Comparison of the Torsional Strength of Material Samples Made Using Selected Rapid Prototyping Methods by Mariusz DĘBSKI (m.debski@prz.edu.pl), Bogdan KOZIK (bogkozik@prz.edu.pl), Łukasz PRZESZŁOWSKI (lprzeszl@prz.edu.pl), Jadwiga PISULA (jpisula@prz.edu.pl)

“…The research results show that producing rotating elements using the hybrid technology reduces the sample core’s ability to undergo plastic deformation due to the adhesion between the materials and the occurrence of notches resulting from the model production process using the layered extrusion method.…”
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Effect of tool angle in nanocutting of single crystal GaN using diamond cutter by Yongqiang WANG, Hao XIA, Zhihang HU, Shuaiyang ZHANG, Shaohui YIN

“…Large-scale MD simulations are meticulously performed to model the nanoscale cutting process of single-crystal GaN using a diamond tool. …”
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Visualization of Information Retrieval in Smart Library Based on Virtual Reality Technology by Shulin Fang

“…The elements and contents of the service context are introduced, and the strategy of constructing the service context of the knowledge service extension of the smart library is proposed. A visual model of information retrieval is constructed. The model integrates the core steps of the information visualization process and introduces the information space and functional system (navigation, organization, indexing, and retrieval) in the information construction theory into it and through five mapping layers (functional space mapping, visualization space mapping, visualization mapping, view mapping, and interactive mapping) and six spatial layers (role space, information space, functional space, visualized information space, visualized object space, and visualized view space), which describe visualization applications that target the user experience model in information construction build process.…”
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Additive Attention for Vetting Transiting Exoplanet Candidates by Àlvar Hernàndez-Carnerero, Miquel Sànchez-Marrè, Juan Carlos Morales

“…Through extensive experimentation, we demonstrate the efficacy of our final model, which integrates CNN, LSTM, and additive attention layers, coupled with feed-forward neural networks, achieving competitive performance with limited model complexity. …”
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Prediction of Final Phosphorus Content of Steel in a Scrap-Based Electric Arc Furnace Using Artificial Neural Networks by Riadh Azzaz, Mohammad Jahazi, Samira Ebrahimi Kahou, Elmira Moosavi-Khoonsari

“…This study aims to develop a machine learning model to estimate steel phosphorus content at the end of the process based on input parameters. …”
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A Combined Approach to Safety and Security of IoT by Applying Fault Tree Analysis and Attack Trees with Minimal Cut Sets by Mohammad Rezaul Karim, Sohag Kabir, Ci Lei, Raluca Lefticaru, Mohammad Abdul Baset

“…Quantitative analysis (mean safety: 0.005, variance: 0.000006) confirmed the methodology’s effectiveness in capturing interdependencies across IoT layers (Perception, Network, Data Processing, Application). …”
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DeepContainer: A Deep Learning-based Framework for Real-time Anomaly Detection in Cloud-Native Container Environments by Ke Xiong, Zhonghao Wu,  Xuzhong Jia

“…DeepContainer implements a multi-layered detection approach, combining feature engineering techniques with optimized deep learning models to identify security anomalies across diverse container workloads. …”
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Optimized DenseNet Architectures for Precise Classification of Edible and Poisonous Mushrooms by Jay Prakash Singh, Debolina Ghosh, Jagannath Singh, Anurag Bhattacharjee, Mahendra Kumar Gourisaria

“…Methods The study analyzes the basic DenseNet-121 model as well as a modified DenseNet-121 with frozen upper layers which preserve important lower level features. …”
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An explainable AI-driven deep neural network for accurate breast cancer detection from histopathological and ultrasound images by Md. Romzan Alom, Fahmid Al Farid, Muhammad Aminur Rahaman, Anichur Rahman, Tanoy Debnath, Abu Saleh Musa Miah, Sarina Mansor

“…The proposed model employs Densenet121 as a foundation, integrating customized Convolutional Neural Network (CNN) layers including GlobalAveragePooling2D, Dense, and Dropout layers along with transfer learning to achieve both high accuracy and interpretability for breast cancer diagnosis. …”
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Corrosion Inhibition of Mild Steel in Acidic Environments using Polyphenol-Rich Extract from Senegalia Senegal (L.) Britton Stem Bark by Y.M. Ohunene, J. Oguegbulu, Maia-Obi Lígia Passos, F. F. Mtunzi, F. Ojo, B.J. Okoli

