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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Dat T. Nguyen Qihang Zeng Xi Tian John S. Ho Integrative Sciences and Engineering Program National University of Singapore Graduate School Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore SIA-NUS Digital Aviation Corporate Laboratory and the Institute for Health Innovation and Technology National University of Singapore Singapore Department of Electrical and Computer Engineering Institute for Health Innovation and Technology N.1 Institute for Health at the National University of Singapore Singapore

Contactless sensors embedded in the ambient environment have broad applications in unobtrusive, long-term health monitoring for preventative and personalized healthcare. Microwave radar sensors are an attractive candidate for ambient sensing due to their high sensitivity to physiological motions, ability to penetrate through obstacles and privacy-preserving properties, but practical applications in complex real-world environments have been limited because of challenges associated with background clutter and interference. In this work, we propose a thin and soft textile sensor based on microwave metamaterials that can be easily integrated into ordinary furniture for contactless ambient monitoring of multiple cardiovascular signals in a localized manner. Evaluations of our sensor’s performance in human subjects show high accuracy of heartbeat and arterial pulse detection, with ≥ 96.5% sensitivity and < 5% mean absolute relative error (MARE) across all subjects. We demonstrate our sensor’s utility for cuffless blood pressure monitoring on a human subject over a continuous 10-minute period. Our results highlight the potential of metamaterial textile sensors in ambient health and wellness monitoring *** relevance—The contactless metamaterial textile sensors demonstrated in this paper provide unobtrusive, convenient and long-term monitoring of multiple cardiovascular health metrics, including heart rate, pulse rate and cuffless blood pressure, which can facilitate preventative and personalized healthcare.

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Deep-Hand: A Deep Inference Vision Approach of Recognizing a Hand Sign Language using American Alphabet 2

Deep-Hand: A Deep Inference Vision Approach of Recognizing a...

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2nd IEEE International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2021

作者： Alon, Helcy D. Ligayo, Michael Angelo D. Melegrito, Mark P. Franco Cunanan, Christopher Uy Ii, Edgar E. Technological Institute of the Philippines Graduate Program Manila Philippines Quezon City University Department of Electronics Engineering Quezon City Philippines Technological University of the Philippines Department of Electronics and Communications Engineering Manila Philippines Polytechnic University of the Philippines Department of Computer Engineering Philippines Bohol Island State University College of Engineering and Architecture Tagbilaran Philippines

ISBN: (纸本)9781665429214

Sign-Language is to help people with hearing or speaking disabilities who are not able to communicate well with other people. Communicating with deaf people is a challenge for some speakers and people who do not know sign language. What the study proposed is to help people with such disabilities using the American Sign-Language with the corresponding hand gesture. Deaf individuals will be able to communicate or interact with other people conveniently. The study proposed hand gesture or hand sign language detection trained by using the YOLOv3 algorithm that aims to detect hand gestures or hand sign language that can recognize its equivalent letter alphabet. The study tools such as LabelImg for annotating the data set, categorizing each image of hand gestures based on their equivalent letter alphabet. In this study, Model 18 with 95.1804% training accuracy, 90.8242% validation accuracy, and mAP of 0.8275 is used for the final testing. As video with different hand gestures is presented, the results of every hand gesture detected range over 90%. © 2021 IEEE.

关键词： Object detection

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Top-Down Fabrication of Diamond Nanostructures

SSRN

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SSRN 2024年

作者： Biswas, Abhijit Li, Chenxi Pieshkov, Tymofii Mei, Zhaobo Xu, Mingfei Li, Tao Murukeshan, Jishnu Vajtai, Robert Zhao, Yuji Ajayan, Pulickel M. Department of Materials Science and NanoEngineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States

Diamond nanostructures can have exciting applications in electronics and thermal management, but their controlled fabrication can be challenging. Here, we present a top-down approach for the fabrication of diamond nanorod (DNR) clusters, via use of metal masks (Al, Ag, Au, and Cr) and reactive-ion etching (RIE). Prolonged RIE on Ag and Cr masks yields distinct etching profiles, and DNR clusters are selectively formed from Ag masks, with individual nanorods having dimensions of ~100 nm diameter and ~1.5 µm length. Detailed electron microscopy shows thin layer of amorphous carbon (a-C) around single crystalline DNR cores. Chemical analyses also show presence of oxygen on the surface of the DNRs. Fabrication of the DNR clusters with scalable top-down approach could lead to new nanodiamond-based applications. © 2024, The Authors. All rights reserved.

