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Scalable and Foldable Origami-Inspired Supernumerary Robotic Limbs for Daily Tasks

IEEE Access 2024年 12卷 53436-53447页

作者： Kusunoki, Mikiya Nguyen, Linh Viet Tsai, Hsin-Ruey Ho, Van Anh Xie, Haoran Japan Advanced Institute of Science and Technology Ishikawa Nomi923-1211 Japan National Chengchi University Department of Computer Science Taipei11605 Taiwan

This paper proposes scalable and foldable origami-inspired supernumerary robotic limbs that incorporate a continuous robotic mechanism to support activities of daily living and presents an analysis of the fabrication process, evaluation experiments, and potential applications of the proposed devices. These origami-inspired supernumerary robotic limbs can augment the wearer's capabilities by adjusting the scale of the devices to various applications and attaching them to parts of the body, such as the hands, wrists, arms, and torso. The device's foldable structure can be unfolded for use and folded when not in use to prevent physical contact with the wearer and the surrounding environment so that the user's movements are not restricted. In addition, the robotic limb is made of lightweight and soft material, so it remains safe to use and fatigue-free even after prolonged use. To verify the durability of the origami module, we conducted an experiment in which the module underwent 1,000 compressions using different materials and layer counts based on the folding pattern outlined in the manufacturing diagram. The experimental results showed that polypropylene was a suitable material for reducing fatigue due to folding, compared to polypropylene synthetic paper or plain paper. We also observed decreased stiffness with an increase in the number of layers. We believe that the proposed origami-inspired supernumerary robotic limbs can enlighten novel approaches to combining soft robotic and wearable devices. © 2013 IEEE.

关键词： Fabrication

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Classifying the Status of CKD Using Randomized Weighted Optimization Model Using Machine Learning Techniques

Classifying the Status of CKD Using Randomized Weighted Opti...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Vijayalakshmi, A. Sumalatha, V. Vels Institute of Science Technology & Advanced Studies Computer Science Chennai India

ISBN: (纸本)9798350348217

Chronic kidney disease (CKD) is a substantial health-care burden owing to its growingoccurrence, enhanced danger of development to end-stage renal disease, and reduced mortality and morbidity prognosis. It is quickly accelerating to a worldwide well-beingcatastrophe. The main causes of CKD include high blood pressure and diabetes. The major function of the kidney is filtering waste from a human body. When kidneys fail, waste builds up in bodies and eventually leads to death. Researchers all around the globe utilize the Glomerular Filtration Rate (GFR) and kidney damage indicators to define CKD as a disorder that causes decreasing renal function over a period of time. A person having CKD is more likely to die early. Doctors have a tough time recognizing the several disorders associated with CKD early enough to avoid the condition. Data mining approaches have recently been exposed to considerable research in CKD diagnosis, with a focus on accuracy, either through the simplicity of illness by conducting feature selection in addition to pre-processing or not before classification. This research work determines creatinine level is a kind of blood metabolite that has a significant relationship with GFR and Blood Urea Nitrogen (BUN)BUN Creatinine Ratio (BCR). Since measuring GFR and BCR is challenging, this work focused in analysing creatinine value is used to determine Estimated GFR (EGFR) and BCR from serum creatinine indirectly utilizing the attributes available in the dataset whereas the 28 attributes are considered inclusive of 'Gender' with 523 records. The EGFR and BCR computing results areused in this prediction analysis for providing an accurately categorizingthe statusof CKDwhich has been utilized by Randomized Weighted Optimization Model (RWOM). Furthermore, the proposed RWOM with Neural Network(NN) is compared to the RWOM with Logistic Regression (LR), NN, LR in terms of analysing the better categorization status of CKD from patient records. © 2023 IEEE.

关键词： Creatinine

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Ultra-low power MoS2 optoelectronic synapse with wavelength sensitivity for color target recognition

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science China(Information sciences) 2025年第4期68卷 187-196页

作者： Bo WEI Yabo CHEN Xiaotong HAN Yan KANG Bujia LIANG Cheng LI Xiaokuo YANG Liang FANG Yuanxi PENG Institute for Quantum Information & State Key Laboratory of High Performance Computing College of ComputerNational University of Defense Technology Fundamentals Department Air Force Engineering University College of Advanced Interdisciplinary Studies National University of Defense Technology Institute of Quantum Information Science and Technology College of ScienceNational University of Defense Technology College of Computer National University of Defense Technology

