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An exploratory user study towards developing a unified, comprehensive assessment apparatus for deaf signers, specifically tailored for signing avatars evaluation: challenges, findings, and recommendations

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Multimedia Tools and Applications 2024年 1-38页

作者： Imashev, Alfarabi Oralbayeva, Nurziya Sandygulova, Anara Department of Robotics and Mechatronics School of Engineering and Digital Sciences Nazarbayev University 53 Kabanbay Batyr ave. Astana010000 Kazakhstan National Laboratory Astana Nazarbayev University 53 Kabanbay Batyr ave. Astana010000 Kazakhstan

Sign Languages (SL) are natural languages used by those who are deaf or have hearing impairments, as well as by hearing persons, including interpreters, family members, and friends of deaf individuals. Spoken languages rely primarily on verbal and written communication, whereas sign language focuses mainly on visual-gestural communication. In their daily lives, unimodal users (deaf people who only use sign language) cannot always rely solely on textual communication. Research on SL recognition and generation has shown enormous promise in addressing concerns related to inclusivity and accessibility. The research on using signing avatars in human-computer interaction is relatively new. The currently available information suggests that the research strategies used to develop sign language-interpreting avatars have drawbacks that hinder the establishment of a strong, dependable, and persuasive signing system. Therefore, to ensure the meaningful involvement of the deaf population in user studies, it is essential to design a standardized procedure for surveying them and acquiring significant insights to assist future improvements. In order to accomplish this objective, we undertook a thorough examination of several scales and metrics, which we endeavored to precisely customize and modify to suit the subjective assessment of SL agents by deaf signers. We conducted this analysis as an exploratory case study involving deaf signers and individuals who use sign language oftentimes. We aimed to address the question: "What should a methodological framework for evaluating sign language agents by deaf signers entail?" The data obtained from both rounds of this preliminary exploratory user study, as outlined in the current paper, became essential for our future work. During the COVID-19 lockdown period in 2020-2021, we conducted the first iteration solely online. We held the second iteration after a year, still adhering to the limitations imposed by the pandemic. © The Author(s), u

关键词： Audition

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Intelligent Deep Learning Enabled Human Activity Recognition for Improved Medical Services

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Computer Systems Science & engineering 2023年第2期44卷 961-977页

作者： E.Dhiravidachelvi M.Suresh Kumar L.D.Vijay Anand D.Pritima Seifedine Kadry Byeong-Gwon Kang Yunyoung Nam Department of Electronics and Communication Engineering Mohamed Sathak A.J.College of EngineeringChennai603103India Department of Information Technology Sri Sairam Engineering CollegeChennai602109India Department of Robotics Engineering Karunya Institute of Technology and SciencesCoimbatore641114India Department of Mechatronics Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Department of Information and Communication Engineering Soonchunhyang UniversityAsanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Human Activity Recognition(HAR)has been made simple in recent years,thanks to recent advancements made in Artiﬁcial Intelligence(AI)*** techniques are applied in several areas like security,surveillance,healthcare,human-robot interaction,and *** wearable sensor-based HAR system includes in-built sensors,human activities can be categorized based on sensor ***,it can also be employed in other applications such as gait diagnosis,observation of children/adult’s cognitive nature,stroke-patient hospital direction,Epilepsy and Parkinson’s disease examination,***-developed Artiﬁcial Intelligence(AI)techniques,especially Deep Learning(DL)models can be deployed to accomplish effective outcomes on HAR *** this motivation,the current research paper focuses on designing Intelligent Hyperparameter Tuned Deep Learning-based HAR(IHPTDL-HAR)technique in healthcare *** proposed IHPTDL-HAR technique aims at recogniz-ing the human actions in healthcare environment and helps the patients in mana-ging their healthcare *** addition,the presented model makes use of Hierarchical Clustering(HC)-based outlier detection technique to remove the ***-HAR technique incorporates DL-based Deep Belief Network(DBN)model to recognize the activities of ***,Harris Hawks Opti-mization(HHO)algorithm is used for hyperparameter tuning of DBN ***,a comprehensive experimental analysis was conducted upon benchmark dataset and the results were examined under different *** experimental results demonstrate that the proposed IHPTDL-HAR technique is a superior per-former compared to other recent techniques under different measures.

