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检索条件"任意字段=Conference on Advances in Optical Data Storage Technology"

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ReRAM Crossbar-Based Analog Computing Architecture for Naive Bayesian Engine

ReRAM Crossbar-Based Analog Computing Architecture for Naive...

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IEEE International conference on Computer Design: VLSI in Computers and Processors, (ICCD)

作者： Bing Wu Dan Feng Wei Tong Jingning Liu Chengning Wang Wei Zhao Mengye Peng Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology (School of Computer Science and Technology Huazhong University of Science and Technology) Ministry of Education of China

Recent advances in Resistive RAM (ReRAM) have explored the in-situ Matrix-Vector Multiplication (MVM) ability of crossbar arrays to achieve high energy-efficiency Process-In-Memory (PIM) architectures for Convolutional Neural Network (CNN), image processing, and so on. However, the existing ReRAM-based PIM architectures suffer from considerable additional auxiliary logic and device variations. In this work, we propose a novel analog computing architecture NB Engine for classification by implementing Naive Bayesian (NB) algorithm on ReRAM crossbar arrays. The two key steps of the NB algorithm, that is, probability calculation and electing the class that has the highest probability, are elaborately accomplished in our architecture. The ReRAM arrays are both used as storage and computation components. We store the pre-calculated prior probabilities and conditional probabilities of every class in crossbar arrays. Then the probability calculation step is completed in parallel through the MVM operation of the array. In general, the election step is a multiple-comparison procedure and is normally implemented by a comparison tree. Here, we reuse the max pooling module in a conventional CNN PIM architecture to realize a compatible comparison logic. However, neither of the two designs can avoid the overhead of costly high bit-precision Analog-to-Digital Converters (ADCs). So we introduce a novel analog parallel comparison design which does not need any ADCs or other computing logic with better energy-saving and area-efficiency. Our proposed NB Engine is tested by 11 various datasets. The influence of several non-ideal device properties is discussed and the NB Engine exhibits great tolerance to these variations. The experiment results show that our design offers a runtime speedup up to 2289.6x compared with the software-implemented NB classifier with negligible accuracy loss. In addition, the NB Engine saves 96.2% energy consumption and 45.2% array area compared with the CNN P

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Heat Assisted Magnetic Recording – Next Generation Mass storage technology.

Heat Assisted Magnetic Recording – Next Generation Mass Sto...

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International conference on Magnetics (INTERMAG)

作者： G. Ju J. Thiele Y. Peng T. Klemmer Y. Ding Y. Kubota A.Q. Wu X. Zhu E.K. Chang L. Gao F. Zavaliche P. Huang H. Amini S.D. Granz C.J. Rea J. Qiu H. Yin M.A. Seigler T. Rausch Y. Chen E. Gage S. Hwang M.E. Re Seagate Technology Fremont CA United States Seagate Technology Shakopee MN United States Seagate Technology Bloomington MN United States

Magnetic hard disk drives (HDDs) store over 90% of the world's digital data enabling the internet and economical access to data to power everything from social media to self-driving cars. Heat assisted magnetic recording (HAMR) is being developed as the next recording system for HDDs. HAMR will bring profound changes to the HDD components and architecture, incorporating laser diodes in an innovative plasmonic light delivery system into the recording heads, and novel nano-magnetic materials and layer architectures in the recording media [1]. Seagate demonstrated the promise of HAMR with a 1 -2 Tb/in 2 areal density demonstration [2, 3] and the subsequent demonstration of a fully functional drive with more than 1000 write power-on hours [4, 5]. The significant progresses have been enabled by breakthroughs in media and head technology together with drive integration. With continuing development efforts in reliability and data density HAMR will serve the demand for economical hard disk drive storage solutions for the world's ever growing data. As announced in a recent blog, Seagate is now shipping HAMR units to select customers for integration tests, and will start shipping commercial HAMR products to key customers by the end of 2018 [6]. This paper will cover the key enablers for HAMR technology to support both high areal density and linear density, which will be critical for bringing a new “S” curve for the magnetic recording industry. It will also be discussed about the challenges and breakthroughs in fundamental magnetic properties for the recording layer and near field optical transducers, to support the extension of HAMR to around 4-5 Tbit/in 2 .

关键词： Magnetics conferences

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Exploring Diabetic Retinopathy Diagnosis: Insights from a Comprehensive Literature Review and Initial Fundus Image Analysis

Exploring Diabetic Retinopathy Diagnosis: Insights from a Co...

