Charting γ-secretase substrates by explainable AI by Stephan Breimann, Frits Kamp, Gabriele Basset, Claudia Abou-Ajram, Gökhan Güner, Kanta Yanagida, Masayasu Okochi, Stephan A. Müller, Stefan F. Lichtenthaler, Dieter Langosch, Dmitrij Frishman, Harald Steiner

“…Using machine learning, we predict the entire human γ-secretase substrate scope, revealing numerous previously unknown substrates. …”
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Deep learning for automated segmentation of radiation-induced changes in cerebral arteriovenous malformations following radiosurgery by Hsing-Hao Ho, Huai-Che Yang, Wen-Xiang Yang, Cheng-Chia Lee, Hsiu-Mei Wu, I-Chun Lai, Ching-Jen Chen, Syu-Jyun Peng

“…The algorithm could be used to predict the course of RICs and facilitate clinical management. …”
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Current Status and Future Potential of Machine Learning in Diagnostic Imaging of Endometriosis : A Literature Review by Palpasa Shrestha, Bibek Shrestha, Jati Shrestha, Jun Chen

“…The machine learning algorithm first computes the image characteristics deemed significant for making predictions or diagnoses about unseen images. …”
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Staring Imaging Real-Time Optimal Control Based on Neural Network by Peiyun Li, Yunfeng Dong, Hongjue Li

“…In this paper, a real-time optimal attitude controller is designed for staring imaging, and the output command is based on future prediction. First, the mathematical model of staring imaging is established. …”
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Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains by Marco Vecchiato, Nicola Borasio, Emiliano Scettri, Vanessa Franzoi, Federica Duregon, Sandro Savino, Andrea Ermolao, Daniel Neunhaeuserer

“…MOVE demonstrated superior accuracy, offering personalized hiking time predictions based on user-specific data and trail characteristics. …”
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SMART PLATFORM FOR SUPPORT ISSUES AT THE FIRST AND LAST MILE IN THE SUPPLY CHAIN - THE CONCEPT OF THE S-MILE PROJECT by Marcin STANIEK, Grzegorz SIERPIŃSKI

“…In addition to the basic functions of a fleet management tool, the educative approach towards environmentally friendly behaviour will be based on promoting ecological solutions, such as unconventionally powered cars, e.g., electric vehicles (EVs). …”
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LTL-Specification of Counter Machines by Egor V. Kuzmin

“…It is known that any algorithm (hypothetically) can be implemented in the form of a Minsky three-counter machine.…”
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Autism in the Faroe Islands: Diagnostic Stability from Childhood to Early Adult Life by Eva Kočovská, Eva Billstedt, Asa Ellefsen, Hanna Kampmann, I. Carina Gillberg, Rannvá Biskupstø, Guðrið Andorsdóttir, Tormóður Stóra, Helen Minnis, Christopher Gillberg

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Empirical Assessment of AI-Powered Tools for Vocabulary Acquisition in EFL Instruction by Yiyun Wang, Jin Wu, Fang Chen, Zhu Wang, Jingjing Li, Liping Wang

“…The findings and conclusions of this study provide valuable insights for EFL educational practice and demonstrate the potential of AI in boosting the effectiveness of language learning, offering empirical support and guidance for future educational decision-making.…”
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Physics-informed modeling and process optimization of friction stir welding of AA7075-T6 with a zinc interlayer by Dejene Alemayehu Ifa, Dame Alemayehu Efa, Naol Dessalegn Dejene, Sololo Kebede Nemomsa

“…The models that are included in the hybrid framework of ANN, SVR, and RFR have all demonstrated noteworthy prediction strengths. The optimum FSW parameters were shown to be: a tool speed of 600 rpm, a pin radius of 5.71 mm, a shoulder radius of 20 mm, and a plunge force of 6369.48 N, with a predicted peak temperature value of 675.71 K. …”
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Multiple Regression-Based Dynamic Amplification Factor Investigation of Monorail Tourism Transit Systems by Hong Zhang, Changxing Wu, Wenlong Liu, Shiqi Wei, Yonggang Wang

“…On this basis, the key regression parameters were selected by using the Pearson correlation coefficient method and the random forest algorithm, and the DAFs prediction model was constructed based on the least absolute shrinkage and selection operator (LASSO) regression theory. …”
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Application of Artificial Intelligence in Tinnitus Diagnosis and Treatment: A Pilot Study by Yu Wang, Kaixiang Pan, Richard Tyler, Zhaoyi Lu, Shan Xiong, Yufei Xie, Tao Pan