关键词： Artiﬁcial intelligence human activity recognition deep learning deep belief network hyperparameter tuning healthcare

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Its All About Context

Its All About Context

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IEEE Southeastcon

作者： Preston Brantley Yusun Chang Razvan Cristian Voicu Department of Robotics & Mechatronics Engineering Kennesaw State University Atlanta Georgia

This paper presents an innovative approach to enhancing context understanding in Generative Pretrained Models (GPTs), a critical step towards achieving Artificial General Intelligence (AGI). While GPTs have significantly advanced natural language processing, their understanding of context remains predominantly limited to linguistic structure. To address this limitation, we introduce a novel layer in the transformer model architecture that computes context weights, integrating both immediate and temporally decaying influences of past tokens. This layer is strategically positioned after the self-attention and before the feed-forward layers, enabling a more nuanced interpretation of sequential language data. Our approach involves the formulation of a decaying temporal factor, which allows the model to consider not only the immediate relevance of tokens but also their historical context. This factor is dynamically adjustable, offering a sophisticated method of context weighting that considers both current and extended contexts. The integration of this context weight into the self-attention mechanism enhances the model's capacity for a deeper, more accurate understanding of language, pushing the boundaries of current AI capabilities towards a system that mirrors human-like intelligence. Our experimental results demonstrate the efficacy of this approach, showing its potential to significantly contribute to the development of AGI.

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Communication Interchange for Artificial Intelligence Systems

Communication Interchange for Artificial Intelligence System...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Razvan Cristian Voicu Aarush Kaunteya Pande Muhammad Hassan Tanveer Yusun Chang Department of Robotics & Mechatronics Engineering Kennesaw State University Atlanta Georgia

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

The rise and proliferation of Artificial Intelligence (AI) technologies are bringing transformative changes to various sectors, signaling a new era of innovation in fields as diverse as medicine, manufacturing, and even day-to-day social interactions. Notable advancements are not just confined to textual understanding, as seen in models like GPT, but also extend to visual cognition through image recognition and more. Beyond surface interactions and predictions, AI finds profound applications in life-saving domains such as medical diagnostics and becomes an integral part of daily life through chatbot- based customer interactions. However, as the horizon of AI expands, a crucial yet often overlooked aspect emerges- the underlying mission-critical infrastructure required to support and deploy these models effectively. The intricacies of efficient communication systems, foundational for real-time AI model operations, take center stage in ensuring the seamless functioning of AI -driven applications. This paper explores the quintessential changes needed in communication paradigms to keep pace with the evolving AI landscape. Specifically, we highlight the pivotal role of multipath communication in enhancing the responsiveness and efficiency of AI applications [1]. As a case in point, we investigate its impact on mission-critical operations in robotics. Through experimentation and analysis, the results elucidate the substantial benefits of this approach, revealing a significant improvement in delay metrics. This work underscores the imperative of aligning communication systems with the ever-growing demands of AI, ensuring that infrastructural capabilities do not lag in the race for innovation.

关键词： Adaptation models Technological innovation Visualization Biological system modeling Mission critical systems Real-time systems Reliability

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Optimizing Data Capture Through Object Recognition for Efficient Sensor and Camera Management with a Quadruped Robot

Optimizing Data Capture Through Object Recognition for Effic...

