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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Hossain, Gahangir Shin, Mikyung Afrose, Mehnaz University of North Texas Dept of Information Science Denton United States West Texas AandM University Dept. of Education Canyon United States West Texas AandM University Dept. of Computer Information Systems and Business Analytics Canyon United States

ISBN: (纸本)9798350324136

Given the increasing significance of promoting cybersecurity awareness within K-12 educational settings, it becomes imperative to provide teachers with appropriate professional development. This paper reports on a current workshop that aimed to assess the viability of cybersecurity online modules developed by researchers and to deliver cybersecurity training to high school STEM educators. The workshop sought to evaluate the level of cybersecurity awareness among teachers and enhance their comprehension of its importance. This evaluation was conducted through scales devised by researchers, aligned with standards set by the National Institute of Standards and Technology and the computer Science Teachers Association. The training also aimed to fortify teachers' grasp of cybersecurity content, encompassing relevant standards, analysis of cyber threats, establishment of secure online environments, and other pivotal cybersecurity concepts. Acknowledging the comprehensive nature and adaptability of cybersecurity education, the workshop endeavored to distill essential ideas and recommended practices tailored for K-12 teachers. In this document, we outline the workshop's structure, in addition to presenting the initial survey and assessment outcomes. The findings demonstrate an enhancement in teachers' awareness of cybersecurity and affirm the social significance of their learning experiences, thereby equipping them for the forthcoming academic year. © 2024 IEEE.

关键词： Cybersecurity awareness NIST and CSTA standards Online privacy STEM education Teacher training

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A Deep Learning-Based System for Detecting Defects in Printed Circuit Boards

A Deep Learning-Based System for Detecting Defects in Printe...

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13th International Electrical engineering Congress, iEECON 2025

作者： Suksukont, Aekkarat Onshaunjit, Jakkrit Srinonchat, Jakkree Dept. of Computer Engineering Suphanburi Thailand Dept. of Electronics and Telecommunication Engineering Pathum Thani Thailand

ISBN: (纸本)9798331543952

Traditional approaches to defect detection, relying on rule-based algorithms or human visual examination, are inadequate and ineffectual in handling intricate fault patterns. Implementing computer vision techniques in PCB defect detection can improve inspection processes' accuracy, reliability, and effectiveness. Deep learning is now used in those processes to explore important technology. This study presents a novel automated method for defect identification using deep learning methods. The system is built utilizing AlexNet, U-Net, ResNet 101, and Inception-v3, prominent frameworks known for their outstanding capacity to extract pertinent visual data components. The proposed technique comprehensively composes PCB photos, including faulty and defect-free samples. This training enhances the system's capacity to precisely differentiate between conventional PCB designs and six additional categories of errors. The suggested architecture of the CNN models consists of double process layers represented as ConV I, Pooling I, ConV II, and Pooling II. The validation procedure is carried out by using a range of learning rate data. The implementation findings indicate that the ResNet-101 variant achieves the highest testing accuracy of 99.286%. Indeed, incorporating this technology into the PCB manufacturing process enables the prompt identification of defective PCBs, leading to less waste, enhanced product quality, and heightened satisfaction among end-users. © 2025 IEEE.

关键词： Deep learning

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Real-time Human Movement Recognition and Interaction in Virtual Fitness using Image Recognition and Motion Analysis 12

Real-time Human Movement Recognition and Interaction in Virt...

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12th International Conference on Awareness Science and Technology, iCAST 2023

作者： Yeh, ChunHsiu Shen, Wei-Cheng Ma, Chi-Wei Yeh, Qiu-Tong Kuo, Chung-Wei Chen, Jong-Shin Dept. of Information Engineering Computer Science Feng Chia University Taichung Taiwan CollegeofComputerScience Jimei University Xiamen China Dept. of Information Communication Engineering ChaoYang University of Technology Taichung Taiwan

ISBN: (纸本)9798350324693

This research focuses on the application of image recognition, motion detection, and artificial intelligence techniques to achieve real-time identification and analysis of human movements in a dynamic manner. The primary goal is to establish a seamless association between captured human movements and corresponding actions performed by virtual avatars. The implementation involves the utilization of image processing methodologies from python's OpenCV and pygame libraries. MediaPipe technology is employed to capture users' images and facilitate accurate detection of specific movement patterns. By calculating the angles between users' limbs and torso, the correctness of certain movements can be assessed. The research is practically developed and applied to a simulated fitness system, where an interactive exercise game platform is devised. The system is characterized by its engaging user interface, enhancing the ease and enjoyment of fitness activities. The seamless integration of interactive virtual avatars and real users within physical activities serves to stimulate greater participation, particularly among the elderly. The amalgamation of image recognition and motion detection technologies presents opportunities for combining fitness and entertainment in diverse life scenarios, offering an enhanced experience of physical exercise and enjoyment. © 2023 IEEE.

关键词： Image recognition

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Triple Band Reflective Metasurface Based Linear to Circular Polarization Converter

Triple Band Reflective Metasurface Based Linear to Circular ...

