Maritime Traffic Knowledge Discovery via Knowledge Graph Theory by Shibo Li, Jiajun Xu, Xinqiang Chen, Yajie Zhang, Yiwen Zheng, Octavian Postolache

“…Intelligent ships are a key focus for the future development of maritime transportation, relying on efficient decision-making and autonomous control within complex environments. …”
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Enhanced Rapid Mangrove Habitat Mapping Approach to Setting Protected Areas Using Satellite Indices and Deep Learning: A Case Study of the Solomon Islands by Hyeon Kwon Ahn, Soohyun Kwon, Cholho Song, Chul-Hee Lim

“…The present study introduces an efficient and accurate methodology for mapping mangrove habitats and prioritizing protection areas utilizing open-source satellite imagery and datasets available through the Google Earth Engine platform in conjunction with a U-Net deep learning algorithm. …”
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Degradation of dyes by fungi: An overview on recent updates by Nagraj, Pankaj Kumar Chaurasia, Shashi Lata Bharati, Nagendra Sharma, Jaynath Kumar, Azhagu Madhavan Sivalingam

“…Different methods for the detoxification of dyes molecules have been studied like physical, chemical, and biological methods. Biological methods utilize the microbial sources (primarily fungi, bacteria, yeast, and microbial enzymes) and plants for the degradation and remediation of dyes pollutants. …”
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Budgetary Factors and the Quality of Education Service Delivery in Public Secondary Schools in Northern Division Kabale District. by Atwongyeire, Redeemer

“…Schools should adopt more sophisticated budget planning and management tools to ensure efficient allocation and utilization of resources. …”
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Knowledge Graph Completion With Pattern-Based Methods by Maryam Sabet, Mohammadreza Pajoohan, Mohammad Reza Moosavi

“…In this paper, we propose a Pattern-based Knowledge Graph Completion (PKGC) method that consists of three phases. The first phase utilizes multi-source information and expands the KG using entity description as external information with efficient Natural Language Processing (NLP) techniques. …”
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Optimizing the Production of LNG and NGL from Arab Crudes and Wet Gases by Adel M. Hemeida, Mohammed S. Al-Blehed, Saad El-Din Desouky

“…The developed model should be utilized as a useful tool to help the design of an efficient processing of natural gases. …”
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A Novel Method for the Estimation of Sea Surface Wind Speed from SAR Imagery by Zahra Jafari, Pradeep Bobby, Ebrahim Karami, Rocky Taylor

“…Wind is one of the important environmental factors influencing marine target detection as it is the source of sea clutter and also affects target motion and drift. …”
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An Integrated Model for Dam Break Flood Including Reservoir Area, Breach Evolution, and Downstream Flood Propagation by Huiwen Liu, Zhongxiang Wang, Dawei Zhang, Liyun Xiang

“…The reasonable and efficient prediction of dam failure events is of great significance to the emergency rescue operations and the reduction in dam failure losses. …”
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Assessment of Collaboration-Based and Non-Collaboration-Based Logistics Risks with Plithogenic SWARA Method by Alptekin Ulutaş, Ieva Meidute-Kavaliauskiene, Ayse Topal, Ezgi Demir

“…<i>Conclusions</i>: The proposed technique will help logistics professionals make informed decisions and manage and analyze risks more efficiently. This study will also contribute to the literature as it is the first time that logistical risks have been addressed by utilizing the Plithogenic SWARA technique.…”
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Biometric and IoT Integration for Secure and Remote Door Access Control Using Fingerprint Recognition and GSM Technology by S Kanagamalliga, S Rajalingam, A Kannan, M Karthikeyan

“…The reliability and flexibility of Arduino, coupled with the GSM capabilities of SIM900, are utilized to create a robust and efficient solution. …”
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Deep Learning-Based Emergency Rescue Positioning Technology Using Matching-Map Images by Juil Jeon, Myungin Ji, Jungho Lee, Kyeong-Soo Han, Youngsu Cho

“…In real-world experiments, our method, utilizing multi-source data, achieved a positioning success rate of 85.27%, which meets the US FCC’s E911 standards for location accuracy and reliability across various conditions and environments. …”
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CHAM-CLAS: A Certificateless Aggregate Signature Scheme with Chameleon Hashing-Based Identity Authentication for VANETs by Ahmad Kabil, Heba Aslan, Marianne A. Azer, Mohamed Rasslan

