Speaker Authentication Using Vector Quantization by Bushra Q. Al-Abudi, Mohammed S. Mahdi

“…The training phase concerned with enrolling the speaker models to build the codebook. The codebook generated from a set of feature vectors belong to each sample of speaker's voice. …”
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Robust Microarray Meta-Analysis Identifies Differentially Expressed Genes for Clinical Prediction by John H. Phan, Andrew N. Young, May D. Wang

“…Although microarrays have increased the rate of genomic data collection, sample size is still a major issue when identifying informative genetic biomarkers. Because of this, feature selection methods often suffer from false discoveries, resulting in poorly performing predictive models. …”
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A Method for Airborne Small-Target Detection with a Multimodal Fusion Framework Integrating Photometric Perception and Cross-Attention Mechanisms by Shufang Xu, Heng Li, Tianci Liu, Hongmin Gao

“…The proposed system achieves multimodal complementarity through two-phase integration: first by establishing cross-modal feature correspondences through attention-guided feature alignment, then performing weighted fusion based on photometric reliability assessment. …”
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Intelligent identification of electromagnetic radiation signals induced by coal rock fractures using machine learning by LI Baolin, FENG Jiaqi, WANG Enyuan, SUN Xinyu, WANG Shuowei

“…Machine learning algorithms, such as linear discriminant analysis, support vector machines, and ensemble learning methods, were utilized to develop intelligent identification models for effective and interference signals. A comparative analysis of the recognition accuracy across different models was performed. …”
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fruit-SALAD: A Style Aligned Artwork Dataset to reveal similarity perception in image embeddings by Tillmann Ohm, Andres Karjus, Mikhail V. Tamm, Maximilian Schich

“…Leveraging a systematic pipeline of generative image synthesis, this visually diverse yet balanced benchmark demonstrates salient differences in semantic category and style similarity weights across various computational models, including machine learning models, feature extraction algorithms, and complexity measures, as well as conceptual models for reference. …”
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Reconstruction of 12-lead ECG: a review of algorithms by Ekenedirichukwu N. Obianom, G. André Ng, G. André Ng, G. André Ng, G. André Ng, Xin Li, Xin Li, Xin Li

“…Linear and nonlinear (including artificial intelligence) algorithms showed promising performances. Their outputs had correlations of greater than 0.90 depending on how the reconstruction models were built.ConclusionThree leads are optimal as input predictors for minimal reconstruction errors, but there is no universal algorithm that applies to every reconstruction task. …”
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Frontiers in microfinance research for small and medium enterprises (SMEs) and microfinance institutions (MFIs): a bibliometric analysis by Francis Lwesya, Adam Beni Swebe Mwakalobo

“…Topics related to COVID-19, Islamic social finance, microfinance institutions, credit scoring models, crowdfunding, and entrepreneurial finance are likely to feature in the domain of microfinance and sustainability of MFIs in future.…”
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Using Machine Learning on Macroeconomic, Technical, and Sentiment Indicators for Stock Market Forecasting by Michalis Patsiarikas, George Papageorgiou, Christos Tjortjis

“…Initially, contextual data are scored using TextBlob and pre-trained DistilBERT-base-uncased models, and then a combined dataset is formed. Followed by preprocessing, feature engineering and selection techniques, three corresponding datasets are generated and their impact on future prices is examined, by employing ML models, such as Linear Regression (LR), Random Forest (RF), Gradient Boosting (GB), XGBoost, and Multi-Layer Perceptron (MLP). …”
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Global Clustering Quality Coefficient Assessing the Efficiency of PCA Class Assignment by Mirela Praisler, Stefanut Ciochina

“…We are proposing a set of indicators inspired from analytical geometry that may be used for an objective quantitative assessment of the data clustering quality as well as a global clustering quality coefficient (GCQC) that is a measure of the overall predictive power of the PCA models. The use of these indicators for evaluating the efficiency of the PCA class assignment is illustrated by a comparative study performed for the identification of the preprocessing function that is generating the most efficient PCA system screening for amphetamines based on their GC-FTIR spectra. …”
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Beyond the Hype Cycle: Experiments with ChatGPT’s Advanced Data Analysis at the Palo Alto City Library by M Ryan Hess and Chris Markman