关键词： Nanorods

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Low-Resource Speech Synthesis with Speaker-Aware Embedding

Low-Resource Speech Synthesis with Speaker-Aware Embedding

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International Symposium on Chinese Spoken Language Processing

作者： Li-Jen Yang I-Ping Yeh Jen-Tzung Chien Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan Graduate Degree Program of Cybersecurity National Yang Ming Chiao Tung University Taiwan

ISBN: (纸本)9798350397970

Speech synthesis has been successfully exploited for mapping from text sequence to speech waveform where high-resource languages have been well studied and learned from a large amount of text-speech paired data in public-domain corpora. However, developing speech synthesis under low-resource languages is challenging for speech communication in local regions since the collection of training data is expensive. In particular, the speaker-aware speech generation under low-resource settings is crucial in real world. Such a problem is increasingly difficult in case of very limited speaker-specific data. This paper presents a speaker-aware speech synthesis under low-resource settings based on an encoder-decoder framework by using transformer. Knowledge transfer is performed by incorporating a speaker-aware embedding through first learning a pretrained transformer from multi-speaker data of a low-populated spoken language and then fine-tuning the transformer to a target speaker with very limited speaker-specific embeddings. Experiments on low-resource Taiwanese speech synthesis are evaluated to show the merit of speaker-aware transformer in terms of Mel cepstral distortion and mean opinion score.

关键词： Vocoders Synthesizers Training data Process control Oral communication Transformers Distortion

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Comparison between Line-Followers and Free Movement Robots in Tasks Execution in a Simulated Environment

Comparison between Line-Followers and Free Movement Robots i...

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IEEE Latin American Robotics Symposium, LARS

作者： Igor Pardal Latini Wilson Eduardo Barioni Marco Teixeira Flavio Neves-Jr Lucia Valeria Ramos de Arruda Universidade Tecnológica Federal do Paraná (UTFPR) Curitiba Parana Brazil Automation and Advanced Control System Laboratory (LASCA) Graduate Program in Electrical and Computer Engineering (CPGEI)

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In Industry 4.0, there is a constant pursuit for efficiency and productivity, and, searching to achieve this, the usage of multiple robots to attend to several tasks simultaneously is usual. Nowadays, there is plenty of robotic architectures, having their navigation system based on numerous different sensors. This work compares the line-follower robots, having a determined path, with the free-moving robots that navigate based on odometry, for load collecting and delivery tasks in specific locations. For this, four simulated experiments are run in two scenes, with two and four tasks, respectively. The comparison is based on a difference in robot quantity, with more line-followers than free-moving ones, aiming to collect values such as idle time, task wait time, and the number of tasks done for each machine. The results show advantages in using less but more intelligent robots with free movement. Such robots are not bound to one unique task and can use their idle time to roam and complete other processes. However, the task wait time is a concerning issue, as too few robots for overcharged situations can increase execution delays.

