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5th International Conference on Optoelectronic Science and Materials, ICOSM 2023

作者： Li, Xin Cui, Mengying Jiang, Shuo Cui, Qiannan Meng, Yingying Li, Bingshao Beijing Institute of Computer and Electronics Application Beijing100089 China China Research and Development Academy of Machinery Equipment Beijing100089 China

ISBN: (纸本)9781510674547

The reflectance spectra data obtained from spectrometer was of great necessity to be processed and analyzed so that the data could be converted to color parameters. Since the Lab color space was characterized by not limited to specific devices, wide color gamut, and high-speed computing process, a data processing program based on python has been developed in this work. Based on the program, Lab color parameters could be calculated from the wavelength and reflectivity obtained from raw data, the relative spectral power distribution of illumination source, and spectral tristimulus values under standard chromaticity observation, which could be visualized in the 3D color space. In comparison with manual data screening and calculation, the efficiency and reliability of color analysis were markedly elevated based on the developed program, by which the color parameters could be quickly and accurately calculated from the reflectance spectra and intuitively displayed in 3D color space. © 2024 SPIE.

关键词： Python

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Comparative Analysis of U-Net Models Using ResNet34, InceptionV3, and VGG16 for the Processing of Satellite Images 2

Comparative Analysis of U-Net Models Using ResNet34, Incepti...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Kumar, Sushil Yadav, Anubhav Varshney, Ajay Sharma, Aayush Shivani, Shivani Computer Science and Engineering Kiet Group of Institutions Dsdl Lab Delhi-NCR Ghaziabad India Kiet Group of Institutions Computer Science Delhi-NCR Ghaziabad India

ISBN: (纸本)9798350360523

Satellite image classification is a crucial component in remote sensing applications, facilitating the automated analysis of land cover and land use patterns. This research explores the effectiveness of the U-Net architecture and state-of-the-art deep learning techniques for satellite image classification. Utilizing diverse and well-annotated satellite image datasets, we demonstrate the capability of U-Net in capturing intricate spatial features within images, making it a powerful tool for discriminating land cover classes. Our experiments involved training the U-Net model with the ResNet34, InceptionV3, and VGG16 architectures. The U-Net-based ResNet34 model achieved the highest accuracy of 81.0% and a validation F1-score of 65.95% after 50 epochs. The findings underscore the potential of U-Net and deep learning techniques to advance the field of remote sensing, providing solutions for real-world challenges such as environmental monitoring, urban planning, disaster management, and precision agriculture. © 2024 IEEE.

关键词： Land use

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Flex Sensor Enabled Glove based Manual Wheelchair for Elderly and Speech-Impaired Assistance

Flex Sensor Enabled Glove based Manual Wheelchair for Elderl...

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International Symposium on Advanced Computing and Communication (ISACC)

作者： Abhishek Tripathi Kasu V S Gopi Reddy K Amarnath C Bavesh Bestha Vardhan Sumitra Singh Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Virudhunagar India Semiconductor Devices Design Group Central Electronics Engineering Research Institute Pilani India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

This paper presents a cost-effective manual wheelchair system designed to enhance mobility and communication for deaf-mute, disabled, and elderly individuals. The system employs a gesture-based mechanism using a glove with embedded flex sensors to detect finger movements, translating them into actionable commands. These commands are processed by a microcontroller to provide real-time feedback through three channels: visual messages displayed on an LCD, wireless communication with a caretaker's device, and audio feedback via a speaker. Testing demonstrates reliable gesture detection and response generation, highlighting the system's effectiveness in meeting the diverse needs of users. The design emphasizes affordability, ease of use, and adaptability, offering a practical and inclusive solution for individuals with varying levels of mobility and communication challenges.

