Advances in Automated Voice Pathology Detection: A Comprehensive Review of Speech Signal Analysis Techniques by Anitha Sankaran, Lakshmi Sutha Kumar

“…The speech signals are also fed to a deep network, a 2D-Convoultional Neural Network-Long Short Term Memory model and a comparative analysis of the performance metrics is performed.…”
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MPFM-VC: A Voice Conversion Algorithm Based on Multi-Dimensional Perception Flow Matching by Yanze Wang, Xuming Han, Shuai Lv, Ting Zhou, Yali Chu

“…Experimental results for both speech and singing voice conversion tasks show that MPFM-VC achieves competitive performance compared to existing state-of-the-art VC models in both subjective and objective evaluation metrics. …”
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WDM-UNet: A Wavelet-Deformable Gated Fusion Network for Multi-Scale Retinal Vessel Segmentation by Xinlong Li, Hang Zhou

“…To preserve fine structural details and facilitate contextual information flow across layers, the model incorporates skip connections with a hierarchical fusion strategy, enabling the effective integration of shallow and deep features. …”
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Objects recognition from traffic video data using improved 2D convolutional stochastic configuration networks by Qinxia Wang, Yue Qiu, Weiqiang Qu, Dianhui Wang

“…The proposed improved 2DConSCN method greatly reduces the number of parameters, and the trained model can quickly obtain results on test data. Experiments are performed on a rail transit dataset, the comparison results show that the proposed method gets better performance in the recognition task, showing its great potential to meet the requirement of railway monitoring.…”
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Antimicrobial resistance in diverse urban microbiomes: uncovering patterns and predictive markers by Rodolfo Brizola Toscan, Wojciech Lesiński, Piotr Stomma, Balakrishnan Subramanian, Paweł P. Łabaj, Witold R. Rudnicki, Witold R. Rudnicki

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Electric vehicle charging station demand prediction model deploying data slotting by A.V. Sreekumar, R.R. Lekshmi

“…Employing such techniques affects the model's forecast accuracy. This article performs data-slotting during pre-processing stage and then selects the best among 1-h, 2-h, 3-h and 4-h slots, to frame the feature vectors. …”
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Ensemble Machine Learning Classifiers Combining CT Radiomics and Clinical-Radiological Features for Preoperative Prediction of Pathological Invasiveness in Lung Adenocarcinoma Pres... by Yunhua Li BS, Jianbang Ding MS, Kun Wu MS, Wanyin Qi BS, Shanyue Lin BS, Gangwen Chen BS, Zhichao Zuo PhD

“…We systematically evaluated both single-algorithm classifiers and ensemble approaches (including hard/soft voting and stacking), incorporating both the radiomic score and clinical-radiological features. Results Among the various evaluated machine learning models, the stacking classifier, which combines radiomic scores and clinical-radiological features, performed the best, achieving an AUC of 0.84, an accuracy of 0.817, an F1 score of 0.869, a precision of 0.818, and a recall of 0.926. …”
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Mandibular condyle detection using deep learning and double attractor-based energy valley optimizer algorithm by Mohamed Abd Elaziz, Abdelghani Dahou, Mushira Dahaba, Dina Mohamed ElBeshlawy, Mohammed Azmi Al-Betar, Mohammed A. Al-qaness, Ahmed A. Ewees, Arwa Mousa

“…Subsequently, leveraging a sophisticated deep learning model, we extract salient features from the identified ROI. …”
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Workplace Preference Analytics Among Graduates by Sin-Yin Ong, Choo-Yee Ting, Hui-Ngo Goh, Albert Quek, Chin-Leei Cham

“…Notably so, results from this study demonstrate that using Random Forest Algorithm resulted in better performance in predicting employment status with an accuracy rate of 99.40%, predicting company type with 66.60% and lastly predicting company sector with 30.80% when compared to other predictive models utilized during our research work's project lifecycle phase.…”
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Large-Scale Hyperspectral Image-Projected Clustering via Doubly Stochastic Graph Learning by Nian Wang, Zhigao Cui, Yunwei Lan, Cong Zhang, Yuanliang Xue, Yanzhao Su, Aihua Li

