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检索条件"任意字段=9th International Conference on Frontier of Computer Science and Technology"

共 21101 条记录，以下是51-60 订阅

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Low-temperature drift and high-accuracy MEMS pressure sensor with inverted package structure 9

Low-temperature drift and high-accuracy MEMS pressure sensor...

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2024 9th international Seminar on computer technology, Mechanical and Electrical Engineering, ISCME 2024

作者： Wang, Shengqi Shi, Zhou Han, Xiangguang Zhao, Libo Wang, Jiuhong School of Instrument Science and Technology Xi’an Jiaotong University Xi’an710049 China

For the application requirements in the temperature range of -40 to 150℃, A pressure sensor with high accuracy and low-temperature drift has been developed by using MEMS (MEMS, Micro-Electro-Mechanical System) technology and SOI (Silicon-On-Insulator) substrate. the silica isolation of SOI is utilized to address the electrical failure of the force-sensitive chip at elevated temperatures. the ion implantation process was optimized to reduce output drift and accuracy drift of the chip with temperature. the back bottom pressure-bearing flushed package structure is designed, and the glass sintering process is used to reduce the lumen effect and improve the frequency response and anti-interference capability of the sensor. the test results show that the sensor has an accuracy error of ±0.2% of Full Scale (FS) over the temperature range of -40 to 150°C. the sensor displays the thermal sensitivity drift of -0.07% FS and the thermal zero drift of +0.006% FS. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Silicon on insulator technology

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Clustering with a Knapsack Constraint: Parameterized Approximation Algorithms for the Knapsack Median Problem 18th

Clustering with a Knapsack Constraint: Parameterized Appro...

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18th international Joint conference on theoretical computer science-frontier of Algorithmic Wisdom, IJTCS-FAW 2024

作者： Zhang, Zhen Liu, Limei Liu, Yao Chen, Jie Feng, Qilong School of Advanced Interdisciplinary Studies Hunan University of Technology and Business Changsha410205 China Xiangjiang Laboratory Changsha410205 China School of Computer Science and Engineering Central South University Changsha410083 China

ISBN: (纸本)9789819777518

the Knapsack Median problem was known to be W[2]-hard if parameterized by the maximal number of opened facilities in feasible solutions (denoted by k), implying that exactly solving this problem in FPT(k) time is unlikely. We focus on parameterized approximation algorithms for the Knapsack Median problem. We give a sampling-based approach for reducing the solution search space, which yields a (3+Ε)-approximation algorithm that runs in (kΕ-1)O(k)nO(1) time in general metric spaces and a (1+Ε)-approximation algorithm with similar running time in d-dimensional Euclidean space. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Approximation algorithms

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the Design of Portrait Photography Guiding System Using VGG16 Model 14th

The Design of Portrait Photography Guiding System Using VGG1...

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14th international conference on frontier Computing, FC 2024

作者： Chiu, Chuan-Feng Huang, Chun-Hong Tseng, Hsiang-Chieh Wu, Pei-Jung Lin, Wei-Sheng Peng, Hsiang-Min Department of Information Management Minghsin University of Science and Technology Hsinchu Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan City Taiwan

ISBN: (纸本)9789819623945

Because of the population of photography camera, human being could have photography equipment to take a picture became an easy task. However, to have a good photography is not an easy task. the basic of a good photo is the composition of the photography. A better photography composition could lead better visual effect. So, in this paper we intent to design a photography guiding system framework for users to have good photos especially for portrait photography. In our work, we design a system framework using VGG16 model based on Rule of thirds and luminance distribution to guide user to select better photography composition. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Photographic equipment

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Human activity recognition using residual deep network with extreme learning 4th

Human activity recognition using residual deep network with ...

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4th international conference on Computational Methods in science and technology, ICCMST 2024

作者： Bohra, Garima Jha, C.K. Sharma, Neelam Department of Computer Science Banasthali Vidyapith Rajasthan India

ISBN: (纸本)9781032911571

In recent years, human activity recognition (HAR) has emerged as an important topic of research due to the multiple applications it has found in various fields, including fitness and strength surveillance, residential care, biometric verification, aged care, and many others. Sensors are a great alternative for activity recognition because of their widespread use. the bulk of wearable sensors, including accelerometer, gyroscope, camera, GPS, microphone, compass, and others, are built into the newest smart devices. Such sensors measure different properties of an object, are simple to use, and are inexpensive. Researchers using machine learning (ML) now have new potential to accurately recognize human behaviours thanks to the usage of sensors in the HAR sector. Deep learning (DL) is gaining popularity among HAR researchers because it outperforms standard machine learning (ML) approaches. In this paper, hybrid features of mechanisms and learning are used by employing deep learning and machine learning;deep learning uses RESNET-50 and machine learning uses XG boosting. In experiments, the proposed approach was validated by a 10-cross comparison with the state-of-the-art approach. In experiment also classified human activities and intruders. © 2025 the Author(s).

