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Greedy Tuning Algorithm for Resource Scheduling of PISA Chips 2

Greedy Tuning Algorithm for Resource Scheduling of PISA Chip...

引用

2nd international conference on Innovations and Development of Information Technologies and robotics, IDITR 2023

作者： Guo, Yikai Liu, Jie Duan, Zhiyu Luo, Zhizhao Li, Wei Ning, Bowei Beijing Institute of Computer Technology and Application Beijing China Beijing Aerocim Technology Corporation Limited Ltd Beijing China Beijing Institute of Remote-Sensing Equipment Beijing China

ISBN: (纸本)9798350345575

PISA (Protocol Independent Switch Architecture) is one of the mainstream programmable chip architectures, allowing users to define the functions and behaviors of the data plane with PISA language. The PISA chip optimizes robot design by providing flexible data processing capabilities, reducing the difficulty of robot maintenance, and enhancing the interoperability of the robot with other devices or systems. However, the application of the PISA chip faces two challenges. (1) Due to the complex dependencies and constraints in the chip, the current chip resource allocation algorithms waste a lot of pipeline stages when executing basic blocks of programs. (2) The time complexity of existing resource scheduling algorithms is high, which affects the efficiency of the chip. To tackle these challenges, we introduce a low-complexity greedy tuning algorithm to schedule the resource of the chip. Firstly, we unify the data dependencies and control dependencies as path constraints, which are derived from the program flowchart and variable read-write information. Then the initial feasible schedule scheme is constructed under the given constraints. Finally, we optimize the initial feasible solution by designing a new data structure, namely segment flowchart, which efficiently solves the resource-sharing problem among basic blocks within the same pipeline stage. In a practical example, basic blocks are successfully placed into the pipeline under given constraints, saving 14.9% of pipeline stages compared with the sequential approach. Our code and dataset are publicly available. © 2023 IEEE.

关键词： Approximation algorithms

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Building a Light Weight Intelligible Text-to-Speech Voice Model for Indian Accent Telugu 2

Building a Light Weight Intelligible Text-to-Speech Voice Mo...

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2nd international conference on Edge Computing and Applications, ICECAA 2023

作者： Kumar, Chevella Anil Chalapathi Rao, Y. Senapati, Ranjan K. Kumar, Vondala Naveen Electronics & Communication Engineering VNRVignana Jyothi Institue of Engineering& Technology Telangana Hyderabad India

ISBN: (纸本)9798350347579

Text-to-speech (TTS) synthesis involves creating machines that can talk. It is the process of automatically converting written text into spoken speech. TTS systems are important in human-computer interaction, and they have become more prominent with the advancement of computer technology. There has been a growing demand for speech applications in various areas such as telemedicine, robotics, Google Assistant, and other fields, especially during the Covid-19 era. It is clear that the existing speech technology is not good enough for users. Many speech applications still use pre-recorded prompts instead of text-to-speech because the quality of text-to-speech isn't good, and it can't pronounce non-standard words. In this study, a dependable and effective approach is proposed for creating speech synthesis voices that are specialized for specific domains and can handle non-standard words. This involves developing lexicon rules for non-standard words. By constructing databases that are closely related to the specific domain of the speech application, concatenative unit selection synthesis techniques, implemented using the festival/festvox tool, can be utilized to achieve high-quality, intelligible, and natural speech synthesis within the targeted domain. And the quality of proposed voice model is measured using Melcepstral distortion as an objective metric and Mean Opinion score as a subjective metric. © 2023 IEEE.

关键词： Speech synthesis

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The Role of System Modeling on Artificial Intelligence: A Review of Emerging Trends 2

The Role of System Modeling on Artificial Intelligence: A Re...

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2nd Edition IEEE international conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023

作者： Aldoihi, Saad Alblalaihid, Khalid Alzemaia, Fozah Almoajel, Alia Institute of Earth and Space Science King Abdulaziz City for Science and Technology Riyadh Saudi Arabia College of Education King Saud University Riyadh Saudi Arabia College of Applied Medical Sciences King Saud University Riyadh Saudi Arabia

ISBN: (纸本)9798350300802

System modeling is essential to the growth and comprehension of artificial intelligence (AI). It offers a way to describe, examine, and improve sophisticated AI systems. The significance of system modeling in AI is explored in this paper, along with examples of its use in robotics, machine learning, and natural language processing. We also discuss the difficulties and possible directions in system modeling for AI, highlighting its potential to further improve the robustness and capabilities of AI systems. © 2023 IEEE.

关键词： Artificial Intelligence Deep Learning Reinforcement Learning System Engineering System Modeling

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Design of a Convenient Upper Limb Exoskeleton Robot Based on Spring Energy Storage 2

Design of a Convenient Upper Limb Exoskeleton Robot Based on...

