Damage Recovery Method for Air–Sea Cross-Domain Communication Network Based on Improved Dijkstra and Load Balancing by Zhigang Shang, Hongyu Zhang, Jing Yang

“…This paper proposes a link selection strategy based on an improved Dijkstra algorithm and load balancing on the basis of link quality prediction. …”
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Using Machine Learning to Shorten and Adapt Fall Risk Assessments for Older Adults by Lilyana Khatib, Adi Toledano-Shubi, Hilla Sarig Bahat, Hagit Hel-Or

“…The adaptive approach reduces task sequences by over 50% while maintaining high predictive accuracy. It also enables remote testing, predicting performance on complex tasks using as few as 2–3 simpler, accessible tasks. …”
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Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs by Hatem Gasmi, Azher M. Abed, Ashit Kumar Dutta, Fahad M. Alhomayani, Ibrahim Mahariq, Fahad Alturise, Salem Alkhalaf, Tamim Alkhalifah, Yasser Elmasry, Baseem Khan

“…By employing regression machine learning algorithms, the research evaluates and enhances system performance, achieving remarkable R-squared accuracy levels of 98.86 % for heating output and 99.89 % for power output predictions. …”
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Identification of serum tRNA-derived small RNAs biosignature for diagnosis of tuberculosis by Zikun Huang, Qing Luo, Cuifen Xiong, Haiyan Zhu, Chao Yu, Jianqing Xu, Yiping Peng, Junming Li, Aiping Le

“…The accuracy of the three-tsRNA biosignature for TB diagnosis was evaluated in the training (n = 289), test (n = 124), and prediction (n = 292) groups. By utilizing cross-validation with a random forest algorithm approach, the training cohort achieved a sensitivity of 100% and specificity of 100%. …”
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Utilization of Data Mining Techniques in SIMPUS towards Smart Library at IAIN Kendari by Samrin, Badarwan, Raehang, Obaid Moh. Yahya, Syahrul

“…This study aims to analyze the application of data mining techniques in SIMPUS at IAIN Kendari, in order to improve the efficiency of library management and provide smarter services to users. By using algorithms such as association rules, clustering, and classification, historical data on borrowing and collection management can be processed to produce valuable insights, such as user behavior patterns, book need predictions, and collection recommendations. …”
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Tasmanian devil whale optimization (TDWO) is introduced for secure video transmission in 5G networks. by Fengren Lin, Minrong Lu

“…Here, the deep convolutional neural network (DCNN) model is deployed for the prediction of the QoE in resource allocation. Moreover, extensive experiments are performed to identify the resource allocation performance of the designed TDWO model. …”
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SYNTHESIS OF THE TECHNICAL CONTROL SYSTEMS WITH VARIABLE STRUCTURE by I. V. Prokopyev

“…The recommendation of modification of Demark trends algorithm by means of the sliding Yazvinsky's window and a method of self-organization for increase of accuracy of creation of a predictive model of damage is made. …”
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Research of a Novel Ship-loading Energy Circulatory System under Multi-process State by Jiang Hui

“…For the problems of high energy consumption,low utilization in ship sailing process,a new type of ship-loading energy circulatory system is presented,the system with the process of the flow field around the sports field of the ships as a power source kinetic energy is transformed into electrical energy.In the model,according to the changing of the sailing process state,the DMC-PID mixed prediction control algorithm is introduced to adjust the transmission ratio of belt drive in the system.Finally,the variable law of the belt drive parameters characteristic and performance indicators of the ship-loading energy circulatory system under the condition of transmission ratio under control are studied.The results show that the designed novel ship-loading energy circulatory system is feasible through analysis of performance indicators,since the introduction of variable transmission ratio belt drive system and DMC-PID control system in the energy circulatory system,the performance of the system is improved.…”
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Trajectory privacy protection scheme based on differential privacy by Si CHEN, Anmin FU, Mang SU, Huaijiang SUN

“…To solve the problem that the current sampling mechanism and data obfuscation method may raise insufficient data availability and privacy protection, a trajectory privacy protection scheme based on differential privacy was proposed.A new efficient sampling model based on time generalization and spatial segmentation was presented, and a k-means clustering algorithm was designed to process sampling data.By employing the differential privacy mechanism, the trajectory data was disturbed to solve the user privacy leaking problem caused by the attacker with powerful background knowledge.Simultaneously, to respond to the error boundary of the query range of pandemic, an effective prediction mechanism was designed to ensure the availability of released public track data.Simulation results demonstrate that compared with the existing trajectory differential privacy protection methods, the proposed scheme has obvious advantages in terms of processing efficiency, privacy protection intensity, and data availability.…”
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Multiphase time-varying batch process monitoring based on stage moving model migration by Luping Zhao, Zhongren Chen

