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A platform for integrated spectrometers based on solution-processable semiconductors

Light(Science & Applications) 2023年第9期12卷 1739-1748页

作者： Yanhao Li Xiong Jiang Yimu Chen Yuhan Wang Yunkai Wu De Yu Kaiyang Wang Sai Bai Shumin Xiao Qinghai Song Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of Technology(Shenzhen)ShenzhenGuangdong 518055China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengduSichuan 611731China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuanShan`xi 030006China

Acquiring real-time spectral information in point-of-care diagnosis,internet-of-thing,and other lab-on-chip applications require spectrometers with hetero-integration capability and miniaturized *** to conventional semiconductors integrated by heteroepitaxy,solution-processable semiconductors provide a much-flexible integration platform due to their solution-processability,and,therefore,more suitable for the multi-material integrated ***,solution-processable semiconductors are usually incompatible with the micro-fabrication *** work proposes a facile and universal platform to fabricate integrated spectrometers with semiconductor substitutability by unprecedently involving the conjugated mode of the bound states in the continuum(conjugated-BIC)***,exploiting the conjugated-BIC photonics,which remains unexplored in conventional lasing studies,renders the broadband photodiodes with ultra-narrowband detection ability,detection wavelength tunability,and on-chip integration ability while ensuring the device *** based on these ultra-narrowband photodiode arrays exhibit high spectral resolution and wide/tunable spectral *** fabrication processes are compatible with solution-processable semiconductors photodiodes like perovskites and quantum dots,which can be potentially extended to conventional *** from the spectrometers directly constitute the incident spectra without being computation-intensive,latency-sensitive,and *** an example,the integrated spectrometers based on perovskite photodiodes are capable of realizing narrowband/broadband light reconstruction and in-situ hyperspectral imaging.

关键词： semiconductors process integration

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The Design of a K-Band 256-Element Reconfigurable Multi-Beam Phased-Array for SATCOM Application

The Design of a K-Band 256-Element Reconfigurable Multi-Beam...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Hong, Ru Tang, Xincheng Zhang, Liang Xiao, Hutao Qi, Xiaokang Xu, Zhiwei Zhejiang University Ocean College Institute of Marine Electronics and Intelligent Systems Zhoushan316000 China Information Technology Co. LTD Hangzhou310000 China

ISBN: (纸本)9798350355581

In this paper, we present a 256-element K-band (17.7-21.2GHz) phased array with 4 concurrent multi-beam, of which the polarization can be reconfigured as linear polarized, dual-polarized or circular polarized. With a stacked patch antenna unit designed of Rogers 4350B, the bandwidth of the phased array can reach 18% with VSWR © 2024 IEEE.

关键词： Bandwidth

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Acoustic based Machine Anomaly Detection using Beamforming and Sequential Transform Learning

Acoustic based Machine Anomaly Detection using Beamforming a...

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2023 IEEE Applied Sensing Conference, APSCON 2023

作者： Sahu, Saurabh Kumar, Kriti Majumdar, Angshul Kumar, A. Anil Chandra, M. Girish Tcs Research Embedded Devices and Intelligent Systems Bangalore India Indraprastha Institute of Information Technology Delhi New Delhi India

ISBN: (纸本)9781665461634

Acoustic-based analysis has been widely used for the maintenance and operation of industrial machines. However, interferences and background noise highly contaminate the observed acoustic signal. Here, we present a novel two-stage multi-channel source separation technique for improved separation and robust anomaly detection. Beamforming is applied in the first stage to provide separation at a coarser level. Sequential transform learning is employed in the second stage to learn the dynamics of the time-varying source signal for more refined source separation. The separated machine sounds are analyzed for anomaly using a simple template matching approach. Results obtained using MIMII dataset demonstrate the superior performance of the proposed method for source separation and anomaly detection compared to other state-of the-art techniques. © 2023 IEEE.

关键词： Source separation

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Development of Method of Generating a Reference Movement Speed of a Group of UAVs

Development of Method of Generating a Reference Movement Spe...

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2024 International Conference on Ocean Studies, ICOS 2024

作者： Gubankov, Anton Gornostaev, Igor Institute of Automation and Control Processes FEB RAS M.D. Ageev Institute of Marine Technology Problems Admiral G.I. Nevelskoy Maritime State University Robotics Laboratory Laboratory of Intelligent Information Systems for Marine Robots Laboratory of Marine Unmanned Aviation and Marine Aviation Systems Vladivostok Russia Institute of Automation and Control Processes FEB RAS M.D. Ageev Institute of Marine Technology Problems Admiral G.I. Nevelskoy Maritime State University Robotics Laboratory Laboratory of Robotic Systems Laboratory of Marine Unmanned Aviation and Marine Aviation Systems Vladivostok Russia

