检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Liu, Xuanwu Li, Zhao Zhang, Jiarun Li, Ming Ren, Guoqi Huang, Jiaming Zhang, Ji Hangzhou Yugu Technology Co. Ltd. Hangzhou China Key Laboratory of Intelligent Education Technology Application of Zhejiang Province Zhejiang Normal University Jinhua China School of Mathematics Physics and Computing University of Southern Queensland Toowoomba Australia

The food delivery industry has undergone significant growth in recent years, providing a large number of jobs globally through on-demand delivery services. In densely populated areas, such as major cities in China, food delivery workers prefer electric bicycles over cars to achieve the highest delivery efficiency while minimizing their costs. However, battery volume limitations force riders to charge the batteries during work to fulfill their work intensity, which often results in wasted time and mileage as riders travel back home for a battery swap or recharge. To address this issue, we have proposed the Battery-swap System as an On-demand delivery service (BaaS), an intelligent IoT-based charging and swapping system that integrates end-cloud collaboration, safety detection, and energy consumption management technologies. BaaS enables efficient battery swapping services to replace battery charging, enabling riders to swap depleted batteries at convenient locations, thereby reducing the time and mileage wasted on traveling home for recharging. Our BaaS has been implemented in over 50 major cities in China, serving almost a million customers, and saving about 15 million kWh of electricity, while reducing approximately 0.7 billion invalid mileage. Despite BaaS’s positive impact on the environment and society, there is a lack of methods and metrics to measure its effect. Therefore, in this paper, we propose a Valid Distance Estimation Model (VDEM) to measure the environmental and social impact of BaaS based only on the daily user logs of BaaS. VDEM collects daily usage logs from our cloud center, processes the user logs to create a new database, and uses two hypotheses to estimate the impact of BaaS based on invalid mileages and order numbers. We further design experiments to demonstrate the effectiveness of BaaS. The results indicate that BaaS prevents delivery riders from losing approximately 40% of orders, demonstrating its significant potential in fields such as en

关键词： Internet of things

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Automatic Recognition of Noisy Code-39 Barcode

Automatic Recognition of Noisy Code-39 Barcode

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International Conference on Artificial Reality and Telexistence (ICAT)

作者： Xianyong Fang Fuli Wu Bin Luo Haifeng Zhao Peng Wang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China College of Information Engineering Zhejiang University of Technology China Motorola China Electronics Limited Corporation China

Barcode has been widely applied in the modern world. This paper presents a fast and robust recognition method of noisy code 39 barcode. The proposed method can be divided into two steps: search and decoding. In the first step, all asterisks in the image are found with evenly defined scan lines and then those with the same directions are matched together to get a valid barcode region. In the second step, a local denoise method is first applied to eliminate noise in the barcode region and then a middle band filter is used to decode the barcode. Our method is simple in comparison with former methods and experimental results show that it is efficient for fast barcode recognition on noisy images.

关键词： Decoding Bars Image edge detection Robustness Equations Low pass filters Signal processing Educational institutions Educational technology Image recognition

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Interactive wearable digital devices for blind and partially sighted people

Nature Reviews Electrical Engineering

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Nature Reviews Electrical Engineering 2025年 1-15页

作者： Wenhao Xue ( Tianfang Zhang ( Xiaonan Dong ( Xuezhi Ma ( Heng Xu ( Jiaqing Zhao ( Yuan Ma ( Department of Mechanical Engineering and Research Institute for Intelligent Wearable Systems The Hong Kong Polytechnic University Hong Kong S.A.R China Department of Rehabilitation Medicine First Affiliated Hospital College of Medicine Zhejiang University Hangzhou China Technology Innovation Center Zhe Jiang Key Laboratory of Intelligent Rehabilitation and Translational Neuroelectronics Hangzhou China Life and Health Institute China Resources Research Institute of Science and Technology Company Ltd Hong Kong S.A.R. China School of Biomedical Sciences LKS Faculty of Medicine The University of Hong Kong Hong Kong S.A.R. China A*STAR Quantum Innovation Centre (Q. InC) Agency for Science Technology and Research Singapore Singapore Institute of Materials Research and Engineering Agency for Science Technology and Research Singapore Singapore Department of Haptic Intelligence CVTE Guangzhou Shiyuan Electronics Company Ltd Guangzhou China Institute of Nuclear and New Energy Technology Tsinghua University Beijing China Research Center for Green and Smart Manufacturing PolyU-Daya Bay Technology and Innovation Research Institute Huizhou China

Digital information has permeated all aspects of life, and diverse forms of information exert a profound influence on social interactions and cognitive perceptions. In contrast to the flourishing of digital interaction devices for sighted users, the needs of blind and partially sighted users for digital interaction devices have not been adequately addressed. Current assistive devices often cause frustration in blind and partially sighted users owing to the limited efficiency and reliability of information delivery and the high cognitive load associated with their use. The expected rise in the prevalence of blindness and visual impairment due to global population ageing drives an urgent need for assistive devices that can deliver information effectively and non-visually, and thereby overcome the challenges faced by this community. This Perspective presents three potential directions in assistive device design: multisensory learning and integration; gestural interaction control; and the synchronization of tactile feedback with large-scale visual language models. Future trends in assistive devices for use by blind and partially sighted people are also explored, focusing on metrics for text delivery efficiency and the enhancement of image content delivery. Such devices promise to greatly enrich the lives of blind and partially sighted individuals in the digital age.

