Agricultural consumer Internet of Things devices: Methods for optimizing data aggregation by Hanan Abdullah Mengash, Hany Mahgoub, Asma Alshuhail, Abdulbasit A. Darem, Jihen Majdoubi, Ayman Yafoz, Raed Alsini, Omar Alghushairy

“…With the advent of state-of-the-art computer and digital technology, modern civilisation has been immensely facilitated and optimised. …”
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Self-Powered Photodetectors with Ultra-Broad Spectral Response and Thermal Stability for Broadband, Energy Efficient Wearable Sensing and Optoelectronics by Peter X. Feng, Elluz Pacheco Cabrera, Jin Chu, Badi Zhou, Soraya Y. Flores, Xiaoyan Peng, Yiming Li, Liz M. Diaz-Vazquez, Andrew F. Zhou

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Molecular Evolution of Rice Blast Resistance Gene bsr-d1 by Wei Li, Mengchen Zhang, Yaolong Yang, Lin Weng, Peisong Hu, Xinghua Wei

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GenVis: Visualizing Genre Detection in Movie Trailers for Enhanced Understanding by Faheem Shaukat, Naveed Ejaz, Zeeshan Ashraf, Mrim M. Alnfiai, Mona Mohammed Alnahari, Reemiah Muneer Alotaibi

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Secure and efficient cloudlet networks: blockchain integration with agent-based proof of trust mechanism by Nothile C. Masango, Jeffrey O. Agushaka, Mercy C. Amaefule, Olutosin Taiwo, Peiying Zhang, Absalom E. Ezugwu, Kashif Saleem, Aseel Smerat, Laith Abualigah

“…These applications generate massive amounts of data, challenging the storage, computational capacity, and battery life of mobile devices. …”
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A Genetic-Algorithms Matrix-Factorization-Based Recommender System Model Using Tags by Manal Almaayah, Yousef Kilani, Ayoub Alsarhan, Mohammad Aljaidi, Mohammed Alshammari, Aadil Alshammari

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A Hybrid CNN Framework DLI-Net for Acne Detection with XAI by Shaila Sharmin, Fahmid Al Farid, Md. Jihad, Shakila Rahman, Jia Uddin, Rayhan Kabir Rafi, Radia Hossan, Hezerul Abdul Karim

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Advanced Interpretation of Bullet-Affected Chest X-Rays Using Deep Transfer Learning by Shaheer Khan, Nirban Bhowmick, Azib Farooq, Muhammad Zahid, Sultan Shoaib, Saqlain Razzaq, Abdul Razzaq, Yasar Amin

“…Multiple computational systems were used to verify the results, which showcased the effectiveness of the proposed solution. …”
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Reading positional codes with fMRI: Problems and solutions. by Kristjan Kalm, Dennis Norris

“…In this paper we use computational simulations and data from two fMRI experiments to show that a host of unrelated neural processes can masquerade as sequence representations. …”
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Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks by Nadia Shamshad, Lei Wang, Kiran Saleem, Danish Sarwr, Salil Bharany, Ahmad Almogren, Jaeyoung Choi, Ateeq Ur Rehman, Ayman Altameem

“…Furthermore, the study employs the KNN-based cost-efficient method to predict nodes’ orientation in dynamic water conditions, thereby facilitating the mapping of the shortest distance between sensor nodes during the underwater context acquisition process. The effectiveness of the proposed KNN-based cost-efficient method is evaluated through real-time experiments conducted in a water tank setup and simulations using the Ns-3.37 version. …”
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Integrating the Prior Shape Knowledge Into Deep Model and Feature Fusion for Topologically Effective Brain Tumor Segmentation by Salma Asif, Ahmad Raza Shahid, Kiran Aftab, Syed Ather Enam

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A Lightweight YOLOv8s Algorithm for Ceiling Fan Blade Defect Detection With Optimized Pruning and Knowledge Distillation by Qinyuan Huang, Chen Fan, Yuqi Sun, Jiaxiong Huang, Wengziyang Jiang

“…Detecting these surface defects is crucial; however, accurate and rapid detection typically involves complex machine vision algorithms, such as You Only Look Once (YOLO) networks, that require considerable computing resources, which contradicts the industry’s preference for simpler algorithms that can be deployed using low-cost computing power. …”
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A Tree Crown Segmentation Approach for Unmanned Aerial Vehicle Remote Sensing Images on Field Programmable Gate Array (FPGA) Neural Network Accelerator by Jiayi Ma, Lingxiao Yan, Baozhe Chen, Li Zhang

“…Deep learning technology has achieved good results in tree crown segmentation and species classification, but relying on high-performance computing platforms, edge calculation, and real-time processing cannot be realized. …”
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Applications of Complex Uncertain Sequences via Lacunary Almost Statistical Convergence by Xiu-Liang Qiu, Kuldip Raj, Sanjeev Verma, Samrati Gorka, Shixiao Xiao, Qing-Bo Cai

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LD-Det: Lightweight Ship Target Detection Method in SAR Images via Dual Domain Feature Fusion by Hang Yu, Bingzong Liu, Lei Wang, Teng Li

“…However, large-scale deep learning algorithm training requires huge computing power support and large equipment to process, which is not suitable for real-time detection on edge platforms. …”
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Forecasting Delivery Time of Goods in Supply Chains Using Machine Learning Methods by V. K. Rezvanov, O. M. Romakina, E. V. Zaytseva

“…Second, forecasting typically requires large amounts of data for machine learning and significant computing resources that are not available to the majority of companies. …”
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Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

“…In this research, a hybrid approach utilises techniques with quantum computing capabilities to tackle complex problems that are not amenable to conventional ML algorithms and to minimise computational expenses. …”
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A hybrid deep learning model approach for automated detection and classification of cassava leaf diseases by G. Sambasivam, G. Prabu kanna, Munesh Singh Chauhan, Prem Raja, Yogesh Kumar

“…The novelty of the hybrid model lies in its ability to combine DenseNet169’s feature reuse capability with EfficientNetB0’s computational efficiency, resulting in improved accuracy and scalability. …”
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A multi-robot collaborative manipulation framework for dynamic and obstacle-dense environments: integration of deep learning for real-time task execution by Afnan Ahmed Adil, Saber Sakhrieh, Jinane Mounsef, Noel Maalouf

“…This multirobot architecture is adaptable, allowing configuration of team size for collaborative tasks based on load requirements and environmental complexity. By integrating computer vision and deep learning for visual processing, and YOLOv2 for object detection, the system efficiently identifies, picks, and transports objects to designated locations, demonstrating the scalability of multi-robot framework for future applications in logistics automation, collaborative manufacturing, and dynamic human-robot interaction scenarios.…”
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Designing a model of the role of social media in crisis management and digital supply chain resilience by Farhad Jahangiri, Abolfazl Danaei, Mahsa Akbari, Younos Vakil Alroaia

“…The smallest disruption in the process of a supply chain can be likened to a fault. …”
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