Technology and Modeling of Nonclassical Transistor Devices by George V. Angelov, Dimitar N. Nikolov, Marin H. Hristov

“…Bulk CMOS technology is developing and innovating to overcome these constraints by introduction of (i) new technologies and new materials and (ii) new transistor architectures. Technology boosters such as high-k/metal-gate technologies, ultra-thin-body SOI, Ge-on-insulator (GOI), AIII–BV semiconductors, and band-engineered transistor (SiGe or Strained Si-channel) with high-carrier-mobility channels are examined. …”
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Advanced Air Quality Forecasting Using an Enhanced Temporal Attention-Driven Graph Convolutional Long Short-Term Memory Model With Seasonal-Trend Decomposition by Yuvaraja Boddu, A. Manimaran, B. Arunkumar, M. Sucharitha, J. Suresh Babu

“…Future research will focus on enhancing the model’s adaptability through multi-scale spatial attention mechanisms and exploring hybrid architectures with Graph Neural Networks (GNNs) to further refine its applicability in real-time air quality forecasting scenarios. …”
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A hybrid Framework for plant leaf disease detection and classification using convolutional neural networks and vision transformer by Sherihan Aboelenin, Foriaa Ahmed Elbasheer, Mohamed Meselhy Eltoukhy, Walaa M. El-Hady, Khalid M. Hosny

“…This proposed model leverages the strength of Convolutional Neural Networks (CNNs) and Vision Transformers (ViT), where an ensemble model, which consists of the well-known CNN architectures VGG16, Inception-V3, and DenseNet20, is used to extract robust global features. …”
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A Novel Pattern Recognition Method for Self-Powered TENG Sensor Embedded to the Robotic Hand by Azat Balapan, Rauan Yeralkhan, Alikhan Aryslanov, Gulnur Kalimuldina, Azamat Yeshmukhametov

“…These findings underscore the potential of integrating TENG sensors with advanced neural network architectures for autonomous dexterous manipulation in various industrial applications, paving the way for future advancements in robotic tactile sensing.…”
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Deep Learning in Music Generation: A Comprehensive Investigation of Models, Challenges and Future Directions by Kong Xiangchen

“…This review explores various and recent deep learning models, such as Long Short-Term Memory (LSTM) networks, Transformer-based models, Reinforcement Learning (RL), and Diffusion-based architectures, and how they are applied to music generation. …”
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Convolutional neural network prediction of the particle size distribution of soil from close-range images by Enrico Soranzo, Carlotta Guardiani, Wei Wu

“…We implemented the model in Python and explored various neural network architectures, image resolutions and data augmentation techniques to optimise performance. …”
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PBVit: A Patch-Based Vision Transformer for Enhanced Brain Tumor Detection by Pratikkumar Chauhan, Munindra Lunagaria, Deepak Kumar Verma, Krunal Vaghela, Ghanshyam G. Tejani, Sunil Kumar Sharma, Ahmad Raza Khan

“…The promising results demonstrate that PBVit can play a important role in facilitating early-stage diagnosis, reducing unnecessary biopsies, and ultimately enhancing patient care, while also showcasing the potential of transformer-based architectures in medical imaging.…”
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Tracking Vehicle Cruising in an Open Parking Lot Using Deep Learning and Kalman Filter by Vijay Paidi, Hasan Fleyeh, Johan Håkansson, Roger G. Nyberg

“…The vehicle is detected using Yolov3, modified Yolo, and custom Yolo deep learning architectures. The detected vehicles are tracked using Kalman filter and the trajectory of multiple vehicles is calculated on an image. …”
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Optimizing multi label student performance prediction with GNN-TINet: A contextual multidimensional deep learning framework. by Xiaoyi Zhang, Yakang Zhang, Angelina Lilac Chen, Manning Yu, Lihao Zhang

“…The GNN-TINet utilizes InceptionNet, transformer architectures, and graph neural networks (GNN) to improve precision in multi-label student performance forecasting. …”
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Multi-bandwidth reconstruction for photoacoustic tomography using cascade U-net by Zezheng Qin, Lingyu Ma, Zhigang Lei, Yiming Ma, Weiwei Fu, Mingjian Sun

“…Utilizing the two semi-ring array PAIs, we have devised a specialized deep learning model, comprising two serially connected U-net architectures, to autonomously generate multi-bandwidth full-view PAIs. …”
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A radix‐8 modulo 2n multiplier using area and power‐optimized hard multiple generator by Naveen Kr. Kabra, Zuber M. Patel

“…The synthesis of the proposed architectures is done using the Cadence tool at Generic Process design Kit‐45 nm technology. …”
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A High-Level Synthesis Scheduling and Binding Heuristic for FPGA Fault Tolerance by David Wilson, Aniruddha Shastri, Greg Stitt

