A certificateless aggregate signature scheme for security and privacy protection in VANET by Eko Fajar Cahyadi, Tzu-Wei Su, Chou-Chen Yang, Min-Shiang Hwang

“…Then, the performance evaluation demonstrates that our proposed scheme is more suitable for deployment in vehicular ad hoc network environments.…”
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Beamline and Flight Comparisons of the ARMAS Flight Module With the Tissue Equivalent Proportional Counter for Improving Atmospheric Radiation Monitoring Accuracy by Brad “Buddy” Gersey, W. Kent Tobiska, William Atwell, Dave Bouwer, Leonid Didkovsky, Kevin Judge, Seth Wieman, Richard Wilkins

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A Scalable and Privacy-Aware Location-Sensing Model for Ephemeral Social Network Service by Yongqiang Lyu, Dezhi Hong, Ying Wang, Yinghong Hou, Zhengwen Yang, Yu Chen, Yuanchun Shi, Alvin Chin

“…The model includes the perspectives of the privacy, architecture, deployment, and positioning algorithms, which can meet the four key requirements. …”
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MSSA: multi-stage semantic-aware neural network for binary code similarity detection by Bangrui Wan, Jianjun Zhou, Ying Wang, Feng Chen, Ying Qian

“…MSSA is a lightweight model with only 0.38M parameters in its backbone network, suitable for deployment in CPU environments. Experimental results show that MSSA outperforms Gemini, Asm2Vec, SAFE, and jTrans in classification performance and ranks second only to the Transformer-based jTrans in retrieval performance.…”
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Efficient anomaly detection in tabular cybersecurity data using large language models by Xiaoyong Zhao, Xingxin Leng, Lei Wang, Ningning Wang, Yanqiong Liu

“…Furthermore, the smaller-scale TAD-GP model outperforms larger models across multiple datasets, demonstrating its practical potential in environments with constrained computational resources and requirements for private deployment. …”
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Shuffle-PG: Lightweight feature extraction model for retrieving images of plant diseases and pests with deep metric learning by Dong Jin, Helin Yin, Yeong Hyeon Gu

“…Previous research in disease and pest diagnosis has relied on large models for feature extraction, posing challenges for deployment in resource-constrained environments like mobile devices. …”
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Online Self-Supervised Learning for Accurate Pick Assembly Operation Optimization by Sergio Valdés, Marco Ojer, Xiao Lin

“…Corrective strategies used to compensate for misalignment can increase cycle times or rely on pre-labeled datasets, offline training, and validation processes, delaying deployment and limiting adaptability in dynamic industrial environments. …”
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Design of CubeSat-Based Multi-Regional Positioning Navigation and Timing System in Low Earth Orbit by Georgios Tzanoulinos, Nori Ait-Mohammed, Vaios Lappas

“…This paper details the system engineering of a novel CubeSat-based multi-regional PNT system tailored for deployment in LEO. The proposed system leverages on a miniaturized CubeSat-compatible PNT payload that includes a chip-scale atomic clock (CSAC) and relies on MEO GNSS technologies to deliver positioning and timing information across multiple regions. …”
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LCFF-Net: A lightweight cross-scale feature fusion network for tiny target detection in UAV aerial imagery. by Daoze Tang, Shuyun Tang, Zhipeng Fan

“…Moreover, we present different scale versions of the LCFF-Net algorithm to suit various deployment environments. Empirical assessments conducted on the VisDrone dataset validate the efficacy of the algorithm proposed. …”
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Deep Reinforcement Learning-Based Resource Allocation for QoE Enhancement in Wireless VR Communications by Georgios Kougioumtzidis, Vladimir K. Poulkov, Pavlos I. Lazaridis, Zaharias D. Zaharis

“…However, the successful deployment of these applications faces challenges in ensuring high quality of experience (QoE), especially in environments with limited network resources. …”
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LoCS-Net: Localizing convolutional spiking neural network for fast visual place recognition by Ugur Akcal, Ugur Akcal, Ugur Akcal, Ivan Georgiev Raikov, Ekaterina Dmitrievna Gribkova, Ekaterina Dmitrievna Gribkova, Anwesa Choudhuri, Anwesa Choudhuri, Seung Hyun Kim, Mattia Gazzola, Rhanor Gillette, Rhanor Gillette, Ivan Soltesz, Girish Chowdhary, Girish Chowdhary, Girish Chowdhary