Optoelectronic synapses that integrate visual perception and pre-processing hold significant potential for neuromorphic vision systems（NVSs）. However, due to a lack of wavelength sensitivity, existing NVS mainly focuses on gray-scale image processing, making it challenging to recognize color images. Additionally, the high power consumption of optoelectronic synapses, compared to the 10 fJ energy consumption of biological synapses, limits their broader application. To address these challenges, an energy-efficient NVS capable of color target recognition in a noisy environment was developed,utilizing a MoS2optoelectronic synapse with wavelength sensitivity. Benefiting from the distinct photon capture capabilities of 450, 535, and 650 nm light, the optoelectronic synapse exhibits wavelength-dependent synaptic plasticity, including excitatory postsynaptic current（EPSC）, paired-pulse facilitation（PPF）, and long-term plasticity（LTP）. These properties can effectively mimic the visual memory and color discrimination functions of the human vision system. Results demonstrate that the NVS, based on MoS2optoelectronic synapses, can eliminate the color noise at the sensor level, increasing color image recognition accuracy from 50% to 90%. Importantly, the optoelectronic synapse operates at a low voltage spike of0.0005 V, consuming only 0.075 fJ per spike, surpassing the energy efficiency of both existing optoelectronic and biological synapses. This ultra-low power, color-sensitive device eliminates the need for color filters and offers great promise for future deployment in filter-free NVS.

关键词： optoelectronic synapse neuromorphic vision system color recognition 2D materials image pre-processing

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Exploring Sequential Feature Selection in Deep Bi-LSTM Models for Speech Emotion Recognition

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computers, Materials & Continua 2024年第2期78卷 2689-2719页

作者： Fatma Harby Mansor Alohali Adel Thaljaoui Amira Samy Talaat Computer Science Department Future Academy-Higher Future Institute for Specialized Technological StudiesCairo12622Egypt Department of Computer Science and Information College of Science at Zulfi Majmaah UniversityP.O.Box 66Al-Majmaah11952Saudi Arabia Preparatory Institute for Engineering Studies of Gafsa ZarrougGafsa2112Tunisia Computers and Systems Department Electronics Research InstituteCairo12622Egypt

Machine Learning(ML)algorithms play a pivotal role in Speech Emotion Recognition(SER),although they encounter a formidable obstacle in accurately discerning a speaker’s emotional *** examination of the emotional states of speakers holds significant importance in a range of real-time applications,including but not limited to virtual reality,human-robot interaction,emergency centers,and human behavior *** identifying emotions in the SER process relies on extracting relevant information from audio *** studies on SER have predominantly utilized short-time characteristics such as Mel Frequency Cepstral Coefficients(MFCCs)due to their ability to capture the periodic nature of audio signals *** these traits may improve their ability to perceive and interpret emotional depictions appropriately,MFCCS has some *** this study aims to tackle the aforementioned issue by systematically picking multiple audio cues,enhancing the classifier model’s efficacy in accurately discerning human *** utilized dataset is taken from the EMO-DB database,preprocessing input speech is done using a 2D Convolution Neural Network(CNN)involves applying convolutional operations to spectrograms as they afford a visual representation of the way the audio signal frequency content changes over *** next step is the spectrogram data normalization which is crucial for Neural Network(NN)training as it aids in faster *** the five auditory features MFCCs,Chroma,Mel-Spectrogram,Contrast,and Tonnetz are extracted from the spectrogram *** attitude of feature selection is to retain only dominant features by excluding the irrelevant *** this paper,the Sequential Forward Selection(SFS)and Sequential Backward Selection(SBS)techniques were employed for multiple audio cues features ***,the feature sets composed from the hybrid feature extraction methods are fed into the deep Bidirectional Long Short

关键词： Artificial intelligence application multi features sequential selection speech emotion recognition deep Bi-LSTM

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Segmentation of Skin Lesion Image Using FCM with Color Transformation Saliency 1

Segmentation of Skin Lesion Image Using FCM with Color Trans...

