Toward Seamless Localization: Situational Awareness Using UWB Wearable Systems and Convolutional Neural Networks by Ghazaleh Kia, David Plets, Ben Van Herbruggen, Eli De Poorter, Jukka Talvitie

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Reverse Correlation Characterizes More Complete Tinnitus Spectra in Patients by Nelson V. Barnett, Alec Hoyland, Divya A. Chari, Benjamin Parrell, Adam C. Lammert

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Time anomaly detection in the duration of civil trials in Italian justice by Antonio Esposito, Beniamino Di Martino, Rosario Ammendolia, Pietro Lupi, Massimo Orlando, Wei Liang

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Non-destructive detection of pre-incubated chicken egg fertility using hyperspectral imaging and machine learning by Md Wadud Ahmed, Asher Sprigler, Jason Lee Emmert, Ryan N Dilger, Girish Chowdhary, Mohammed Kamruzzaman

“…The CatBoost models with fewer important features showed good prediction performance, making them computationally efficient, robust, and interpretable. …”
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Species distribution model performance improves when habitat characterizations are centered on detected individuals instead of observers by Fang-Yu Shen, Fiona Victoria Stanley Jothiraj, Rebecca A. Hutchinson, Tyler A. Hallman, Jenna R. Curtis, W. Douglas Robinson

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A Hybrid Speech Enhancement Technique Based on Discrete Wavelet Transform and Spectral Subtraction by Yasir Iqbal, Tao Zhang, Teddy Surya Gunawan, Agus Pratondo, Xin Zhao, Yanzhang Geng, Mira Kartiwi, Nasir Saleem, Sami Bourouis

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MACHINE LEARNING TECHNIQUES FOR RETINOPATHY DETECTION IN DIABETIC PATIENTS by Ajay Kushwaha, Ahankari Sachin Suresh, Chennoju Phanindra, Anil Kumar Sahu, Devanand Bhonsle, Yamini Chouhan

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Data augmentation using SMOTE technique: Application for prediction of burst pressure of hydrocarbons pipeline using supervised machine learning models by Afzal Ahmed Soomro, Ainul Akmar Mokhtar, Masdi B. Muhammad, Mohamad Hanif Md Saad, Najeebullah Lashari, Muhammad Hussain, Abdul Sattar Palli

“…Traditional methods have limitations, including high experimental costs, conservative empirical models, and computationally expensive numerical algorithms. Machine learning (ML) models have supplanted traditional methods in recent years. …”
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Benchmarking reinforcement learning and accurate modeling of ground source heat pump systems: Intelligent strategy using spiking recurrent neural network combined with spider WASP... by Sana Qaiyum, Kashif Irshad, Mohamed E. Zayed, Salem Algarni, Talal Alqahtani, Asif Irshad Khan

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A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein by Bahareh Behkamal, Fatemeh Asgharian Rezae, Amin Mansoori, Rana Kolahi Ahari, Sobhan Mahmoudi Shamsabad, Mohammad Reza Esmaeilian, Gordon Ferns, Mohammad Reza Saberi, Habibollah Esmaily, Majid Ghayour-Mobarhan

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Diagnostic performance of biopsy-based methods for determination of Helicobacter pylori infection in dyspeptic Mozambican patients by Nashon D Majaliwa, Muhammad Ismail, Edília Botão, Carla Carrilho, Regina Victor, Luzmira Dimande, Sheila Machatine, Liana Mondlane, Elisa Taviani, Jorge MB Vítor, Filipa F Vale, Jahit Sacarlal

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A New Framework to Reduce Doctor’s Workload for Medical Image Annotation by Yang Deng, Yao Sun, Yongpei Zhu, Yue Xu, Qianxi Yang, Shuo Zhang, Zhanyu Wang, Jirang Sun, Weiling Zhao, Xiaobo Zhou, Kehong Yuan

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Stent graft treatment for ruptured pseudoaneurysms of the splanchnic arteries after pancreaticoduodenectomy: a case report by Masaru Nemoto, Ken Koyama, Midori Enokido, Shohei Kudo, Fuyo Yoshimi

“…On postoperative day 85, computed tomography revealed the presence of air within the latter stent graft, which indicated infection of the stent graft. …”
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Microcirculatory disorders in patients with coronary heart disease and type 2 diabetes by Yu. N. Belenkov, E. V. Privalova, A. A. Shchendrygina, I. S. Chekneva, T. V. Emelyanova

“…We evaluated functional (occlusion index (IO)) and structural disorders (refl ection index (RI,%) of arterioles. …”
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SCoralDet: Efficient real-time underwater soft coral detection with YOLO by Zhaoxuan Lu, Lyuchao Liao, Xingang Xie, Hui Yuan

“…Second, we integrate lightweight components such as GSConv and VoV-GSCSP to reduce computational overhead without sacrificing performance. …”
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Performance-Based Design Assessment of a Chilean Prescriptive R.C. Shear Wall Building Using Nonlinear Static Analysis by Mario Gutiérrez, Juan C. Vielma-Quintero, Jorge Carvallo, Juan C. Vielma

“…In Chile, where reinforced concrete shear wall buildings are the predominant structural typology, evaluating their seismic response beyond traditional linear methodologies is crucial. …”
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A Novel Multi-Task and Ensembled Optimized Parallel Convolutional Autoencoder and Transformer for Speech Emotion Recognition by Zahra Sharifzadeh Jafari, Sanaz Seyedin

“…Recognizing the emotions from speech signals is very important in different applications of human-computer-interaction (HCI). In this paper, we present a novel model for speech emotion recognition (SER) based on new multi-task parallel convolutional autoencoder (PCAE) and transformer networks. …”
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Laparoscopic partial nephrectomy for the management of large renal tumors: Experience at a tertiary care hospital by Truong TT, Le QH, Le HQ, Nguyen VT, Giang NP, Trang TM

“…Background: Laparoscopic partial nephrectomy is increasingly replacing open surgery as a standard, yet technically demanding, treatment for kidney tumors. The study aimed to evaluate some characteristics of large kidney tumors and results of retroperitoneal laparoscopic partial nephrectomy for large kidney tumors at a provincial general hospital. …”
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Uncertainty-Aware Parking Prediction Using Bayesian Neural Networks by Alireza Nezhadettehad, Arkady Zaslavsky, Abdur Rakib, Seng W. Loke

“…Although BNNs have shown promise in other domains, they remain underutilised in parking prediction—likely due to the computational complexity and the absence of real-time context integration in earlier approaches. …”
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A new metaheuristic algorithm for solving multi-objective single-machine scheduling problems by Khraibet Tahani Jabbar, Kalaf Bayda Atiya, Mansoor Wafaa

“…The MCA is further integrated with the traditional branch-and-bound (BAB) method, utilizing it as an upper bound to significantly improve the accuracy and efficiency of the solutions. Comprehensive computational experiments were conducted to evaluate the MCA’s performance against state-of-the-art algorithms, including the bald eagle search optimization algorithm (BESOA) and the standalone BAB method. …”
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