“…Due to the critical time constraints in VANETs, efficient batch verification techniques are crucial. …”
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Method for Extracting Arterial Pulse Waveforms from Interferometric Signals by Marian Janek, Ivan Martincek, Gabriela Tarjanyiova

“…Visual analyses highlight amplitude variations and residual noise sources, primarily attributed to sensor bandwidth limitations and interpolation methods, considerations critical for real-world deployment. …”
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Enhancing SR-Tree for Nearest Neighbor Search by Kayumov Abduaziz, Shincheol Lee, Ji Sun Shin

“…While dynamic index structures have been extensively utilized for indexing dynamic data, their performance in nearest neighbor search can further be improved. …”
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An Intelligent Technique for Android Malware Identification Using Fuzzy Rank-Based Fusion by Altyeb Taha, Ahmed Hamza Osman, Yakubu Suleiman Baguda

“…Android’s open-source nature, combined with its large market share, has made it a primary target for malware developers. …”
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Advanced computational methods for news classification: A study in neural networks and CNN integrated with GPT by Fahim Sufi

“…This research offers substantial practical contributions, providing detailed insights into news source contributions, effective anomaly detection, and predictive trend analysis using neural networks. …”
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Model of the malicious traffic classification based on hypergraph neural network by Wenbo ZHAO, Zitong MA, Zhe YANG

“…As the use and reliance on networks continue to grow, the prevalence of malicious network traffic poses a significant challenge in the field of network security.Cyber attackers constantly seek new ways to infiltrate systems, steal data, and disrupt network services.To address this ongoing threat, it is crucial to develop more effective intrusion detection systems that can promptly detect and counteract malicious network traffic, thereby minimizing the resulting losses.However, current methods for classifying malicious traffic have limitations, particularly in terms of excessive reliance on data feature selection.To improve the accuracy of malicious traffic classification, a novel malicious traffic classification model based on Hypergraph Neural Networks (HGNN) was proposed.The traffic data was represented as hypergraph structures and HGNN was utilized to capture the spatial features of the traffic.By considering the interrelations among traffic data, HGNN provided a more accurate representation of the characteristics of malicious traffic.Additionally, to handle the temporal features of traffic data, Recurrent Neural Networks (RNN) was introduced to further enhance the model’s classification performance.The extracted spatiotemporal features were then used for the classification of malicious traffic, aiding in the detection of potential threats within the network.Through a series of ablative experiments, the effectiveness of the HGNN+RNN method was verified.These experiments demonstrate the model’s ability to efficiently extract spatiotemporal features from traffic, resulting in improved classification performance for malicious traffic.The model achieved outstanding classification accuracy across three widely-used open-source datasets: NSL-KDD (94% accuracy), UNSW-NB15 (95.6% accuracy), and CIC-IDS-2017 (99.08% accuracy).These results underscore the potential significance of the malicious traffic classification model based on hypergraph neural networks in enhancing network security and its capacity to better address the evolving landscape of network threats within the domain of network security.…”
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Evaluation of Photo-Fenton and Photo-Fenton-Like Methods for Removing Direct Orange 118 Dye from Wastewater by Tamara Kawther Hussein, Nidaa Adil Jasim

“… Wastewater treatment has used efficient technology methods that can remove any pollutant. …”
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High-throughput discovery of perturbation-induced topological magnons by Mohammed J. Karaki, Ahmed E. Fahmy, Archibald J. Williams, Sara Haravifard, Joshua E. Goldberger, Yuan-Ming Lu

“…In this work, we significantly advance the symmetry-based approach for identifying topological magnons through developing a fully automated algorithm, utilizing the theory of symmetry indicators, that enables a highly efficient and large-scale search for candidate materials hosting perturbation-driven topological magnons. …”
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Phylo-rs: an extensible phylogenetic analysis library in rust by Sriram Vijendran, Tavis Anderson, Alexey Markin, Oliver Eulenstein

“…Phylo-rs focuses on the efficient and convenient deployment of software aimed at large-scale phylogenetic analysis and inference. …”
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