“…Secondly, to analyze and capture the relationship between the process variables of both the old mode and new mode and the final quality variable, the JY-PLS algorithm is utilized on each time slice within sliding windows for quality prediction. …”
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Cloud native intelligent operation and maintenance technology by Long XUE, Gang LU, Qi ZHOU, Huiyan ZHANG, Tingjun WAN

“…Relying on the advantages of simple and fast applications,easy deployment of applications,and on-demand scaling of running applications,cloud native technology has been rapidly promoted.However,with the application of cloud native,the system architecture has become more complex and the scale of resources has become larger,and there is an urgent need for more intelligent operation and maintenance.Using intelligent operation and maintenance can better assist cloud-native application development,reduce operation and maintenance costs,and improve service quality.The application scenarios,key points,classic practices and existing problems of intelligent operation and maintenance were analyzed,and a cloud-native intelligent operation and maintenance architecture were proposed,and the main principles of the three scenarios:the trend prediction,data anomaly detection and fault location diagnosing in the core service algorithm platform were introduced in detail,and finally the future of intelligent operation and maintenance were looked forward.…”
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Optimal fusion β-quaternion filtering from delayed observations and packet losses with compensation strategy under properness by J. D. Jiménez-López, R. M. Fernández-Alcalá, F. Gutiérrez-Trujillo, E. Grassucci, D. Comminiello

“…A numerical example is presented to illustrate, among other aspects, the substantial reduction in computational time achieved by the proposed algorithm, as well as its superior estimation accuracy compared to conventional quaternion processing methods.…”
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Thermal one-point functions and their partial wave decomposition by Ilija Burić, Francesco Russo, Volker Schomerus, Alessandro Vichi

“…We also extract an asymptotic behaviour of conformal blocks and use it to analyse the density of heavy-heavy-light OPE coefficients for spinning operators, comparing it with semi-classical predictions, such as the dimensions of operators at large charge.…”
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Artificial Intelligence: The Latest Advances in the Diagnosis of Bladder Cancer by Satyendra Singh, Ram Mohan Shukla

“…Moreover, AI-driven diagnostic tools can assist in risk stratification, predicting disease progression, and personalizing treatment plans, thereby contributing to more targeted and effective therapies.…”
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Singularity-Free Adaptive Controller for Uncertain Hysteresis Suspension Using Magnetorheological Elastomer-Based Absorber by Hoa Thi Truong, Xuan Bao Nguyen, Cuong Mai Bui

“…First, a model is designed for the MRE-based absorber to portray the behavior of MRE and predict the appropriate electric current supplied. …”
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Roles of Modeling and Artificial Intelligence in LPBF Metal Print Defect Detection: Critical Review by Scott Wahlquist, Amir Ali

“…The primary objectives of this article are to introduce the reader to the most widely read published data on (1) the roles of numerical and analytical models in LPBF defect detection; (2) AI algorithms and models applicable to predict LPBF metal defects and causes; and (3) the integration of modeling, AI, and sensing technology, which is commonly used in material characterization and has been proven efficient and applicable to LPBF metal part defect detection over extended periods.…”
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Detection of Foreign Bodies in Transmission Line Channels Based on Fusion of Swin Transformer and YOLOv5 by XUE Ang, JIANG Enyu, ZHANG Wentao, LIN Shunfu, MI Yang

“…Finally, considering the mismatch between the real frame and the predicted frame, the structural similarity intersection over union (SIoU) is introduced to optimize the boundary errors and improve the generalization ability of the model. …”
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Kinetic Modelling of Methanol to Propylene Process on Cerium-hierarchical SAPO-34 Catalyst by masoumeh ghalbi-ahangary, Ali Taheri Najafabadi, Parviz Rashidi-Ranjbar, Zahra Taheri

“…The parameters were then estimated based on the experimental data using genetic algorithms. Comparing the experiments with the predicted data suggests a good correlation between the experimental data and the model.…”
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Lay beliefs about AI assessment of interpersonal skills in personnel selection by Ilyung Cheong, Young Eun Huh, Stefano Puntoni

“…Field studies of nurses provide preliminary evidence that AI can outperform humans in predicting interpersonal skills. However, a series of surveys and experiments document widespread lay beliefs in the opposite direction: individuals perceive AI as being less capable than humans in assessing interpersonal skills. …”
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Detecting and Explaining Postpartum Depression in Real-Time with Generative Artificial Intelligence by Silvia García-Méndez, Francisco de Arriba-Pérez

“…Moreover, it addresses the black box problem since the predictions are described to the end users thanks to the combination of LLMS with interpretable ML models (i.e. tree-based algorithms) using feature importance and natural language. …”
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