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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Chen, Changxin Luo, Xinjie Yan, Yunyao Xiang, Guoqing Zhang, Peng Huang, Xiaofeng Yan, Wei Peking University School of Software Microelectronics Beijing China Advanced Institute of Information Technology Peking University Beijing China School of Electronic and Computer Engineering Peking University Shenzhen China School of Communication Engineering Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781665441544

Third generation audio and video coding standard (AVS3) is a latest video coding standard developed by China. AVS3 allows flexible coding unit (CU) partition by applying quad-tree (QT), binary tree (BT), and extended quad-tree (EQT) partitioning structures. The increased block partition flexibility brings the significant coding complexity cost. This paper proposes a fast CU partition decision method based on the gradient and the variance for AVS3 intra coding. Experimental results show that the proposed fast algorithm can achieve a good balance between computational complexity and coding performance. Compared with AVS3 software reference HPM4.0, the coding time is reduced by 43%, while the average BD-Rate is only increased by 0.9% in AI (All-Intra) configuration. © 2022 IEEE.

关键词： Binary trees

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AI LipReader-Transcribing Speech from Lip Movements

AI LipReader-Transcribing Speech from Lip Movements

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： D Ajitha Disha Dutta Falguni Saha Parus Giri Rohan Kant Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Vellore Vellore India Department of Database Systems School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Information Security School of Computer Science and Engineering Vellore Institute of Technology Vellore Vellore India

Lip Reading AI is a discipline that is rapidly changing and has numerous applications in security, accessibility and human-computer interaction. This paper proposes a model which combines Convolutional Neural Networks (CNNs) to capture spatial capabilities, Long Short-Term Memory (LSTM) networks to examine temporal dependencies, and an adaptive interest mechanism. Meticulous preprocessing of the MIRACL VC-l dataset addressing challenges including one of a kind lip moves and occlusions accompanied with the aid of transitioning this study effortlessly to LRS2 dataset to complement lexemic versatility is one of its key function. The effects verify its robustness throughout unique datasets with superior overall performance towards cutting-edge techniques. Ablation checks suggest the crucial significance of every element in phrases of improving lip analyzing accuracy. Our proposed model version additionally suggests flexibility in restricted and naturalistic language situations.

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Improving sentiment analysis accuracy with emoji embedding

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Journal of Safety Science and Resilience 2021年第4期2卷 246-252页

作者： Chuchu Liu Fan Fang Xu Lin Tie Cai Xu Tan Jianguo Liu Xin Lu College of Systems Engineering National University of Defense TechnologyChangsha410073China College of Computer National University of Defense TechnologyChangsha410073China School of Software Engineering Shenzhen Institute of Information TechnologyShenzhen518172China Institute of Accounting and Finance Shanghai University of Finance and EconomicsShanghai200433China

Due to the diversity and variability of Chinese syntax and semantics,accurately identifying and distinguishing individual emotions from online texts is *** overcome this limitation,we incorporate a new source of individual sentiment,emojis,which contain thousands of graphic symbols and are increasingly being used for expressing emotion in online *** examined popular sentiment analysis algorithms,including rule-based and classification algorithms,to evaluate the impact of supplementing emojis as additional features to improve the algorithm *** were also translated into corresponding sentiment words when con-structing features for comparison with those directly generated from emoji label *** addition,considering different functions of emojis in texts,we classified all posts in the dataset by their emoji usage and examined the changes in algorithm *** found that emojis are effective as expanding features for improving the accuracy of sentiment analysis algorithms,and the algorithm performance can be further increased by taking different emoji usages into *** this study,we developed an improved emoji-embedding model based on Bi-LSTM(namely,CEmo-LSTM),which achieves the highest accuracy(around 0.95)when analyzing online Chinese *** applied the CEmo-LSTM algorithm to a large dataset collected from Weibo from December 1,2019 to March 20,2020 to understand the sentiment evolution of online users during the COVID-19 *** found that the pandemic remarkably impacted individual sentiments and caused more passive emotions(e.g.,horror and sadness).Our novel emoji-embedding algorithm creatively combined emojis as well as emoji usage with the sentiment analysis model and can handle emotion mining tasks more effectively and efficiently.