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Plucking Point and Posture Determination of Tea Buds Based on Deep Learning by Chengju Dong, Weibin Wu, Chongyang Han, Zhiheng Zeng, Ting Tang, Wenwei Liu

“…Finally, the plucking posture was obtained according to the results of the feature points matching. The matching results on the test dataset show that the PIRM has superior performance, with a matching accuracy of 99.229% and an average matching time of 2.363 milliseconds. …”
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LEM-Detector: An Efficient Detector for Photovoltaic Panel Defect Detection by Xinwen Zhou, Xiang Li, Wenfu Huang, Ran Wei

“…LFA effectively improves model training performance and robustness. Furthermore, the Efficient Feature Enhancement Module (EFEM) is presented to enhance the receptive field, suppress redundant information, and emphasize meaningful features. …”
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Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance by M. Elhoseny, Deepak Dasaratha Rao, Bala Dhandayuthapani Veerasamy, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

“…From the analysis, it clearly shows that proposed method accomplished better results in terms of accuracy, precision and specificity of 97.78%, 93.76% and 93.43%, respectively, when compared with various conventional models with respect to diverse performance measures.…”
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Employing transfer learning for breast cancer detection using deep learning models. by Frimpong Twum, Charlyne Carol Eyram Ahiable, Stephen Opoku Oppong, Linda Banning, Kwabena Owusu-Agyemang

“…This study proposes a novel model based on the four pretrained deep learning models, Mobilenetv2, Inceptionv3, ResNet50, and VGG16, which were also used as feature extractors and fed on multiple supervised learning models using the BUSI dataset. …”
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Sentiment works in small-cap stocks: Japanese stock’s sentiment with language models by Masahiro Suzuki, Yasushi Ishikawa, Masayuki Teraguchi, Hiroki Sakaji

“…The DeBERTaV2 model trained on Economy Watchers Survey data performed best in terms of returns at the highest sentiment quantile.…”
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Empowering Diagnostics: An Ensemble Machine Learning Model for Early Liver Disease Detection by Abdulrahman Ahmed Jasim, Hajer Alwindawi, Layth Rafea Hazim

“…In this study, we present a robust ensemble learning framework applied to the Indian Liver Patient Dataset, incorporating systematic data cleaning, normalization, and Synthetic Minority Over‑Sampling (SMOTE) to address missing values, outliers, and class skew. We then perform correlation-based feature reduction before training a stacking classifier that combines Random Forest, XGBoost, and ExtraTrees base learners with an ExtraTrees meta‑learner. …”
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Fuzzy Computation Tree Temporal Logic with Quality Constraints and Its Model Checking by Xianfeng Yu, Yongming Li, Shengling Geng, Huirong Li

“…We provide a comprehensive definition of QFCTL’s syntax, conduct an in-depth analysis of its logical characteristics, outline a precise model checking algorithm for QFCTL, and perform a meticulous complexity assessment of said algorithm. …”
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Vascular dysfunction in a mouse model of Rett syndrome and effects of curcumin treatment. by Anna Panighini, Emiliano Duranti, Ferruccio Santini, Margherita Maffei, Tommaso Pizzorusso, Niccola Funel, Stefano Taddei, Nunzia Bernardini, Chiara Ippolito, Agostino Virdis, Mario Costa

“…A relevant, and so far unexplored feature of RTT patients, is a marked reduction in peripheral circulation. …”
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INFORMATION MODELING OF ORGANIZATION OF BRIDGES’ CONSTRUCTION UNDER STOCHASTIC UNCERTAINTY OF TIME PARAMETERS by T. V. Bobrova, M. S. Ratanin, E. P. Timofeeva

“…The algorithm for informational modeling of bridge construction organization is developed. …”
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Evolutionary modeling reveals that value-oriented knowledge creation behaviors reinvent jobs by Yihang Cheng, Zhaoqi Yang, Yuan Cheng, Yong Ge, Hengshu Zhu

“…This model incorporates dynamic knowledge creation behaviors and is validated using a substantial dataset from a leading online recruitment platform in China, featuring over 20 million job postings and 1 million skill-related keywords. …”
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