ISBN: (纸本)9798331532307

The article presents the results of the development of a method for the automatic formation of reference speeds for autonomous unmanned aerial vehicles of multirotor type, performing specified missions (such as monitoring of the sea and coastal territory in order to track populations of rare and endangered species, as well as evaluating the potential volumes of biological resources) singly or as part of a group (in formation). At the same time, the trajectories of these aircraft are set by smooth spatial curves - parametric splines of the third order, which makes it easy to adjust the specified trajectories during the mission. In order to maintain a high speed of movement of vehicles along trajectories with high accuracy of movement and saving formation, it is proposed to adjust the specified speed directly during the mission in such a way that the thrusters can ensure their required movements, taking into account the restrictions on the thrust vectors. At the same time, a simplified model of the dynamics of a quadcopter was used to calculate the values of reference speeds, taking into account the influence of wind force, environmental resistance, gravity and the total thrust vector of the propellers. The systems synthesized on the basis of this method can be implemented even on low-power onboard computing devices of unmanned aerial vehicles. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A novel myocarditis detection combining deep reinforcement learning and an improved differential evolution algorithm

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CAAI Transactions on Intelligence technology 2024年第6期9卷 1347-1360页

作者： Jing Yang Touseef Sadiq Jiale Xiong Muhammad Awais Uzair Aslam Bhatti Roohallah Alizadehsani Juan Manuel Gorriz Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia Centre for Artificial Intelligence Research(CAIR) Department of Information and Communication TechnologyUniversity of AgderGrimstadNorway Department of Creative Technologies Air UniversityIslamabadPakistan School of Information and Communication Engineering Hainan UniversityHaikouHainanChina Institute for Intelligent Systems Research and Innovation(IISRI) Deakin UniversityWaurn PondsVictoriaAustralia Data Science and Computational Intelligence Institute University of GranadaGranadaSpain

Myocarditis is a serious cardiovascular ailment that can lead to severe consequences if not promptly *** is triggered by viral infections and presents symptoms such as chest pain and heart *** detection is crucial for successful treatment,and cardiac magnetic resonance imaging(CMR)is a valuable tool for identifying this ***,the detection of myocarditis using CMR images can be challenging due to low contrast,variable noise,and the presence of multiple high CMR slices per *** overcome these challenges,the approach proposed incorporates advanced techniques such as convolutional neural networks(CNNs),an improved differential evolution(DE)algorithm for pre-training,and a reinforcement learning(RL)-based model for *** this method presented a significant challenge due to the imbalanced classification of the Z-Alizadeh Sani myocarditis dataset from Omid Hospital in *** address this,the training process is framed as a sequential decision-making process,where the agent receives higher rewards/penalties for correctly/incorrectly classifying the minority/majority ***,the authors suggest an enhanced DE algorithm to initiate the backpropagation(BP)process,overcoming the initialisation sensitivity issue of gradient-based methods like back-propagation during the training *** effectiveness of the proposed model in diagnosing myocarditis is demonstrated through experimental results based on standard performance ***,this method shows promise in expediting the triage of CMR images for automatic screening,facilitating early detection and successful treatment of myocarditis.

关键词： classification differential evolution myocarditis reinforcement learning

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Graph Assisted Unsupervised Domain Adaptation for Machine Fault Diagnosis 31

Graph Assisted Unsupervised Domain Adaptation for Machine Fa...

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31st European Signal Processing Conference, EUSIPCO 2023

作者： Pattnaik, Naibedya Kumar, Kriti Kumar, A. Anil Chandra, M. Girish Embedded Devices and Intelligent Systems TCS Research Bangalore India Indraprastha Institute of Information Technology Delhi New Delhi India

ISBN: (纸本)9789464593600

Domain adaptation has emerged as a useful technology that leverages the knowledge learned from labeled data in the source domain to build an effective classifier for the target domain, given that the source and target data have different underlying distributions. Most of the existing techniques aim to address the marginal distribution discrepancy alone, ignoring the conditional distribution divergence that may exist between the two domains. In order to achieve good adaptation performance, both the marginal and conditional distribution of the source and target data need to be aligned. The problem becomes challenging when the data is limited, and no labels are available for the target domain data. To address this scenario, in this paper, we propose a novel formulation that utilizes the concepts of Class-wise Maximum Mean Discrepancy and label propagation over the graph for unsupervised domain adaptation. We have applied it to the challenging scenario of adaptation between physically different but related machines for fault diagnosis. Two publicly available bearing fault datasets have been employed for performance evaluation. The experimental results indicate the superior performance of the proposed method compared to the state-of-the-art methods showing efficient transfer learning capabilities for machine fault diagnosis. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Failure analysis

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ADL-VTON: Advanced Deep Learning Virtual Try-On Technique 7

ADL-VTON: Advanced Deep Learning Virtual Try-On Technique

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7th International Conference on Image information Processing, ICIIP 2023

作者： Tajinder Sharma, Sahil International Institute of Information Technology Bangalore India Ulster University School of Computing Engineering And Intelligent Systems Londonderry United Kingdom