关键词： Sentiment analysis Emoji CEmo-LSTM Sentiment evolution COVID-19

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MSCKF-DVIO: Multi-State Constraint Kalman Filter based RGB-D Visual-Inertial Odometry with Spline Interpolation and Nonholonomic Constraint

MSCKF-DVIO: Multi-State Constraint Kalman Filter based RGB-D...

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International Conference on Ubiquitous Robots (UR)

作者： Kwangyik Jung Jaebong Song Samwoo Seong Hyun Myung Department of Autonomous Driving Software Development Twinny Yuseong-gu Republic of Korea Urban Robotics Lab School of Electrical Engineering Korea Advanced Institute of Science and Technology Republic of Korea

ISBN: (数字)9798350361070

ISBN: (纸本)9798350361087

This study presents MSCKF-DVIO (Multi-State Constraint Kalman Filter - Depth-aided Visual Inertial Odom-etry) as an innovative approach to address the limitations of existing methods. MSCKF-DVIO leverages RGB-D images and low-cost IMU measurements to enhance the accuracy and efficiency of visual-inertial odometry systems. The proposed framework jointly optimizes RGB-D images and low-cost IMU measurements, enabling robust and precise state estimation. By reducing the number of state variables compared to the existing MSCKF-VIO, the efficiency of state augmentation and covariance computations is significantly enhanced. Notably, the prediction of the future state is achieved through the interpolation of past keyframe viewpoint poses from the image and short-time IMU integration. The proposed MSCKF-DVIO improves the accuracy of estimation by applying nonholonomic constraints (NHCs) of a differential-wheeled mobile robot and utilizing the zero velocity update (ZUPT) based on stationary state determination. The efficacy of MSCKF -DVIO is evaluated through the Absolute Pose Error (APE) using 3D LiDAR-based localization as the ground truth. The evaluation includes pose estimation outcomes and performance evaluations in comparison to other algorithms. The results demonstrate significant promise of MSCKF-DVIO for improving the performance and reliability of visual-inertial odometry systems.

关键词： Interpolation Visualization Accuracy Stationary state Filtering algorithms Information filters Real-time systems

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CAC 2.0: A Corrupt and Correct Logic Locking Technique Resilient to Structural Analysis Attacks

arXiv

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arXiv 2024年

作者： Aksoy, Levent Yasin, Muhammad Pagliarini, Samuel Department of Computer Systems Tallinn University of Technology Tallinn Estonia Department of Computer and Software Engineering National University of Sciences and Technology Islamabad Pakistan Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh United States

Logic locking proposed to protect integrated circuits from serious hardware threats has been studied extensively over a decade. In these years, many efficient logic locking techniques have been proven to be broken. The state-of-the-art logic locking techniques, including the prominent corrupt and correct (CAC) technique, are resilient to satisfiability (SAT)-based and removal attacks, but vulnerable to structural analysis attacks. To overcome this drawback, this paper introduces an improved version of CAC, called CAC 2.0, which increases the search space of structural analysis attacks using obfuscation. To do so, CAC 2.0 locks the original circuit twice, one after another, on different nodes with different number of protected primary inputs using CAC, while hiding original protected primary inputs among decoy primary inputs. This paper also introduces an open source logic locking tool, called HIID, equipped with well-known techniques including CAC 2.0. Our experiments show that CAC 2.0 is resilient to existing SAT-based, removal, and structural analysis attacks. To achieve this, it increases the number of key inputs at most 4× and the gate-level area between 30.2% and 0.8% on circuits with low and high complexity with respect to CAC. © 2024, CC BY.

