Real-time traffic monitoring system using IoT-aided robotics and deep learning techniques by Mohammed Qader Kheder, Aree Ali Mohammed

“…One alternative solution is vehicular cloud computing (VCC). Additionally, an IoT-aided robotic (IoRT) model has been developed with a modern architecture that integrates IoT sensor nodes and cameras to gather real-time traffic data. …”
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Determination of sulphite in wine samples with the aid of three different analytical techniques by Kingsley Sunday, Patrick Omuku, Collins Odidika, Ebuka Emenike, Steve Eshiemogie, Kingsley Iwuozor

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Measuring countries relative efficiencies in using development assistance: a data envelopment analysis approach by Mohamed F. Sakr, Kamal Samy Selim, Sherin Gamaleldin Taha

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Computer-Aided Diagnosis Techniques for Brain Tumor Segmentation and Classification Using MRI by Gadicha A. B., Kale Prachi V., Dalvi G. D., Mohod M. M., Pakhale S. C., Khan S. M.

“…This paper presents a comprehensive review of various AI-driven techniques, including traditional ML models, deep convolutional neural networks, and hybrid systems, that have been employed for the automatic detection, segmentation, and categorization of brain tumors using MRI data. …”
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Data Mining Techniques in Decision Making by Amna Sajid, Basit Amin

“… Data mining aims to find relevant information for decision-making, forecasting, optimising, and other business or research reasons. …”
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Data augmentation for numerical data from manufacturing processes: an overview of techniques and assessment of when which techniques work by Henry Ekwaro-Osire, Sai Lalitha Ponugupati, Abdullah Al Noman, Dennis Bode, Klaus-Dieter Thoben

“…A significant challenge in ML applications is obtaining sufficient training data, which data augmentation aims to address. While widely applied to image, text, and sound data, data augmentation for numerical data in manufacturing has seen limited investigation. …”
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Data Augmentation Techniques for fMRI Data: A Technical Survey by Valentina Sanchez, Cicek Guven, Gonzalo Napoles, Marie Safar Postma

“…In this technical survey, we outline the main existing techniques for augmenting fMRI data, primarily represented as image, time series, and graph data. …”
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A Methodical Review of Iridology-Based Computer-Aided Organ Status Assessment Techniques by Suja Alphonse, Ramachandran Venkatesan, Theena Jemima Jebaseeli

“…The methodologies, data acquisition source, and volume of data used for both training and testing in the pre-diagnosis of human organs utilizing iris patterns are thoroughly studied. …”
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Data Mining Classification Techniques for Diabetes Prediction by Hindreen Rashid Abdulqadir, Adnan Mohsin Abdulazeez, Dilovan Assad Zebari

“…The fact that disease recognition and investigation require many details, data mining plays a critical role in healthcare. …”
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Efficient Data Storage in DNA Sequences Aided by p-gram Huffman Coding by Kun Tu, Dariusz Puchala

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Design and analysis of a small satellite design hosting lidar sensor for data acquisition aimed at environmental protection by Paschalidis Maria, Kolios Stavros

“…This study presents the design and analysis of a small satellite design hosting a Lidar sensor for data acquisition aimed at environmental protection. …”
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Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system by Qianwen LI, Jianfeng CHEN, Miao CUI, Guangchi ZHANG

“…A rechargeable unmanned aerial vehicle (UAV) aided wireless sensor network was considered, which consists of multiple ground terminals with a large amount of time-sensitive data to be collected.Due to the limited battery capacity, the UAV cannot collect the data from all terminals through a single flight mission, and it needs to return to the charging pile to replenish its flight energy several times during the whole mission.The optimization of the terminal scheduling, trajectory, flight speed and transmission rate for the UAV was studied to maximize the number of terminals whose data had been collected within the data lifetime limit.Due to the variable coupling and the existence of discrete binary scheduling variables, the considered optimization problem is difficult to solve.To tackle such a difficulty, an efficient algorithm was proposed based on the stochastic optimization and the feature engineering.Specifically, the flight hover communication protocol was introduced to simplify the UAV flight process.And then a terminal scheduling algorithm was innovatively proposed with the influence factor and the stochastic preference, which extracted the features that affect the service time of the UAV, optimized the weights of the features, and further simplified the optimization problem into multiple subproblems.The subproblems were then solved by using the block coordinate descent and successive convex approximation techniques.Simulation results show that the proposed optimization algorithm achieves significant performance gains over several benchmark schemes in the scenarios with different data lifetime requirements and different numbers of ground terminals.…”
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Effective deep learning aided vehicle classification approach using Seismic Data by Sherief Hashima, Mohamed H. Saad, Ahmad B. Ahmad, Takeshi Tsuji, Hamada Rizk

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Numerical Simulation Data-Aided Domain-Adaptive Generalization Method for Fault Diagnosis by Tao Yan, Jianchun Guo, Yuan Zhou, Lixia Zhu, Bo Fang, Jiawei Xiang

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Application of Data Mining Techniques on Tourist Expenses in Malaysia by Miao Cai, Tan Shi An

“…Besides that, this paper implementation of 4 data mining classification techniques was experimented for extracting important insights from the tourism data set. …”
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Data Mining Techniques for Iraqi Biochemical Dataset Analysis by Sarah Sameer, Suhad Faisal Behadili

“… This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. …”
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Modelling Tyre-Road Noise with Data Mining Techniques by Elisabete Fraga FREITAS, Joaquim TINOCO, Francisco SOARES, Jocilene COSTA, Paulo CORTEZ, Paulo PEREIRA

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Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study by Ahad Amini Pishro, Shiquan Zhang, Alain L’Hostis, Yuetong Liu, Qixiao Hu, Farzad Hejazi, Maryam Shahpasand, Ali Rahman, Abdelbacet Oueslati, Zhengrui Zhang

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MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects by Domenico Lofù, Paolo Sorino, Tommaso Colafiglio, Caterina Bonfiglio, Rossella Donghia, Gianluigi Giannelli, Angela Lombardi, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci

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Navigating the missing data maze: exploring multiple imputation techniques for environmental performance index data by Muhammed Haziq Muhammed Nor, Mohd Aftar Abu Bakar, Noratiqah Mohd Ariff, Wan Hanna Melini Wan Mohtar, Bernard Kok Bang Lee

“…Future research may explore deep learning techniques for handling missing data in environmental datasets like EPI.…”
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