Improvement of classification accuracy of functional near-infrared spectroscopy signals for hand motion and motor imagery using a common spatial pattern algorithm by Omid Asadi, Mahsan Hajihosseini, Sima Shirzadi, Zahra Einalou, Mehrdad Dadgostar

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Real-Time DTM Generation with Sequential Estimation and OptD Method by Wioleta Błaszczak-Bąk, Waldemar Kamiński, Michał Bednarczyk, Czesław Suchocki, Andrea Masiero

“…In this study, a novel concept of generating DTMs based on real-time data acquisition using the principles of sequential estimation is proposed. Since DTM generation occurs simultaneously with data acquisition, the proposed algorithm also incorporates data reduction techniques to manage the large dataset. …”
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Research on Abstraction-Based Search Space Partitioning and Solving Satisfiability Problems by Yuexin Huang, Qinzhou Niu, Yanfang Song

“…By introducing an abstraction method for partitioning the search space—distinct from traditional assignment-based approaches—the paper proposes sequential, parallel, and hybrid solving algorithms. …”
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Determining of the laser heat flux for three-dimensional conduction model by the sequential method by Nguyen Nhat Phi Long, Son Hoai Nguyen, Nguyen Quan

“…To confirm the effectiveness of the presented method, the paper has given two specific applications. Indeed, in this research, based on the results that have been achieved in two illustrations, the sequential method to determine the inversely laser heat flux in the three-dimensional conduction model is a reasonable, correct, and powerful method. …”
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Integrated intelligent neuro-evolutionary computing approach to study SEIRC model representing campylobacteriosis transmission dynamics by Muhammad Shoaib, Saba Kainat, Areej Abdullah Alabduljabbar, Kottakkaran Sooppy Nisar, Muhammad Asif Zahoor Raja

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Optimising Insider Threat Prediction: Exploring BiLSTM Networks and Sequential Features by Phavithra Manoharan, Wei Hong, Jiao Yin, Hua Wang, Yanchun Zhang, Wenjie Ye

“…We analyse the performance of the four supervised learning algorithms on manual features, sequential features, and the ground truth of the day with different combinations. …”
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Automated reinforcement learning for sequential ordering problem using hyperparameter optimization and metalearning by André Luiz Carvalho Ottoni

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Efficient Joint Transmit and Receive Beam Alignment via Sequential CNN LSTM Networks by Takumi Yoshida, Koji Ishibashi, Hiroki Iimori, Paulo Valente Klaine, Szabolcs Malomsoky

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Two-Way Feature Extraction Using Sequential and Multimodal Approach for Hateful Meme Classification by Apeksha Aggarwal, Vibhav Sharma, Anshul Trivedi, Mayank Yadav, Chirag Agrawal, Dilbag Singh, Vipul Mishra, Hassène Gritli

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Modification of Haessler’s sequential heuristic procedure for the one-dimensional cutting stock problem with setup cost by Mateus Martin, Antonio Moretti, Marcia Gomes-Ruggiero, Luiz Salles Neto

“…The solution strategy is to generate different cutting plans using MSHP, and then to use an integer programming model to seek even better results. Research method It is a axiomatic research, ordinary in studies of Operational Research. …”
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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…To overcome these limitations, the study utilizes 5112 petrophysical log samples from three wells located in a Middle Eastern deepwater carbonate reservoir. Three sequential deep learning models—Recurrent Neural Network and Gated Recurrent Unit—were developed and optimized using the Adam algorithm. …”
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Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data by Chien Wei Oei, Eddie Yin Kwee Ng, Matthew Hok Shan Ng, Yam Meng Chan, Vinithasree Subbhuraam, Lai Gwen Chan, U. Rajendra Acharya

“…The combination of using DL algorithms, such as multi-layer perceptron (MLP) and long short-term memory (LSTM), which can process complex patterns in the data, and the inclusion of new data types, such as sequential data, helped to improve model performance. …”
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Development Binary Search Algorithm by Baghdad Science Journal

“…This research develops binary search algorithm by using new structure called Triple, structure in this structure data are represented as triple. …”
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Nonlinear Model Predictive Control for Pumped Storage Plants Based on Online Sequential Extreme Learning Machine with Forgetting Factor by Chen Feng, Chaoshun Li, Li Chang, Zijun Mai, Chunwang Wu

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Dynamic SOFA component scores-based deep learning for short to long-term mortality prediction in sepsis survivors by Juan Wei, Feihong Lin, Tian Jin, Qian Yao, Sheng Wang, Di Feng, Xin Lv, Wen He

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Integrating Social Determinants of Health in Machine Learning–Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study by Seung-Yup Lee, Leslie W Hayes, Bunyamin Ozaydin, Steven Howard, Alison M Garretson, Heather M Bradley, Andrew M Land, Erin W DeLaney, Amy O Pritchett, Amanda L Furr, Ashleigh Allgood, Matthew C Wyatt, Allyson G Hall, Jane C Banaszak-Holl

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Localization of Conveyor Belt Damages Using a Deep Neural Network and a Hybrid Method for 1D Sequential Data Augmentation by Iwona Komorska, Andrzej Puchalski, Damian Bzinkowski

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An Improved Correlation Filtering Method for Tracking Maritime Small Targets of GF-4 Staring Satellite Sequence Images by Deyang Zhang, Yao Xu, Haimin Hu

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Subsampling Algorithms for Irregularly Spaced Autoregressive Models by Jiaqi Liu, Ziyang Wang, HaiYing Wang, Nalini Ravishanker

“…To overcome this challenge, subsampling algorithms are widely used to perform statistical analyses on smaller, more manageable subsets of the data. …”
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Neuromorphic devices assisted by machine learning algorithms by Ziwei Huo, Qijun Sun, Jinran Yu, Yichen Wei, Yifei Wang, Jeong Ho Cho, Zhong Lin Wang

“…Second, the fabrication and research progress of neuromorphic devices are presented regarding to materials and structures. …”
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