“…The second goal of this experiment aimed to enhance our web user experience by revising our BiblioCommons taxonomy to better match customer interests and make the upcoming Personalized Promotions feature more relevant. ChatGPT helped us perform what would otherwise be a time-consuming analysis of customer catalog usage to determine a list of taxonomy terms better aligned with that usage. …”
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METHODOLOGICAL SEMINAR MADI-IGIP AS A FORMOF ENGINEERING PEDAGOGY DEVELOPMENT: HISTORY AND PROSPECTS by Zoya S. Sazonova

“…The teamwork contributes to the development of the significant objectives and to designing models of their achievements in terms of self8organization.…”
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Identification of zones of increased vibroacoustic emission by means of the inverse method by L. Stryczniewicz

“…Key words: acoustic modeling, inverse method, sound source. …”
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Towards reliable object representation via sparse directional patches and spatial center cues by Muwei Jian, Hui Yu

“…Inspired by the HVS mechanism, in this paper, we aimed to describe and exploit multiscale decomposition-based patch detection models for automatic visual feature representation and object localization in images. …”
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CINet: A Constraint- and Interaction-Based Network for Remote Sensing Change Detection by Geng Wei, Bingxian Shi, Cheng Wang, Junbo Wang, Xiaolin Zhu

“…Although many deep learning based RSCD models perform well, challenges remain in effectively extracting change information between dual-temporal images and fully leveraging interactions between their feature maps. …”
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Exosome-related genes influence the progression of stroke through neuroinflammatory responses by Boyan Zhao, Boyan Zhao, Jianing Wu, Mingyang Han, Xuan Rong, Jin Jin, Shiya Liu, Cheng Zhang, Ruotian Zhang, Xin Chen, Fei Peng, Xingli Dong, Shiguang Zhao, Shiguang Zhao

“…The least absolute shrinkage and selection operator regression and random forest models were performed to detect feature genes. Search Tool for the Retrieval of Interacting Genes and Cytoscape were employed to recognize the hub genes. …”
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Depression Analysis and Detection Using Machine Learning: Incorporating Gender Differences in a Comparative Study by Marina Galanina, Anna Rekiel, Anna BaCzyk, Bozena Kostek

“…This is achieved through the implementation of a tailored feature vector methodology. In most models, this approach led to measurable improvements: SVM improved by 1.43% (p =0.044), MLP-CNN by 7.25% (p =0.008), and Perceptron by 7.39% (p =0.05). …”
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Design and Implementation of a Bionic Marine Iguana Robot for Military Micro-Sensor Deployment by Gang Chen, Xin Tang, Baohang Guo, Guoqi Li, Zhengrui Wu, Weizhe Huang, Yidong Xu, Ming Lu, Jianfei Liang, Zhen Liu

“…Gait and trajectory planning are optimized using kinematic modeling for both terrestrial and aquatic locomotion. …”
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Visual WetlandBirds Dataset: Bird Species Identification and Behavior Recognition in Videos by Javier Rodriguez-Juan, David Ortiz-Perez, Manuel Benavent-Lledo, David Mulero-Pérez, Pablo Ruiz-Ponce, Adrian Orihuela-Torres, Jose Garcia-Rodriguez, Esther Sebastián-González

“…The proposed dataset comprises 178 videos recorded in Spanish wetlands, capturing 13 different bird species performing 7 distinct behavior classes. In addition, we also present baseline results using state of the art models on two tasks: bird behavior recognition and species classification.…”
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Semantics-Driven Migration of Java Programs: a Practical Experience by Artyom O. Aleksyuk, Vladimir M. Itsykson

“…For example, it may arise when a project should be ported to a more secure or feature-rich library, a new platform or a new version of an already used library. …”
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Neural network distillation of orbital dependent density functional theory by Matija Medvidović, Jaylyn C. Umana, Iman Ahmadabadi, Domenico Di Sante, Johannes Flick, Angel Rubio

“…Functionals treated in this way are then called global density approximations and can be seamlessly integrated with existing DFT workflows. Tests are performed for a dataset featuring a large variety of molecular structures and popular meta–generalized gradient approximation density functionals, where we successfully eliminate orbital dependencies coming from the kinetic energy density, and discover a high degree of transferability to a variety of physical systems. …”
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