关键词： Active learning

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A Hybrid Vectorized Merge Sort on ARM NEON 24th

A Hybrid Vectorized Merge Sort on ARM NEON

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24th international conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Zhou, Jincheng Zhang, Jin Zhang, Xiang Xiao, Tiaojie Ma, Di Gong, Chunye School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China College of Computer National University of Defense Technology Hunan Changsha410073 China Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China National Supercomputer Center in Tianjin Tianjin300457 China

ISBN: (纸本)9789819615506

Sorting algorithms are the most extensively researched topics in computer science and serve for numerous practical applications. Although various sorts have been proposed for efficiency, different architectures offer distinct flavors to the implementation of parallel sorting. In this paper, we propose a hybrid vectorized merge sort on ARM NEON, named NEON Merge Sort for short (NEON-MS). In detail, according to the granted register functions, we first identify the optimal register number to avoid the register-to-memory access, due to the write-back of intermediate outcomes. More importantly, following the generic merge sort framework that primarily uses sorting network for column sort and merging networks for three types of vectorized merge, we further improve their structures for high efficiency in an unified asymmetry way: 1) it makes the optimal sorting networks with few comparators become possible;2) hybrid implementation of both serial and vectorized merges incurs the pipeline with merge instructions highly interleaved. Experiments on a single FT2000+ core show that NEON-MS is 3.8 and 2.1 times faster than std::sort and boost::block_sort, respectively, on average. Additionally, as compared to the parallel version of the latter, NEON-MS gains an average speedup of 1.25. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Memory architecture

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Design and Evaluation of Emotional Prompts for Generating Videos with High Emotion Consistency 14th

Design and Evaluation of Emotional Prompts for Generating Vi...

引用

14th international conference on frontier Computing, FC 2024

作者： Chu, Chao-Ting Chen, You-Yu Chang, Jia-Wei Hung, Jason C. Chunghwa Telecom Laboratories Internet of Things Laboratory No. 99 Dianyan Rd. Yangmei District Taoyuan City32661 Taiwan Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan

ISBN: (纸本)9789819623945

Artificial Intelligence Generated Content (AIGC) is an advanced AI technology that can automatically create multimedia content including text, images, sound, and video. With the development of technologies such as ChatGPT, AIGC has made significant progress in natural language processing and exhibits excellent fluency and diversity in human-computer interaction. Text prompt generation is a new challenge for AIGC. Existing models can not only generate video content containing text and image elements, but also strive to weave a world of stories full of emotion and logical coherence to cater to users’ personalized desires. In the process of generating with text prompts, the clever use of adjectives is key to creating engaging scenarios. this study focuses on the design of Emotional Prompts using emotional words, adjectives, and onomatopoeic words to generate videos and sounds with corresponding emotions and further evaluate the emotional consistency of audio and video, enhancing the emotional depth of the content and resonating with the audience. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： AI Generated Diffusion Model Multimodal Learning

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Retrospective and Perspectives of TTS & STT technology Development and Implementation for South Slavic Under-Resourced Languages 26th

Retrospective and Perspectives of TTS & STT Technology Devel...

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26th international conference on Speech and computer

作者： Secujski, Milan Popovic, Branislav Pekar, Darko Jakovljevic, Niksaa Pakoci, Edvin Suzic, Sinisaa Nosek, Tijana Simic, Nikola Stanojev, Vuk Delic, Vlado Univ Novi Sad Fac Tech Sci Novi Sad Serbia AlfaNum Ltd Novi Sad Serbia

ISBN: (纸本)9783031779602;9783031779619

Speech technologies such as text-to-speech (TTS) and speech-to-text (STT) are becoming increasingly applicable. Significant improvements in their quality are driven by advancements in deep machine learning. the ability of devices to deeply understand human speech and generate appropriate responses is a hallmark of AI capabilities. Developing speech technology requires extensive speech and language resources, which is why many languages with smaller speaker bases lag behind widely spoken languages in the development of speech technologys. Prior to the deep learning (DL) paradigm, hidden Markov models (HMM) and probabilistic approaches dominated speech technology development. this paper reviews the challenges and solutions in TTS and STT development for Serbian, highlighting the transition from HMM to DL. It also explores the future prospects of speech technology development for under-resourced languages and its role in preserving these languages.

