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Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023

作者： Mutasim, Aunnoy K. Batmaz, Anil Ufuk Hudhud Mughrabi, Moaaz Stuerzlinger, Wolfgang Simon Fraser University VancouverBC Canada Computer Science & Software Engineering Department Concordia University MontrealQC Canada Mechatronics Engineering Department Kadir Has University Istanbul Turkey

ISBN: (纸本)9781450394222

To identify if novel/unfamiliar keyboard layouts like OPTI can outperform QWERTY, lengthy training through longitudinal studies is typically required. To reduce this logistical bottleneck, a popular approach in the literature requires participants to type the same phrase repeatedly. However, it is still unknown whether this approach provides a good estimate of expert performance. To validate this method, we set up a study where participants were tasked with typing the same phrase 96 times for both OPTI and QWERTY. Results showed that this approach has the potential to estimate expert performance for novel/unfamiliar keyboards faster than the traditional approach with different phrases. Yet, we also found that accurate estimates still require training over several days and, therefore, do not eliminate the need for a longitudinal study. Our findings thus show the need for research on faster, easier, and more reliable empirical approaches to evaluate text entry systems. © 2023 Owner/Author.

关键词： Taps

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A Three-Dimensional Real-Time Gait-Based Age Detection System Using Machine Learning

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computers, Materials & Continua 2023年第4期75卷 165-182页

作者： Muhammad Azhar Sehat Ullah Khalil Ullah Habib Shah Abdallah Namoun Khaliq Ur Rahman Department of Computer Science&IT University of MalakandChakdara18800Pakistan Department of Software Engineering University of MalakandChakdara18800Pakistan College of Computer Science King Khalid UniversityAbha62529Saudi Arabia Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan

Human biometric analysis has gotten much attention due to itswidespread use in different research areas, such as security, surveillance,health, human identification, and classification. Human gait is one of the keyhuman traits that can identify and classify humans based on their age, gender,and ethnicity. Different approaches have been proposed for the estimation ofhuman age based on gait so far. However, challenges are there, for which anefficient, low-cost technique or algorithm is needed. In this paper, we proposea three-dimensional real-time gait-based age detection system using a machinelearning approach. The proposed system consists of training and testingphases. The proposed training phase consists of gait features extraction usingthe Microsoft Kinect (MS Kinect) controller, dataset generation based onjoints’ position, pre-processing of gait features, feature selection by calculatingthe Standard error and Standard deviation of the arithmetic mean and bestmodel selection using R2 and adjusted R2 techniques. T-test and ANOVAtechniques show that nine joints (right shoulder, right elbow, right hand, leftknee, right knee, right ankle, left ankle, left, and right foot) are statisticallysignificant at a 5% level of significance for age estimation. The proposedtesting phase correctly predicts the age of a walking person using the resultsobtained from the training phase. The proposed approach is evaluated on thedata that is experimentally recorded from the user in a real-time *** (50) volunteers of different ages participated in the experimental *** the limited features, the proposed method estimates the age with 98.0%accuracy on experimental images acquired in real-time via a classical generallinear regression model.

关键词： Age estimation gait biometrics classical linear regression model

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Convolutional Neural Network Based Thermal Image Classification 2

Convolutional Neural Network Based Thermal Image Classificat...

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2nd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2022

作者： Ashfaq, Qirat Usman Akram, Muhammad National University of Sciences and Technology Department of Computer Software Engineering Islamabad Pakistan

ISBN: (纸本)9781665498197

Classification of Thermal Images has been extensively used for its significant applications in many fields. There are many problems with the visible spectrum like object shadows, clothes or the body of a human being matches the background and different lighting conditions. These limitations are overcome by using thermal imaging. Each and every object emits heat (Infrared energy) according to its temperature. Normally the hotter object emits more radiation than the colder one. As all objects have a mostly different temperature so thermal camera detects them and these objects get appear as distinct objects. In the start, thermal imaging was used by the military for detection, recognition, and identification of enemy personnel and equipment. Nowadays it is extensively used in the detection of face, self-driving car, detection of pedestrians and it also has application in the field of environmental work that is monitoring for energy conservation and pollution control. This research presents a novel study for the classification of thermal images using convolutional neural networks (CNN). The research focused on developing a framework that detects multiple thermal objects using CNN. Developed a framework based on deep learning Inception v3 model;work with thermal images that are captured by Seek Thermal and FLIR. For training and testing of the model two datasets are used that include three classes' cat, car, and man. For the FLIR dataset the highest accuracy achieved is 98.91% and for Seek thermal dataset highest accuracy achieved is 100%. A comparison of the proposed framework with some other CNN models (DenseNet, MobileNet, and YOLOv4), with a customized CNN model and with a conventional model is also presented. The results of the proposed framework and comparison with other models prove that the proposed framework is effective for the classification of thermal images. © 2022 IEEE.

