A Novel Statistical Feature Analysis-Based Global and Local Method for Face Recognition by Mohammed Ahmed Talab, Suryanti Awang, Mohd Dilshad Ansari

“…Experimental results on Yale and FEI datasets validate the superiority of the proposed technique over the other top-performing feature analysis methods. …”
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Identification of an Immune Gene-Based Cisplatin Response Model and CD27 as a Therapeutic Target against Cisplatin Resistance for Ovarian Cancer by Ying Guo, Na Yang, Gang Li, Xiurong Yin, Lixia Dong

“…The expression profiles of cisplatin-sensitive and cisplatin-resistant OV specimens were integrated from multiple public datasets. The abundance scores of 22 immune cells were estimated with CIBERSORT algorithm. …”
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BACVC: Bi-adaptive and cross-view consistency for incomplete multi-view subspace clustering by Jiaqiyu Zhan, Yuesheng Zhu, Guibo Luo

“…Extensive experiments on four benchmark datasets show that BACVC outperforms eleven state-of-the-art methods, with improvements of up to 4.39%, 5.43%, and 3.95% in ACC, NMI, and purity, respectively. …”
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THE LIMBIC SYSTEM IN ADULT HUMAN BRAINS – COMPARATIVE MORPHOMETRIC ANATOMO-IMAGISTIC STUDY by Alin Horatiu Nedelcu, David-Constantin Bulgaru, Simona Alice Partene Vicoleanu, Razvan Tudor Tepordei, Cosmin Gabriel Popa, Roxana-Andreea Popa, Marius Constantin Moraru, Manuela Ursaru

“…Our study aims to demonstrate the variability of the components of the limbic system through their morphometric evaluation on anatomical parts and, respectively on CT images. 13 adult brains without known neurological abnormalities, fixed in 10% formalin solution for a minimum of 10 weeks, and 22 CT craniocerebral datasets of patients without any organic cerebral dysfunctions were evaluated. …”
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Empowering Urdu sentiment analysis: an attention-based stacked CNN-Bi-LSTM DNN with multilingual BERT by Lal Khan, Atika Qazi, Hsien-Tsung Chang, Mousa Alhajlah, Awais Mahmood

“…Various experiments have been conducted to evaluate the effectiveness of our proposed model on two Urdu sentiment analysis datasets named as UCSA-21 and UCSA, and an accuracies of 83.12% and 78.91% achieved, respectively.…”
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Travel route recommendation with a trajectory learning model by Xiangping Wu, Zheng Zhang, Wangjun Wan

“…Extensive experiments on four large real-world datasets demonstrate that TLMR outperforms existing methods in four key performance metrics. …”
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An Examination of the Leadership and Management Traits and Style in the Forest Fire Incident Command System: The Cyprus Forest Fire Service by Nicolas-George Homer Eliades, Achilleas Karayiannis, Georgios Tsantopoulos, Spyros Galatsidas

“…The research subject was addressed using mixed method research, employing quantitative and qualitative data. Both datasets were used to distinguish the purposes of the applied triangulation, enabling the examination of differentiation between the trends/positions recorded in terms of the object of study. …”
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Headline-Guided Extractive Summarization for Thai News Articles by Pimpitchaya Kositcharoensuk, Nakarin Sritrakool, Ploy N. Pratanwanich

“…Experiments on publicly available Thai news datasets demonstrate that CHIMA outperforms baseline models across ROUGE, BLEU, and F1 scores. …”
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Exploring the Mechanisms of Zhenbao Pills in the Treatment of Stroke through Network Pharmacology Combined with Mendelian Randomization by Yanhong Liu, Yunqi Hua, Xiaoe Jia

“…Furthermore, molecular docking and Gene Expression Omnibus (GEO) datasets were used for preliminary confirmation. Results: This study identified 14 core components and 105 stroke-related targets for ZBP. …”
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EdgeGuard: Decentralized Medical Resource Orchestration via Blockchain-Secured Federated Learning in IoMT Networks by Sakshi Patni, Joohyung Lee

“…EdgeGuard outperforms existing solutions in terms of computational performance, data value, and privacy protection across a wide range of real-world medical datasets. This work enhances safe, effective, and privacy-preserving medical data management in IoMT ecosystems while maintaining outstanding standards for data security and resource efficiency, enabling large-scale collaborative learning in healthcare.…”
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Optimizing healthcare big data performance through regional computing by Tariq Alsahfi, Afzal Badshah, Omar Ibrahim Aboulola, Ali Daud