引用

2nd international conference on Advanced Manufacturing technology and Manufacturing systems, ICAMTMS 2023

作者： Ning, Yeyan Li, Yunji Zhang, Zhenyu Cai, Jun The 21st Research Institute of China Electronics Technology Group Corporation Shanghai China

ISBN: (纸本)9781510667327

The development of upper limb exoskeleton robots is an important stage in the high-quality development of robotics technology. The existing upper limb exoskeleton robots have a single function and complex structure, and their wearability needs to be improved. This paper designs a convenient upper limb exoskeleton robot based on spring energy storage, analyzes the degree of freedom of muscle joints when the human arm moves from the perspective of human bionics, solves the convenience and comfort of users' wearing from the mechanical structure, improves man-machine cooperation, analyzes the calculation principle of joint torque when the human arm moves, optimizes the spring energy storage module, and innovatively adopts the extension spring scheme, Increasing the interchangeability of parts is conducive to the convenient replacement of mechanical structures, and the combination of forearm assistance and boom assistance is used to effectively improve the assistance effect. The effectiveness of the prototype movement is verified by calculating the assistance ratio. © 2023 SPIE.

关键词： Energy storage

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A Comparative Study of Cross-Sentence Features for Named Entity Recognition 2

A Comparative Study of Cross-Sentence Features for Named Ent...

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2nd international conference on Innovations and Development of Information Technologies and robotics, IDITR 2023

作者： Wang, Sheng-Fu Huang, Jing Zhang, Baohua Li, Jia Beijing Institute of Technology School of Computer Science and Technology Beijing China Co. Ltd China State Key Laboratory of Media Convergence Production Technology and Systems China Xinhua New Media Culture Communication Co Ltd China Big DataandArtificial Intelligence Laboratory Industrial and Commercial Bank of China Shanghai China

ISBN: (纸本)9798350345575

Recently, a growing number of Named Entity Recognition (NER) methods utilize cross-sentence features (also known as contexts) to improve the performance of NER models, instead of using single-sentence information alone. As far as we know, most NER models choose to exploit pre-and post-sentences to capture cross-sentence features. Generally, current NER studies focus only on the model architecture to capture better token representations. However, there is no in-depth exploration on how to better model cross-sentence features. In this paper, based on the span classification model, we investigate the effect of cross-sentence features under different settings. Specifically, we evaluate the impact of context stitching, context window size, context window padding, and classifier token of pre-Trained language model (PLM) on model performance. Comparative experimental results show that appropriate incorporation of document-level contexts can considerably improve the NER metrics. Furthermore, we find that several factors can be used to improve the performance of NER models: (1) use domain-specific PLMs, but not classifier tokens;(2) use only preceding contexts for generic text, and random contexts for specialized text;(3) truncate overly long contexts when the context window is small, and preserve sentence integrity when the window is large;(4) set the context window size to about 200 for the basic size PLM. © 2023 IEEE.

关键词： Classification (of information)

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Port Smart Gate Ground Scale Line Pressure Detection using Federated Learning: Backdoor Attacks 2

Port Smart Gate Ground Scale Line Pressure Detection using F...

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2nd international conference on Artificial Intelligence, Human-Computer Interaction and robotics, AIHCIR 2023

作者： Tang, Chunming Liu, Jinghong Dai, Xinguang Li, Yan Tiangong University Tianjin Key Experiment on Intelligent Control of Electrical Equipment Tianjin China Tianjin Port Information Technology Development Co. Tianjin China

ISBN: (纸本)9798350360363

The traditional port smart gate ground scale line pressure detection system employs a centralized data training method that carries the risk of privacy leakage. Federated Learning offers an effective solution to this issue by enabling each port gate to locally train data, sharing only model parameters, without the need to transmit raw data to a central server. This is particularly crucial for ground scale line pressure detection systems dealing with sensitive data. However, researchers have identified potential risks of backdoor attacks when applying Federated Learning. Currently, most existing backdoor attacks are directed towards image classification and centralized object detection. However, backdoor attacks for Federated Learning-based object detection tasks have not been explored. In this paper, we reveal that these threats may also manifest in this task. To analyze the impact of backdoor attacks on this task, we designed three backdoor attack triggers and proposed three trigger attack operations. To assess backdoor attacks on this task, we developed corresponding metrics and conducted experiments on local datasets from three port gates. The experimental results indicate that Federated Learning-based object detection tasks are susceptible to backdoor threats. © 2023 IEEE.

关键词： Object detection

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Human Motion State Recognition Method Based on Plantar Pressure Sensing technology 2

Human Motion State Recognition Method Based on Plantar Press...