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1st IEEE International Conference on Computing and Data science, ICCDS 2024

作者： Bavya, S. Saravana Kumar, V. Kavitha, M. Anantha SivaPrakasam, S. Vels Institute of Science Technology & Advanced Studies Department of Computer Science & Engineering Chennai India Sreenidhi Institute of Science and Technology Department of Information Technology Hyderabad India S A Engineering College Department of Computer Science & Engineering Chennai India Rajalakshmi Engineering College Department of Computer Science & Technology Chennai India

ISBN: (数字)9798350365337

ISBN: (纸本)9798350365337

In the majority of Western nations including America, Australia and Europe, skin cancer is badly-behaved. Skin concealing, inadequacy of Sun-lights, climate, age, and inherited are major risk factors. Early identification of skin cancer and proceed the treatment can avoid death. The abnormal skin region determines where the skin diseases had been found. Various sorts of skin ailments be existent currently. Melanoma is the sort of skin threat which has grows the greater part of mortality rate. The timely identification and intercession of melanoma include myriad changes of fix. Melanoma has been recognized by shape, size, concealing and outward of the skin injury. This paper demonstration about the traditional clustering technique in particular Fuzzy Clustering technique is acted in these skin lesion pictures. This strategy is segmenting this melanoma from these dermoscopic images effectively. The presentation of this strategy is assessed as far as pixel grouped and time complexity. © 2024 IEEE.

关键词： Feature extraction

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Beamforming and Reflection Design for Short Packet ISAC With Non-Ideal RIS: An A3C-Based Approach

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8379-8384页

作者： Mahmoudi, Behrad Khonsari, Ahmad Zeinali, Farshad Mili, Mohammad Robat Mashhadi, Mahdi Boloursaz Xiao, Pei University of Tehran Department of Electrical and Computer Engineering Tehran Iran University of Tehran School of Electrical and Computer Engineering College of Engineering Tehran Iran School of Computer Science in the Institute for Research in Fundamental Sciences Tehran Iran United Kingdom Institute for Advanced Innovative Solutions Tehran Iran

Integrated sensing and communication (ISAC) is a promising solution to mitigate the increasing congestion of the wireless spectrum. In this paper, we investigate the short packet communication regime within an ISAC system assisted by a reconfigurable intelligent surface (RIS) to meet the low latency ultra-reliable requirements in the next-generation wireless networks. We consider a non-ideal RIS model that captures effects of the phase-dependent amplitude variations in the reflection coefficients, and we have incorporated the near-field model into the channels between the RIS and the users or targets. In this setup, we jointly design the transmit beamforming and the RIS phase shifts to maximize the sum rate while satisfying the sensing signal-to-noise ratio (SNR) requirement. The system simultaneously carries out multitarget sensing and multi-user short packet communications with the help of the RIS. Considering the non-convex and dynamic nature of the resulting optimization problem, we propose an asynchronous advantage actor-critic (A3C) based method for beamforming and reflection design in this setup. Numerical results demonstrate the superiority of the proposed scheme over the benchmarks. © 1967-2012 IEEE.

关键词： Beamforming

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An efficient and accurate approach to identify similarities between biological sequences using pair amino acid composition and physicochemical properties

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Soft Computing 2024年第17-18期28卷 9341-9357页

作者： Hooshyar, L. Hernández-Jiménez, M.B. Khastan, A. Vasighi, M. Department of Mathematics Institute for Advanced Studies in Basic Sciences Zanjan Iran Departmento de Economia Metodos Cuantitativos E Historia Economica Universidad Pablo de Olavide Seville Spain Department of Computer Sciences Institute for Advanced Studies in Basic Sciences Zanjan Iran

Our study presents a novel method for analyzing biological sequences, utilizing Pairwise Amino Acid Composition and Amino Acid physicochemical properties to construct a feature vector. This step is pivotal, as by utilizing pairwise analysis, we consider the order of amino acids, thereby capturing subtle nuances in sequence structure. Simultaneously, by incorporating physicochemical properties, we ensure that the hidden information encoded within amino acids is not overlooked. Furthermore, by considering both the frequency and order of amino acid pairs, our method mitigates the risk of erroneously clustering different sequences as similar, a common pitfall in older methods. Our approach generates a concise 48-member vector, accommodating sequences of arbitrary lengths efficiently. This compact representation retains essential amino acid-specific features, enhancing the accuracy of sequence analysis. Unlike traditional approaches, our algorithm avoids the introduction of sparse vectors, ensuring the retention of important information. Additionally, we introduce fuzzy equivalence relationships to address uncertainty in the clustering process, enabling a more nuanced and flexible clustering approach that captures the inherent ambiguity in biological data. Despite these advancements, our algorithm is presented in a straightforward manner, ensuring accessibility to researchers with varying levels of computational expertise. This enhancement improves the robustness and interpretability of our method, providing researchers with a comprehensive and user-friendly tool for biological sequence analysis. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Amino acids

