Predicting lncRNA and disease associations with graph autoencoder and noise robust gradient boosting by Lili Tang, Liangliang Huang, Yi Yuan

“…Subsequently, the performance of LDA-GARB against LDA-LNSUBRW, GAMCLDA, LDA-VGHB, LDAGM, and GANLDA on imbalanced data was evaluated. We also performed parameter sensitivity analysis and ablation experiments. …”
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RootTracer: An intuitive solution for root image annotation by Maichol Dadi, Annalisa Franco, Giuseppe Sangiorgi, Silvio Salvi, Alessandra Lumini

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Adaptive DecayRank: Real-Time Anomaly Detection in Dynamic Graphs with Bayesian PageRank Updates by Ocheme Anthony Ekle, William Eberle, Jared Christopher

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CoCEC: An Automatic Combinational Circuit Equivalence Checker Based on the Interactive Theorem Prover by Wilayat Khan, Farrukh Aslam Khan, Abdelouahid Derhab, Adi Alhudhaif

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Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees by Shobha Aswal, Neelu Jyothi Ahuja, Ritika Mehra

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Consensus-Based Load Frequency Control of a Multi-Area Power System by Ravi Patel, Chathura Wanigasekara, Akshya Swain, Abhisek Ukil

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A CNN-Based Indoor Positioning Algorithm for Dark Environments: Integrating Local Binary Patterns and Fast Fourier Transform with the MC4L-IMU Device by Nan Yin, Yuxiang Sun, Jae-Soo Kim

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Development of a Smart Lock System using QR Code Technology by Mary Adedoyin, Farouq Olukoya

“… A smart lock system refers to a modern security solution that enables users to remotely control access to their homes or businesses using a smart device such as smartphone, tablet, or computer. This paper presents the development of a smart lock system using Quick Response (QR) code technology to address the problem of insecurity, inconvenience, and inflexibility in access control. …”
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An optimized LSTM-based deep learning model for anomaly network intrusion detection by Nitu Dash, Sujata Chakravarty, Amiya Kumar Rath, Nimay Chandra Giri, Kareem M. AboRas, N. Gowtham

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Abnormality detection in nailfold capillary images using deep learning with EfficientNet and cascade transfer learning by Mona Ebadi Jalal, Omar S. Emam, Cristián Castillo-Olea, Begoña García-Zapirain, Adel Elmaghraby

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Bio-control of Chocolate spot disease of Faba bean using potential rhizobacterial strains under field conditions in Northwestern Ethiopia by Gebeyehu Y. Mengstie, Zewdu T. Awlachew, Atsede M. Degefa

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Adaptive image encryption approach using an enhanced swarm intelligence algorithm by Sachin Minocha, Suvita Rani Sharma, Birmohan Singh, Amir H. Gandomi

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Reimagining falls prevention with insights from systems mapping on the use of millimetre-wave radar for remote health monitoring by Elif Dogu, José A. Paredes, Akram Alomainy, Janelle M. Jones, Khalid Z. Rajab

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Robust Anti-Jamming Method for Large-Array Radar Systems Using Deep Learning Based Null-Space Beamforming by Jaehyuk Lim, Hogeun Yoo, Euihyuk Lee, Sunjin Oh, Jaehoon Lee

“…The proposed method combines the computational simplicity of null-space beamforming with the adaptability of deep learning to effectively suppress interference and maintain a high signal-to-interference-plus-noise ratio (SINR). …”
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An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…This work advances large-scale UAV mission planning by offering a scalable, adaptive, and computationally efficient solution.…”
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Morphological-Priors-Guided Network With Semantic Booster and Scalable Bins Module for Height Estimation From Single-View Remote Sensing Images by Tao Zhang, Furong Shi, Yuanping Zhu

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A hybrid approach for cervical cancer detection: Combining D-CNN, transfer learning, and ensemble models by Abu Hanzala, Tanjila Akter, Md. Sadekur Rahman

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Simultaneous Learning Knowledge Distillation for Image Restoration: Efficient Model Compression for Drones by Yongheng Zhang

“…This dual-teacher approach enables the student model to learn from both degraded and clean images simultaneously, achieving robust image restoration while significantly reducing computational complexity. Experimental evaluations across five benchmark datasets and three restoration tasks—deraining, deblurring, and dehazing—demonstrate that, compared to the teacher models, the SLKD student models achieve an average reduction of 85.4% in FLOPs and 85.8% in model parameters, with only a slight average decrease of 2.6% in PSNR and 0.9% in SSIM. …”
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Botnet detection in internet of things using stacked ensemble learning model by Mudasir Ali, Muhammad Faheem Mushtaq, Urooj Akram, Daniel Gavilanes Aray, Manuel Masias Vergara, Hanen Karamti, Imran Ashraf

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Modified Whale Optimization Algorithm for Multiclass Skin Cancer Classification by Abdul Majid, Masad A. Alrasheedi, Abdulmajeed Atiah Alharbi, Jeza Allohibi, Seung-Won Lee

“…A more effective feature selection methodology improves accuracy and reduces computational overhead while maintaining robust performance. …”
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