关键词： Wireless communication Flexible printed circuits Wheelchairs Manuals Gesture recognition Sensor systems Real-time systems Reliability Older adults Intelligent sensors

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The Ability-Based design Mobile Toolkit (ABD-MT): Developer Support for Runtime Interface Adaptation Based on Users' Abilities

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Proceedings of the ACM on Human-computer Interaction 2024年第MHCI期8卷 1-26页

作者： Kong, Junhan Zhong, Mingyuan Fogarty, James Wobbrock, Jacob O. The Information School DUB Group University of Washington SeattleWA United States Paul G. Allen School of Computer Science and Engineering DUB Group University of Washington SeattleWA United States

Despite significant progress in the capabilities of mobile devices and applications, most apps remain oblivious to their users' abilities. To enable apps to respond to users' situated abilities, we created the Ability-Based design Mobile Toolkit (ABD-MT). ABD-MT integrates with an app's user input and sensors to observe a user's touches, gestures, physical activities, and attention at runtime, to measure and model these abilities, and to adapt interfaces accordingly. Conceptually, ABD-MT enables developers to engage with a user's "ability profile,'' which is built up over time and inspectable through our API. As validation, we created example apps to demonstrate ABD-MT, enabling ability-Aware functionality in 91.5% fewer lines of code compared to not using our toolkit. Further, in a study with 11 Android developers, we showed that ABD-MT is easy to learn and use, is welcomed for future use, and is applicable to a variety of end-user scenarios. © 2024 Owner/Author.

关键词： accessibility developer tools.} interface adaptation keywords{ability-based design mobile toolkit

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Smart Firefighting Early Warning and Evacuation System Based on Edge Computing with Led Dynamic Indicator Devices 6

Smart Firefighting Early Warning and Evacuation System Based...

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6th International Conference on Communications, Information System and computer engineering, CISCE 2024

作者： Yu, Liang Lai, Yangbing Mo, Jiayu Zeng, Yuze Tan, Guoshen Xu, Haonan College of Computer Guangdong University of Science and Technology Dongguan China AIoT Edge Computing Engineering Technology Research Center of Dongguan City Guangdong AIoT Application Innovation Joint Laboratory Dongguan China

ISBN: (纸本)9798350353174

The current standard practice for building fire safety relies heavily on regular lighting, emergency lighting, and smoke sensors. The management and control centers for these systems are typically separate and independent, resulting in a bulky and expensive local control system that is difficult to use and manage. Additionally, the traditional fixed instructions in fire protection systems do not allow for adaptive planning of optimal escape routes based on the location of the fire, leading to delays in evacuation and ultimately causing significant casualties. This paper presents the design of a smart fire warning and evacuation system based on edge computing utilizing LED dynamic indication devices. The system integrates LED dot-matrix technology to create a smart indicator and emergency light with dynamic adaptive indication capabilities. Additionally, it includes temperature, humidity, and smoke sensors to monitor the building's environmental conditions. Through Mesh wireless networking, time-series sensing data is aggregated to the edge gateway, where a miniature machine learning model trained by the Edge Impluse (EI) platform performs edge computing for predicting and reasoning about fire situations. The data is then uploaded to a cloud server and forwarded to mobile users via Cat.1 communication protocol for real-time monitoring. The system also incorporates an improved ant colony algorithm for automatic execution in the cloud and allows manual commands from mobile terminals to control adaptive and dynamic indication of indicator lights and emergency lights, guiding building personnel to the safest evacuation path. System testing demonstrates a high accuracy rate of 95% for fire prediction and inference, with an average inference time of less than 1 ms. This system provides a novel approach to adaptive building fire prediction and evacuation, enhancing safety measures for orderly and secure evacuations. © 2024 IEEE.

关键词： Ant colony optimization

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Hyborg Agency: Cultivating Conversational AI Creatures through Community Connections 23

Hyborg Agency: Cultivating Conversational AI Creatures throu...

