RETRACTED: A flight control method for unmanned aerial vehicles based on vibration suppression by Xinhua Wang, Xiulin Zhang, Huajun Gong, Ju Jiang, Hari Mohan Rai

“…In order to study the effect of structural deformation on the reliability and safety of UAVs under normal flight conditions, a certain type of UAV as a research object is discussed and the augmented tracking model based on the original object system by using the Lyapunov function is built up. The performance is observed in terms of rise time and overshoot and it is observed from the simulation outcomes that the system is stable at all design points in the range of 0–9000 m, providing a rise time of 10 s and zero overshoot. …”
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Enhanced Stability and Control of Solar Powered EV Charging Stations Using Disturbance Observer-Based Adaptive Sliding Mode Control for DC Voltage Stabilization by Surabhi Bagherwal, Subhasish Mahapatra

“…The stability of the proposed control system is determined using the Lyapunov candidate function. The robustness of the controller is validated by comparing it to traditional control strategies like PID, Lyapunov and sliding mode controllers. …”
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Detection of Maize Pathogenic Fungal Spores Based on Deep Learning by Yijie Ren, Ying Xu, Huilin Tian, Qian Zhang, Mingxiu Yang, Rongsheng Zhu, Dawei Xin, Qingshan Chen, Qiaorong Wei, Shuang Song

“…Finally, MPDIoU loss function was applied to refine the localization performance of bounding boxes. …”
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Enhanced mixup for improved time series analysis by Khoa Tho Anh Nguyen, Khoa Nguyen, Taehong Kim, Ngoc Hong Tran, Vinh Dinh

“…This adaptation involves mixing samples while aiming to maintain the data's temporal structure and integrating target contributions into the loss function. Empirical studies show that EMixup improves the performance of time series models across various architectures (improving 23/24 forecasting cases and 12/24 classification cases). …”
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DEVELOPMENT AND RESEARCH OF A NOVEL DNC SYSTEM FOR REMOTE MONITORING OF THE MACHINE TOOLS WITH FANUC NC SYSTEM by YAO Peng, LI NanNan, CAO ZhiJun, LI HeLin, XING JunWei, LIU GuoNing

“…A novel DNC（distributed numerical control） system,which is used to remotely monitor CNC machine tools of FANUC NC system as well as inspection equipment or devices,has been developed based on Socket communication and multithread technology by using SQL Server database and.NET platform.This DNC system can collect the real time information of CNC machines and inspection equipment or devices,and has the functions like the machine state monitoring,data integration and management,performance analysis,fault remote diagnosis,workshop production management,and product quality management and control.In this way,the data integrity and integration has been realized.The architecture of the system is presented and the approaches to the realization of the function modules are elaborated.The data flow,data interpretation and alarm monitoring mechanism are also discussed.This system has been applied in manufacturing plants and performs well.…”
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Deep neural networks have an inbuilt Occam’s razor by Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

“…This analysis shows that structured data, together with a specific Occam’s razor-like inductive bias towards (Kolmogorov) simple functions that exactly counteracts the exponential growth of the number of functions with complexity, is a key to the success of DNNs.…”
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Integrating Neuroscience and Pedagogical Practices to enhance University Learning by Claudio O. Cervino

“…The effectiveness of Neuroeducation is supported by studies highlighting methods like collaborative learning and constructive feedback, which positively influence academic performance. …”
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Improved throughput of Elliptic Curve Digital Signature Algorithm (ECDSA) processor implementation over Koblitz curve k-163 on Field Programmable Gate Array (FPGA) by Firas Ghanim Tawfeeq, Alaa M. Abdul-Hadi

“…The widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. …”
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Data-driven prediction of cardiovascular and cerebrovascular diseases in a nationwide study by Sehyun Kim, Beomsang Ryu, Mingee Choi, Sangyon Lee, Jaeyong Shin, Sok Chul Hong

“…Models based on logistic regression analysis with penalty terms on the objective function were used, and their predictive performances were compared using multiple evaluation metrics, including the area under the receiver operating characteristic curve. …”
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A deep multiple self-supervised clustering model based on autoencoder networks by Ling Zhu, Zijin Liu, Guangyu Liu