“…We describe the curation of the input data, the algorithm (CTGan) used to extend the dataset, and the ML model (Random Forest) to predict each of the suggested treatments. …”
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Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping by Yong Dai, Ming Zhao

“…In addition, we propose an adaptive local data association (Range-SLAM) scheme to improve the computational efficiency for the algorithm of the nearest neighbor (NN) data association in the iteration of the RBPF prediction. …”
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In Situ Stress Inversion and Distribution Characteristics of Tunnel Based on Numerical Simulation and Neural Network Technology by Pei Zhang

“…The neural network optimized by genetic algorithm is used to establish the nonlinear relationship between the measured value and the simulated value of the variable boundary condition, and the optimal boundary condition function is obtained. …”
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Channel modeling of molecular communication via free diffusion with multiple receiver by Zhuo SUN, Xu BAO, Jie LIN, Wence ZHANG

“…A coexistence scenario with a point source, a pair of absorbing and transparent receiver was considered, an interference factor was introduced in the proposed channel model based on the receiving molecular probability in the transparent receiver considering the influences of the absorbing receiver on the transparent one.Furthermore, the channel model of point source and transparent receiver had been proposed by using Levenberg-Marquardt algorithm combined with artificial neural network to study and predict channel model parameters.The simulation results not only verify the effectiveness of the proposed channel model, but also show that the peak time of any point in the environment is directly proportional to the square of the distance from the point source to the receiver, and inversely proportional to the molecular diffusion coefficient, and the peak time is not affected by the absorbing receiver in the environment.…”
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Joint optimization of edge computing and caching in NDN by Yu ZHANG, Min CHENG

“…Named data networking (NDN) is architecturally easier to integrate with edge computing as its routing is based on content names and its nodes have caching capabilities.Firstly, an integrated framework was proposed for implementing dynamic coordination of networking, computing and caching in NDN.Then, considering the variability of content popularity in different regions, a matrix factorization-based algorithm was proposed to predict local content popularity, and deep reinforcement learning was used to solve the the problem of joint optimization for computing and caching resource allocation and cache placement policy with the goal of maximizing system operating profit.Finally, the simulation environment was built in ndnSIM.The simulation results show that the proposed scheme has significant advantages in improving cache hit rate, reducing the average delay and the load on the remote servers.…”
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Efficient signcryption scheme based on Cocks’ identity cryptosystem by Changgen PENG, Xiaoyu ZHANG, Hongfa DING, Shanhui YANG

“…Most of the existing identity-based signcryption schemes are based on bilinear or multilinear pairing operations construction.To solve the problem of low efficiency caused by complex pair operation, a new efficient signcryption scheme based on the identity cryptosystem of Cocks was proposed.Firstly, the security model of the proposed scheme was formalized, and the definition of confidentiality and unforgeability was given.Secondly, the quadratic residue problem was used to realize the concrete construction of the proposed scheme, and the signature algorithm was designed in a logical step by combining Jacobi symbol operation.Finally, the security proofed that the scheme satisfied the confidentiality and unforgeability was given under the random prediction model.The efficiency analysis shows that compared with the existing identity-based signcryption scheme, the proposed scheme greatly improves the computing efficiency and has good characteristics of identity-based cryptosystem.…”
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Complexity control method of random forest based HEVC by Peng WEN, Zongju PENG, Fen CHEN, Gangyi JIANG, Mei YU

“…High efficiency video coding (HEVC) has high computational complexity,and fast algorithm cannot perform video coding under restricted coding time.Therefore,a complexity control method of HEVC based on random forest was proposed.Firstly,three random forest classifiers with different prediction accuracy were trained to provide various coding configurations for coding tree unit (CTU).Then,an average depth-complexity model was built to allocate CTU complexity.Finally,the CTU coding configuration,determined by the smoothness,average depth,bit,and CTU-level accumulated coding error,was used to complete complexity control.The experimental results show that the proposed method has better complexity control precision,and outperforms the state-of-the-art method in terms of video quality.…”
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基于改进Kriging模型的主动学习可靠性分析方法 by 陈哲, 杨旭锋, 程鑫

“…,the differential evolution algorithm is introduced to explore the optimal parameter of Kriging model and improve the accuracy of Kriging prediction information.As a result,the training point in each iteration is guaranteed to be the global optimal one and the efficiency of ALK model is largely improved.…”
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Image colorization based on transformer by Min Xu

“…To ensure the generated image mimics a real-life image in terms of pixel accuracy and visual quality, the algorithm employs a variety of loss functions. Experimental results demonstrate significant performance improvements in black and white image colorization. …”
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