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Quantum state and process tomography via adaptive measurements

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Science China(Physics,Mechanics & Astronomy) 2016年第10期59卷 25-32页

作者： HengYan Wang WenQiang Zheng NengKun Yu KeRen Li DaWei Lu Tao Xin Carson Li ZhengFeng Ji David Kribs Bei Zeng XinHua Peng JiangFeng Du Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of ChinaHefei 230026China Department of Applied Physics Zhejiang University of TechnologyHangzhou 310023China Institute for Quantum Computing University of WaterlooWaterloo N2L 3G1Canada 4Department of Mathematics&Statistics University of GuelphGuelph N1G 2W1Canada Centre for Quantum Computation&Intelligent Systems Faculty of Engineering and Information TechnologyUniversity of Technology SydneySydney NSW 2007Australia State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics Tsinghua UniversityBeijing 100084China Department of Physics University of GuelphGuelph N1G 2W1Canada State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China Canadian Institute for Advanced Research Toronto M5G 1Z8Canada

We investigate quantum state tomography(QST) for pure states and quantum process tomography(QPT) for unitary channels via adaptive measurements. For a quantum system with a d-dimensional Hilbert space, we first propose an adaptive protocol where only 2d. 1 measurement outcomes are used to accomplish the QST for all pure states. This idea is then extended to study QPT for unitary channels, where an adaptive unitary process tomography(AUPT) protocol of d2+d.1measurement outcomes is constructed for any unitary channel. We experimentally implement the AUPT protocol in a 2-qubit nuclear magnetic resonance system. We examine the performance of the AUPT protocol when applied to Hadamard gate, T gate(/8 phase gate), and controlled-NOT gate,respectively, as these gates form the universal gate set for quantum information processing purpose. As a comparison, standard QPT is also implemented for each gate. Our experimental results show that the AUPT protocol that reconstructing unitary channels via adaptive measurements significantly reduce the number of experiments required by standard QPT without considerable loss of fidelity.

关键词： quantum tomography state reconstruction nuclear magnetic resonance

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Shock-induced HCNH+ abundance enhancement in the heart of the starburst galaxy NGC 253 unveiled by ALCHEMI

arXiv

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arXiv 2025年

作者： Gong, Y. Henkel, C. Bop, C.T. Mangum, J.G. Behrens, E. Du, F.J. Zhang, S.B. Martin, S. Menten, K.M. Harada, N. Bouvier, M. Tang, X.D. Tanaka, K. Viti, S. Yan, Y.T. Yang, W. Mao, R.Q. Quan, D.H. Purple Mountain Observatory Key Laboratory of Radio Astronomy Chinese Academy of Sciences 10 Yuanhua Road Nanjing210023 China Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Xinjiang Astronomical Observatory Chinese Academy of Sciences Urumqi830011 China - UMR 6251 RennesF-35000 France Nantes Université CNRS CEISAM UMR 6230 NantesF-44000 France National Radio Astronomy Observatory 520 Edgemont Road CharlottesvilleVA22903-2475 United States Department of Astronomy University of Virginia P. O. Box 400325 530 McCormick Road CharlottesvilleVA22904-4325 United States European Southern Observatory Alonso de Córdova 3107 Vitacura Santiago763-0355 Chile Joint ALMA Observatory Alonso de Córdova 3107 Vitacura Santiago763-0355 Chile National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Institute of Astronomy and Astrophysics Academia Sinica 11F of AS/NTU Astronomy-Mathematics Building No.1 Sec. 4 Roosevelt Road Taipei10617 Taiwan 2-21-1 Osawa Mitaka Tokyo181-1855 Japan Leiden Observatory Leiden University PO Box 9513 Leiden2300 RA Netherlands Key Laboratory of Radio Astronomy Chinese Academy of Sciences Urumqi830011 China Department of Physics Faculty of Science and Technology Keio University 3-14-1 Hiyoshi Kanagawa Yokohama223-8522 Japan School of Astronomy & Space Science Nanjing University 163 Xianlin Avenue Nanjing210023 China Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China

