Student Engagement Recognition: Comprehensive Analysis Through EEG and Verification by Image Traits Using Deep Learning Techniques by Ajitha Sukumaran, Arun Manoharan

“…The experimental results of the proposed system were verified by analyzing the image traits of the students using the engagement indicator algorithm. Both systems were further validated through a quiz conducted at the end of the session.…”
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Vibration Reliability Analysis of Aeroengine Rotor Based on Intelligent Neural Network Modeling Framework by Jia-Qi Liu, Yun-Wen Feng, Cheng Lu, Wei-Huang Pan, Da Teng

“…INNMF is based on the artificial neural network (ANN) algorithm through improved particle swarm optimization (PSO) algorithm and Bayesian Regularization (BR) optimization. …”
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Improving the selection of object-analogues of oil and gas fields in designing reservoir engineering by Alexander V. Karsakov, Pavel N. Zyatikov, Kirill V. Sinebriukhov, Irina V. Sharf

“…Aim. Development of an algorithm for qualitatively selection of the best object-analogue of the project field, taking into account the verification of the selected analogues. …”
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Trust evaluation model of social internet of things based on implicit social relationship by Hongbin ZHANG, Fan FAN, Dongmei ZHAO, Bin LIU, Yan YIN, Jian LIU

“…The social internet of things （SIoT） is a new paradigm that combines social networks and the internet of things to enhance network scalability and navigability.However, with increased openness and mobility of intelligent objects, there are rising security risks related to information security and reliable service delivery, which poses a significant challenge to the SIoT.Trust is a critical factor in providing secure and reliable services.Therefore, a new trust assessment model was proposed from the perspective of social relationships.A trust transfer algorithm was proposed based on the explicit social relationships and potential features between nodes.The algorithm can tap and establish the implicit social relationships among nodes to solve the SIoT sparsity and cold start problem.Additionally, the social relations were fine-grained and divided to build a single-relationship sub-network.Multiple single-relationship sub-networks were fused to build a multiple-relationship composite network.Thus, the impact of multiple dynamically changing social relationships among nodes on trust evaluation can be effectively fused.The comprehensive trust assessment of intelligent objects was conducted based on three indicators: direct trust, indirect recommendation trust, and service satisfaction.The experimental results on real smart city datasets demonstrate the model’s robustness in non-sparse and sparse network scenarios.It can effectively evaluate trusted and untrusted objects in the network and improve the accuracy and convergence of trust evaluation.…”
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A Novel Improved Maximum Entropy Regularization Technique and Application to Identification of Dynamic Loads on the Coal Rock by Chunsheng Liu, Chunping Ren

“…A new signal processing algorithm was proposed to identify the dynamic load acting on the coal-rock structure. …”
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PharmRL: pharmacophore elucidation with deep geometric reinforcement learning by Rishal Aggarwal, David R. Koes

“…With this algorithm, we show better prospective virtual screening performance, in terms of F1 scores, on the DUD-E dataset than random selection of ligand-identified features from co-crystal structures. …”
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Automatic Classification System of Drainage Hole Blockage Based on Convolution Neural Network Transfer Learning by Jianbing Lv, Weijun Wu, Xiaoyu Kang, Juan Huang, Gongfa Chen, Shuai Teng, Hejie Gao

“…The results show that when the SGDM gradient optimisation algorithm is used and the learning rate is 0.0001, the identification effect of these samples is the best. …”
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Cost-Efficient LEO Navigation Augmentation Constellation Design under a Constrained Deployment Approach by Jing Ren, Dan Sun, Deng Pan, Mingtao Li, Jianhua Zheng

“…They are solved by the genetic algorithm and differential evolution algorithm, and both Walker and Flower constellations are adopted. …”
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Real world data on digital remote refraction in a healthy population of 14,680 eyes by Casper van der Zee, Heshow Jamal, Marc Muijzer, Laurence Frank, Gerko Vink, Robert Wisse

“…We report real-world 2021–2022 data of the underlying algorithm and validated these to conventional prescriptions among healthy individuals (high visual acuity and satisfactied current refraction). …”
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Enhancing Transient Stability of DFIG-Based Wind Turbine Systems Using Deep Learning-Controlled Resistance-Based Fault Current Limiters by Yaoying Wang

“…MATLAB/Simulink confirms the efficacy of the proposed limiter and algorithm in boosting transient stability for DFIG-based wind energy systems. …”
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Migration and mutation (MeTa) hybrid trained ANN for dynamic spectrum access in wireless body area network by Geoffrey Eappen, Shankar T, Rajesh A

