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29th International Conference on Computational Linguistics, COLING 2022

作者： Elsafoury, Fatma Wilson, Steven R. Katsigiannis, Stamos Ramzan, Naeem School of Physics Engineering and Computing The University of The West of Scotland United Kingdom Department of Computer Science and Engineering Oakland University United States Department of Computer Science Durham University United Kingdom

Systematic Offensive stereotyping (SOS) in word embeddings could lead to associating marginalised groups with hate speech and profanity, which might lead to blocking and silencing those groups, especially on social media platforms. In this work, we introduce a quantitative measure of the SOS bias, validate it in the most commonly used word embeddings, and investigate if it explains the performance of different word embeddings on the task of hate speech detection. Results show that SOS bias exists in almost all examined word embeddings and that the proposed SOS bias metric correlates positively with the statistics of published surveys on online extremism. We also show that the proposed metric reveals distinct information compared to established social bias metrics. However, we do not find evidence that SOS bias explains the performance of hate speech detection models based on the different word embeddings. © 2022 Proceedings - International Conference on Computational Linguistics, COLING. All rights reserved.

关键词： Embeddings

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Enhancement of Electronic Medical Record (EMR) Security in Private Networks with Blockchains 3

Enhancement of Electronic Medical Record (EMR) Security in P...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： El-Hamed, Osama M. Abd El-Samie, Fathi E. Abd El-Atty, Saied M. Abd El-Din Hemdan, Ezz Badawy, Wael Menoufia University Faculty of Electronic Engineering Dept. of Electronics and Electrical Communications Menouf Egypt Menoufia University Faculty of Electronic Engineering Dept. of Computer Ecience and Engineering Menouf Egypt University of Hertfordshire Hosted by Gaf School of Physics Engineering and Computer Science United Kingdom

ISBN: (纸本)9798350323511

In this paper, we propose a system for improving the security of Electronic Medical Records (EMRs) in private networks using Blockchain technology. There are currently problems with data integrity in database systems that contain health records. Application Programming Interfaces (APIs) are frequently used by amateur organizations to create internal frameworks, which might result in data manipulation in an improper way and unauthorized access. We put up a practical solution for this issue that makes use of Blockchain immutability. Our system depends on HTML forms and NodeJS to store patient-related records in a MySQL database. However, using the secure hashing SHA-256, we store the hash values of the records in blocks rather than the actual records themselves. This method ensures that any unauthorized alterations in the records may be quickly identified by comparing the stored hash value with the actual hash of the data that is obtained from the database. Our system performance analysis, which shows acceptable latency, was done. The Blockchain runs in the background without having a substantial influence on speed, thus the database continues to run quickly. Our system also saves money, because it is designed to be used with a user-programmed Blockchain within private networks. It is offered at no additional cost, and is primarily made to verify data accuracy. For private networks depending on EMR systems, our suggested solution provides improved security, effective performance, and affordability as compared to existing approaches and frameworks. © 2023 IEEE.

关键词： Blockchain

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Strain-balanced AlScN/GaN HEMTs with fT/fMAX of 173/321 GHz

Strain-balanced AlScN/GaN HEMTs with fT/fMAX of 173/321 GHz

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2024 IEEE International Electron Devices Meeting, IEDM 2024

作者： Nguyen, T.S. Nomoto, K. Zhao, W. Savant, C. Xing, H.G. Jena, D. Department of Materials Science and Engineering Cornell University IthacaNY14853 United States School of Electrical and Computer Engineering Cornell University IthacaNY14853 United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Kavli Institute Cornell for Nanoscale Science Cornell University IthacaNY14853 United States

ISBN: (纸本)9798350365429

We report the effect of scaling the gate length from 0.8 µm to 40 nm on the performance of novel strain-balanced AlScN/GaN high electron mobility transistors (HEMTs) on SiC substrates. A new strain-balanced heterostructure is introduced where the tensile strain of the AlN interlayer is balanced by the compressive strain in the AlScN barrier layer. MBE regrown source/drain ohmics with ultralow contact resistance of 0.09 Ω·mm allow a low HEMT on resistance of 0.83 Ω·mm. The shortest gate length AlScN/GaN HEMTs exhibit maximum drain currents of 2.8 A/mm, peak transconductance of 0.55 S/mm, and speed characterized by fT/fMAX of 173/321 GHz. The highest fMAX obtained here is ∼2X higher than previous AlScN HEMTs. © 2024 IEEE.