“…The migration of large datasets to centralized cloud infrastructures often results in latency, which impedes real-time applications. …”
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Addressing Missing Data in Slope Displacement Monitoring: Comparative Analysis of Advanced Imputation Methods by Seungjoo Lee, Yongjin Kim, Bongjun Ji, Yongseong Kim

“…This study addresses these challenges by evaluating advanced machine learning models—SAITS, ImputeFormer, and BRITS (Bidirectional Recurrent Imputation for Time Series)—for missing data imputation in slope displacement datasets. Sensors installed at two field locations, Yangyang and Omi, provided high-resolution displacement data, with approximately 34,000 data points per sensor. …”
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Unleashing the power of pinyin: promoting Chinese named entity recognition with multiple embedding and attention by Jigui Zhao, Yurong Qian, Shuxiang Hou, Jiayin Chen, Kui Wang, Min Liu, Aizimaiti Xiaokaiti

“…We conducted experiments on four standard Chinese NER benchmark datasets, and the results show that our method outperforms most baselines, demonstrating the effectiveness of our proposed model.…”
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A Comparative Study Evaluated the Performance of Two-class Classification Algorithms in Machine Learning by Shilan Abdullah Hassan, Maha Sabah Saeed

“…By leveraging Azure Machine Learning's capabilities, researchers and healthcare professionals can analyze large datasets containing patient information and medical records to identify patterns and risk factors associated with heart attacks. …”
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First-principles based data-driven strain engineering for ferroelectrics via active machine learning: A nonlinear piezoelectric constitutive equation by Susumu MINAMI, Yasuaki MARUYAMA, Yoshimasa ABE, Tomohiro NAKAYAMA, Takahiro SHIMADA

“…We demonstrated the active learning technique to successfully and efficiently construct an accurate machine learning model for ferroelectric PbTiO3 with minimal first-principles datasets (only 3.7% of the vast strain-space). Our machine learning model can accurately predict the nonlinear mechanical deformation and electromechanical response in the three components of normal strain loading. …”
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Image Quality and Dose Comparison of Single-Energy CT (SECT) and Dual-Energy CT (DECT) by Ramin Ghasemi Shayan, Maryam Oladghaffari, Fakhrosadat Sajjadian, Mona Fazel Ghaziyani

“…The concept of dual-energy computed tomography (DECT) is almost as old as the CT technology itself; DECT initially required substantially higher radiation doses (nearly two times higher than those employed in single-energy CT) and presented problems associated with spatial misregistration of the two different kV image datasets between the two separate acquisitions. The basic principles of single-energy and dual-energy computed tomography and their important physical differences can cause better diagnostic evaluation. …”
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Rapid Identification of Saline–Alkali Stress-Tolerant Peanut Varieties Based on Multimodal Data by Fan Zhang, Longgang Zhao, Tingting Guo, Ziyang Wang, Peng Lou, Juan Li

“…Specifically, the research first established multimodal datasets for peanuts at different growth stages and constructed a saline–alkali stress score standard based on unsupervised learning. …”
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Tibetan–Chinese speech-to-speech translation based on discrete units by Zairan Gong, Xiaona Xu, Yue Zhao

“…This evolution has been driven by advancements in model performance and the expansion of cross-lingual speech datasets. Despite the paucity of research on Tibetan speech translation, this paper endeavors to tackle the challenge of Tibetan-to-Chinese direct speech-to-speech translation within the multi-task learning framework, employing self-supervised learning (SSL) and sequence-to-sequence model training. …”
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TMFN: a text-based multimodal fusion network with multi-scale feature extraction and unsupervised contrastive learning for multimodal sentiment analysis by Junsong Fu, Youjia Fu, Huixia Xue, Zihao Xu

“…Experimental results show that our proposed model outperforms the state-of-the-art models in MSA on two benchmark datasets.…”
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The algorithm for foggy weather target detection based on YOLOv5 in complex scenes by Zhaohui Liu, Wenshuai Hou, Wenjing Chen, Jiaxiu Chang

“…The comparative experimental results on the RTTS and Foggy Driving datasets indicate that the YOLOv5-RCBiW model significantly outperforms existing models in object detection accuracy under foggy and complex scenes. …”
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