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Special Interest group on computer Graphics and Interactive Techniques Conference - Art Gallery, SIGGRAPH 2023

作者： Sun, Yuqian Lee, Chang Hee Asadipour, Ali Computer Science Research Centre Royal College of Art United Kingdom Design Department College of Engineering KAIST Korea Republic of

ISBN: (纸本)9798400701573

Hyborg Agency, an interactive art installation, integrates a digital forest with a human discord chat channel, enabling communication with AI deer or 'hyborgs'. The forest metaphorically represents human society, where AI agents use the large language model (LLM) ChatGPT to learn and grow by summarising conversations and updating their knowledge base, assimilating community thoughts as enriching nutrients. © 2023 Owner/Author.

关键词： Knowledge based systems

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Voice Controlled Operations and Navigations for e-Commerce

Voice Controlled Operations and Navigations for e-Commerce

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2023 IEEE International Conference on Network, Multimedia and Information Technology, NMITCON 2023

作者： Kalangutkar, Aditi Yadav, Radha Hadapad, Priya S. Naik, Vinisha V. Menezes, Valerie Sawant, Shreedatta Agnel Institute of Technology and Design Department of Computer Engineering Goa India

ISBN: (纸本)9798350300826

Voice based operations are increasingly being used by the users in their day to day lives and are being used in various sectors for making their lives easier simply by speaking rather than typing keywords. Performing actions using voice is faster and accessible to the users who are not comfortable with the UI of the application. However, there are very few implementations of these voice-controlled systems on the web and e-commerce. This paper presents a browser extension which can be used on various e-commerce sites and get appropriate responses. This tool will allow users to perform human-to-machine interaction, anytime and anywhere using speech recognition and provide ease to the users without using their fingertips. This tool will be a chrome extension (add-on or plugin), that will take voice as an input and will convert it to text, extract meaning from the text, and then perform a wide variety of tasks including the product search, add to cart, in-app navigations, and other operations through speech. This extension will be a combination of technologies, such as automatic speech recognition, text-to-speech service, and natural language understanding, to engage in natural conversational interactions with humans. © 2023 IEEE.

关键词： Speech recognition

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Comparative Study of User design Ideas in Generative Artificial Intelligence: An SEM Model Based on Multimodal Discourse Theory

Frontiers in Artificial Intelligence and Applications

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Frontiers in Artificial Intelligence and applications 2025年 404卷 632-641页

作者： Tan, Zhengtang Zhang, Huixiang Yuan, Zhuyun Gu, Fangzhou National Teaching Demonstration Center Laboratory College of Engineering and Design Hunan Normal University Changsha China College of Engineering and Design Hunan Normal University Changsha China School of Art and Design Changsha University Changsha China

With the widespread application of generative artificial intelligence (AIGC) in design, its impact on design conception across different user groups is a significant research issue in design education. This study explores the differences in design conception between designer users and ordinary users using AIGC for poster design, and evaluates the application of multimodal discourse theory and SEM models. The study defines four variables in the poster design concept: representational meaning, interactive meaning, compositional meaning, and color meaning. A questionnaire with 22 items was distributed to 120 respondents. SEM analysis showed a good fit and significant inter-group differences. designers’ design ideation is influenced by all dimensions, while compositional meaning does not affect ordinary users. designers’ path coefficients were balanced across dimensions, while ordinary users showed significant differences, particularly in representational and interactive meaning. This study verifies the applicability of multimodal discourse theory and offers insights into design conception differences in the AIGC context. It emphasizes the need to improve non-professional users’ design skills and provides guidance for developing more user-friendly AIGC tools. © 2025 The Authors.