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IEEE Southeastcon

作者： Roxie Reese Aiden Kovarovics Arielle Charles Charles Koduru M. Hassan Tanveer Razvan C. Voicu Department of Robotics & Mechatronics Engineering Kennesaw State University Marietta Georgia

This paper explores the integration of object recognition to advance autonomous mobile robotics, with a specific focus on employing sensor fusion in quadrupedal swarm units, exemplified by the Unitree GO1 robotic dog. The proposed system utilizes an RGB camera and the YOLOv8 machine learning module to enable the robotic dog to identify objects, subsequently triggering predefined actions or activating additional hyper-spectral sensors and cameras. This approach enhances the robot's environmental interaction, allowing it to optimize power efficiency by activating sensors selectively, resulting in a more focused dataset. The technology's applications span various domains, including threat detection in home defense, surveillance of civic structures, and monitoring industrial components. The paper delves into the customization potential through the creation of bespoke datasets and model training, incorporating techniques such as transfer learning and domain adaptation to tailor the system to user-specific requirements. Beyond its immediate applications, the implications of object recognition and AI-assisted robotics extend to diverse scientific communities, offering a versatile tool for a wide array of applications.

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The Development and Implementation of a Cost-Effective Educational Robotic Arm Using ROS-MoveIT

The Development and Implementation of a Cost-Effective Educa...

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IEEE Integrated STEM Education Conference (ISEC)

作者： Matthew Eaton M. Hassan Tanveer Department of Robotics & Mechatronics Engineering Kennesaw State University Marietta GA

ISBN: (数字)9798350352801

ISBN: (纸本)9798350352818

This paper introduces a cost-effective robotic arm designed to match the performance of expensive counterparts, addressing the financial barriers hindering the widespread adoption of modern robotic arms in educational settings. The affordability of this robotic arm not only allows for greater student involvement, but its open-source nature fosters a deeper understanding of the robotics development process. This paper details the features and characteristics of the robotic arm design, as well as outlines the opportunities for mechatronics and robotics labs this design provides to students and educators through discussions ranging from the pros and cons of various stepper motor gearbox configurations, and structural material choices, to choices regarding various popular computational platforms. The overall initiative of the paper aims to create a more inclusive learning environment by reducing financial constraints, enabling broader student participation, and contributing to the advancement of robotics education.

关键词： Solid modeling Accuracy Three-dimensional displays Service robots Education Manipulators Control systems

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High-Performance Admittance Control of An Industrial Robot Via Disturbance Observer 48

High-Performance Admittance Control of An Industrial Robot V...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Samuel, Kangwagye Haninger, Kevin Oh, Sehoon Dgist Department of Robotics and Mechatronics Engineering Daegu Korea Republic of Fraunhofer Ipk Department of Automation Berlin Germany

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Safe physical interaction using admittance control on an industrial robot with inner-loop motion control remains challenging. This is partly due to the low intrinsic admittance and stability issues from inner-loop motion control limitations (e.g. bandwidth). To increase the admittance at an interaction point with the user/environment, this paper proposes a robust admittance control architecture. A disturbance observer (DOB) is used to improve effective inner-loop motion control, suppressing the effects of velocity disturbances. The DOB uses the robot's closed-loop task space velocity control as the nominal model, compensating disturbances between the commanded robot velocity and realized robot velocity output. An admittance controller uses measured force to generate robot velocity commands. Detailed analyses are carried out to theoretically evaluate the proposed control system. Experiments conducted on a COMAU RACER-7-1.4 industrial robot verify the effectiveness of the proposed admittance control scheme and stability in environmental contact. Moreover, the proposed method is simple to implement on the existing robot system. © 2022 IEEE.