关键词： Gallium nitride

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Technical note: Error analysis of material-decomposition-based effective atomic number quantification method

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Medical physics 2024年第1期51卷 419-427页

作者： Chen, Li Ji, Xu Wang, Zhe Chen, Yang Laboratory of Image Science and Technology the School of Computer Science and Engineering Southeast University Nanjing China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Southeast University Nanjing China Beijing Engineering Research Center of Radiographic Techniques and Equipment Institute of High Energy Physics Chinese Academy of Sciences Beijing China Jinan Laboratory of Applied Nuclear Science Jinan China Ministry of Education China

Background: The effective atomic number (Zeff) is widely applied to the identification of unknown materials. One method to determine the Zeff is material-decomposition-based spectral X-ray imaging. The method relies on certain approximations of the X-ray interaction cross-sections such as empirical model coefficients. The impact of such approximations on the accuracy of Zeff quantification has not been fully investigated. Purpose: To perform an error analysis of the material-decomposition-based Zeff quantification method and propose a coefficient calibration-in-groups method to improve the modeling accuracy and reduce the Zeff quantification error. Methods: The model of the material-decomposition-based Zeff quantification method relies on the dependence of the interaction cross-sections (σPE) on the atomic number Z and corresponding coefficient, that is, (Formula presented.). In this work, all the data is from the National Institute of Standards and Technology (NIST) website. First, the coefficient m is calibrated through a logarithmic fitting method to quickly determine the m values for any certain energy and Zeff ranges. Then materials including elements and common compounds with Zeff ranging from 6–20 are selected as the objects whose effective atomic numbers are to be quantified. Different combinations of basis materials are applied to decompose the object materials and their quantification errors are analyzed. With the help of error analysis, the object materials are divided into high-error and low-error groups based on the decomposition coefficient ratio (Formula presented.), which is found to have a strong correlation with error, and their coefficients are calibrated in groups. Finally, the average errors of three m selection strategies: (1) using an empirical m value of 3.94, which is also considered a standard method;(2) using a single m value, which is calibrated through the logarithmic fitting method;(3) using different m values calibrated in groups, are

关键词： Atoms

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Three-Dimensional Station Distribution Design for TDOA Positioning System of Sea Launch Site 14th

Three-Dimensional Station Distribution Design for TDOA Posit...

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14th China Satellite Navigation Conference, CSNC 2024

作者： Chen, Maolin Li, Xianglu Liu, Changjiang Ji, Zhengyu Sun, Yimao Institute of Electronic Engineering China Academy of Engineering Physics Sichuan Province Mianyang City China Troop of PLA Sichuan Province Chengdu City78090 China School of Computer Science Sichuan University Sichuan Province Chengdu City China

ISBN: (纸本)9789819969272

In recent years, USA, Russia and China have carried out many sea launch and recovery experiments, sea launch site exhibits better safety and economical efficiency compared with land launch site, which can provide launch service for spacecraft with different orbits. GNSS/INS integrated navigation system is adopted by rockets to acquire positioning results, nevertheless, owing to the inherit vulnerability of GNSS and possible INS failure, other navigation system is required to offer independent multi-source positioning data. TDOA positioning system is able to calculate rocket’s position utilizing time measurement data from telemetering signals, on one hand, the reliability can be promoted, and on the other hand, real-time central monitoring can be achieved, which aroused an increasing number of interests. However, present TDOA system usually apply land stations to obtain time measurements and localization results, because the characteristics of flat station distribution along the vertical direction, the vertical positioning precision cannot be satisfactory, especially for the need of rocket recovery on the sea launch site. To solve this problem, this work first discusses the precision influence of different surveying ships distribution layouts, "T" shape distribution is recommended for surveying ships according to evaluation results, then introduces air-based surveying station into TDOA positioning system to improve vertical localization accuracy, probes the performance variation utilizing different UAVs, including tethered UAV, multi-rotor UAV, medium-scale vertical takeoff and landing fixed wing UAV and large-scale fixed wing UAV, confirms the optimal UAV height in the rocket recovery key area under 10 km height, then researches on surveying station optimal distribution layout strategy according to predefined trajectory. This work can enhance the positioning precision and reliability, and provide three-dimensional surveying station distribution guidance in sea launc