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2nd international conference on Artificial Intelligence, Human-Computer Interaction and robotics, AIHCIR 2023

作者： Xu, Zhiwei Tian, Chenhao Zhu, Xiaolin Lu, Zongxing School of Advanced Manufacturing Fuzhou University Jinjiang China School of Mechanical Engineering and Automation Fuzhou University Fuzhou China

ISBN: (纸本)9798350360363

As one of the important health indicators of the body, plantar pressure distribution has great reference value in clinical medicine, sports and fitness training, and rehabilitation fields. The purpose of plantar pressure collection is to identify the movement patterns and pressure distribution information of the human lower limbs. This article focuses on introducing the design of plantar pressure detection and motion detection systems from the aspects of array plantar pressure sensors, STM32 acquisition circuits, acquisition programs, and gait segmentation recognition algorithms. During the process of human body state recognition, the collection system sequentially scans 16 plantar pressure sensors and transmits the collected data to the pressure measurement recognition software for real-time graphic display and motion recognition. Wireless communication is carried out using WiFi transmission, and repetitive action segmentation and different pose recognition are achieved using gait segmentation algorithm and SVM algorithm. And a detection system experimental platform was built to recognize 8 daily movements such as sitting, standing, and going up and down stairs, with a recognition rate of 93.65%, laying the experimental foundation for motion parameter analysis and foot rehabilitation evaluation. © 2023 IEEE.

关键词： Motion estimation

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A Novel Microwave Imaging using Flexible Triangular Fractal Monopole and Antipodal Vivaldi Antennas 2

A Novel Microwave Imaging using Flexible Triangular Fractal ...

引用

2nd international conference on Smart Technologies, Communication and robotics, STCR 2022

作者： Satheesh Kumar, S. Vanathi, P.T. KPR Institute of Engineeing and Technology Department of Electronics and Communication Engineering Coimbatore India PSG College of Technology Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9781665460477

Designing an antenna is a significant challenge with as small-size and high performance architecture. The novelty relies in the changes that would have been adopted on the fundamental shape of the antenna. The Fractal antenna is designed based on the composite structure formed by the repetition of fundamental shape without altering the self-analogues and space occupying feature. In this design, the ISM band monopole antenna structure is planted on a Sierpinski Gasket with the help of iterative triangular function systems. In this paper, convergence criterion of a moment of a Vivaldi antenna and mesh convergence of a simple dipole antenna was investigated with a new novel design-"Antipodal Vivaldi Antenna"which can be used with various biomedical applications. © 2022 IEEE.

关键词： Monopole antennas

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Research on Data Information Security Anti-attack technology to Improve ASON Network Architecture 2

Research on Data Information Security Anti-attack Technology...

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2nd international conference on Artificial Intelligence and Autonomous Robot systems, AIARS 2023

作者： Xie, Yingzhao Dai, Cheng Zheng, Yuanbing Wang, Jian Information & Telecommuniccation Branch of State Grid Chongqing Power Company Chongqing401102 China

ISBN: (纸本)9798350324358

As a general control plane, ASON optical network successfully introduced distributed signaling. By overcoming various drawbacks and shortcomings caused by traditional optical network's over-reliance on static manual configuration, ASON optical network successfully obtained the fusion state of switching and transmission in optical layer. In this paper, the research of data information security anti-attack technology for improving ASON network architecture is carried out. In this paper, we propose a technical scheme to improve the data information security of ASON network architecture, and improve Dijkstra algorithm to realize multi-constraint routing calculation to meet ASON routing requirements. The research results show that the data information security anti-breach technology proposed in this paper has a better transmission effect because its transmission bit error rate is less than 0.5% for two different attacks. In the case of attack, with the increase of network load, the blocking rate caused by routing protocol with security mechanism is obviously lower than that caused by routing protocol without security mechanism. © 2023 IEEE.

关键词： Network architecture

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SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation 25

SCONE: A Novel Stochastic Sampling to Generate Contrastive V...

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18th international conference on Web Search and Data Mining-WSDM

作者： Lee, Chaejeong Choi, Jeongwhan Wi, Hyowon Cho, Sung-Bae Park, Noseong Korea Telecom Seoul South Korea Yonsei Univ Seoul South Korea Korea Adv Inst Sci & Technol Daejeon South Korea

ISBN: (纸本)9798400713293

Graph-based collaborative filtering (CF) has emerged as a promising approach in recommender systems. Despite its achievements, graph-based CF models face challenges due to data sparsity and negative sampling. In this paper, we propose a novel Stochastic sampling for i) COntrastive views and ii) hard NEgative samples (SCONE) to overcome these issues. SCONE generates dynamic augmented views and diverse hard negative samples via a unified stochastic sampling approach based on score-based generative models. Our extensive experiments on 6 benchmark datasets show that SCONE consistently outperforms state-of-the-art baselines. SCONE shows efficacy in addressing user sparsity and item popularity issues, while enhancing performance for both cold-start users and longtail items. Furthermore, our approach improves the diversity of the recommendation and the uniformity of the representations. The code is available at https://***/jeongwhanchoi/SCONE.

关键词： recommender systems collaborative filtering contrastive learning negative sampling score-based generative models

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