai Yan, Mengnan Liu, Mingyue Shi

“…Finally, a nonlinear model predictive control cooling optimization strategy is proposed, with the optimization objectives of quickly achieving battery temperature regulation and reducing compressor energy consumption. …”
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Phase Diagram of Extensive-Rank Symmetric Matrix Denoising beyond Rotational Invariance by Jean Barbier, Francesco Camilli, Justin Ko, Koki Okajima

“…In this case, the information-theoretic limits and an efficient Bayes-optimal denoising algorithm, called the rotational invariant estimator, are known. …”
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Identification and application of shale lithofacies based on conventional logging curves: A case study of the second member of Funing Formation in Qintong Sag, Subei Basin by WANG Xinqian, YU Wenduan, MA Xiaodong, ZHOU Tao, TAI Hao, CUI Qinyu, DENG Kong, LU Yongchao, LIU Zhanhong

“…Additionally, a BP neural network method optimized by the ASO（Atom Search Optimization） algorithm was utilized to perform data mining on logging information. …”
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Design, modeling and manufacture error identification of a new 6-degree-of-freedom (6-DOF) compliant parallel manipulator by H. Li, W. Chen, L. Yi, C. Leng, H. Wu

“…The Levenberg–Marquardt optimization algorithm is utilized to solve the identification model, with the results verified through finite-element analysis. …”
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Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach. by Josh L Espinoza, Chris L Dupont, Aubrie O'Rourke, Sinem Beyhan, Pavel Morales, Amy Spoering, Kirsten J Meyer, Agnes P Chan, Yongwook Choi, William C Nierman, Kim Lewis, Karen E Nelson

“…Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. …”
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Neural network for prediction solar radiation in Relizane region (Algeria) - Analysis study by Dahmani Abdennasser, Yamina Ammi, Salah Hanini

“…The inputs used in the neural network are: time (h), day, month, year, temperature (k), relative humidity (%), pressure (mbar), wind speed (m/s), wind direction (°), and rainfall (kg/m2). The neural network-optimal model was trained and tested using 80 %, and 20 % of whole data, respectively. …”
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Congenital Melanocytic Nevus of the Nose: Clinical Experience and Reconstructive Approaches by Alexander Margulis, MD, Allan Billig, MD, Neta Adler, MD

“…The authors developed a treatment algorithm with the aim of offering an optimal surgical management plan. …”
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Probabilistic alignment of multiple networks by Teresa Lázaro, Roger Guimerà, Marta Sales-Pardo

“…Our approach opens the door to a whole new family of network alignment algorithms, and to their application to problems for which existing methods are perhaps inappropriate.…”
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Impacts of inter-train distances on aerodynamic drag reduction in heavy-haul train groups by LYU Jun, XIANG Tao, SONG Zongying, GAO Guangjun

“…Comparisons at different inter-train distances showed that the drag reduction effect was minimal at distances greater than 700 meters, while no significant improvement in drag reduction effect was observed at distances less than 200 meters. In summary, optimization of aerodynamic characteristics for trailing trains in group operation occurs at spacings of less than 700 meters, achieving the optimal drag reduction effect when the spacing is reduced to 200 meters.…”
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