Semi-physical Simulation of Adaptive Cruise Control for Electric Vehicle Based on xPC by DING Xiying, WANG Chunqiang, ZHANG Hongyue, WANG Yanan, LIU Xipeng

“…Furthermore, it was translated into C code and then downloaded to the target model machine for simulating the real vehicle. An embedded computer of DSP2812 was used as the adaptive cruise physical controller of vehicles to swith control algorithm for different working conditions and adjust vehicle speed online, so that the constant speed drive or isometric tracking for front vehicles could be realized. …”
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Robotic manipulation via the assisted 3D point cloud of an object in the bin-picking application by Duc Minh Phan, Ha Quang Thinh Ngo

“…This information is transmitted to our embedded computer via TCP/IP communication protocol. The outcome of the proposed approach is to properly enable the grasping operation without the human intervention. …”
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Design of an Effective WSN-Based Interactive u-Learning Model by Hye-jin Kim, Ronnie D. Caytiles, Tai-hoon Kim

“…The communication between devices and the embedded computers in the environment allows learners to learn in an environment of their interest while they are moving, hence, attaching them to their learning environment.…”
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Perspectives on Intelligence in Soft Robotics by Vera Gesina Kortman, Barbara Mazzolai, Aimeé Sakes, Jovana Jovanova

“…Additionally, the perspectives on intelligence based on their computational approach are distinguished: centralized computation, decentralized computation, or embedded computation. It is concluded that a tailored robotic design approach attuned to specific environmental demands is needed. …”
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Decentralized nonlinear model predictive control-based flock navigation with real-time obstacle avoidance in unknown obstructed environments by Nuthasith Gerdpratoom, Kaoru Yamamoto

“…The results demonstrate that the agents can safely navigate through obstructed environments, and the HIL simulation confirms the feasibility of deploying this scheme on an embedded computer. These results suggest that the proposed NMPC scheme is suitable for real-world robotics deployment in decentralized robotic systems operating in complex environments.…”
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A review on control systems hardware and software for robots of various scale and purpose. Part 2. Service robotics by Aleksey M. Romanov

“…The following conclusions are made on the basis of the review results: the key technology in service robotics from the point of view of scalability is the Robot Operating System (ROS); service robotics is today the main springboard for testing intelligent algorithms for the tactical and strategic control levels that are integrated into a common system based on ROS; the problem of ensuring fault tolerance in the service robotics is practically neglected, with the exception of the issue of increasing reliability by changing behavioral algorithms; in a number of areas of service robotics, in which the reduction of mass and dimensions is especially important, the robot control systems are implemented on a single computing device, in other cases a multi-level architecture implemented on Linux-based embedded computers with ROS are used.…”
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Prediction of protein–protein interaction based on interaction-specific learning and hierarchical information by Tao Tang, Taiguang Shen, Jing Jiang, Weizhuo Li, Peng Wang, Sisi Yuan, Xiaofeng Cao, Yuansheng Liu

“…The distance between the origin and the hyperbolic embedding computed by HI-PPI naturally reflects the hierarchical level of proteins. …”
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Capturing research literature attitude towards sustainable development goals: an LLM-based topic modeling approach by Francesco Invernici, Francesca Curati, Jelena Jakimov, Amirhossein Samavi, Anna Bernasconi

“…For topic modeling, we leverage the stack of BERTopic scaled up to be applied on large corpora of textual documents (we find hundreds of topics on hundreds of thousands of documents), introducing (i) a novel LLM-based embeddings computation for representing scientific abstracts in the continuous space, and (ii) a hyperparameter optimizer to efficiently find the best configuration for any new dataset. …”
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THOR2: Topological Analysis for 3D Shape and Color‐Based Human‐Inspired Object Recognition in Unseen Environments by Ekta U. Samani, Ashis G. Banerjee

“…Robot. 2024, 40, 886) while capturing object color information through slicing‐based color embeddings computed using a network of coarse color regions. …”
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FLEDNet: Enhancing the Drone Classification in the Radio Frequency Domain by Boban Sazdic-Jotic, Milenko Andric, Boban Bondzulic, Slobodan Simic, Ivan Pokrajac

“…The effectiveness of this approach is validated using the publicly available VTI_DroneSET dataset across two different frequency bands and confirmed through practical inference on the embedded computer NVIDIA Jetson Orin NX with radio frequency receiver USRP-2954. …”
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Emotion-Aware Embedding Fusion in Large Language Models (Flan-T5, Llama 2, DeepSeek-R1, and ChatGPT 4) for Intelligent Response Generation by Abdur Rasool, Muhammad Irfan Shahzad, Hafsa Aslam, Vincent Chan, Muhammad Ali Arshad

“…The processed embeddings, computed using BERT, GPT-3, and RoBERTa, are stored in the Facebook AI similarity search vector database, which enables efficient similarity search and clustering across dense vector spaces. …”
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Micro-CT Assessment During Embedding of Prototype Ti Alloy Multi-Spiked Connecting Scaffold in Subchondral Trabecular Bone of Osteoarthritic Femoral Heads, Depending on Host BMI by Ryszard Uklejewski, Mariusz Winiecki, Adam Patalas, Patryk Mietliński, Paweł Zawadzki, Mikołaj Dąbrowski

“…This study aimed to explore, depending on the occurrence of obesity, changes in the microstructure and mechanical properties of the subchondral trabecular bone in femoral heads of osteoarthritis (OA) patients caused by the MSC-Scaffold embedding. Computed microtomography (micro-CT) scanning of femoral heads from OA patients was conducted before and after the mechanical embedding of the MSC-Scaffold. …”
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Breaking Digital Health Barriers Through a Large Language Model–Based Tool for Automated Observational Medical Outcomes Partnership Mapping: Development and Validation Study by Meredith CB Adams, Matthew L Perkins, Cody Hudson, Vithal Madhira, Oguz Akbilgic, Da Ma, Robert W Hurley, Umit Topaloglu

“…The system processes input terms by generating vector embeddings, computing cosine similarity against precomputed Observational Health Data Sciences and Informatics vocabulary embeddings, and ranking potential matches. …”
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