MDPNet: a dual-path parallel fusion network for multi-modal MRI glioma genotyping by Huaizhi Wang, Haichao Liu, Fang Du, Fang Du, Fang Du, Di Wang, Xianhao Huo, Jihui Tian, Lijuan Song, Lijuan Song, Lijuan Song

“…To mitigate the impact of data imbalance, we developed a cross-gene feature-sharing classifier and implemented an adaptive weighted loss function, substantially enhancing the model’s predictive performance.ResultsIn this study, each gene classification task was formulated as a binary classification problem. …”
Get full text

Unsupervised and Semi-Supervised Speech Recognition System: A Review by Mazin Al-Zakarya, Yusra Al-Irhaim

“…It looks at recent developments as well as problems in this area of study. This study looks into feature extraction, classifiers, and the structure of the speaker recognition system. …”
Get full text

Stabilization of Stochastic Dynamic Systems with Markov Parameters and Concentration Point by Taras Lukashiv, Igor V. Malyk, Venkata P. Satagopam, Petr V. Nazarov

“…This paper addresses the problem of optimal stabilization for stochastic dynamical systems characterized by Markov switches and concentration points of jumps, which is a scenario not adequately covered by classical stability conditions. …”
Get full text

Enhanced futures price-spread forecasting based on an attention-driven optimized LSTM network: integrating an improved grey wolf optimizer algorithm for enhanced accuracy by Yongli Tang, Zhenlun Gao, Zhongqi Cai, Jinxia Yu, Panke Qin

“…Benchmark tests on optimization problems validate IGWO’s superior convergence efficiency. …”
Get full text

Urologic Complications following Gynecologic Surgery in a Sub-Saharan West African Country by Dehi Boston Mian, Virginie Angoi, Raoul Kasse, Alexis Yao, Sophia Akinloye, Fatoumata Ampoh, Koffi N'Guessan, Serge Boni

“…The socio-demographic features, clinical data, intraoperative UTI features, and treatment outcome parameters were studied. …”
Get full text

Recognition of Facial Expressions of Different Emotional Intensities in Patients with Frontotemporal Lobar Degeneration by Roy P. C. Kessels, Lotte Gerritsen, Barbara Montagne, Nibal Ackl, Janine Diehl, Adrian Danek

“…Behavioural problems are a key feature of frontotemporal lobar degeneration (FTLD). …”
Get full text

Improving Boreal Summer Precipitation Predictions From the Global NMME Through Res34‐Unet by Xuan Tong, Wen Zhou, Jiangjiang Xia

“…Current seasonal forecasts are based mainly on numerical models, but raw forecasts suffer from systematic bias and under/overdispersion problems and cannot be directly used in applications. …”
Get full text

Practical guide to SHAP analysis: Explaining supervised machine learning model predictions in drug development by Ana Victoria Ponce‐Bobadilla, Vanessa Schmitt, Corinna S. Maier, Sven Mensing, Sven Stodtmann

“…We address this issue by providing a practical guide to SHapley Additive exPlanations (SHAP), a popular feature‐based interpretability method, which can be seamlessly integrated into supervised ML models to gain a deeper understanding of their predictions, thereby enhancing their transparency and trustworthiness. …”
Get full text

Quantum Statistical Effects on Warm Dark Matter and the Mass Constraint from the Cosmic Structure at Small Scales by Zhijian Zhang, Weikang Lin

“…The suppression of the small-scale matter power spectrum is a distinct feature of warm dark matter (WDM), which permits a constraint on the WDM mass from galaxy surveys. …”
Get full text

Multi-source information transmission and classification algorithm for equipment based on compressed sensing by Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU

“…Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.…”
Get full text

Multi-source information transmission and classification algorithm for equipment based on compressed sensing by Xiaohu ZHAO, Gang WANG, Boming SONG, Jiacheng YU

