Biomechanical simulations of intracerebral hemorrhage expansion show tissue displacement has significant impact on electrical impedance tomography results by Antti Paldanius, Jussi Toivanen, Nina Forss, Daniel Strbian, Ville Kolehmainen, Jari Hyttinen

“…In-silico models are usually used for development and evaluation of algorithms for EIT image reconstruction. …”
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STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG by Raquel Fernández-Martín, Alfonso Gijón, Odile Feys, Elodie Juvené, Alec Aeby, Charline Urbain, Xavier De Tiège, Vincent Wens

“…This proof-of-concept study represents a first step towards the use of STIED and DL algorithms in the routine clinical MEG evaluation of epilepsy.…”
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Land Use/Land Cover Change Impact on Hydrological Process in the Upper Baro Basin, Ethiopia by Tewodros Getu Engida, Tewodros Assefa Nigussie, Abreham Berta Aneseyee, John Barnabas

“…Overall, LU/LC significantly affected the hydrological condition of the watershed. Therefore, different conservation strategies to maintain the stability and resilience of the ecosystem are vital.…”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…The performance of the ESN-EICM was compared to that of a standard ESN and a Long Short-Term Memory (LSTM) network. The evaluation used data from three discrete chaotic systems (Logistic, Sine, and Ricker) for both one-step and multi-step prediction tasks.ResultsThe experimental results indicate that the ESN-EICM produced lower error metrics (MSE, RMSE, MAE) compared to the standard ESN and LSTM models across the tested systems, with the performance difference being more pronounced in multi-step forecasting scenarios. …”
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Expression‐based machine learning models for predicting plant tissue identity by Sourabh Palande, Jeremy Arsenault, Patricia Basurto‐Lozada, Andrew Bleich, Brianna N. I. Brown, Sophia F. Buysse, Noelle A. Connors, Sikta Das Adhikari, Kara C. Dobson, Francisco Xavier Guerra‐Castillo, Maria F. Guerrero‐Carrillo, Sophia Harlow, Héctor Herrera‐Orozco, Asia T. Hightower, Paulo Izquierdo, MacKenzie Jacobs, Nicholas A. Johnson, Wendy Leuenberger, Alessandro Lopez‐Hernandez, Alicia Luckie‐Duque, Camila Martínez‐Avila, Eddy J. Mendoza‐Galindo, David Cruz Plancarte, Jenny M. Schuster, Harry Shomer, Sidney C. Sitar, Anne K. Steensma, Joanne Elise Thomson, Damián Villaseñor‐Amador, Robin Waterman, Brandon M. Webster, Madison Whyte, Sofía Zorilla‐Azcué, Beronda L. Montgomery, Aman Y. Husbands, Arjun Krishnan, Sarah Percival, Elizabeth Munch, Robert VanBuren, Daniel H. Chitwood, Alejandra Rougon‐Cardoso

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Investigation of deep learning image fusion techniques for medical imaging by Angayarkanni Veeraputhiran, Muthukumar Balamurugan, Varun P. Gopi

“…Experiments on the fusion of MRI and PET medical images are being conducted to evaluate performance, algorithm stability, and other parameters. …”
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Deep learning-based analysis of 12-lead electrocardiograms in school-age children: a proof of concept study by Shuhei Toba, Yoshihide Mitani, Yusuke Sugitani, Yusuke Sugitani, Hiroyuki Ohashi, Hirofumi Sawada, Mami Takeoka, Naoki Tsuboya, Kazunobu Ohya, Noriko Yodoya, Takato Yamasaki, Yuki Nakayama, Hisato Ito, Masahiro Hirayama, Motoshi Takao

“…The specificity of the deep learning-based model for detecting abnormal electrocardiograms was not significantly different from that of the conventional algorithm. …”
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L2D2: A Novel LSTM Model for Multi-Class Intrusion Detection Systems in the Era of IoMT by Gokhan Akar, Shaaban Sahmoud, Mustafa Onat, Unal Cavusoglu, Emmanuel Malondo

“…In this paper, we propose a novel approach for detecting various intrusion attacks targeting Internet of Medical Things (IoMT) devices, utilizing an enhanced version of the LSTM deep learning algorithm. To evaluate and compare the proposed algorithm with other methods, we used the CICIoMT2024 dataset, which encompasses various types of equipment and corresponding attacks. …”
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Speaker Recognition Using Wavelet Cepstral Coefficient, I-Vector, and Cosine Distance Scoring and Its Application for Forensics by Lei Lei, She Kun

“…Moreover, linear discriminant analysis (LDA) and the within-class covariance normalization (WCNN) are added to the CDS algorithm to deal with the channel variability problem. …”
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Contrastive Learning‑based Simplified Graph Convolutional Network Recommendation by YU Yuchen, WU Siqi, ZHAO Qinghua, WU Xuhong, WANG Lei

“…The algorithm was evaluated on Amazon-Book, Yelp2018, and Gowalla datasets. …”
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Heisenberg Group-Based Digital Signatures for Secure Communications by Najla Althuniyan, Ahmed Alamer, Awais Yousaf, Muhammad Waseem, Sarah Aljohani