关键词： Recovery

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Analysis of Vegetable Sales Volume Distribution and Pricing Strategy: A Study Based on Nonparametric Kernel Density Estimation and Neural Network Modeling 3

Analysis of Vegetable Sales Volume Distribution and Pricing ...

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3rd IEEE International Conference on Electrical engineering, Big Data and Algorithms, EEBDA 2024

作者： Lin, Binru Shi, Yuxuan Wang, Jingyi Chen, Xinying School of Economics and Management Fuzhou University Fuzhou China School of Mathematics and Statistics Fuzhou University Fuzhou China College of Physics and Information Engineering Fuzhou University Fuzhou China College of Computer and Data Science Fuzhou University Fuzhou China

ISBN: (纸本)9798350380989

In this study, the distribution pattern of sales volume of each category and individual product of vegetables is analyzed by firstly using the non-parametric kernel density estimation method to obtain the kernel density estimation curves of the daily sales volume of each category and individual product of vegetables, and analyzing them in combination with statistical indicators. Secondly, based on the visualization of the monthly sales volume of each category of vegetables over time and the seasonal component plot, the sales trend is studied. Finally, Spearman rank correlation analysis is utilized to explore the correlation between the sales volume of each category and individual product of vegetables. Based on this, the total sales volume of each vegetable category is further analyzed in relation to cost plus pricing, and the sales volume is predicted by a time series model optimized by a neural network model to develop a pricing strategy for the coming week in order to maximize revenue. © 2024 IEEE.

关键词： Neural network model Non-parametric kernel density estimation method Spearman rank correlation analysis Time series

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Mean-Closure Based Multimodal Biometric System using Sum- Combinational Rule 2

Mean-Closure Based Multimodal Biometric System using Sum- Co...

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2nd IEEE International Conference on Intelligent Technologies, CONIT 2022

作者： Tomar, Peeyush Singh, Ram C. Abidi, Ali Imam Vidya College of Engineering Department of Computer Science and Engineering Meerut India School of Basic Sciences and Research Sharda University Department of Physics Greater Noida India School of Engineering and Technology Sharda University Department of Computer Science and Engineering Greater Noida India

ISBN: (数字)9781665484077

ISBN: (纸本)9781665484077

Under the basic sum-rule-based score-level fusion, the performance of a multi-biometric system can be enhanced by applying an effective normalization technique. It can also be improved by applying weighting techniques to the individual biometric scores under the score-level fusion method. Under the weighted sum-rule-based score-level fusion, each biometric score is assigned a weight as per weighting schemes. This paper presents a multimodal biometric system using fingerprints and faces under a score-level fusion scheme. The Mean-Closure weighting scheme is used to assign weights to the biometric scores of fingerprints and faces. This scheme resolves the problem of scores that lie in the overlapping region of the biometric score distribution. The resultant scores are fused using a simple sum rule to generate a score that distinguishes between genuine and imposter scores on different thresholds. The experimental results are carried out on a self-constructed database of fingerprints and faces of 150 people. The proposed biometric system delivers an accuracy of 97.65% and a GAR of 98.55%, which outperforms the performance of the unimodal biometric system. © 2022 IEEE.

关键词： Biometrics

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When the Robotic Maths Tutor is Wrong - Can Children Identify Mistakes Generated by ChatGPT?

When the Robotic Maths Tutor is Wrong - Can Children Identif...