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Highly-efficient(>70%)and Wide-spectral(400-1700 nm)sub-micron-thick InGaAs photodiodes for future high-resolution image sensors

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Light(science & Applications) 2024年第12期13卷 3224-3235页

作者： Dae-Myeong Geum Jinha Lim Junho Jang Seungyeop Ahn SeongKwang Kim Joonsup Shim Bong Ho Kim Juhyuk Park Woo Jin Baek Jaeyong Jeong SangHyeon Kim School of Electrical Engineering Korea Advanced Institute of Science and Technology(KAIST)Daejeon 34141Republic of Korea Department of Electrical and Computer Engineering Inha UniversityIncheon 22212Republic of Korea

This paper demonstrates the novel approach of sub-micron-thick InGaAs broadband photodetectors(PDs)designed for high-resolution imaging from the visible to short-wavelength infrared(SWIR)*** approaches encounter challenges such as low resolution and crosstalk issues caused by a thick absorption layer(AL).Therefore,we propose a guided-mode resonance(GMR)structure to enhance the quantum efficiency(QE)of the InGaAs PDs in the SWIR region with only sub-micron-thick *** TiOx/Au-based GMR structure compensates for the reduced AL thickness,achieving a remarkably high QE(>70%)from 400 to 1700 nm with only a 0.98μm AL InGaAs PD(defined as 1μm AL PD).This represents a reduction in thickness by at least 2.5 times compared to previous results while maintaining a high ***,the rapid transit time is highly expected to result in decreased electrical *** effectiveness of the GMR structure is evident in its ability to sustain QE even with a reduced AL thickness,simultaneously enhancing the transit *** breakthrough offers a viable solution for high-resolution and low-noise broadband image sensors.

关键词： thick resolution image

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Role of Artificial Intelligence for Noninvasive Height Measurement Applications: A Survey 7

Role of Artificial Intelligence for Noninvasive Height Measu...

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7th IEEE Pune Section International Conference, PuneCon 2024

作者： Ruchitha, Inaganti Dhavale, Sunita Defence Institute of Advanced Technology Department of Computer Science and Engineering Pune India

ISBN: (纸本)9798331527822

Height measurement is crucial across various domains including healthcare, ergonomics, security, and forensic analysis. Traditional methods, such as stadiometers, often require cooperation from the subject and can be intrusive, posing significant challenges especially with children, the elderly, or individuals with disabilities. This survey paper addresses the growing need for artificial intelligence (AI) based noninvasive, automated height measurement techniques that can effectively estimate height without physical interaction. In this paper, we examined different state of the art methodologies for height measurement application area, including AI, computer vision (CV), deep learning (DL), depth imaging, and 3D laser scanning. While 3D scanning and depth imaging methodologies provide precise measurements, but they require specialized equipments which leads to additional costs for implementation. Recently, DL and advanced CV models have shown great accuracy in height estimation. Promising solutions for uncooperative subjects can be found by utilizing facial recognition and anatomical traits, and incorporating biometric parameters which can improve prediction accuracy. Despite these advancements, challenges remain with methods requiring multiple images or additional equipment, underscoring the need for more practical and user-friendly solutions. This survey highlights the necessity for tailored approaches to address specific measurement challenges and proposes guidelines for future studies to improve efficiency of noninvasive height estimation technologies. © 2024 IEEE.

关键词： Laser applications

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A Comprehensive Review on the Prediction of Video Frame and Motion Contents

A Comprehensive Review on the Prediction of Video Frame and ...

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2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Mohana Priya, P. Ulagapriya, K. Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331541170

ISBN: (纸本)9798331541187

The capability of predicting, or analyzing the future outcomes of motion pictures using intelligent systems is the video frame prediction process. Video frame prediction is a significant and challenging aspect of computer Vision (CV) applications. Video prediction plays a vital role in terms of robotics and Artificial Intelligence (AI) applications in detecting the future frames of a video, depending on which, the decision-making process can be carried out. The existing video frame prediction processes include pixel law based and motion-based predictions, which have been proven to be ambiguous. This leads to inaccurate predictions and indirectly deteriorates the performance of the real time applications. This paper performs a detailed review of the existing methodologies, their merits, pitfalls and challenges that create havoc in the video frame prediction process. In addition, this paper performs a detailed analysis on the existing datasets that assist in the video prediction process. This review summarizes various methodologies and datasets along with their performance analysis, which will open research possibilities in the field of video frame prediction. © 2024 IEEE.

关键词： Artificial Intelligence computer Vision Datasets Robotics Video frame prediction

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