“…This paper proposes a new digital signature algorithm that employs the Heisenberg group over a prime field and exploits its structure to provide strong cryptographic properties. …”
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Multiple UAV Swarms Collaborative Firefighting Strategy Considering Forest Fire Spread and Resource Constraints by Pei Zhu, Rui Song, Jiangao Zhang, Ziheng Xu, Yaqi Gou, Zhi Sun, Quan Shao

“…The critical water flow rate required for fire suppression is calculated to evaluate the firefight performance, and an emergency bidding algorithm is applied to enable multiple UAV swarms collaborative firefighting under limited resources, including different payloads per UAV and swarm number. …”
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Integrating Multiple RIS for Enhanced SWIPT-IoT Performance: Optimization Strategies by Neha Sharma, Sumit Gautam, Symeon Chatzinotas, Bjorn Ottersten

“…Numerical simulations are conducted to evaluate system performance highlight rate-energy trade-off across different scenarios, considering factors such as RIS angular placement, surfaces count, element count, separation distance, EH and data rate demands. …”
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AI approaches for phenotyping Alzheimer's disease and related dementias using electronic health records by Sara Knox, Stephanie Aghamoosa, Paul M. Heider, Maxwell Cutty, Andrew Wright, Dmitry Scherbakov, Gabriel Hood, Sara A. Nolin, Jihad S. Obeid

“…RESULTS A foundational LLM derived from Llama 2 demonstrated superior performance in identifying patients with ADRD (area under the curve [AUC] = 0.9534, F1 score 0.8571) compared to both the current standard CCW algorithm (AUC = 0.8482, F1 score 0.8323, although only the AUC was statistically significantly different) and other AI‐based models. …”
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Validation of Artificial Intelligence Computer-Aided Detection of Colonic Neoplasm in Colonoscopy by Hannah Lee, Jun-Won Chung, Kyoung Oh Kim, Kwang An Kwon, Jung Ho Kim, Sung-Cheol Yun, Sung Woo Jung, Ahmad Sheeraz, Yeong Jun Yoon, Ji Hee Kim, Mohd Azzam Kayasseh

“…When evaluating and comparing the polyp detection ability of ALPHAON^® with that of endoscopists with different levels of expertise (regarding years of endoscopic experience), it was found that ALPHAON^® outperformed the experts in accuracy (0.97, 95% CI: 0.96 to 0.99), sensitivity (0.91, 95% CI: 0.85 to 0.97), and specificity (0.99, 95% CI: 0.97 to 0.99). …”
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Optimal Midcourse Guidance with Terminal Relaxation and Range Convex Optimization by Jiong Li, Jinlin Zhang, Jikun Ye, Lei Shao, Xiangwei Bu

“…Additionally, a systematic comparison was conducted to evaluate the impact of different interpolation methods and discretization point quantities on algorithm performance.…”
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Dynamic Stability and Reactive Power Control Using Dandelion-Optimized Cascaded Fractional Order Tilt Controller in Renewable Energy Systems by G. M. Sachin, Abhik Banerjee, S. N. Deepa

“…The tunable parameters of the proposed controller are optimized using an improved dandelion optimization (DO) algorithm. The controller’s performance is evaluated by comparing its dynamic voltage characteristics with those of traditional controllers. …”
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Transceiver design and performance analysis for uplink SCMA based on CP-free OFDM by Li ZHOU, Xiqing LIU

“…A typical sparse code multiple access (SCMA) system utilizes orthogonal frequency division multiplexing (OFDM) technology with cyclic prefix (CP) to combat multipath fading in wireless channels.Therefore, its capacity is reduced by the CP-insertion.To address this issue, the SCMA scheme based on CP-free OFDM using the time domain precoding (TDP) algorithm was proposed and the proposed scheme was termed as TDP-OFDM SCMA.The transceiver structure was designed, and the capacity plus the bit error rate (BER) performances under various channels with different overload rates and with channel estimation errors were evaluated via the simulations.Also, the power consumption problem in TDP-OFDM SCMA was discussed.The simulation results show that under the same overload rate, the capacity of TDP-OFDM SCMA can be increased by up to 25% if compared with the SCMA based on CP-OFDM.…”
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Two-Timescale Cross-Layer Design for URLLC Over Parallel Fading Channels With Imperfect CSI by Hongsen Peng, Meixia Tao

“…Based on the small timescale optimization method, we adopt the ternary search algorithm to optimize the pilot length and pilot power through Monte Carlo evaluations in the large timescale. …”
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An improved particle swarm optimization for multilevel thresholding medical image segmentation. by Jiaqi Ma, Jianmin Hu

“…Besides, we used image segmentation quality metrics to evaluate the impact of different segmentation algorithms on images, and the experimental results show that the MRI images segmented by the CIWP-PSO has achieved the best fitness value more times than images segmented by other comparison algorithm in terms of Structured Similarity Index and Feature Similarity Index, which explains that the images segmented by CIWP-PSO has higher image quality.…”
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