关键词： Artificial intelligence

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Multi-channel CNN to classify Nepali COVID-19 related tweets using hybrid features

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Journal of Ambient Intelligence and Humanized Computing 2024年第3期15卷 2047-2056页

作者： Sitaula, Chiranjibi Shahi, Tej Bahadur Department of Electrical and Computer Systems Engineering Monash University Wellington Rd ClaytonVIC3800 Australia Earth Observation and AI Research Group Department of Infrastructure Engineering The University of Melbourne ParkvilleVIC3010 Australia School of Engineering and Technology Central Queensland University Rockhampton Australia Central Department of Computer Science and Information Technology Tribhuvan University TU Rd Kathmandu Kirtipur44618 Nepal

Because of the current COVID-19 pandemic’s increasing fears among people, it has triggered several health complications such as depression and anxiety. Such complications have not only affected developed countries but also developing countries such as Nepal. These complications can be understood from peoples’ tweets and comments posted online after their felicitous analysis and sentiment classification. Nevertheless, owing to the limited number of tokens and words in each tweet, it is crucial to capture multiple pieces of information associated with them for better understanding. In this study, we, first, represent each tweet by combining both syntactic and semantic information, called hybrid features. The syntactic information is generated from the bag-of-words method, whereas the semantic information is generated from the combination of the fastText-based (ft) and domain-specific (ds) methods. Second, we design a novel multi-channel CNN (MCNN) model, which ensembles the multiple CNNs, to capture multi-scale information for better classification. Last, we evaluate the efficacy of both the proposed feature extraction method and the MCNN model classifying tweets into three sentiment classes (positive, neutral, and negative) on the NepCOV19Tweets dataset, which is the only public COVID-19 tweets dataset in the Nepali language. The evaluation results show that the proposed hybrid features outperform individual feature extraction methods with the highest classification accuracy of 69.7% and the MCNN model outperforms the existing methods with the highest classification accuracy of 71.3% during classification. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

关键词： COVID-19

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Evaluating the Inclusiveness of Artificial Intelligence Software in Enhancing Project Management Efficiency - A review and examples of quantitative measurement methods

Evaluating the Inclusiveness of Artificial Intelligence Soft...

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2024 International Conference on Artificial Intelligence, computer, Data Sciences, and applications, ACDSA 2024

作者： Alevizos, Vasileios Georgousis, Ilias Simasiku, Akebu Messinis, Antonis Karypidou, Sotiria Malliarou, Dimitra Karolinska Institute Department of Learning Informatics Managament and Ethics Stockholm Sweden International Hellenic University Mlv Research Group Department of Computer Science Kavala Greece Zambia University Department of Computer Software Engineering Ndola Zambia Greece International Hellenic University Mlv Research Group Department of Computer Science Greece IntelliSolutions Athens Greece

ISBN: (纸本)9798350394528

The escalating integration of Artificial Intelligence (AI) in various domains, especially Project Management (PM), has brought to light the imperative need for inclusivity in AI systems. This paper investigates the role of AI software in augmenting both the inclusiveness and efficiency within the realm of PM. The research pivots around specific criteria that define and measure the inclusiveness of AI in PM, highlighting how AI, when developed with inclusiveness in mind, can significantly enhance project outcomes. However, there are inherent challenges in achieving this inclusiveness, primarily due to biases embedded in AI learning databases and the design and development processes of AI systems. The study offers a comprehensive examination of AI's potential to revolutionize PM by enabling managers to concentrate more on people-centric aspects of their work. This is achieved through AI's ability to perform tasks such as data collection, reporting, and predictive analysis more consistently and efficiently than human counterparts. However, the incorporation of AI in PM extends beyond mere efficiency;it represents a paradigm shift in the epistemology of PM, calling for a deeper understanding of AI's role and impact on society. Despite these advantages, the adoption of AI comes with significant challenges, particularly in terms of bias and inclusiveness. Biased AI learning databases, which use shared and reusable datasets, often perpetuate initially discriminatory algorithms. Moreover, unconscious biases and stereotypes of AI designers, developers, and trainers can inadvertently influence the behavior of the AI systems they create. This necessitates a paradigmatic shift in how AI systems are developed and governed to ensure they do not replicate or exacerbate existing social inequalities. The research proposes a methodological approach involving the development of criteria for inclusion and exclusion, alongside data extraction, to evaluate the inclusiveness and efficienc

关键词： Project management

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