Edge-optimized multimodal cross-fusion architecture for efficient crop disease detection by Thomas Kinyanjui Njoroge, Kelvin Mugoye Shindu, Rachael Kibuku

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Depression and Anxiety Screening for Pregnant Women via Free Conversational Speech in Naturalistic Condition by Rafael T. Sousa, Gustavo D. M. Silva, Paula L. L. Pinto, Juliano Backes, Amanda S. Mota, Thiago M. Paixao, Maria G. S. Teixeira, Wilian H. Hisatugu, Anilton S. Garcia, Kelly S. Prado, Rodrigo S. Dias, Marco A. Galletta, Hermano Tavares

“…Machine learning algorithms were utilized combined with different audio feature sets to analyze these recordings in conjunction with PHQ-4 questionnaire scores. …”
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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…Initially, data is passed through preprocessing to address outliers and missing values. In addition, we developed a novel hybrid feature selection model that combined correlation filtering with mutual information, Cross-Validation (CV) along with Recursive Feature Eliminatio (RFE) (R, and stability selection to identify the most impactful features. …”
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Efficient approximate Bayesian inference for quantifying uncertainty in multiscale animal movement models by Majaliwa M. Masolele, J. Grant C. Hopcraft, Colin J. Torney

“…In our simulations, individuals respond to two environmental covariates and we employ all combinations of positive and negative selection coefficients corresponding to attraction to an environmental feature and avoidance of an environmental feature, respectively. …”
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A multi-module enhanced YOLOv8 framework for accurate AO classification of distal radius fractures: SCFAST-YOLO by Yu Wang, Haifu Sun, Tiankai Jiang, JunFeng Shi, JunFeng Shi, Qin Wang, Qin Wang, Hongwei Yang, Hongwei Yang, Yusen Qiao

“…Secondly, we develop the C2f-Faster-EMA module that preserves fine-grained spatial details through optimized information pathways and statistical feature aggregation. …”
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Incorporating edge convolution and correlative self-attention into graph neural network for material properties prediction by Zexi Yang, Qi Yu, Yapeng Zhan, Jiying Liu

“…Indeed, even the periodic patterns of the crystal structures are not seriously considered. …”
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A hybrid deep learning model EfficientNet with GRU for breast cancer detection from histopathology images by M. Pradeepa, B. Sharmila, M. Nirmala

“…This study aims to develop a high-performance deep learning framework for accurate classification of breast cancer in histopathology images, addressing limitations in feature extraction and spatial dependency modeling. …”
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Integration of geospatial techniques and machine learning in land parcel prediction by Nekkanti Haripavan, Subhashish Dey, Chimakurthi Harika Mani Chandana

“…By harnessing the temporal and spectral information captured by Earth observation satellites, we aim to identify patterns and trends in land parcel changes. These insights are used to train and fine-tune our machine learning models, which will subsequently forecast future land parcel developments. …”
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SHIFA: SBERT-Based Healthcare Information Focused Arabic Question Answering by Rahaf Alruwaithi, Sarah AlHumoud

“…The idea behind this research is to use the SBERT method for entities and context patterns to effectively capture the semantics between QA pairs in two different ways: the feature extractor and the transfer learning model. …”
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Potential of EnMAP Hyperspectral Imagery for Regional-Scale Soil Organic Matter Mapping by Yassine Bouslihim, Abdelkrim Bouasria

“…Partial Least Squares Regression (PLSR) models were developed under different pre-treatment scenarios. …”
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ADA-NAF: Semi-Supervised Anomaly Detection Based on the Neural Attention Forest by Andrey Ageev, Andrei Konstantinov, Lev Utkin

“…First, a proposed end-to-end training methodology over normal data minimizes the reconstruction errors while learning and optimizing neural attention weights to focus on hidden features. Second, a novel encoding mechanism leverages NAF’s hierarchical structure to capture complex data patterns. …”
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Testing different function fitting methods for mobile eye-tracker calibration by Börn Severitt, Thomas Kübler, Enkelejda Kasneci

“…We investigate how different fitting methods impact accuracy under different noise factors, such as mobile eye-tracker imprecision or detection errors in feature extraction during calibration. For this purpose, a simulation of binocular gaze was developed for a) different calibration patterns and b) different noise characteristics. …”
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The Evolution of the Idiolect over the Lifetime: A Quantitative and Qualitative Study of French 19th Century Literature by Olga Seminck, Philippe Gambette, Dominique Legallois, Thierry Poibeau

“…Using the Corpus for Idiolectal Research (CIDRE) that contains the dated works of 11 prolific 19th century French fiction writers, we propose new methods to identify, quantify and describe the grammatical-stylistic changes that take place using lexico-morphosyntactic patterns, also called motifs. To examine the strength of the chronological signal of change, we developed a method to calculate if a distance matrix of literary works contains a stronger chronological signal than expected by chance. …”
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MESS to live with schizophrenic parental history: A systematic review of developmental checkpoints. by Maryam Khan, Rabia Batool, Uzma Mushtaq, Shakir Iqbal, Sana Shaheen, Aimen Zafar Butt, Anees Ahmed

“…Parental history of schizophrenia, a complex and multifaceted psychological disorder, is recognized as a well-established risk factor in the development of the disorder among offspring. However, the developmental patterns of such children and adolescents before the onset of the problem have not yet been systematically documented. …”
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Graphical Notation for Document Database Modeling by M. V. Smirnov, R. S. Tolmasov

“…On the one hand, the development is well known to practitioners who have previously worked with relational data models, since its development took into account many years of experience in using graphical models in the field of relational database design, and on the other hand, it reflects the features of the structure of the document model.Conclusion. …”
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Urban change detection with airborne LiDAR for hostilities’ impact estimation: a case study of Kharkiv by Sergiy V. Kostrikov, Denys S. Serohin

“…This research demonstrates the application of LiDAR for urban change detection (CD), focusing on distinguishing between CD-patterns of normal urban development and from those caused by military hostilities. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…After modeling, we derived feature importance for each of the two models and decreased the number of features to reach a parsimonious highly performing model. …”
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HCAP: Hybrid cyber attack prediction model for securing healthcare applications. by Mohanad Faeq Ali, Mohammed Shakir Mohmood, Ban Salman Shukur, Rex Bacarra, Jamil Abedalrahim Jamil Alsayaydeh, Masrullizam Mat Ibrahim, Safarudin Gazali Herawan

“…The gathered information is processed with the help of Principal Component-Recursive Feature Elimination (PC-RFE), which eliminates the irrelevant features. …”
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Prediction of crystalline structure evolution during solidification of aluminum at different cooling rates using a hybrid neural network model by Rafi B. Dastagir, Shorup Chanda, Farsia K. Chowdhury, Shahereen Chowdhury, K. Arafat Rahman

“…By combining the temporal pattern descriptors of LSTMs with the feature extraction potential of convolutional neural networks (CNN), the hybrid Conv1D-LSTM model achieves higher accuracy in predicting crystal structural evolution curves, in contrast to the performance of standalone LSTM and CNN models. …”
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Tipping the balance: robustness of tip cell selection, migration and fusion in angiogenesis. by Katie Bentley, Giovanni Mariggi, Holger Gerhardt, Holger Gerhardt, Paul A Bates

“…A novel filopodia-adhesion driven migration mechanism is presented and validated against in vivo data. Due to the unique feature of ongoing lateral inhibition, 'stabilised' tip/stalk cell patterns show sensitivity to the formation of new cell-cell junctions during fusion: we predict cell fates can reverse. …”
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