关键词： Structural analysis

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Energy Efficiency Improvement System for AC Circuits

Energy Efficiency Improvement System for AC Circuits

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2024 Conference of Young Researchers in Electrical and Electronic engineering, ElCon 2024

作者： Kulagin, Vladimir Selivanov, Kirill Vlasov, Andrey Aminev, Dmitrii Bunina, Lyudmila Bikovsky, Sergey Moscow Technical University of Communications and Informatics Moscow Russia Bauman Moscow State Technical University Bmstu Department of Design and Technology of Electronic Devices Moscow Russia Russian Technological University - Mirea Department of Development of Software Solutions and System Programming Moscow Russia Russian Technological University - Mirea Department of Electrical Engineering Systems Moscow Russia

ISBN: (纸本)9798350360646

The problem of the rational use of energy resources remains constantly relevant and requires the search for new approaches. One of them is power control. In AC circuits, the authors see the most promising method of phase AC power control. Based on it, a power control module was developed. The structural and circuit diagrams of the developed device are presented to implement the proposed solution. The authors produced its experimental prototype and conducted experimental testing at various levels of regulated power. Savings when using the proposed power control module were calculated using the example of energy consumption in various sectors of energy-intensive systems. According to the data obtained, the module allows saving energy consumption without significant discomfort to the energy user. The calculated results allow concluding that the proposed AC power control module is fully operational, and its widespread use will significantly reduce the need for electricity. © 2024 IEEE.

关键词： energy consumption energy efficiency power control

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Enhancing Group Privacy for Effective CIoT Data Mining in 6G Networks Using Differential Privacy

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IEEE Transactions on Consumer Electronics 2025年

作者： Ning, Bo Zhang, Xinjian Liu, Chengfei Wang, Ning Li, Guanyu Dalian Maritime University School of Information Science and Technology Liaoning Dalian116026 China Swinburne University of Technolgy Department of Computer Science and Software Engineering MelbourneVIC3122 Australia Guangzhou University Cyberspace Institute of Advanced Technology Guangdong Guangzhou511442 China

In the realm of 6G wireless networks, the Consumer Internet of Things (CIoT) aims to revolutionize consumer electronics by integrating advanced technologies such as Artificial Intelligence (AI). As CIoT environments become more dynamic and data-rich, ensuring data privacy while maintaining the utility of data mining is crucial. Graph data mining, which models object relationships with expressive capabilities, is central to this transformation but may pose data leakage risks. Traditional differential privacy methods in graphs often focus on releasing attribute or node information or adding excessive noise, reducing data availability. Therefore our focus is on protecting group relationships and leveraging their closeness to design budget allocation mechanisms that reduce noise. The proposed model uses k-cores to hierarchically manage group relationships, considering the variation in edges between k-cores and (k-1)-cores. Significant changes indicate a high degree of aggregation and interdependence at higher levels, warranting greater privacy protection. By allocating the privacy budget according to edge levels, our approach balances protection and data availability. Experiments on four types of graphs show that the network generated by our model accurately represents the original graph, making it suitable for subsequent data mining applications. © 2025 IEEE.

关键词： Information leakage

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On the properties of kullback-leibler divergence between multivariate Gaussian distributions 23

On the properties of kullback-leibler divergence between mul...

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Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Yufeng Zhang Jialu Pan Kenli Li Wanwei Liu Zhenbang Chen Xinwang Liu Ji Wang College of Computer Science and Electronic Engineering Hunan University Changsha China College of Computer Key Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China College of Computer State Key Laboratory for High Performance Computing Key laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China

Kullback-Leibler (KL) divergence is one of the most important measures to calculate the difference between probability distributions. In this paper, we theoretically study several properties of KL divergence between multivariate Gaussian distributions. Firstly, for any two n-dimensional Gaussian distributions Ɲ1 and Ɲ2, we prove that when KL(Ɲ2‖Ɲ1) ≤ ε (ε > 0) the supremum of KL (Ɲ1‖Ɲ2) is (1/2) ((-W0 (-e-(1+2ε)))-1 + log(-W0 (-e-(1+2ε))) - 1), where W0 is the principal branch of Lambert W function. For small ε, the supremum is ε + 2ε1.5 + O (ε2). This quantifies the approximate symmetry of small KL divergence between Gaussian distributions. We further derive the infimum of KL(Ɲ1‖Ɲ2) when KL(Ɲ2‖Ɲ1) ≥ M (M > 0). We give the conditions when the supremum and infimum can be attained. Secondly, for any three n-dimensional Gaussian distributions Ɲ1, Ɲ2, and Ɲ3, we theoretically show that an upper bound of KL (Ɲ1‖Ɲ3) is 3ε1 + 3ε2 + 2√ε1ε2 + o(ε1)+ o(ε2) when KL (Ɲ1‖Ɲ2) ≤ ε1 and KL(Ɲ2‖Ɲ3) ≤ ε2 (ε1, ε2 ≥ 0). This reveals that KL divergence between Gaussian distributions follows a relaxed triangle inequality. Note that, all these bounds in the theorems presented in this work are independent of the dimension n. Finally, we discuss several applications of our theories in deep learning, reinforcement learning, and sample complexity research.

