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Hierarchical Attention Mechanism for Domain-invariant Spoken Language Identification via Inter-domain Alignment and Intra-domain Language Discrimination

Hierarchical Attention Mechanism for Domain-invariant Spoken...

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2024 IEEE Conference on engineering Informatics, ICEI 2024

作者： Goswami, Urvashi Muralikrishna, H. Kumar, Sujeet Dileep, A.D. Thenkanidiyoor, Veena Indian Institute of Technology Mandi School of Computing and Electrical Engineering Mandi India Manipal Institute of Technology Manipal Academy of Higher Education Department of Electronics and Communication Engineering Manipal576104 India Indian Institute of Technology Dharwad Department of Computer Science and Engineering Dharwad India National Institute of Technology Goa Department of Computer Science and Engineering Goa India

ISBN: (纸本)9798331505776

Modern methods for spoken language identification (LID) have demonstrated promising results when trained on large datasets. However, their effectiveness is considerably impacted by the discrepancies between the training and testing distributions. Unsupervised domain adaptation (UDA) addresses the domain discrepancies by aligning feature distributions across source and target domains without using labeled target data, thereby ensuring the model performs consistently across both domains. This alignment, however, may come at the cost of reduced model discriminability. To enhance performance under domainmismatched conditions, a LID system should learn domaininvariant representations of speech while maintaining language discriminability at every level, from initial segment-level representations to final utterance-level representations. To address this issue, in this paper, we propose a hierarchical attention network that simultaneously enhances model domain invariance through inter-domain alignment and improves model's language discriminability using intra-domain contrastive discrimination. The performance on the target domain shows that the proposed method exceeds the effectiveness of the top-performing existing approaches. © 2024 IEEE.

关键词： Distribution transformers

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MahitiBandhu: A Solar-Powered Information Kiosk System for Rural Community Empowerment

MahitiBandhu: A Solar-Powered Information Kiosk System for R...

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2024 IEEE International Conference on Information technology, Electronics and Intelligent Communication Systems, ICITEICS 2024

作者： Arakeri, Megha P. Lakshmana Jain, Ayush Hemachandra, G. Mohan Gowda, V. Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Department of Computer Science and Engineering Manipal India Seamovations Labs Pvt. Ltd Bangalore India Ramaiah Institute of Technology Department of Information Science and Engineering Bangalore India Ramaiah Institute of Technology Department of Electrical and Electronics Engineering Bangalore India Gitam School of Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350382693

A major portion of Karnataka's population lives in rural areas. Most of the rural people are illiterate and poor due to lack of proper services and infrastructure. There are various rural development schemes run by the government of Karnataka/India for the benefit of villagers. However, most people in the villages of Karnataka are unaware of these schemes due to lack of education, poverty, inaccessibility, and lack of technological knowledge. Hence, the government is trying to render services and information to the public using ICT tools. While there are few examples of achievements of ICT in rural development, there are many failures due to lack of connectivity, bandwidth, language problems, and power supply. Also, Gram Panchayat of the village does not have proper facilities to give widespread publicity about government services and many people do not have smartphones to access information online. Thus, this paper focuses on the development of a solar-powered interactive touch-screen based kiosk system for the rural region. This single system can provide information about all rural schemes for education, agriculture, healthcare, and employment. It also gives information on other services like banking, vaccination drives, and fertilizers for farmers. This is an end-to-end user application with a text-free user interface and interacts based on audio, video, and image display irrespective of the user's literacy level. © 2024 IEEE.

