Lightweight opportunistic routing forwarding strategy based on Markov chain by Feng LI, Ya-li SI, Zhen CHEN, Li-min SHEN

“…A lightweight opportunistic routing forwarding strategy (MOR) was proposed based on Markov chain.In the scheme,the execute process of network was divided into a plurality of equal time period,and the random encounter state of node in each time period was represented by activity degree.The state sequence of a plurality of continuous time period constitutes a discrete Markov chain.The activity degree of encounter node was estimated by Markov model to predict its state of future time period,which can enhance the accuracy of activity degree estimation.Then,the method of comprehensive evaluating forwarding utility was designed based on the activity degree of node and the average encounter interval.MOR used the utility of node for making a routing forwarding decision.Each node only maintained a state of last time period and a state transition probability matrix,and a vector recording the average encounter interval of nodes.So,the routing forwarding decision algorithm was simple and efficient,low time and space complexity.Furthermore,the method was proposed to set optimal number of the message copy based on multiple factors,which can effectively balance the utilization of network resources.Results show that compared with existing algorithms,MOR algorithm can effectively increase the delivery ratio and reduce the delivery delay,and lower routing overhead ratio.…”
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A New Privacy-Preserving Scheme for Continuous Query in Location-Based Social Networking Services by Eric Ke Wang, Yunming Ye

“…In this paper, we analyze the existing location privacy protection systems and algorithms for location based services; considering their disadvantages of slow responding time and high anonymization costs, we propose a new enhanced greedy cloaking algorithm which predicts a cloaking area at the initial query to be the cloaking region in the whole query lifetime by the comprehensive computation of privacy monitor, quality monitor, and dynamic adjuster. …”
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BCAST IDS: A Novel Network Intrusion Detection System for Broadcast Networks by Javier Gombao

“…A modern approach to enhancing the capabilities of NIDSs is the use of machine learning (ML) algorithms that predict attacks based on data. This study introduces a novel and lightweight NIDS called Broadcast IDS (BCAST IDS) that uses specific network traffic patterns and the Isolation Forest algorithm to detect anomalies in broadcast networks. …”
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Optimised Implant Selection Using Digital Volume Tomography (DVT) Osteodensitometry by Manfred Nilius, Jörg Winterhoff

“…At the same time, the point at which loading occurs can already be defined at the planning stage, thanks to the predictable primary stability. A standard integration of DVT osteodensitometry in the algorithms of implant planning software thus seems desirable.…”
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Data-Driven Modeling and Enhancement of Surface Quality in Milling Based on Sound Signals by Paschalis Charalampous

“…These signals are then transformed into Mel-Frequency Cepstral Coefficients (MFCCs), which yield a compact time–frequency representation optimized for human auditory perception. Next, several AI algorithms were trained in order to classify these MFCCs into predefined surface roughness categories. …”
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Immune-Mediated Adverse Events Associated with Ipilimumab CTLA-4 Blockade Therapy: The Underlying Mechanisms and Clinical Management by Ahmad Tarhini

“…Implementation of these irAE management algorithms will help ensure that patients are able to benefit from ipilimumab therapy with adequate control of toxicities.…”
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A recurrent sigma pi sigma neural network by Fei Deng, Shibin Liang, Kaiguo Qian, Jing Yu, Xuanxuan Li

“…Abstract In this paper, a novel recurrent sigma‒sigma neural network (RSPSNN) that contains the same advantages as the higher-order and recurrent neural networks is proposed. The batch gradient algorithm is used to train the RSPSNN to search for the optimal weights based on the minimal mean squared error (MSE). …”
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Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition by Yuyang Li, Xia Wang, Min Zhang, Ruiqiang Li, Qiyang Sun

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GRRIS: A Real-time Intrasite Observation Scheduling Scheme for Distributed Survey Telescope Arrays by Yajie Zhang, Ce Yu, Chao Sun, Yi Hu, Zhaohui Shang, Jizeng Wei, Xu Yang