关键词： Industrial robots

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Preprocessing Taste Data for Deep Neural Networks 14

Preprocessing Taste Data for Deep Neural Networks

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14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Lee, Hyunjong Jung, Han Hee Kwak, Jeongho Yea, Junwoo Choi, Jihwan P. Jang, Kyung-In Department of Electrical Engineering and Computer Science Daegu Korea Republic of Dgist Department of Robotics and Mechatronics Engineering Daegu Korea Republic of Dgist Department of Electrical Engineering and Computer Science Daegu Korea Republic of Department of Aerospace Engineering Dajeon Korea Republic of

ISBN: (纸本)9798350313277

Analyzing wine using taste data is a promising field due to the explosive expansion of online commerce. However, because of the wide variety of wine types with different flavors and aromas, it is difficult for consumers to choose the wine that suits their taste, and also difficult for sellers to recommend appropriate wines to consumers. Therefore, it is necessary to numerically analyze and classify wine, and a deep learning algorithm which mimics the human brain is appropriate for analyzing the wine data [1]. In this paper, we introduce several studies of wine classification using deep learning architectures and propose preprocessing methods for applying the taste data of wine to deep learning networks. © 2023 IEEE.

关键词： data augmentation deep learning preprocessing taste classification taste sensor wine

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Resampling Strategies for Increasing Point Density in Narrow Passages for Probabilistic Roadmaps

Resampling Strategies for Increasing Point Density in Narrow...

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ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Bartłomiej Bonar Tomasz Buratowski Department of Robotics and Mechatronics Faculty of Mechanical Engineering and Robotics AGH University of Krakow Kraków Poland

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

This paper presents multiple point-sampling strategies for stochastic approach to path planning. Their main purpose is to increase points density in narrow corridors, which are often difficult areas to navigate using non-deterministic approach for path planning. At the same time, algorithms for distributing points over the area of narrow regions and reducing their number in open space are described as well as postprocessing algorithm distancing samples from obstacles. Simulation-based tests are performed to compare achieved results and estimate calculation times.

关键词： Navigation Gaussian distribution Probabilistic logic Vectors Path planning Computational efficiency Complexity theory

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Designing Optimal Parameters for Single-Axis Solar-Tracker through Analysis of Sun-Path and Tracking Vector Dynamics 6

Designing Optimal Parameters for Single-Axis Solar-Tracker t...

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6th International Conference on Electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Akhtaruzzaman, M. Islam, Md Shofiqul Shahryer, Fahim Arif, Muammer Din Mollik, Md. Sazib Rahman, Muhammad Towfiqur Rahman, Md. Mahbubur Hasan, Mohammad Kamrul Ahmed, Shugata Ashrafuzzaman, Md. Department of Computer Science and Engineering Dhaka1216 Bangladesh Department of Mechanical Engineering Dhaka1216 Bangladesh Department of Electrical and Electronic Engineering Dhaka Bangladesh Department of Computer Science and Engineering Dhaka Bangladesh Faculty of Information Science and Technology Bangi Malaysia Department of Robotics and Mechatronics Engineering Bangladesh Sdn. Bhd. Cyberjaya Malaysia

ISBN: (纸本)9798350385779

The persistent challenges faced by sun-tracking systems include inefficient power production, wastage of energy, ineffective control, and high costs. Most of the existing systems are either static or dual-axis tracking which lead to inefficient output or increasing energy wastage and cost overheads. Though, single-axis tracking system has some benefits over the static or dual-axis tracking, most of the systems do not analyze the selection of optimal sun-path which again leads to inefficient and inadequate absorption of sunlight. Addressing the issues, this article presents a design of optimal parameters for single-axis solar-tracking by analyzing the sun-path and tracking vector dynamics. The study mainly focuses on analyzing solar-tracking dynamics, variations in sunray angles, Azimuth and Elevation dynamics throughout the day for the twelve months, Sun-vector calculation for local coordinates, joint rotational-axis, and joint motion control using a Proportional-Derivative controller. Additionally, the article outlines a conceptual architecture for automated control, monitoring, and power distribution for the potential development of a sustainable smart city. The proposed strategy addresses the issues of the optimal design of a single-axis solar-tracker, thus ensuring the reduction of cost overhead and energy wastage. © 2024 IEEE.

关键词： Dynamics

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