关键词： Service robots Navigation Robot sensing systems Time measurement Sensor systems Sensors Delays

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Customer Segmentation and Churn Prediction via Customer Metrics

Customer Segmentation and Churn Prediction via Customer Metr...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Tunahan Bozkan Tuna Ç akar Alperen Sayar Seyit Ertuğ rul MEF University Information Technology Graduate Program Istanbul Turkey Computer Engineering Department MEF University Istanbul Turkey Department of Information Technology MEF University Istanbul Turkey

ISBN: (数字)9781665450928

ISBN: (纸本)9781665450935

In this study, it is aimed to predict whether customers operating in the factoring sector will continue to trade in the next three months after the last transaction date, using data- driven machine learning models, based on their past transaction movements and their risk, limit and company data. As a result of the models established, Loss Analysis (Churn) of two different customer groups (Real and Legal factory) wascarried out. It was estimated by the XGBoost model with anF1 Score of 74% and 77%. Thanks to this modeling, it was aimed to increase the retention rate of customers through special promotions and campaigns to be made to these customer groups, together with the prediction of the customerswho will leave. Thanks to the increase in retention rates, a direct contribution to the transaction volume on a company basis was ensured.

关键词： Measurement Analytical models Law Companies Machine learning Predictive models Signal processing

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To Sharpen or not to Sharpen? On the Effect of Sharpening Filters Applied to Magnified Images 14

To Sharpen or not to Sharpen? On the Effect of Sharpening Fi...

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14th International Conference on Digital Image Processing, ICDIP 2022

作者： Emmendorfer, Leonardo R. de Olviveira, Vinicius Menezes Schein, Tatiana T. de Jesus, Junior C. Rodriguez, Bárbara D.A. Electrical Energy Processing Department Federal University of Santa Maria 97105-340 Brazil Center for Computational Science Federal University of Rio Grande 96201-900 Brazil Computational Modeling PhD Program Federal University of Rio Grande 96201-900 Brazil Computer Engineering Graduate Program Federal University of Rio Grande 96201-900 Brazil Institute of Mathematics Statistics and Physics Federal University of Rio Grande 96201-900 Brazil

ISBN: (纸本)9781510657564

Super-resolution algorithms aim to produce magnified high-resolution versions from low-resolution images. Some methods, however, are prone to generate blur during the process. Simple sharpening filters are adopted to alleviate this type of artifact. However, the actual effectiveness of this approach is not clear-cut in the literature. This work evaluates the effect of three simple sharpening filters on the quality of images obtained from super-resolution methods. Two metrics were considered in the evaluation: the Peak signal-to-noise ratio (PSNR) metric, and the Learned Perceptual Image Patch Similarity (LPIPS). One of the filters could consistently improve the LPIPS metric of magnified images from diverse benchmark sets on top of seven super-resolution methods. The increments obtained for the perceptual metric seem to occur due to the sharpening effect. Improvements on PSNR values were not as consistent. © 2022 SPIE.

关键词： Quality control

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Wearable Active Vibration Sensing for Mid-Activity Knee Health Assessment

Wearable Active Vibration Sensing for Mid-Activity Knee Heal...

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International Workshop on Wearable and Implantable Body Sensor Networks (BSN)

作者： Goktug C. Ozmen Christopher J. Nichols Lan Lan Emily Moise Christopher Sugino Alper Erturk Omer T. Inan School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA BioEngineering Graduate Program Georgia Institute of Technology Atlanta GA USA Coulter Department of Biomedical Engineering Georgia Institute of Technology Atlanta GA USA George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA Coulter Department of Biomedical Engineering School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

Non-invasive vibration measurements from the knee offer a convenient and affordable alternative to benchtop or biomechanics lab joint health monitoring systems. Recently, joint acoustic emissions (JAEs) measured from the knee were shown to be an indicator of knee health. However, the origin of JAEs is still not fully understood, which limits its acceptance and use by clinical experts. In this proof-of-concept study, rather than relying on the movements of the knee and corresponding frictional rubbing of internal surfaces to produce vibrations, we propose using an active vibration sensing approach with a known vibration source interrogating the knee. We aim to elucidate the linkage between knee vibration characteristics and structural changes in the joint following injuries. We measured tibial vibration responses of two participants using a laser vibrometer system to quantify the frequency band where the most repeatable tibial vibration measurement can be taken. Subsequently, a custom-designed wearable system measured mid-activity tibial vibration characteristics from four participants (five healthy knees and three knees with prior acute injury) during unloaded knee flexion-extensions. An active sensing knee health score was defined as the ratio of the changes in low- to high-frequency response during flexion-extension. Since changes in the boundary of tibia would alter low-frequency response more than high frequency response, we found that increased knee laxity with acute injuries resulted in an increased active sensing knee health score. Our findings demonstrate the potential of active vibration sensing as an interpretable, computationally inexpensive alternative to JAEs for wearable knee health assessment.