“…Visual place recognition (VPR) is the ability to recognize locations in a physical environment based only on visual inputs. It is a challenging task due to perceptual aliasing, viewpoint and appearance variations and complexity of dynamic scenes. …”
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RAPID: real-time automated plankton identification dashboard using Edge AI at sea by Sophie G. Pitois, Robert E. Blackwell, Hayden Close, Noushin Eftekhari, Sarah L. C. Giering, Mojtaba Masoudi, Eric Payne, Joseph Ribeiro, James Scott

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A scoping review of robustness concepts for machine learning in healthcare by Alan Balendran, Céline Beji, Florie Bouvier, Ottavio Khalifa, Theodoros Evgeniou, Philippe Ravaud, Raphaël Porcher

“…Our findings offer valuable insights for stakeholders seeking to understand and navigate the robustness of machine learning models during their development, validation, and deployment in healthcare settings, where interpretation of robustness may vary.…”
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Automated Dead Chicken Detection in Poultry Farms Using Knowledge Distillation and Vision Transformers by Ridip Khanal, Wenqin Wu, Joonwhoan Lee

“…The system’s robustness and scalability make it suitable for large-scale farm deployment, minimizing the need for labor-intensive manual inspections. …”
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The Effect of Emotional Intelligence on Higher Education: A Pilot Study on the interplay Between Artificial Intelligence, Emotional Intelligence, and E-Learning by Abdullah Alenezi

“…Firstly, it aims to uncover how Emotional Intelligence influences students' receptivity to AI-infused E-Learning environments, potentially elucidating strategies for optimizing user experience and learning outcomes. …”
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A Dual-Channel and Frequency-Aware Approach for Lightweight Video Instance Segmentation by Mingzhu Liu, Wei Zhang, Haoran Wei

“…These scenarios rely on real-time and efficient target-tracking capabilities for accurate perception and intelligent analysis of dynamic environments. However, traditional video instance segmentation methods face complex models, high computational overheads, and slow segmentation speeds in time-series feature extraction, especially in resource-constrained environments. …”
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Response of Hard-Bottom Macro-Zoobenthos to the Transition of a Mediterranean Mariculture Fish Plant (Mar Grande of Taranto, Ionian Sea) into an Integrated Multi-Trophic Aquacultur... by Roberta Trani, Cataldo Pierri, Antonella Schiavo, Tamara Lazic, Maria Mercurio, Isabella Coccia, Adriana Giangrande, Caterina Longo

“…The results from seasonal sampling performed in a treatment site, where bioremediators (filter-feeding invertebrates such as sponges, polychaetes, mussels, and macroalgae) were deployed, and a control site without bioremediators were compared. …”
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Specific Bias Design in Cell Range Expansion for Picocell Network by Le Men, Tan Wang

“…As an important part of the heterogeneous deployments,picocells are flexible to be deployed,easy to be planned and better for outdoor coverage.Due to the coexistence of macro and micro base stations,interference environment is complex,but also brought new challenges to the system radio resource management.This paper studies the cell selection for picocell networks.Based on cell range extension,a specific bias for each picocell is designed,according to its interference environment,which can effectively improve the cell average and cell edge spectrum efficiency,compared with those of fixed bias value.…”
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AADL Extension to Model Classical FPGA and FPGA Embedded within a SoC by Dominique Blouin, Daniel Chillet, Eric Senn, Sébastien Bilavarn, Robin Bonamy, Christian Samoyeau

“…The design space exploration of an application deployment using this model is also presented.…”
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AN EFFECTIVE APPROACH TO FACE RECOGNITION WITH ARTIFICIAL INTELLIGENCE AND THE INTERNET OF THINGS USING NVIDIA JETSON NANO by Ngoc Giau Pham, Nhien Loc Bui, Quang Hien Tran, Le Thanh Hai Tong, Hong Ngoc Tran

“…The paper begins by outlining the motivation for this investigation, then proceeds with a literature review to evaluate the prospective applications, challenges, and benefits of AI in IoT environments. It explores in detail the technical attributes of the NVIDIA Jetson Nano, including its compact design, robust computing power, and the availability of software libraries that facilitate the deployment of AI models on devices with limited resources. …”
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