ISBN: (数字)9798350371406

ISBN: (纸本)9798350371406

The objective of Image-based Virtual Try-On (VTO) is to effectively superimpose retail clothing items onto a specific individual, creating a seamless integration between the garments and the person. Despite significant advancements in VTO (Virtual Try-On) technology, numerous techniques struggle to maintain semantic integrity, particularly when faced with difficult inputs like complicated human poses and complex clothing designs. The presence of these discrepancies undermines the overall quality of the final visual outputs, hence reducing both the user experience and the effectiveness of the Virtual Try-On (VTO) system. This study provides an in-depth investigation into the enduring problem by utilizing advanced deep learning techniques. In addition to just recognizing the obstacles, this study emphasizes a thorough comprehension derived from extensive literature reviews and practical code experiments. We aim to tackle the significant issue of preserving semantic detail in VTO applications by implementing cutting-edge techniques. This article adopts a future-oriented approach to not only illuminate current constraints but also provide a trajectory for forthcoming initiatives that seek to enhance the virtual retail domain and fully actualize the capabilities of AI-driven fashion technology. © 2023 IEEE.

关键词： Computer vision

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Dynamic Control Framework for Automated Particle Transport Based on Optically Induced Dielectrophoresis

Dynamic Control Framework for Automated Particle Transport B...

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2022 IEEE International Conference on Real-Time Computing and robotics, RCAR 2022

作者： Liu, Jiaxin Wang, Huaping Shi, Qing Dong, Xinyi Lin, Kaijun Sun, Tao Huang, Qiang Fukuda, Toshio Intelligent Robotics Institute Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beijing Institute of Technology Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

As a high-Throughput and highly flexible technique, optically induced dielectrophoresis (ODEP) is one of the most promising micromanipulation techniques applied for biomedical studies. However, most ODEP-based manipulation methods have not been explored deeply in terms of accurate control under unstructured environments with multiple interference. This paper reports a dynamic control framework for automatically transporting single particle to goal position in a complex environment with an optically induced dielectrophoresis platform. The POMDP-based path planner periodically provides the optimal motion strategy based on the real-Time environmental information and current position of the particle to avoid collisions with randomly moving obstacles. The optimal motion strategies are smoothly expanded to short-distance trajectories, which are dynamically followed by the target particle with proxy-based sliding mode control (PSMC) closed-loop controller. Experimental results indicated that compared with traditional controllers such as PID, our control method possesses higher accuracy and stability in path following. In addition, the performance of the path planner was demonstrated by transporting a NIH/3T3 cell to the desired position within a relatively crowded environment. © 2022 IEEE.

关键词： Controllers

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Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

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Petroleum Science 2024年第1期21卷 641-653页

作者： Yun-Peng He Hai-Bo Cheng Peng Zeng Chuan-Zhi Zang Qing-Wei Dong Guang-Xi Wan Xiao-Ting Dong State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016LiaoningChina Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016LiaoningChina Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169LiaoningChina University of Chinese Academy of Sciences Beijing100049China School of Artifcial Intelligence Shenyang University of TechnologyShenyang 110870LiaoningChina

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well *** learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis ***,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational ***,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different ***,there is heterogeneity in field data,which can dramatically impair the diagnostic *** solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this ***,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC ***,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data ***,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the *** on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational *** the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

关键词： Sucker-rod pumping system Dynamometer card Working condition recognition Deep learning Time-frequency signature Time-frequency signature matrix

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Adaptive Temporal Attention with Key-frame Loss for Speech Emotion Recognition 5

Adaptive Temporal Attention with Key-frame Loss for Speech E...

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5th International Seminar on Artificial Intelligence, Networking and information technology, AINIT 2024

作者： Chen, Jing Wang, Kejun Xu, Tao School of Information Engineering Jiaxing Nanhu University Jiaxing China School of Information Technology Beijing Institute of Technology Zhuhai Zhuhai China College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9798350385557

Speech emotion recognition has received growing attention to improving the user-friendly experience, but it is still a difficult challenge. That is mainly due to the problem of uneven distribution of emotional information in speech samples. The overall state label of a sample is not sufficient to fully describe each part of the sample. In other words, each part contributes differently to the overall recognition. In this paper, we build unidirectional and bidirectional temporal attention networks to enhance the ability to extract essential features, and build the key-frame loss function to make the attention weight closer to 0 and 1. The purpose of using the attention module and key-frame loss is to extract the information that is effective for classification and filter out the unimportant information. A large number of experiments were conducted on the IEMOCAP dataset to verify the effectiveness of the model and loss function. The experimental results show that under the combined effect of the attention model and the loss function, our method has achieved better performance than the existing methods, with a weighted accuracy of 59.15% and an unweighted accuracy of 60.87%. © 2024 IEEE.

关键词： Classification (of information)

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