关键词： Touch screens

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Single-shot single-beam coherent Raman scattering thermometry based on optically induced air lasing

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Light(science & Applications) 2024年第12期13卷 3253-3260页

作者： Xu Lu Yewei Chen Francesco Mazza Siyi He Zihan Li Shunlin Huang Quanjun Wang Ning Zhang Bo Shen Yuzhu Wu Jinping Yao Ya Cheng State Key Laboratory of High Field Laser Physics Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China Faculty of Aerospace Engineering Delft University of TechnologyKluyverweg 12629 HS DelftThe Netherlands Institute of Modern Optics Nankai UniversityTianjin 300350China School of Microelectronics Shanghai UniversityShanghai 200444China

Thermometric techniques with high accuracy,fast response and ease of implementation are desirable for the study of dynamic combustion environments,transient reacting flows,and non-equilibrium ***,single-shot singlebeam coherent Raman scattering(SS-CRS)thermometry is developed,for the first time to our knowledge,by using air lasing as a *** show that the air-lasing-assisted CRS signal has a high signal-to-noise ratio enabling single-shot measurements at a 1 kHz repetition *** SS-CRS thermometry consistently exhibits precision of<2.3%at different temperatures,but the inaccuracy grows with the increase in *** high measurement repeatability,1 kHz acquisition rate and easy-to-implement single-beam scheme are achieved thanks to the unique temporal,spectral and spatial characteristics of air *** work opens a novel avenue for high-speed CRS thermometry,holding tremendous potential for fast diagnostics of transient reacting flows and plasmas.

关键词： scattering lasing beam

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Cleaning of two mirrors in the first mirror unit using radiofrequency capacitively coupled plasma

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Plasma science and technology 2024年第9期26卷 165-171页

作者： Chenxue WANG Rong YAN Yuming LIU Su XU Lei MU Wei ZHENG Rui DING Junling CHEN Institute of Plasma Physics Chinese Academy of SciencesHefei 230031People’s Republic of China University of Science and Technology of China Hefei 230026People’s Republic of China School of Computer Engineering Anhui Sanlian UniversityHefei 230601People’s Republic of China

First mirror(FM)cleaning,using radio frequency(RF)plasma,has been proposed to recover FM reflectivity in nuclear fusion reactors such as the International Thermonuclear Experimental Reactor(ITER).To investigate the influence of simultaneous cleaning of two mirrors on mirror cleaning efficiency and uniformity,experiments involving single-mirror cleaning and dual-mirror cleaning were conducted using RF capacitively coupled plasma in the *** the test and simultaneous cleaning of two mirrors,the FM and second mirror(SM),both measuring 110 mm×80 mm,were placed inside the first mirror unit(FMU).They were composed of 16 mirror samples,each with a dimension of 27.5 mm×20 *** mirror samples consist of a titanium-zirconium-molybdenum alloy substrate,a 500 nm Mo intermediate layer and a 30 nm Al_(2)O_(3) surface coating as a proxy for Be *** cleaning of a single first mirror(SFM)and the simultaneous cleaning of the FM and SM(DFM and DSM)lasted for 9 h using Ar plasma at a pressure of 1 *** total reflectivity of mirror samples on the DSM did not fully recover and varied with location,with a self-bias of−140 *** a self-bias of−300 V,the total reflectivity of mirror samples on the SFM and DFM was fully *** energy dispersive spectrometer results demonstrated that the Al_(2)O_(3) coating had been completely removed from these mirror ***,the mass loss of each mirror sample on the SFM and DFM before and after cleaning varied depending on its location,with higher mass loss observed for mirror samples located in the corners and lower loss for those in the *** with SM cleaning,the simultaneous cleaning of two mirrors reduced the difference between the highest and lowest mass ***,this mass loss for the mirror samples of the DFM facing the DSM was *** indicated that mirror samples cleaned face to face in the FMU simultaneously could influence each other,highlighting the need for special attention in

关键词： first mirror unit dual-mirror cleaning reflectivity sputtering rate

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Robust Sensor Networks: Applying AI for Fault Identification in Challenging Operational Contexts 5

Robust Sensor Networks: Applying AI for Fault Identification...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Manjunatha, A.S. Venkatramana Bhat, P. Ramakrishna, M. Prabhu, Matti Nidhi Dept. of Computer and Communication Engineering NMAM Institute of Technology Nitte Karnataka Mangaluru India Dept. of Computer Science and Engineering NMAM Institute of Technology Nitte Karnataka Mangaluru India Manipal Academy of Higher Education Dept. of Data Science and Computer Applications Manipal Institute of Technology Manipal576104 India