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Artificial Intelligence, Robotics and Control (AIRC), International Conference on

作者： Manal Helal Patrick Holthaus Luke Wood Vignesh Velmurugan Gabriella Lakatos Silvia Moros Farshid Amirabdollahian School of Physics Engineering and Computer Science University of Hertfordshire College Lane Hatfield UK

ISBN: (数字)9798350385076

ISBN: (纸本)9798350385083

This study delves into integrating Large Language Models (LLMs), particularly ChatGPT-powered robots, as educational tools in primary school mathematics. Against the backdrop of Artificial Intelligence (AI) increasingly permeating educational settings, our investigation focuses on the response of young learners to errors made by these LLM-powered robots. Employing a user study approach, we conducted an experiment using the Pepper robot in a primary school classroom environment, where 77 primary school students from multiple grades (Year 3 to 5) took part in interacting with the robot. Our statistically significant findings highlight that most students, regardless of the year group, could discern between correct and incorrect responses generated by the robots, demonstrating a promising level of understanding and engagement with the AI-driven educational tool. Additionally, we observed that students' correctness in answering the Maths questions significantly influenced their ability to identify errors, underscoring the importance of prior knowledge in verifying LLM responses and detecting errors. Additionally, we examined potential confounding factors such as age and gender. Our findings underscore the importance of gradually integrating AI-powered educational tools under the guidance of domain experts following thorough verification processes. Moreover, our study calls for further research to establish best practices for implementing AI-driven pedagogical approaches in educational settings,

关键词： Brain Large language models Atmospheric modeling Education Learning (artificial intelligence) Chatbots Mathematical models

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DWT-Net: A Medical Image Segmentation Model Incorporating Frequency Domain Information 4

DWT-Net: A Medical Image Segmentation Model Incorporating Fr...

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4th International Conference on Communication Technology and Information Technology, ICCTIT 2024

作者： Chen, Lixian Wu, Xueyan Ma, Jiayi Li, Shichu Shi, Yang Huang, Mingxuan Guangdong University of Technology School of Management Guangzhou China Shenzhen University College of Physics and Optoelectronic Engineering Shenzhen China Guangdong University of Technology School of Computer Science and Technology Guangzhou China Sun Yat-sen University Zhongshan School of Medicine Guangzhou China

ISBN: (纸本)9798331528973

Numerous medical image segmentation frameworks have been proposed by researchers;however, the incorporation of frequency domain information has been largely overlooked in previous studies. By incorporating frequency information, we avoid the issue where traditional downsampling reduces computational load and communication bandwidth but also removes redundant and important information, leading to accuracy loss. This paper introduces a novel supervised convolutional neural network architecture, termed "DWT-Net,"which incorporates discrete wavelet convolution and a custom residual downsampling mechanism. Through wavelet transformation, the model not only achieves a near-global receptive field but also significantly enhances its responsiveness to low-frequency information. To bolster the model's performance, data augmentation techniques were employed to enrich the dataset. Our model has been applied to the public datasets Kvasir-SEG and CVCClinicDB. Compared to other frameworks, it has shown significant improvements in display, achieving the state-of-the-art accuracy. © 2024 IEEE.

关键词： Discrete wavelet transforms

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Adaptive energy-preserving algorithms for guiding center system

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Plasma science and Technology 2023年第4期25卷 11-22页

作者：朱贝贝刘健张嘉炜祝爱卿唐贻发 Department of Applied Mathematics School of Mathematics and PhysicsUniversity of Science and Technology BeijingBeijing 100083Peopleʼs Republic of China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230026Peopleʼs Republic of China Advanced algorithm Joint Lab Shandong Computer Science CenterQilu University of TechnologyJinan 250014Peopleʼs Republic of China The State Key Laboratory of Scientific and Engineering Computing The Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190Peopleʼs Republic of China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049Peopleʼs Republic of China

We develop two types of adaptive energy preserving algorithms based on the averaged vector field for the guiding center dynamics,which plays a key role in magnetized *** adaptive scheme is applied to the Gauss Legendre’s quadrature rules and time stepsize respectively to overcome the energy drift problem in traditional energy-preserving *** new adaptive algorithms are second order,and their algebraic order is carefully *** results show that the global energy errors are bounded to the machine precision over long time using these adaptive algorithms without massive extra computation cost.

关键词： guiding center system energy-preserving methods adaptive energy conservation

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