Brain tumor detection through image fusion using whale optimization and edge preserving filter by Bhattiprolu Nagasirisha, Venkatesh Munagala, Ramakrishna Reddy Eamani, Mocherla Venkata Srikanth, Asileti Suneel Kumar, Varre Venkata Kanaka Durga Prasad

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Acoustic Emission as a Method for Analyzing Changes and Detecting Damage in Composite Materials During Loading by Katarzyna PANASIUK, Krzysztof DUDZIK, Grzegorz HAJDUKIEWICZ

“…The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. …”
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SILVERRUSH. XIV. Lyα Luminosity Functions and Angular Correlation Functions from 20,000 Lyα Emitters at z ∼ 2.2–7.3 from up to 24 deg2 HSC-SSP and CHORUS Surveys: Linking the Postr... by Hiroya Umeda, Masami Ouchi, Satoshi Kikuta, Yuichi Harikane, Yoshiaki Ono, Takatoshi Shibuya, Akio K. Inoue, Kazuhiro Shimasaku, Yongming Liang, Akinori Matsumoto, Shun Saito, Haruka Kusakabe, Yuta Kageura, Minami Nakane

“…We present luminosity functions (LFs) and angular correlation functions (ACFs) derived from 18,960 Ly α emitters (LAEs) at z  = 2.2−7.3 over a wide survey area of ≲24 deg ^2 that are identified in the narrowband data of the HSC-SSP and CHORUS surveys. …”
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LMGD: Log-Metric Combined Microservice Anomaly Detection Through Graph-Based Deep Learning by Xu Liu, Yuewen Liu, Miaomiao Wei, Peng Xu

“…Therefore, there is an urgent need for fast and accurate anomaly detection capabilities. However, the existing microservice anomaly detection methods do not pay attention to the multi-source data of the microservice system and thus have low accuracy. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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Evaluating machine learning-based intrusion detection systems with explainable AI: enhancing transparency and interpretability by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Machine Learning (ML)-based Intrusion Detection Systems (IDS) are integral to securing modern IoT networks but often suffer from a lack of transparency, functioning as “black boxes” with opaque decision-making processes. …”
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Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

“…The Industrial Internet of Things (IIoT) faces significant cybersecurity threats due to its ever-changing network structures, diverse data sources, and inherent uncertainties, making robust intrusion detection crucial. …”
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Detection of Greenhouse and Typical Rural Buildings with Efficient Weighted YOLOv8 in Hebei Province, China by Bingkun Wang, Zhiyuan Liu, Jiangbo Xi, Siyan Gao, Ming Cong, Haixing Shang

“…However, in rural and mountainous areas, the resolution and accessibility of remote sensing satellite images from a single source are poor, making it difficult to detect greenhouses and rural buildings effectively and automatically. …”
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Functional Elements of Entrusted Professional Activities for Dental Educators: Protocol for a Scoping Review by Noraini Abu Bakar, Nurhanis Syazni Roslan, Muhammad Ainul Haq, Yasmin Mustafa Byrnes, Muhamad Saiful Bahri Yusoff

“…ObjectiveThis paper presents a scoping review protocol aimed at systematically elucidating the extent, range, and nature of the literature on EPAs for dental educators, as evaluated in the included resources. This review seeks to answer the following research question: what are the key functional elements of EPAs for dental educators as described in the existing literature? …”
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Cross-Domain Communication Method Based on Load Balancing for SDNs by Xiaomao Wang, Yi Zhou, Feng Dan, Xian Yang

“…Therefore, the multi-domain control plane needs to consider more network resource states during the path selection, such as link weights, load saturation, and resource occupancy rates, in order to select the optimal paths to maximize the satisfaction of data plane requirements while maintaining network load balance. …”
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Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring by Kaitlin J. Palmer, Sam Tabbutt, Douglas Gillespie, Jesse Turner, Paul King, Dominic Tollit, Jessica Thompson, Jason Wood

“…Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. …”
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SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI by Ami Tsuchida, Martin Goubet, Philippe Boutinaud, Iana Astafeva, Victor Nozais, Pierre-Yves Hervé, Thomas Tourdias, Stéphanie Debette, Marc Joliot

“…An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL). …”
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Dual Function Radar and Communication Waveform Design Based on Sub-pulse Hybrid Modulation by Yu LIU, Junhao ZHANG, Xue YAO, Xianxiang YU, Guolong CUI

“…To address the low data rate issue in the design of Dual-Function Radar-Communication (DFRC) waveforms with radar detection as the primary function, this paper proposes an information modulation method for multiple sub-pulse structure waveforms called Sub-pulse Hybrid Modulation (SHM). …”
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User preference–based QoS-aware service function placement in IoT-Edge cloud by Briytone Mutichiro, Younghan Kim

“…We formulate the service function placement at the edge problem. We employ user service request patterns in terms of user preference and service selection probability to model service placement. …”
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Assessment of Changes in Executive Functions and Attention of Cadets as a Result of Military Parachute Jumping by Dariusz Jamro, Marek Kociuba, Maciej Lachowicz, Pawel Korytko, Grzegorz Zurek

“…Parachute jumping, as an intense stressor, mobilizes cognitive resources, which can lead to short-term improvements in executive functions. …”
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Finite mixtures of functional graphical models: Uncovering heterogeneous dependencies in high-dimensional data. by Qihai Liu, Kevin H Lee, Hyun Bin Kang

“…In this work, we propose finite mixtures of functional graphical models (MFGM), which detect the heterogeneous subgroups of the population and estimate single graph for each subgroup by considering the correlation structures. …”
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Diversity and Abundance of Breeding Birds, Habitat, and Nesting Substrate Selection in Urban Areas: A Relevant Case from the Southern Slope of the Mediterranean by Ikram Douini, Wafae Squalli, Ismail Mansouri, Mohamed Mounir, El-Mostafa Benka, Mohamed Dakki, Soumaya Hammada

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Multimodal imaging analysis and structure-function correlation in patients exposed to pentosan polysulfate sodium by Sandra Hoyek, Eleni Konstantinou, Francesco Romano, Darren Chen, Celine Chaaya, Magdalena G. Krzystolik, Daniel Hu, Rachel Huckfeldt, Demetrios G. Vavvas, Leo A. Kim, Jason Lee, Elise De, John B. Miller, Nimesh A. Patel

“…Purpose: To study the anatomic and functional retinal changes in patients exposed to pentosan polysulfate (PPS) using multimodal imaging and mesopic microperimetry. …”
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Fluorescent carbon quantum dots from Syzygium aromaticum as a selective sensor for Fe3+ and Cd2+ detection in aqueous solution by Said Ali Akbar, Muhammad Hasan, Muhammad Nazar, Ilham Zulfahmi, Edy Miswar, Muhammad Iqhrammullah, Zulkarnain Jalil

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A Surrogate Piecewise Linear Loss Function for Contextual Stochastic Linear Programs in Transport by Qi Hong, Mo Jia, Xuecheng Tian, Zhiyuan Liu, Shuaian Wang

“…We test our method with a binary route selection task—the simplest setting to isolate and assess the impact of our modeling approach on decision quality. …”
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