ISBN: (纸本)9798331518097

Wireless Sensor Networks (WSNs) are highly implemented in harsh and dynamic environments. In such configurations, faults and anomalies easily occur, causing unwanted disruptions in data accuracy and network performance. In the context of reliability and stability in WSN operations, effective fault detection techniques are vital. This research work discusses how several machine learning models may be applied, including Logistic Regression, Decision Tree, Random Forest, and K-Nearest Neighbors in order to detect fault in WSNs. The performance evaluation was performed based on major criteria, which are accuracy, precision, recall, and Fl score. This, therefore, makes these approaches to machine learning effective in identifying faults efficiently, hence offering a well-balanced solution that is scalable and robust for integrity and operational effectiveness of WSN s. © 2024 IEEE.

关键词： Random forests

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Triboelectric-electromagnetic hybrid generator with swing-blade structures for effectively harvesting distributed wind energy in urban environments

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Nano Research 2023年第9期16卷 11621-11629页

作者： Yangyang Yan Jinzhi Zhu Yuejun Zhang Zhaohui Wang Lin Jiang Zhong Lin Wang Jianyang Zhu Tinghai Cheng Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and TechnologyWuhan 430081China Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijing 101400China Georgia Institute of Technology AtlantaGA 30332-0245USA Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China

The wind energy in cities cannot be exploited effectively because natural wind is unstable and ***,a triboelectricelectromagnetic hybrid generator with swing-blade structures(SBS-TEHG)was designed to effectively harvest intermittent and continuous wind energy in an urban ***,the spring structure and base were considered to realize the maximum output performance of triboelectric ***,the computational fluid dynamics method was applied to optimize the structure of the SBS-TEHG to improve its aerodynamic *** starting wind speed of the SBS-TEHG was 2 m/s,and its energy conversion efficiency was 9.04%,159%higher than that of the SBS-TEHG without guide plates at 4 m/*** results demonstrated that the SBS-TEHG lit 105 light-emitting diodes(LEDs)under the intermittent-wind harvesting mode at a wind frequency of 1 Hz when the single swing blade operated,while a wireless PM_(2.5)&PM_(10)sensor was powered by the SBS-TEHG after a period of operation under the continuous-wind harvesting *** findings of this study provide a novel solution for lowspeed wind energy harvesting in cities and demonstrate the potential of SBS-TEHG as a distributed energy source.

关键词： triboelectric nanogenerator swing-blade structure low-speed wind energy computational fluid dynamics distributed energy source

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Characterizing sEMG changes with muscle fatigue for lower-extremity prostheses and exoskeletons control 46

Characterizing sEMG changes with muscle fatigue for lower-ex...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Shang, Wenze Huang, Ruisen Lin, Yongji Liang, Fengyan Yin, Ming Lu, Xiao-Ping Wu, XinYu Gao, Fei Chinese Academy of Science Shenzhen Institute of Advanced Technology Guangdong Shenzhen China Hainan University Key Laboratory of Biomedical Engineering of Hainan Province School of Biomedical Engineering Haikou China Macau University of Science and Technology School of Computer Science and Engineering Taipa China

ISBN: (纸本)9798350371499

In powered lower limb prostheses and exoskeleton control, sEMG based methods have been widely explored and utilized due to non-invasive nature and ability to directly reflect user intentions. However, in practical use, neuromuscular fatigue (NMF) caused by long-term use can cause significant changes in sEMG signals. These issues are constraining sEMG's active prosthetics from the laboratory to real life. In this study, the changes in sEMG signals with muscle fatigue was investigated. sEMG data from one healthy subject and a below-knee amputee were logged and analyzed when they walked on a treadmill for a long time. They will experience from no NMF to NMF and then adapt to no NMF. A variational mode decomposition-based soft interval threshold (VMD-SIT) method was used to denoise the sEMG signals. Feature extraction methods were used to extract the features of the sEMG signal, and the distribution changes of these features during walking were analyzed. The results indicated that the NMF of the amputee was quite different from and more variable than that of the healthy subject, and the ratios of features' mean value of amputee and healthy are much higher in residual-limb side (12.35-26.18) than normal side (3.52-5.91). © 2024 IEEE.