关键词： Convolutional neural networks

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DocTTT: Test-Time Training for Handwritten Document Recognition Using Meta-Auxiliary Learning

arXiv

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arXiv 2025年

作者： Gu, Wenhao Gu, Li Wang, Ziqiang Suen, Ching Yee Wang, Yang Department of Computer Science and Software Engineering Concordia University Canada

Despite recent significant advancements in Handwritten Document Recognition (HDR), the efficient and accurate recognition of text against complex backgrounds, diverse handwriting styles, and varying document layouts remains a practical challenge. Moreover, this issue is seldom addressed in academic research, particularly in scenarios with minimal annotated data available. In this paper, we introduce the DocTTT framework to address these challenges. The key innovation of our approach is that it uses test-time training to adapt the model to each specific input during testing. We propose a novel Meta-Auxiliary learning approach that combines Meta-learning and self-supervised Masked Autoencoder (MAE). During testing, we adapt the visual representation parameters using a self-supervised MAE loss. During training, we learn the model parameters using a meta-learning framework, so that the model parameters are learned to adapt to a new input effectively. Experimental results show that our proposed method significantly outperforms existing state-of-the-art approaches on benchmark datasets. Copyright © 2025, The Authors. All rights reserved.

关键词： Self-supervised learning

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People Counting System Using OpenCV Algorithms and Edge Computing for Safety Management

People Counting System Using OpenCV Algorithms and Edge Comp...

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2023 IEEE International Conference on Smart Information Systems and Technologies, SIST 2023

作者： Seitbattalov, Zhexen Y. Canbolat, Huseyin Atanov, Sabyrzhan K. Moldabayeva, Zhanar S. Kyzyrkanov, Abzal E. Maidanov, Adil K. L. N. Gumilyov Eurasian National University Department of Computer and Software Engineering Astana Kazakhstan Ankara Yildirim Beyazit University Department of Electrical and Electronics Engineering Ankara Turkey

ISBN: (纸本)9798350335040

The necessity of ensuring people's safety in urban conditions during gathering in a certain indoor or outdoor area, as well as during the operation of technical equipment, requires measurement of their number, weights, the distance between them, density and many other parameters. The collection of those parameters and analysis allows you to ensure the optimal numerical value of people per area and not exceed the critical peak value, ensuring the safety of people's health and life. However, automating those processes requires stable network bandwidth and enormous computing resources for data transferring to the data center and its processing, as well as applying artificial intelligence algorithms to the data and sending the results back to the end-user. In this paper, to avoid the disadvantages of cloud computing, we consider Raspberry Pi with a camera module as an edge device to develop an automated people-counting system based on using OpenCV algorithms and Edge Computing for Safety Management. The proposed system can be used for indoor or outdoor areas, during scaffolding works and lift's operation for controlling an optimal number of people. As a result of the application the edge computing, network bandwidth and computing resources of the data center have been optimized. © 2023 IEEE.

关键词： Image processing

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Academates – Your Path to Personalized Learning

Academates – Your Path to Personalized Learning

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International Conference on Communication, Computing and Internet of Things (IC3IoT)

作者： Aayushma Thapa Sachin Singh Samyak Maharjan Manish Yadav Karthikeyan S Department of Computer Engineering (Software Engineering) FET Jain (Deemed-to-be University) Bangalore