“…The novel MeTa hybrid optimization algorithm achieves a balance between global and local search abilities by optimizing the weights of the ANN. …”
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Prediction method of 0day attack path based on cyber defense knowledge graph by Cheng SUN, Hao HU, Yingjie YANG, Hongqi ZHANG

“…To solve the difficulty of attack detection caused by the 0day vulnerability, a prediction method of 0day attack path based on cyber defense knowledge graph was proposed.The cyber defense knowledge graph was constructed to refine the discrete security data such as threat, vulnerability and asset into the complete and high-related knowledge format by extracting concepts and entities related to network attack from cyber security ontology research finds and databases.Based on the knowledge integrated by the knowledge graph, assumed and restricted the unknown attributes such as the existence, availability and harmfulness of 0day vulnerabilities, and model the concept of ＆quot;attack＆quot; as a relationship between attacker entities and device entities in the knowledge graph to transform the attack prediction to the link prediction of knowledge graph.According to this, apply path ranking algorithm was applied to mine the potential 0day attack in the target system and construct the 0day attack graph.Predicted the 0day attack path by utilizing the scores output by classifiers as the occurrence probabilities of single step attack and computing the occurrence probabilities of different attack paths.The experimental result shows that with the help of complete knowledge system provided by knowledge graph, the proposed method can reduce the dependence of prediction analysis on expert model and overcome the bad influence of 0day vulnerability to improve the accuracy of 0day attack prediction.And utilizing the characteristic that path ranking algorithm reasons based on the structure of graph can also help to backtrack the reasons of predicting results so as to improve the explainability of predicting.…”
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CT-Scan Method-based Artificial Neural Network for Diagnosis of COVID-19 by Humam Adnan Sameer, Ammar Hussein Mutlag, Sadik Kamel Gharghan

“…This paper aims to use an ANN algorithm based on CT and some laboratory and clinical parameters to determine whether a person is infected with Covid-19 or not. …”
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Downlink Multiuser Hybrid Beamforming for MmWave Massive MIMO-NOMA System with Imperfect CSI by Jing Jiang, Ming Lei, Huanhuan Hou

“…For digital beamforming, the weak user applies the block diagonalization algorithm based on the strong user’s effective channel to reduce its intracluster interference. …”
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Gesture Recognition with Residual LSTM Attention Using Millimeter-Wave Radar by Weiqing Bai, Siyu Chen, Jialiang Ma, Ying Wang, Chong Han

“…A series of experimental results show that the algorithm proposed in this paper has higher recognition performance.…”
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Location-assistant content distribution scheme for emergency rescue by Guomin Zhang, Lihua Song, Haitao Wang, Chao Hu, Na Wang

“…Due to the intermittent network connectivity and variety of emergency service, a content-classification-based publish/subscribe architecture and a GenericSpray routing algorithm based on the prediction of overlap opportunity in spatio-temporal positions are proposed. …”
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Improving Diabetes Prediction by Selecting Optimal K and Distance Measures in KNN Classifier by Emad Majeed Hameed, Hardik Joshi

“…This paper discusses diabetes prediction by using the K-Nearest Neighbors (KNN) classifier, which is a widely used algorithm in machine learning. Most studies only dealt with investigating the optimal value of k in the KNN algorithm and did not address the best method to measure distance alone or together with the optimal value of k to improve the efficiency of diabetes prediction. …”
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Manhattan Distance-based K-Medoids Clustering Improvement for Diagnosing Diabetic Disease by Solikhun, Muhammad Rahmansyah Siregar, Lise Pujiastuti, Mochamad Wahyudi

“…In testing with the Quantum K-Medoids algorithm, it was found that the cost value in the 8th epoch showed a significant decrease compared to the Classical K-Medoids algorithm. …”
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Long-Term Rainfall Information Forecast by Utilizing Constrained Amount of Observation through Artificial Neural Network Approach by Muhammed E. Akiner

“…From 2010 to 2020, a two-layer feed-forward ANN was trained using the gradient descent algorithm to forecast daily average rainfall data by month. …”
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THE APPLICATION OF DIGITAL MARKETING COMMUNICATION IN FACING THE PHENOMENON OF TIKTOK SHOPPERTAINMENT AS A MARKETING COMMUNICATION STRATEGY FOR UMKM by Pakpahan J.P., Avina D.A.A.

“…However, MSMEs are also facing challenges such as competition from artists and influencers, the complexity of TikTok's algorithm, and limited human resources and expertise. …”
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