关键词： Speech technology Development and Implementation Text-to-Speech Speech-to-Text Hidden Markov Models Deep Neural Networks

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Novel technology for IoT Charging Battery 9th

Novel Technology for IoT Charging Battery

引用

9th international conference on Internet of things, ICIOT 2024, Held as Part of the Services conference Federation, SCF 2024

作者： Maman Guéro, Abdel-Majid Abghour, Noreddine Chiba, Zouhair Moussaid, Khalid Mounia, Miyara Ouaguid, Abdellah LIS Labs Faculty of Sciences Ain Chock Hassan II University of Casablanca Casablanca Morocco 2IACS Laboratory ENSET of Mohammedia Hassan II University of Casablanca Casablanca Morocco

ISBN: (纸本)9783031770029

the Internet of things (IoT) stands out as a dynamic and transformative force in contemporary technology, facilitating the connection of physical objects to the internet for seamless data exchange among themselves and with humans. this connectivity enables automation, real-time monitoring, and improved decision-making, fostering significant advancements across various industries and aspects of daily life. However, the proliferation of IoT devices has led to a notable surge in energy consumption, posing a considerable challenge. this paper delves into a pioneering solution aimed at mitigating the energy consumption issue inherent in the widespread adoption of IoT devices. Our approach involves tapping into the energy generated by the magnetic fields of electrical wires, presenting a novel perspective to address this growing concern. through a thorough comparative analysis of existing methodologies, we not only highlight the limitations of current approaches but also introduce a more efficient technique. the proposed methodology exhibits promising advantages in terms of energy recovery and device sustainability, paving the way for a more environmentally conscious and resource-efficient IoT ecosystem. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Energy harvesting

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Developing an Esports Assistant System for First Person Shooting Game Based on Multimodal Learning 14th

Developing an Esports Assistant System for First Person Shoo...

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14th international conference on frontier Computing, FC 2024

作者： Chiu, Wei-Hsiang Hung, Jason C. Ma, Hao-Shang Huang, Chun-Hong Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan City Taiwan

ISBN: (纸本)9789819623945

We plan to develop a specialized training system to enhance the competitive skills of players in the first-person shooter game "Valorant", aiming to improve their abilities and tactical understanding within the game. We will adopt a multimodal image-text fusion technique to enhance the model’s learning of sample similarity. Specifically, we will use the cross-entropy function to maximize the diagonal values of the similarity matrix, thereby capturing the features of similar samples and reducing the similarity between dissimilar samples. through this process, we ensure that the model can map the same entity across different modalities into similar embedding representations, while distinguishing unrelated samples. Our goal is to find a way of embedding representation during the learning process that enables the model to better understand and represent multimodal data. We will utilize the YOLOv7 model for object detection to identify destructible skills. Based on the results of object detection, we will generate relevant textual descriptions for each object. this will enable novice players to quickly understand the function of diverse and complex skills and take appropriate actions when encountering them. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Object detection

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Reward-Based Spectrum Sensing and Allocation Mechanism Defending Against SSDF Attacks 14th

Reward-Based Spectrum Sensing and Allocation Mechanism Defe...

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14th EAI international conference on Wireless and Satellite Systems, WiSATS 2024

作者： Huang, Liubi Wang, Wei Lu, Xiaozhen Sun, Jinge Zhou, Bo Wang, Mingjie College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China Academy for Network and Communications of China Electronics Technology Group Corporation Shijiazhuang050081 China

ISBN: (纸本)9783031862021

the acquisition of reliable spectrum data is a prerequisite for spectrum sharing. However, current spectrum sensing faces serious Spectrum Sensing Data Falsification (SSDF) attacks. To mitigate this challenging issue, we propose a reward-based joint spectrum sensing and channel allocation scheme, where secondary users are required to submit estimated revenue values along with their sensing results to the fusion center, the center then allocates channels based on the revenue results. the channel allocation problem is formulated as an optimization problem to maximize revenue, which is then solved using the Hungarian algorithm. Simulation results show that the obtained revenue of the secondary user with normal sensing is significantly higher than that of when launching SSDF attacks, demonstrating the effectiveness of the proposed scheme in mitigating SSDF attacks. Moreover, the proposed scheme outperforms existing spectrum sensing and channel allocation schemes when the number of trusted users is small. © ICST Institute for computer sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Credible Spectrum Sensing Spectrum Access SSDF Attacks

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