ISBN: (数字)9798350352689

ISBN: (纸本)9798350352696

Academates is a creative web-based training stage intended to overcome any barrier among instructors and understudies. With an easy-to-understand interface based on Respond, educators can enlist, make definite profiles, and determine their mastery in subjects and themes. Understudies, thusly, can look for instructors in light of their advancing necessities, seeing an organized rundown complete with educator evaluations. The stage works with consistent arrangement planning with incorporated video gatherings including a whiteboard and screen-sharing choices. Installment exchanges are safely handled through the stage, with a rate designated as the stage’s administration charge. Academates focus on client security and information protection, executing encryption and consistency with significant guidelines. The versatility and responsive plan of the stage guarantee a consistent encounter across gadgets. Promoting methodologies will be utilized to draw in a different client base, laying out Academates as a main center for quality web-based schooling. With a strong rating and survey framework, Academates means to cultivate a flourishing instructive local area, offering a dynamic, secure, and customized opportunity for growth for the two instructors and understudies.

关键词： Training Surveys Technological innovation Image edge detection Turning Telecommunication computing Planning

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Work-in-Progress: Merkle Tree-Based Secure Routing for Digital Twin-Assisted Aircraft Network in 6G Wireless

Work-in-Progress: Merkle Tree-Based Secure Routing for Digit...

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2023 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2023

作者： Bilen, Tugce Erel-Ozcevik, Muge Bozkaya, Elif Ozcevik, Yusuf Turk Telekom Istanbul Turkey Manisa Celal Bayar University Department of Software Engineering Manisa Turkey National Defence University Turkish Naval Academy Department of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350337822

Providing Internet access above-the-clouds has made the development of aircraft networks more important than ever. However, new and emerging Internet applications have increased the challenge of providing seamless and real-time connectivity with traditional routing algorithms for aircraft networks in the upcoming 6G due to the highly-dynamic and unstable topology. Moreover, traditional routing mechanisms are prone to routing attacks, which can increase the packet transfer delay. To this end, in this paper, we present Merkle Tree-based secure routing mechanism with the assistance of digital twin. First, we construct a blockchain-based system with decentralized and distributed characteristics for the clustering of aircraft. Then, we propose a novel Merkle-Tree-based secure routing algorithm by combining real-time and historical data with digital twins. A Merkle tree is a data structure that contains gathered data from sender and receiver aircraft. Merkle root in an aircraft cluster forwards the gathered data to a satellite or a ground station in a secure manner. Accordingly, Secure Hash Algorithm (SHA)-256 is used for data integrity and a tree-based structure is built to reduce the number of transactions so that it is aimed to prevent malicious aircraft attacks. Finally, we show through a simulation environment, how blockchain processing time and the number of transactions can be reduced by meeting the strict Quality of Service (QoS) requirements for aircraft networks in 6G. Furthermore, we also use Proof of Stake (PoS) to reduce the computational time for mining a block as well as reducing the packet delivery ratio and packet transfer delay. © 2023 IEEE.

关键词： Blockchain

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A novel deep learning approach for investigating liquid fuel injection in combustion system

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Discover Artificial Intelligence 2025年第1期5卷 1-14页

作者： Inam, Syed Azeem Khan, Abdullah Ayub Ahmed, Noor Mazhar, Tehseen Shahzad, Tariq Khan, Sunawar Saeed, Mamoon M. Hamam, Habib Department of Artificial Intelligence and Mathematical Science Sindh Madressatul Islam University Sindh Karachi Pakistan Department of Computer Science and Information Technology Shaheed Benazir Bhutto University Lyari Karachi Pakistan Department of Computer Science Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology Karachi Pakistan Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Software Engineering Islamia University of Bahawalpur Bahawalnagar62300 Pakistan Sana’a00967 Yemen Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Electrical and Electronic Engineering Sciences University of Johannesburg Johannesburg South Africa Av. Grandes Ecoles BP 1989 Libreville Gabon Bridges for Academic Excellence Spectrum Center-ville Tunis Tunisia