“…It leverages a gradient-like approach for data reconstruction, enabling the autoencoder to learn features more conducive to clustering, thereby enhancing clustering performance. …”
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Glycated hemoglobin levels and geriatric depression impact cognitive status in an Indian urban elderly community by Bhaktee Dongaonkar, Arman Deep Singh, Swathi B. Hurakadli, Ashwini Godbole

“…HbA1c levels correlated inversely with processing speed and executive function. Vitamin B12 levels did not correlate with performance on any cognitive test. …”
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AMAY-Net: adaptive multi-scale attention YOLO network for liver and gallbladder segmentation in laparoscopic cholecystectomy by Yuyang Zhou, Yulai You, Xiaokai Tan, Juncheng Tang

“…Building upon the powerful feature extraction capabilities of You Only Look Once (YOLO), AMAY-Net incorporates several advanced modules to enhance performance in medical image segmentation tasks. First, a multi-scale feature extraction module is employed to capture anatomical structures of various sizes, ensuring effective detection of large organs like the liver and smaller structures such as the gallbladder and surgical instruments. …”
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Nursing Value Analysis and Risk Assessment of Acute Gastrointestinal Bleeding Using Multiagent Reinforcement Learning Algorithm by Fang Liu, Xiaoli Liu, Changyou Yin, Hongrong Wang

“…The performance metrics like classification accuracy, area under the receiver-operating characteristic curve (AUROC), area under the curve (AUC), sensitivity, specificity, and precision are analyzed and compared with the traditional approaches. …”
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Comparative Study of Person Re-Identification Techniques Based on Deep Learning Models by Mossaab Idrissi Alami, Abderrahmane Ez-zahout, Fouzia Omary

“…This study explores deep metric learning models, specifically Siamese and Triplet networks, to improve Re-ID performance. We evaluate these methods on the Market-1501 dataset using Cumulative Matching Characteristic (CMC) and Cumulative Distribution Function (CDF) curves. …”
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Time-restricted eating in early-stage Huntington's disease: A 12-week interventional clinical trial protocol. by Russell G Wells, Lee E Neilson, Andrew W McHill, Amie L Hiller

“…Recent research indicates that time-restricted eating (TRE), a type of intermittent fasting where caloric intake is confined to a specific time window each day, may be beneficial in treating neurodegenerative diseases like HD. TRE has been found to enhance mitochondrial function, stimulate autophagy, lower oxidative stress, and improve cognitive performance. …”
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Sparse Regularization With Reverse Sorted Sum of Squares via an Unrolled Difference-of-Convex Approach by Takayuki Sasaki, Kazuya Hayase, Masaki Kitahara, Shunsuke Ono

“…Traditional sparse regularization functions, such as <inline-formula><tex-math notation="LaTeX">$L_{1}$</tex-math></inline-formula>-norm, suffer from problems like amplitude underestimation and vanishing perturbations. …”
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Chronic circadian disruption in adolescent mice impairs hippocampal memory disrupting gene expression oscillations by Ines Gallego-Landin, Paula Berbegal-Sáez, Olga Valverde

“…Here, we induced chronic chronodisruption in adolescent mice through light/dark cycle manipulation. We performed a battery of established behavioral tests alongside an analysis of daily rhythms of expression of genes involved in relevant physiological functions. …”
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An Interpretable Machine Learning-Based Hurdle Model for Zero-Inflated Road Crash Frequency Data Analysis: Real-World Assessment and Validation by Moataz Bellah Ben Khedher, Dukgeun Yun

“…The first stage uses binary classification to identify road segments with potential crash occurrences, applying a customized loss function to tackle data imbalance. The second stage predicts crash frequency, also utilizing a customized loss function for count data. …”
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Enhanced DDPG algorithm for latency and energy-efficient task scheduling in MEC systems by Fei Zhou, Lihong Zhao, Xiaomei Ding, Shuqin Wang

“…Experimental results demonstrate that the nonlinear reward function achieves faster convergence and better system performance. …”
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Human and environmental feature-driven neural network for path-constrained robot navigation using deep reinforcement learning by Nabih Pico, Estrella Montero, Alisher Amirbek, Eugene Auh, Jeongmin Jeon, Manuel S. Alvarez-Alvarado, Babar Jamil, Redhwan Algabri, Hyungpil Moon

“…Additionally, common metrics like success rate, collision avoidance, time to reach the goal, and new comprehensive log information are included to provide an overview of the robot’s performance. …”
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