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Voice-Based Virtual-Controlled Intelligent Personal Assistants

Voice-Based Virtual-Controlled Intelligent Personal Assistan...

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Satya Prakash Yadav Amit Gupta Caio Dos Santos Nascimento Victor Hugo C. de Albuquerque Mahaveer Singh Naruka Sansar Singh Chauhan Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management (GLBITM) GreaterNoida U.P. India Graduate Program in Telecommunications Engineering. (PPGET) Federal Institute of Education Science and Technology of Ceará (IFCE) Fortaleza-CE Brazil Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India Department of Teleinformatics Engineering Federal University of Ceará Fortaleza Fortaleza/CE Brazil Computer Science & Engineering GL Bajaj Institute of Technology & Management Greater Noida India

Virtual assistants are improving and providing consumers with greater advantages. The comprehension and fulfilment of requests by virtual assistants will increase as voice recognition and natural language processing continue to grow. Virtual assistants are projected to be employed in more commercial activities as speech recognition technology advances. The main goal of developing personal assistant software (virtual assistant) is to use web-based semantic data sources, user-generated content, and knowledge from knowledge libraries. Basically, main objective of making this Voice-Based Virtual Assistant is to make life easier and having a personal assistant to everyone which can perform many tasks. As the end user interacts with a virtual assistant, the AI programming learns from the data provided and improves its ability to forecast the end user's needs. Virtual assistants are often used to do things like add tasks to a calendar, provide information that would normally be found in a website, and operate and monitor Smart Home devices like lighting and cameras and thermostats. Massive volumes of data are required to fuel virtual assistant technologies, which feed Artificial Intelligence (AI) platforms such as machine learning, natural language processing, and speech recognition. Speech recognition has a lengthy history and has seen several key advancements. On smartphones and wearable devices, speech recognition for dictation, search, and voice commands has become a standard feature. Design of a small, large vocabulary speech recognition system that can run quickly, accurately, and with minimum latency on mobile devices.

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Near-Optimal Pilot Assignment in Cell-Free Massive MIMO

arXiv

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arXiv 2023年

作者： Guedes, Raphael M. de Rezende, José F. Barbosa, Valmir C. Informatics and Computer Science Department State University of Rio de Janeiro RJ Rio de Janeiro20550-900 Brazil Systems Engineering and Computer Science Program Federal University of Rio de Janeiro RJ Rio de Janeiro21941-914 Brazil Graduate Program in Computational Sciences State University of Rio de Janeiro RJ Rio de Janeiro20550-900 Brazil

Cell-free massive MIMO systems are currently being considered as potential enablers of future (6G) technologies for wireless communications. By combining distributed processing and massive MIMO, they are expected to deliver improved user coverage and efficiency. A possible source of performance degradation in such systems is pilot contamination, which contributes to causing interference during uplink training and affects channel estimation negatively. Contamination occurs when the same pilot sequence is assigned to more than one user. This is in general inevitable, as the number of mutually orthogonal pilot sequences corresponds to only a fraction of the coherence interval. We introduce a new algorithm for pilot assignment and analyze its performance both from a theoretical perspective and in computational experiments. We show that it has an approximation ratio close to 1 for a plausibly large number of orthogonal pilot sequences, as well as low computational complexity under massive parallelism. We also show that, on average, it outperforms other methods in terms of per-user SINR and throughput on the uplink. Copyright © 2023, The Authors. All rights reserved.

关键词： Channel estimation

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