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Design Optimization Method and Application of High-Efficiency and Variable-Pitch Axial Flow Fan by Lee Chan, Yang Sang Ho, Lee Sang Yeol

“…The design program for constructing axial flow fan geometry is developed by combining fan blade section design and through-flow performance prediction methods. The optimization technique of this study is Hybrid Metaheuristic Algorithm which is combined with the design program to find optimal design values of blade setting angles, camber angles and chord lengths, and then to maximize the fan efficiency. …”
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Comprehensive assessment on estimating the thermodynamic and mechanical properties of multicomponent Fe–Cr-based alloys using machine learning techniques by Ahed Habib, Bashar Alibrahim, Mahdi Z. Alnunu, Hussein Moussa, Maan Habib

“…This study investigates the performance of 11 different machine learning algorithms to predict the mixing enthalpy, Young’s modulus, and the shear-to-bulk modulus ratio of Fe–Cr alloys with additions of Ni, Mo, Al, W, V, and Nb. …”
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Machine learning-driven multi-omics analysis identifies a prognostic gene signature associated with programmed cell death and metabolism in hepatocellular carcinoma by Xiang Li, Donghao Yin, Jiahao Geng, Yanyu Xu, Zijing Xu, Xuemeng Yang, Quanwei Li, Zimeng Shang, Zhiyun Yang, Zhong Xu, Jiabo Wang, Enxiang Zhang, Xinhua Song

“…Based on prognosis-related DEGs, patients and cells were stratified into high- and low-expression groups using corresponding computational algorithms. The intersecting DEGs from both datasets were analyzed using univariate Cox regression, and a prognostic risk score model was constructed through machine learning algorithms. …”
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A Cloud-Based Intelligence System for Asian Rust Risk Analysis in Soybean Crops by Ricardo Alexandre Neves, Paulo Estevão Cruvinel

“…Rules derived from time-series data are employed to enable scenario prediction for risk evaluation related to disease development. …”
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Transfer learning based feature selection for feedforward neural network for speech emotion classifier by D. V. Krasnoproshin, M. I. Vashkevich

“…This technique allowed us to significantly reduce initial feature vector size while increasing models’ prediction quality. We used TESS and RAVDESS datasets to estimate the performance of proposed method. …”
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Sentiment Analysis using Twitter Dataset by Ibrahim Moge Noor, Metin Turan

“…We perform Multi nominal naïve Bayes classifier algorithm to classify tweets documents. We split our dataset using k-folder validation since we had limited amounts of data, so to achieve unbiased prediction of the model. . …”
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A general framework for active space embedding methods with applications in quantum computing by Stefano Battaglia, Max Rossmannek, Vladimir V. Rybkin, Ivano Tavernelli, Jürg Hutter

“…The application of this scheme to study localized electronic states in materials is showcased through the accurate prediction of the optical properties of the neutral oxygen vacancy in magnesium oxide (MgO). …”
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Monthly Electricity Generatıon Forecast in Solar Power Plants with LSTM by Ali Hakan Isık, Ömer Çetin

“…In the study, predictions and analyses were made using the LSTM (Long Short-Term Memory) method, which is one of the artificial neural networks. …”
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Research Progress of Finite Element Technology in Wood Processing by Maosen Wang, Lin Yang

“…It highlights challenges such as model accuracy and algorithm optimization, suggesting that continuous improvements in FEA models and algorithms can further enhance processing efficiency and product quality. …”
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Artificial Intelligence—What to Expect From Machine Learning and Deep Learning in Hernia Surgery by Robert Vogel, Björn Mück

“…The term AI incorporates various technologies including ML, Neural Networks (NN), and DL. Classical ML algorithms depend on structured, labeled data for predictions, requiring significant human oversight. …”
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Optimizing Wheat Yields: AI and IoT Techniques for Continuous Agricultural Monitoring by Nandy Manish, Afzal Md

“…This data is analyzed using AI algorithms developed predictive models and actionable insights. …”
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