“…Aiming at the characteristics of various types of equipment in coal preparation plant and the dispersion of monitoring points,a multi-source information wireless transmission and classification algorithm for equipment based on compressed sensing was proposed.By constructing a multi-hop information transmission model,the information transmission problem was transformed into the compressed sensing problem of multi-path measurement signals,thereby the measurement matrix acquisition was transformed into the routing problem of the multi-hop information transmission model.Aiming at the large coherence of the obtained measurement matrix and affecting the signal reconstruction effect,the idea of random routing was introduced into the routing construction,and a random dynamic self-organizing routing algorithm was proposed.In order to solve the problem that the time domain features of the reconstructed signal were difficult to accurately classify the fault type,a new time domain feature,the total variation (TV) of the vibration signal,was introduced for the reconstructed signal,and the compensation distance estimation algorithm was adopted to verify the superiority of the introduction of indicators.The analysis of the measured data of the coal preparation plant shows that the proposed multi-source information transmission and classification algorithm can effectively improve the fault recognition accuracy under the condition of improving the real-time transmission efficiency of the monitoring data.…”
Get full text

Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority by Xiaoye Zhou, Yuhao Feng

“…Second, a two-stage hybrid algorithm is proposed for the problem model. In the first stage, the deep neural network and the grid search improved support vector machine algorithm (DNN-GSM-SVM) are used to screen and classify customer priority features, and in the second stage, adaptive large-scale neighborhood search improved genetic algorithms (ALNS-GA) are used to solve the problem of vehicle-drone joint distribution path planning problem. …”
Get full text

Furniture design based on image color extraction algorithm by Binglu Chen, Guanyu Chen, Qianqian Hu

“…The results revealed that in the foreground part, the correct rate of color match based on the design method was 95.7%, and in the background part, the correct rate of color match based on the design method was 94.81 %, which proved its effectiveness. The average feature point extraction time and the average feature point matching time of the design-based algorithm were 5.45 ms and 9.83 ms, respectively, which proved its high computational efficiency. …”
Get full text

A Capsule Decision Neural Network Based on Transfer Learning for EEG Signal Classification by Wei Zhang, Xianlun Tang, Xiaoyuan Dang, Mengzhou Wang

“…In order to solve the problem of feature distortion caused by EEG feature extraction algorithm, a deep capsule decision network was constructed. …”
Get full text

A Multisource Data Fusion Modeling Prediction Method for Operation Environment of High-Speed Train by Decang Li, Juhui Zhang, Ruxun Xu, Jianjun Meng, Jianming Wang, Xiaoqiang Chen, Xin Jia, Junhui Ma

“…Providing accurate and reliable railway regional environmental data is a key consideration in operation control and dynamic dispatching of high-speed train. However, there are problems of low reliability and high uncertainty in the single data processing of high-speed train operating area environment. …”
Get full text

SVMWPE-HLLE Based Fault Diagnosis Approach for Rolling Bearing by Chunhui Li, Youfu Tang, Guolin Xu

“…The high-dimensional matrix obtained by MPE feature extraction to pattern recognition was solved by introducing Hessian local linear embedding (HLLE) dimension reduction method, and the feature extraction method based on SVMWPE-HLLE was proposed. …”
Get full text

Digital security risk identification and model construction of smart city based on deep learning by Zhilei Zhao

“…In order to deal with these problems, this paper designs a flexible three-layer architecture framework, and introduces a new intrusion detection feature selection method that combines flock optimization (CSO) and genetic algorithm (GA) to reduce the complexity of feature selection and enhance the detection and processing power of security vulnerabilities through deep neural networks (DNN). …”
Get full text

Prioritizing image processing and big data analytics factors for software development using DEMATEL-choquet method in bipolar complex fuzzy context by Ruimin Ma

“…Abstract Bipolar complex fuzzy set (BCFS) theory is a newly developed framework for addressing real-world decision-making (DM) problems that involve ambiguous, uncertain, and dual-valued information. …”
Get full text

Machine Learning and Medical Data: Predicting ICU Mortality and Re-admission Risks by Runia Roy, Ulya Bayram

“…Four machine learning algorithms are applied to the finalized feature set to understand the difference between the binary and the multi-class classification problems. …”
Get full text

Hybrid Deep Learning Model for Cataract Diagnosis Assistance by Zonghong Feng, Kai Xu, Liangchang Li, Yong Wang

“…Therefore, this paper proposes a hybrid deep learning network for assisting in the diagnosis of cataract fundus images, attempting to solve the above problems and limitations. The network is based on the idea of transfer learning for feature extraction of fundus images, and introduces the Squeeze-and-Excitation (SE) module and prototype network for feature enhancement and classification, improving the model’s generalization ability for new disease samples. …”
Get full text