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2023 International Telecommunications Conference, ITC-Egypt 2023

作者： El-Nady, Shaza M. Eldesouki, Eman M. Soliman, Shimaa A. M. Attiya, Ahmed M. Microstrip Department Cairo Egypt Microwave Engineering Department Cairo Egypt Queen's University Dept. of Electrical and Computer Engineering KingstonON Canada

ISBN: (纸本)9798350326062

Converting the polarization of electromagnetic waves from linear to circular is required for many microwave applications. This article discusses the use of metasurface MS based reflective surface for converting the polarization from linear to circular. A new MS element is proposed to manipulate the phase, amplitude, and polarization of waves. It consists of two tilted and crossed bi-directional metallic arrows with elliptical ring. By applying two small slits in the long arrow, the operating bandwidth of the proposed structure is significantly increased. The geometrical dimensions of this MS reflective element are chosen so that the magnitudes of the co-polarized and cross-polarized reflected wave components are nearly equal while maintaining a ±90 degree phase difference. Linear to dual circular polarization conversation has been achieved at three frequency bands. The simulated results show that right hand circular polarized (RHCP) waves can be sensed in 14.1-15.8 GHz and 25.2-41.5 GHz while the left hand circular polarized wave (LHCP) can be observed from 45.75 to 49 GHz with y-polarized incident wave. The proposed MS structure has a high energy conversation efficiency (ECE) above 98%. For more validation a 20× 20 MS elements arranged in two-dimensional rectangular lattice and simulated to verify the results of the single element. Moreover, the polarization conversion ratio (PCR) is calculated beside the circular polarization conversion ratio, ellipticity and elliptical angle to detect the direction of the reflected CP wave. © 2023 IEEE.

关键词： Circular polarization

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Examining Strategies for Correcting Color Vision Deficiency: A Survey

Examining Strategies for Correcting Color Vision Deficiency:...

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Software engineering and Artificial Intelligence (SEAI), IEEE International Conference on

作者： Gariman Gangwani Ashwin Ragupathy Neeharika Anand Nimit Mann K S Srinivas dept. Computer Science Engineering PES University Bengaluru India dept. Computer Science Engineering (AIML) PES University Bengaluru India

ISBN: (数字)9798350374346

ISBN: (纸本)9798350374353

Color blindness (CVD) is a condition experienced by millions around the world and thus has created many difficulties in multiple fields. This is a survey on the existing approaches and the latest improvements in it that are used in the CVD adaptation. This research, in fact, studies the way of self-adapting recoloring methods, color correction for salient features, coloring based on fuzzy algorithms, Swin transformer architecture for feature extraction and the usage of GANs for effective colorblind data conversion. In addition, approaches to CVD-friendly personalized image generation techniques, which may vary depending on the severity of CVD, are also considered. This is a multifaceted approach which presents many methods, each one being part of the larger landscape of CVD adaptation strategies. Along the way we will also touch upon the potential issues and the opportunities for improvement within the existing approach. Furthermore, we will present information on some of the currently available tests for color blindness diagnosis and correction methods. Through integrating these contributions with other associated studies, we present a comprehensive analysis that emphasizes the advancements, obstacles, and future implications on CVD adaptation techniques.

关键词： Surveys Visualization Technological innovation PSNR Image color analysis Feature extraction Transformers

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Stratification of metastatic melanoma patients based on mutational signatures

Stratification of metastatic melanoma patients based on muta...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Alfano, Caterina Farina, Lorenzo Petti, Manuela Sapienza University of Rome Program in Network Oncology and Precision Medicine Rome Italy Sapienza University of Rome Program in Network Oncology and Precision Medicine Dept. of Computer Control and Management Engineering Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9798350337488

Genetic instability is one of the hallmarks of cancer, however mutations can occur for different causes and induce different effects. Mutational signatures are characteristic patterns of somatic mutations in cancer genomes, reflecting the underlying mutational processes. A mutational signature can be determined by studying the kind of mutations a patient has acquired during their life: patient stratification based on mutational signatures has become more and more useful in genomic studies, given its possible clinical implications. In this work we focused on Single Base Substitution (SBS) signatures to study a cohort of 115 metastatic melanoma patients. We inferred and identified two mutational signatures characterizing the patients. Based on these signatures we divided patients into two group: the bigger group was characterized by a signature associated with exposure to ultraviolet light, while the smaller group resulted to be mostly composed of patients which did not respond to immunotherapy (anti-PD1) and that presented a low mutational count. More importantly this second group showed a significantly worse survival outcome. The use of mutational signatures is clearly a powerful tool to identify disease sub-types that have a clinical relevance, however we believe that this topic needs further investigation focused on the characterization of patient subtypes with a multi-omics based approach. © 2023 IEEE.

关键词： computational medicine genomics metastatic melanoma mutational signatures patient stratification precision oncology

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Quantitative Analysis of Error Propagation in Hindi-English Cascaded Speech-to-Speech Translation Models

Quantitative Analysis of Error Propagation in Hindi-English ...