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Discrepancies of remote techno-tolerance due to COVID-19 pandemic within Arab middle-east countries

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Journal of Umm Al-Qura University for engineering and Architecture 2023年第3期14卷 151-165页

作者： Abu-Hashem, Muhannad A. Gutub, Adnan Salem, Osama Shambour, Mohd Khaled Shambour, Qusai Shehab, Mohammad Izzat, Ahmad Alrawashdeh, Mufda J. Department of Geomatics Architecture and Planning Faculty King Abdulaziz University Jeddah Saudi Arabia Computer Engineering Department College of Computer and Information Systems Umm Al-Qura University Makkah Saudi Arabia Educational Technology and E-Learning Department College of Education Umm Al-Qura University Makkah Saudi Arabia The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura University Makkah Saudi Arabia Software Engineering Department Faculty of IT Al-Ahliyya Amman University Amman Jordan Artificial Intelligence & Software Engineering Departments Faculty of Information Technology Aqaba University of Technology Aqaba Jordan Faculty of Engineering and Information Technology Israa University Gaza Palestine Department of Mathematics College of Sciences and Arts Qassim University Al-Ras Saudi Arabia

The coronavirus disease (COVID-19) changed the world’s lifestyle switching many techno-services to be provided remotely instead of direct usual physical interactions between people. This study focused on university students’ perceptions of this virtual technology-engineering change as discrepancies to be analyzed. The research surveyed 777 different students from four Arab middle-east neighboring countries, with related demographics and specifications, expressing full remarkable experiences of e-technology in virtual as well as traditional performances helping reveal overall tolerance possibilities. The study adopted examination technology via ANOVA to test discrepancies within students' perceptions for overall multi-factors deep analysis classification. The exploration highlighted an interesting range of pros and cons remarks including feminism and economic effect as well as other cultural and engineering interaction issues, raising signals to essentially consider and mutually benefit from adequate future generation e-techno adaptation within the region. © The Author(s) 2023.

关键词： ANOVA COVID-19 E-techno Students’ perceptions Traditional and virtual classes

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A Hybrid Algorithm for the Laser Stripe Centreline Extraction 17

A Hybrid Algorithm for the Laser Stripe Centreline Extractio...

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17th CIRP Conference on Computer Aided Tolerancing, CAT 2022

作者： Mao, Zirui Xu, Yuanping Guo, Benjun Li, Tukun Jiang, Xiangqian Shi, Yajing Cao, Yanlong Xu, Zhijie Zhang, Chaolong Huang, Jian School of Software Engineering Chengdu University of Information Technology Chengdu China School of Computing and Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province College of Mechanical Engineering Zhejiang University Hangzhou310027 China

Centreline extraction is one of the critical processes of structured light systems that play an increasingly important role in industry 4.0. This paper proposes a novel algorithm to extract the centreline by combining an improved skeleton thinning algorithm to extract the initial centreline and an improved grey centroid algorithm to establish the final centreline. It consists of several steps: Firstly, an image difference operation and a thresholding operation are undertaken, and the Canny edge detection algorithm is applied to locate the approximate position of the laser stripe to reduce the image matrix calculation cost;Secondly, an initial centreline is extracted via the use of an image morphology operation and a skeleton thinning algorithm;Finally, a high-power grey centroid method is employed to acquire the centreline at the sub-pixel level. Experiments together with a comparison with other mainstream methods is conducted to test the validity and practicability of the proposed hybrid algorithm. The experimental results show that the speed of the proposed algorithm is 50% faster than the Steger algorithm, and the root-mean-square error is 40% lower than the grey centroid method. © 2022 The Author(s).

关键词： Mean square error

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