The intricacies and instability of introducing cryogenic propellants into the combustion system have piqued the curiosity of scientists studying the procedure. The latest innovation is utilizing data-driven machine learning and deep learning approaches to gain deeper insights into the related difficulties. However, the current work serves as a baseline for future research because relatively few studies have used data-driven methodologies to assess the temperature of liquid fuel injections in combustion systems. The performance of Linear Regression (LR), Random Forest (RF), Extra Trees Regressor (ETR), Polynomial Regression (PR), Support Vector Regressor (SVR), Decision Tree Regressor (DTR), Gradient Boost Regressor (GBR), XGB Regressor (XGBoost), AdaBoost Regressor (ABR), K-Neighbors Regressor (KNR), Long-Short Term Memory (LSTM), Bi-LSTM (Bi-directional Long-Short Term Memory) has all been investigated in this study. The study also suggested a Fully Connected Neural Network (FCNN) to examine its performance and paired it with an Extra Tree Regressor (ETR). The coupled FCNN and Extra Tree Regressor outperform the other algorithms with a Mean Square Error (MSE) of 0.0000005062, Root Mean Square Error (RMSE) of 0.00071148, Mean Absolute Error (MAE) of 0.00020672, and R-squared (R2) value of 0.99998689. Linear Regression, Polynomial Regression, and Support Vector Regressor are found to be the least-performing algorithms. The current work uses machine learning and deep learning methods to make data-driven decisions for liquid fuel injection in the combustion system. © The Author(s) 2025.

关键词： Deep learning

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A Case Study on Blockchain-based Anonymous Reviewer Incentive Token (BARIT)

A Case Study on Blockchain-based Anonymous Reviewer Incentiv...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Shrestha, Pratiksha Bhunia, Suman Carvalho, Arthur Anderson, Chad Lee, Gabe Miami University Department of Computer Science and Software Engineering OxfordOH United States Farmer School of Business Miami University OxfordOH United States

ISBN: (纸本)9781665410205

Peer review is an integral part of academic publication and is necessary to maintain high standards and novelty of published research. Despite its importance, peer reviewers are rarely provided incentives, leading to journals having difficulty finding reviewers inclined to accept invitations and submit reviews on time. This paper proposes a Blockchain-based Anonymous Reviewer Incentive Token (BARIT) to incentivize peer reviewers. BARIT introduces flexible incentive schemes to provide both recognition and tangible benefits for the reviewers' contribution while preserving the anonymity of reviewers. Using blockchain technology to record reward tokens ensures their permanence and acceptance across different publishers. Incentive models are designed to encourage the involvement of researchers as reviewers, reduce reviewer refusal rates, and prompt the timely submission of review reports. © 2024 IEEE.

关键词： Blockchain

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User story clustering in agile development:a framework and an empirical study

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Frontiers of computer Science 2023年第6期17卷 43-59页

作者： Bo YANG Xiuyin MA Chunhui WANG Haoran GUO Huai LIU Zhi JIN School of Information Science and Technology Beijing Forestry UniversityBeijing 100083China Engineering Research Center for Forestry Oriented Intelligent Information Processing National Forestry and Grassland AdministrationBeijing 100083China School of Information Science and Technology North China University of TechnologyBeijing 100144China College of Computer Science and Technology Inner Mongolia Normal UniversityHohhot 010020China Department of Computer Science and Software Engineering Swinburne University of TechnologyHawthorn VIC 3122Australia Key Laboratory of High Confidence Software Technologies(Peking University) Ministry of EducationBeijing 100871China Institute of Software School of Computer SciencePeking UniversityBeijing 100871China

Agile development aims at rapidly developing software while embracing the continuous evolution of user requirements along the whole development *** stories are the primary means of requirements collection and elicitation in the agile development.A project can involve a large amount of user stories,which should be clustered into different groups based on their functionality’s similarity for systematic requirements analysis,effective mapping to developed features,and efficient ***,the current user story clustering is mainly conducted in a manual manner,which is time-consuming and subjective to human *** this paper,we propose a novel approach for clustering the user stories automatically on the basis of natural language ***,the sentence patterns of each component in a user story are first analysed and determined such that the critical structure in the representative tasks can be automatically extracted based on the user story *** similarity of user stories is calculated,which can be used to generate the connected graph as the basis of automatic user story *** evaluate the approach based on thirteen datasets,compared against ten baseline *** results show that our clustering approach has higher accuracy,recall rate and F1-score than these *** is demonstrated that the proposed approach can significantly improve the efficacy of user story clustering and thus enhance the overall performance of agile *** study also highlights promising research directions for more accurate requirements elicitation.

关键词： user story agile development user story mapping clustering

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