Context. Understanding the chemistry of molecular clouds is pivotal to elucidate star formation and galaxy evolution. As one of the important molecular ions, HCNH+ plays an important role in this chemistry. Yet, its behavior and significance under extreme conditions, such as in the central molecular zones (CMZs) of external galaxies, are still largely unexplored. Aims. We aim to reveal the physical and chemical properties of the CMZ in the starburst galaxy NGC 253 with multiple HCNH+ transitions to shed light on the molecule’s behavior under the extreme physical conditions of a starburst. Methods. We employ molecular line data including results for four rotational transitions of HCNH+ from the ALMA Comprehensive High-resolution Extragalactic Molecular Inventory (ALCHEMI) large program to investigate underlying physical and chemical processes. Results. Despite weak intensities, HCNH+ emission is widespread throughout NGC 253’s CMZ, which suggests that this molecular ion can effectively trace large-scale structures within molecular clouds. Using the quantum mechanical coupled states approximation, we computed rate coefficients for collisions of HCNH+ with para-H2 and ortho-H2 at kinetic temperatures up to 500 K. Using these coefficients in a non-LTE modeling framework and employing a Monte Carlo Markov chain analysis, we find that HCNH+ emission originates from regions with H2 number densities of ∼ 102.80 − 103.55 cm−3, establishing HCNH+ as a tracer of low-density environments. Our analysis reveals that most of the HCNH+ abundances in the CMZ of NGC 253 are higher than all reported values in the Milky Way. We performed static, photodissociation region (PDR), and shock modeling, and found that recurrent shocks could potentially account for the elevated HCNH+ abundances observed in this CMZ. Conclusions. We propose that the unexpectedly high HCNH+ abundances may result from chemical enhancement, primarily driven by the elevated gas temperatures and cosmic ray ionizatio

关键词： Cosmic rays

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Organic-inorganic hybrid piezotronic bipolar junction transistor for pressure sensing

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Microsystems & Nanoengineering 2024年第3期10卷 229-244页

作者： Emad Iranmanesh Zihao Liang Weiwei Li Congwei Liao Shunyu Jin Chuan Liu Kai Wang Shengdong Zhang Charalampos Doumanidis Gehan A.J.Amaratunga Hang Zhou Guangdong Provincial Key Laboratory of In-Memory Computing Chips School of Electronic and Computer EngineeringPeking University Shenzhen Graduate SchoolShenzhen 518055P.R.China School of Mechanical Engineering Guangdong Technion-Israel Institute of TechnologyShantou 515063P.R.China State Key Laboratory of Microelectronics Device and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029P.R.China Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 23000PR China School of Electronics and Information Technology Sun Yat-sen UniversityNo.132 East Waihuan RoadGuangzhou 510006P.R.China Department of Mechanical Aerospaceand Biomedical EngineeringUniversity of South AlabamaShelby Hall3128MobileAL 36688USA Electrical Engineering Division Department of EngineeringUniversity of Cambridge9 JJ Thomson AvenueCambridge CB30FAUnited Kingdom Zhejiang University International CampusHainingChina

With the rapid development of the Internet of Things(IoTs),wearable sensors are playing an increasingly important role in daily monitoring of personal health and *** signal-to-noise-ratio has become the most critical performance factor to *** enhance it,on the one hand,good sensing materials/devices have been employed;on the other hand,signal amplification and noise reduction circuits have been ***,most of these devices and circuits work in an active sampling mode,requiring frequent data acquisition and hence,entailing high-power *** this scenario,a flexible and wearable event-triggered sensor with embedded signal amplification without an external power supply is of great ***,we report a flexible two-terminal piezotronic n-p-n bipolar junction transistor(PBJT)that acts as an autonomous and highly sensitive,current-and/or voltage-mediated pressure *** PBJT is formed by two back-to-back piezotronic diodes which are defined as emitter-base and collectorbase *** force exertion on the emitter side,as a result of the piezoelectric effect,the emitter-base diode is forward biased while the collector-base diode is reverse *** to the inherent BJT amplification effect,the PBJT achieves record-high sensitivities of 139.7 kPa^(-1)(current-based)and 88.66 kPa^(-1)(voltage-based)in sensing *** PBJT also has a fast response time of<110 ms under exertion of dynamic stimuli ranging from a flying butterfly to a gentle finger ***,the PBJT advances the state of the art not only in terms of sensitivity but also in regard to being self-driven and autonomous,making it promising for pressure sensing and other IoT applications.