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Advancement in Computation & computer Technologies (InCACCT), International Conference on

作者： Mahendra Gupta Maitreyee Dutta Chandresh Kumar Maurya Dept. of Computer Science and Engineering NITTTR Chandigarh Chandigarh India Dept. of IMEE NITTTR Chandigarh Chandigarh India Dept. of Computer Science and Engineering IIT Indore Indore India

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Speech-to-Speech Translation (S2ST) plays a crucial role in reducing language barriers and enabling seamless communication between people from different linguistic backgrounds. Traditional S2ST systems typically rely on a cascaded design, where components like Automatic Speech Recognition (ASR), Machine Translation (MT), and Text-to-Speech (TTS) work together in sequence to complete the translation process. Cascaded models are widely used S2ST models and are prone to error propagation (EP) across the pipeline, significantly impacting translation quality. EP is discussed in various literature. However, a comprehensive quantitative analysis is not available, particularly for low-resource languages like Hindi and English. This work presents a detailed quantitative study of EP in Hindi-English cascaded S2ST models, bridging this critical research gap. This study utilizes both text-based and textless evaluation metrics such as BLEU, Translation Edit Rate (TER), and BLASER score for translation accuracy to quantify the impact of EP at various stages of the pipeline on the FLEURES dataset. The result analysis shows that due to EP, the translation quality of the S2ST model decreases in BLEU score of 11.55 for English→Hindi and BLEU score of 12.16 for Hindi→English. Similarly, reference-based BLASER decreases by 0.61 and 0.45 for English→Hindi and Hindi→English, respectively.

关键词： Measurement Analytical models Translation Accuracy Statistical analysis Computational modeling Pipelines Linguistics Text to speech Machine translation

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Breaking Barriers: Investigating the Sense of Belonging Among Women and Non-Binary Students in Software engineering

arXiv

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arXiv 2024年

作者： Boman, Lina Andersson, Jonatan de Oliveira Neto, Francisco Gomes University of Gothenburg Dept. of Computer Science and Engineering Gothenburg Sweden Chalmers and the University of Gothenburg Dept. of Computer Science and Engineering Gothenburg Sweden

Women in computing were among the first programmers in the early 20th century and were substantial contributors to the industry. Today, men dominate the software engineering industry. Research and data show that women are far less likely to pursue a career in this industry, and those that do are less likely than men to stay in it. Reasons for women and other underrepresented minorities to leave the industry are a lack of opportunities for growth and advancement, unfair treatment and workplace culture. This research explores how the potential to cultivate or uphold an industry unfavourable to women and non-binary individuals manifests in software engineering education at the university level. For this purpose, the study includes surveys and interviews. We use gender name perception as a survey instrument, and the results show small differences in perceptions of software engineering students based on their gender. Particularly, the survey respondents anchor the values of the male software engineer (Hans) to a variety of technical and non-technical skills, while the same description for a female software engineer (Hanna) is anchored mainly by her managerial skills. With interviews with women and non-binary students, we gain insight on the main barriers to their sense of ambient belonging. The collected data shows that some known barriers from the literature such as tokenism, and stereotype threat, do still exist. However, we find positive factors such as role models and encouragement that strengthen the sense of belonging among these students. © 2024, CC BY.

关键词： Students

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Enhancing Network Intelligence with LLM-Based IBN and DRL: A Dynamic Approach for SAGIN Resource Management

Enhancing Network Intelligence with LLM-Based IBN and DRL: A...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Sajid Alam Wang-Cheol Song Dept. Electronics Engineering Jeju National University Dept. Computer Engineering Jeju National University

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

We propose an innovative Intent-Based Networking (IBN) system that leverages Large Language Models (LLMs) to translate high-level user intents into actionable network policies. By integrating an LLM-based translation engine with a Deep Reinforcement Learning (DRL) agent, our system enables dynamic and intelligent resource allocation within Space-Air-Ground Integrated Networks (SAGINs). The LLM interprets user requests expressed in natural language to generate precise network configurations, which the DRL agent uses to optimize resource utilization while meeting Quality of Service (QoS) requirements. Simulations demonstrate that our approach effectively reduces latency, enhances bandwidth utilization, minimizes QoS violations, and increases Virtual Network Request (VNR) acceptance rates compared to static allocation strategies. These results highlight the potential of combining LLMs with DRL in IBN systems to improve network adaptability, efficiency, and user satisfaction.

关键词： Translation Large language models Quality of service Bandwidth Dynamic scheduling Deep reinforcement learning Space-air-ground integrated networks Network resource management Engines Standards

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An Ising Machine-Based Hybrid Optimization Method Using Constraint Conversion and Correction

An Ising Machine-Based Hybrid Optimization Method Using Cons...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Kinya Iwata Masashi Tawada Nozomu Togawa Dept. of Computer Science and Communications Engineering Waseda University Green Computing Systems Research Organization Waseda University

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

This paper proposes an Ising machine-based hy-brid optimization method to solve combinatorial optimization problems, which consists of an approximate formulation process, an annealing process with an Ising machine, and a correction process. The approximate formulation and correction aim to improve the performance of the Ising machine. Computational experiments were conducted on the multi-dimensional knapsack problem (MKP) using an Ising machine. We compare the results with those of the proposed method and the conventional method and demonstrate the effectiveness of the proposed approach.

关键词： Annealing Optimization methods Consumer electronics

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