“…Results indicated that increasing concentrations of PRFSS notably reduced the corrosion rate of mild steel and enhanced surface coverage, suggesting effective protective layer formation. Thermodynamic analyses confirmed that the adsorption process of PRFSS onto mild steel is exothermic and spontaneous, with the adsorption behavior fitting Langmuir, Freundlich, and El-Awady isotherm models. …”
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Mapping the evolution of digital human resource management: a systematic review and bibliometric analysis by Md. Nazmus Sakib, Muhammad Shariat Ullah, Md. Mahbubur Rahman

“…From the literature synthesis, this research offers an integrated socio-technical definition of DHRM and a three-layer definition framework (operational, relational, and transformational) that explains how digital technologies reshape HR processes and strategic value creation. …”
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Water Basin Effect of Cofferdam Foundation Pit by Guofeng Li, Qinchao Zuo, Xiaoyan Zhou, Yanbo Hu, Ning Li

“…This study addresses the water basin effect in the underwater sand layer of steel pipe pile cofferdams by integrating the concept from building foundation pits to cofferdam foundation pit analysis. …”
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Effects of Mesoscale Eddies on Southern Ocean Biogeochemistry by Lydia Keppler, Yassir A. Eddebbar, Sarah T. Gille, Nicola Guisewhite, Matthew R. Mazloff, Veronica Tamsitt, Ariane Verdy, Lynne D. Talley

“…These findings underscore the importance of considering eddy impacts in observing networks and climate models.…”
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Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach by Khadim Hussain, Kaleem Mehmood, Sun Yujun, Tariq Badshah, Shoaib Ahmad Anees, Fahad Shahzad, Nooruddin, Jamshid Ali, Muhammad Bilal

“…The model underwent 10,000 iterations during its training process, and a thorough statistical analysis was conducted to assess the impact of each driving component. …”
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An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images by Kiran Jabeen, Muhammad Attique Khan, Ameer Hamza, Hussain Mobarak Albarakati, Shrooq Alsenan, Usman Tariq, Isaac Ofori

“…Both fine‐tuned models are later trained using a deep transfer learning process and extracted features from the deeper layer. …”
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A New Efficient Classifier for Bird Classification Based on Transfer Learning by Lesia Mochurad, Stanislav Svystovych

“…A dataset of 525 bird species was analyzed and preprocessed in detail. The model training process was carried out, which includes two phases: only the upper layers are deactivated and the last 92 layers of the pretrained EfficientNetB5 model (not including BatchNormalization layers) and the top layers are activated. …”
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Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues by Gianmarco Lazzini, Mario D’Acunto

“…These models, especially RFC and MLPC, showed excellent classification performances, with accuracy reaching 99.7%. …”
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Deep Learning Image Classification Rontgen Dada pada Kasus Covid-19 Menggunakan Algoritma Convolutional Neural Network by Leni Anggraini Susanti, Agus Mohamad Soleh, Bagus Sartono

“…The study's results indicate that adding dropout layers with a 50% probability for both architectures effectively addressed overfitting and improved the model's performance. …”
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Dynamic Agricultural Pest Classification Using Enhanced SAO-CNN and Swarm Intelligence Optimization for UAVs by Shiwei Chu, Wenxia Bao

“…Key contributions include: (1) A hybrid SAO-CNN architecture that dynamically adjusts convolution kernels and leverages unlabeled data through self-supervised learning, improving adaptability to lighting and background variations. (2) A UAV swarm intelligence framework optimized via bio-inspired algorithms, reducing flight time by 29.2% and energy consumption by 32% compared to non-optimized systems. (3) Superior performance with 91.2% classification accuracy, 0.89 recall, and 32 FPS processing speed, outperforming state-of-the-art models (e.g., YOLO variants, ResNet, and ConvLSTM) in both static and dynamic scenarios. …”
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Explainable deep learning approaches for high precision early melanoma detection using dermoscopic images by Md Abdullah All Mahmud, Sadia Afrin, M. F. Mridha, Sultan Alfarhood, Dunren Che, Mejdl Safran

“…The novel approach proposed through this research addresses this gap by utilizing a proposed model with advanced layers, including Global Average Pooling, Batch Normalization, Dropout, and dense layers with ReLU and Swish activations to improve model performance. …”
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