关键词： bipolar transistor IoT

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Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting

arXiv

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arXiv 2024年

作者： Zhuo, Linhai Wang, Zheng Qian, Tianwen Fu, Yuqian College of Computer and Data Science Fuzhou University Fuzhou China Zhejiang University of Technology College of Computer Science Zhejiang China Key Laboratory of Data Science and Intelligent Computing Hangzhou International Innovation Institute Beihang University Zhejiang China INSAIT Sofia University Bulgaria

The source-free cross-domain few-shot learning (CD-FSL) task aims to transfer pretrained models to target domains utilizing minimal samples, eliminating the need for source domain data. Addressing this issue requires models to have robust generalization abilities and strong feature representation, aligning with the characteristics of large-scale pretrained models. However, large-scale models tend to lose representational ability in cross-domain scenarios due to limited sample diversity. Given the abundant diversity provided by semantic modality, this paper utilize prompt as "free lunch" to enhance the diversity and leverages textual modality to guide the prompt generating. Specifically, we propose the SeGD-VPT framework, which is divided into two phases. The first step aims to increase feature diversity by adding diversity prompts to each support sample, thereby generating varying input and enhancing sample diversity. Furthermore, we use diversity descriptions of classes to guide semantically meaningful learning of diversity prompts, proposing random combinations and selections of texts to increase textual diversity. Additionally, deep prompt tuning is introduced to enhance the model's transfer capability. After training of the first step, support samples with different diversity prompts are input into the CLIP backbone to generate enhanced features. After generation, the second phase trains classifiers using the generated features. Extensive experimental results across several benchmarks verify our method is comparable to SOTA source-utilized models and attain the best performance under the source-free CD-FSL setting. Copyright © 2024, The Authors. All rights reserved.

关键词： Zero-shot learning

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Ru Li Aimin Li Rong Fei Xie Guo Fang-Xiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions.

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Prediction of exosomal piRNAs based on deep learning for sequence embedding with attention mechanism

Prediction of exosomal piRNAs based on deep learning for seq...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Yulian Ding Aimin Li Rong Fei Xie Guo Fangxiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

PIWI-interacting RNAs (piRNAs) are a type of small non-coding RNAs which bind with the PIWI proteins to exert biological effects in various regulatory mechanisms. A growing amount of evidence reveals that exosomal piRNAs are potential biomarkers for diagnosis and treatment of complex diseases. Effective methods for the prediction of exosomal piRNAs are the foundation of piRNA functional research. In this study, we propose an end-to-end deep network for identifying exosomal piRNAs based on features learned from natural language processing (NLP) models for sequence embedding with attention mechanism. First, a benchmark dataset is constructed by processing piRNA subcellular localization annotated data and sequence data. Moreover, bagging positive unlabeled learning is applied to get the reliable negative set. Finally, we treat a piRNA sequence as a sentence and its k-mer subsequence as a token. Sequence embedding models with self-attention mechanism is designed to extract features from exosome piRNA sequences, which are used for the prediction task. Compared with three competing methods, our model achieves the best performance and reveals the key factors of exosomal piRNA sequences by the attention mechanism. Our model characterizes exosomal piRNAs and could be beneficial for researchers to investigate exosomal piRNAs’ functions.

关键词： Proteins Location awareness RNA Biological system modeling Predictive models Feature extraction Natural language processing

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VOLUMETRIC MESHFREE FRAMEWORK FOR JOINT SEGMENTATION AND MOTION TRACKING OF THE LEFT VENTRICLE

VOLUMETRIC MESHFREE FRAMEWORK FOR JOINT SEGMENTATION AND MOT...

引用

IEEE International Symposium on biomedical Imaging

作者： Ling Zhuang Huafeng Liu Hujun Bao Pengcheng Shi State Key Laboratory of CAD & CG University of Zhejiang Hangzhou China Medical Image Computing Group Hong Kong University of Science and Technology Hong Kong China State Key Laboratory of Modern Optical Instrumentation University of Zhejiang Hangzhou China School of Biomedical Engineering Southern Medical University Guangzhou China

ISBN: (纸本)9781424406715;1424406714

Meshfree particle method (MPM) exhibits improved flexibility and accuracy in dealing with problems with large deformation, complex geometry and material discontinuities. In this paper, we present a MPM based framework for the simultaneous shape recovery and motion tracking of the left ventricle. The myocardium is modeled as an anisotropic elastic body accounting for the fiber directions, represented by sampling nodes bounded by endocardial and epicardial boundaries. Cardiac dynamics is then driven by external force constructed individually for each node through integration of measures of image edgeness, image derived salient feature coherence, prior tissue distribution model, and temporal motion model. The displacement field throughout the cardiac cycle is obtained when the total energy of the elastic body is minimized to reach equilibrium state. Experiments with 3D canine MR images illustrate the benefits and potentials of such effort.

关键词： Myocardium Shape Anisotropic magnetoresistance Image segmentation Computer vision Particle tracking biomedical imaging Joining materials Image sampling Force measurement

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