关键词： Exoskeleton (Robotics)

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A Review on Alzheimer's Disease Detection using Machine Learning 2

A Review on Alzheimer's Disease Detection using Machine Lear...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Moorthy, Deepthi K Nagaraj, P. Subhashini, S.J. Mar Baselios College of Engineering and Technology Department of Computer Science and Engineering Nalanchira Trivandrum India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil Virudhunagar India Srm Madurai College of Engineering and Technology Department of Information Technology Sivagangai India

ISBN: (纸本)9798350325799

Alzheimer's disease is a progressive and irreversible brain disorder affecting millions worldwide. The timely detection of Alzheimer's Disease (AD) is essential for the effective management and treatment of the disease. Machine learning (ML) approaches have shown promising results in detecting AD at an early stage. This review article provides an overview of the recent developments in the application of ML techniques for AD detection. Also discusses the application of certain image processing, feature extraction, and ML techniques for detecting AD. The article covers various ML algorithms and their performance in detecting AD with different data sources, such as MRI, PET, etc. with their advantages and limitations. Overall, this research study demonstrates the potential of ML approaches in improving the accuracy and efficiency of Alzheimer's disease detection, which could lead to better patient outcomes and disease management. © 2023 IEEE.

关键词： Neurodegenerative diseases

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An Exploration of Contagion Infection in Citrus Plant with Augmented Data using ConvNet 2

An Exploration of Contagion Infection in Citrus Plant with A...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Shanmugapriya, S. Dhanasekaran, S. Murugan, B.S. Kalasalinagam Academy of Research and Education Departement of Computer Science and Engineering India Kalasalinagam Academy of Research and Education Departement of Information Technology India M. Kumarasamy College of Eengineering Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350325799

Citrus is widely cultivated and consumed fruit across the global. It gains its popularity from its nutritional benefits. Citrus fruit has gained its international trading due to freshly consumed, processed products, oil production and other by-products. Citrus production is cut short mainly due its diseases. Identifying the diseases at early stage and stepping forward to cure them is vital role in improving the production. Automated disease identification cuts down the manual effort and also improves the efficiency in identification. With various degrees of accuracy, both machine learning and deep learning algorithms have been successful in identifying citrus leaf and fruit diseases. This research study proposes a novel disease classification method using CNN and also provides a comparative study with models like SVM, k-means clustering, ANN and CNN for disease identification. © 2023 IEEE.

关键词： Citrus fruits

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Real Time Eye-Tracking Mouse Control Using Recurrent Neural Network

Real Time Eye-Tracking Mouse Control Using Recurrent Neural ...

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2023 International Conference on Integrated Intelligence and Communication Systems, ICIICS 2023

作者： Balakrishnan, D. Mariappan, Umasree Niteesh, Vedula Reddy, Yeruva Akhileswara Reddy, Vangala Mahesh Reddy, Velagala Venkata Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamil Nadu Krishnakoil India Sri Vidya College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Virudhunagar India

ISBN: (纸本)9798350315455

Machine Learning (ML) techniques, specifically Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost), were employed to achieve precise and intuitive real-time eye tracking mouse control through computer vision. However, XGBoost may suffer from overfitting when dealing with a large number of features compared to the training data size, or when dealing with noisy or imbalanced data. To address this issue, this paper introduces a Recurrent Neural Network (RNN), for eye tracking mouse control in Human computer Interaction (HCI). Gaze Direction Estimation (GDE) is initially employed to estimate gaze direction, utilizing pupil positions and camera calibration parameters. The estimated gaze direction is then used as input for the RNN to eye-tracking mouse control for HCI. The experimental results shows that the GDE-RNN has 26.03% and 8.24% superior accuracy, 24.93% and 86.76% better precision, and 27.36% and 8.75% high recall in comparison to SVM and XGBoost for eye tracking mouse control. © 2023 IEEE.

关键词： Eye tracking gaze direction estimation human computer interaction mouse control recurrent neural network

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