“…In this paper, we present a more transparent high-level synthesis approach that uses scheduling and binding to provide attractive tradeoffs between area, performance, and redundancy, while focusing on FPGA implementation considerations, such as resource realization costs, to produce more efficient architectures. Compared to TMR applied to existing RTL, our approach shows resource savings up to 80% with average resource savings of 34% and an average clock degradation of 6%. …”
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Textural analysis and artificial intelligence as decision support tools in the diagnosis of multiple sclerosis – a systematic review by Filip Orzan, Ştefania D. Iancu, Laura Dioşan, Zoltán Bálint

“…The study emphasizes common models, including U-Net, Support Vector Machine, Random Forest, and K-Nearest Neighbors, alongside their evaluation metrics.ResultsThe analysis revealed a fragmented research landscape, with significant variation in model architectures and performance. Evaluation metrics such as Accuracy, Dice score, and Sensitivity are commonly employed, with some models demonstrating robustness across multi-center datasets. …”
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Multimodal Autism Spectrum Disorder Method Using GCN With Dual Transformers by Tianming Song, Zhe Ren, Jian Zhang, Yawei Qu, Yingying Cui, Zhengda Liang

“…This study proposes a novel diagnostic approach that integrates Graph convolutional networks (GCN) with dual transformer architectures, optimized through a Co-training strategy. …”
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Deep Learning Framework for Advanced De-Identification of Protected Health Information by Ahmad Aloqaily, Emad E. Abdallah, Rahaf Al-Zyoud, Esraa Abu Elsoud, Malak Al-Hassan, Alaa E. Abdallah

“…This rigorous approach to architectural design and hyperparameter tuning, often underexplored in the existing literature, significantly enhances the model’s capacity for accurate PHI tag detection while preserving the essential clinical context. …”
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An MLLM-Assisted Web Crawler Approach for Web Application Fuzzing by Wantong Yang, Enze Wang, Zhiwen Gui, Yuan Zhou, Baosheng Wang, Wei Xie

“…Web application fuzzing faces significant challenges in achieving comprehensive test interface (attack surface) coverage, primarily due to the complexity of user interactions and dynamic website architectures. While web crawlers can automatically access and extract critical website information—including form fields and request parameters—which are essential for generating effective fuzzing test cases, current crawler technologies exhibit three primary limitations: (i) insufficient capabilities in analyzing page relationships and determining page states; (ii) lack of functionality-aware exploration capabilities, resulting in generated inputs with poor contextual relevance; (iii) generation of unstructured operation sequences that fail to execute effectively due to their incompatibility with state-based testing logic. …”
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The Comparison of Using Andesite Waste Powder and Fly Ash in Concrete by Hakan Ceylan, Metin Davraz

“…Andesite stone is widely used in civil engineering and architectural applications in Turkey. The production, cutting and polishing of the andesite stone by mining methods causes a large amount of waste. …”
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Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection by Yinting Wu, Pai Peng, Bo Cai, Le Li

“…Through extensive experiments on three benchmark datasets with two network architectures in both single-step (Noise-Fast Gradient Sign Method, N-FGSM) and multi-step (Projected Gradient Descent, PGD) scenarios, models trained within the BB framework consistently demonstrate superior adversarial accuracy across various adversarial settings, notably achieving an improvement of more than 13% on the SVHN dataset with an attack radius of 8/255 compared to N-FGSM. …”
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Corps sensible, environnement urbain moderniste by Françoise Michel-Jones

“…In it, he confronts his character Hulot with a transitionless shift from the familiar conventions of a historic capital (Paris), which make it possible to stroll peacefully, to the exhausting and deceptive signage and plastic and formal components of a big city that makes for a world in itself, with no space or time outside the frame: a city that asserts the international, modernist version of a city rather than its modern version, being ubiquitous and timeless, devoted to accelerated communication, circulation and consumption.Lost in a disappointing “quest” with multiplying loops and dead-ends, Hulot often appears to be dissolving—shadowless body—at the whim of avatars, doubles and reflections, despite the virtues of transparency and communication, considered to be linked with the “new” architectural and urban environment. Then the dwindling of the “me, of the subject, of the person” (Mauss) is manifested in the opacity and absurdity of the loss of meaning and negation of history that accompany the presumed “functional” requirement of the serial and the undifferentiated.…”
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Three-dimensional direct lithography of stable quantum dots in hybrid glass by Dezhi Zhu, Shangben Jiang, Ying Wang, Dejun Liu, Weijia Bao, Liwei Liu, Junle Qu, Yiping Wang, Changrui Liao

“…The printed micro-/nano- structures possess thermal stability up to 600 °C, which can be transformed to inorganic architectures with a volume shrinkage. Due to the encapsulated QDs within the densely silicon-oxygen molecular networks, the functional structures demonstrate good stability against ultraviolet irradiation, corrosive solutions, and elevated temperatures. …”
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