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Electrical Electronics and Computing Technologies (ICEECT), International conference on

作者： K Uday Kumar Reddy M Malleswari P Phanindra Kumar Reddy Shaik Karimullah Fahimuddin Shaik Peddapullaiahgari Hariobulesu Artificial Intelligence and Data Science Department Annamacharya University Rajampet Computer Science and Engineering Department Sri Annamacharya Institute of Technology and Sciences AI&DS Department Annamacharya University Rajampet ECE Department Annamacharya University Rajampet

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

This article looks at recent advances in diabetic retinopathy (DR) detection with retinal fundus and optical coherence tomography angiography (OCTA) pictures. Key studies have investigated a variety of methods, including combining Multiscale Retinex with Chromaticity Preservation (MSRCP) and Bi-LSTM networks for high accuracy, integrating the Internet of Things (IoT) with deep learning for increased sensitivity, and using Multi-Stream Deep Neural Networks to classify DR severity. Innovations like the PMNPDR system for microaneurysm detection and deep learning ensembles for OCT images have also performed well. Despite these gains, issues like as data transfer latency, model complexity, and reliance on tiny datasets remain. Overall, while current models show great potential, they require further modification and validation to assure their efficacy and applicability in clinical situations.

关键词： Deep learning Diabetic retinopathy Technological innovation Accuracy Sensitivity Retina data transfer data models Complexity theory Internet of Things

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Features of the implementation of software package for circuits hierarchical clustering

Features of the implementation of software package for circu...

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International conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science

作者： R. Bazylevych I. Podolskyy Institute of Computer Science and Information Technologies Lviv Polytechnic National University Lviv Ukraine

The high-speed implementation of the algorithm of hierarchical clustering for very large-scale circuits is considered in this issue. It proposes effective date structures and program implementation with optimal utiliz... 详细信息

关键词： Software packages Circuits Clustering algorithms Large-scale systems Merging data structures optical character recognition software Very large scale integration Computer science Information technology

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The advances in the Carbon Source/Sink Researches of Typical Grassland Ecosystem in China

The Advances in the Carbon Source/Sink Researches of Typical...

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2011 3rd International conference on Environmental Science and Information Application technology(ESIAT 2011)

作者： Chengcheng GANG Jie ZHANG Jianlong LI College of Life Science Nanjing University

With the deepening research of global change, studies of carbon cycle of grassland ecosystem, one of the widely distributed vegetation type, is of great significance in estimating global carbon cycle. Grassland degradation and desertification caused by human activities(such as land reclamation and grazing etc) is becoming increasingly serious in our country, so it is urgency to study the effects of human on grassland soil carbon. Under the condition of increasing measuring precision and region density, it is superior to use remote sensing in grassland carbon storage measurement through acquisition and inversion vegetation information and related biophysics parameters, it is possible to monitor the space distribution of grassland carbon-fixed amount in large range and multi-scale timely and accurately. In this paper, the importance of carbon cycle of grassland ecosystem was discussed, and researches on carbon cycle of grassland ecosystem in China was summarized and analysed, including the three carbon pools(plants carbon pool, litterfall carbon pool and soil carbon pool), effects of natural or human activities on carbon storage and methods to estimate the carbon storage. Additionally, based on the principal of grass growth, together with analysis of various global ecosystem NPP estimation methods, we put forward a novel thought to establish an carbon estimation model and testify its accuracy with meteorological data and field observation data such as grassland biomass, NPP, net ecological productivity(NEP) etc, which is much more suitable for carbon source/sink estimation of grassland ecosystem in China. At last, the existing problems and prospects of carbon source/sink researches of main grassland in China were discussed.

关键词： grassland ecosystem carbon source/sink carbon pools grassland classification integrated data method

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Early Retinal Degeneration Detection with Deep Faster CNNs

Early Retinal Degeneration Detection with Deep Faster CNNs

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International conference on advances in Information technology (ICAIT)

作者： K. Priyadharshini Sindhusaranya Balraj JV Rama Kumar Deepak A. Vidhate Thilakavathy. P P. Vanathi Department of Computing Technologies School of Computing SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering Sona College of Technonolgy Salem India Computer Science and Engineering SRKR Engineering College Bhimavaram Andhra Pradesh Department of Information Technology Dr. Vithalrao Vikhe Patil College of Engineering Ahmednagar Maharashtra Computer science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai Department of Information Technology Adhiyamaan College of Engineering Hosur

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

The issue of retinogenesis probably constitutes a major public health threat which gives the reason to carry out its early detection for intervention purposes to be efficient. Throughout this investigation, we suggest a new technique which uses the faster CNNs for early detection of retina degradation. We set up a diverse data collection where OCT(optical coherence tomography), fundus photography and angiography modality were included. This collection covered the various stages of degeneration. The dataset was prepared for instance with resizing, normalizing, and data augmentation were used to improve share quality and diversity. Deeper and faster networks that were developed and trained using the backpropagation technique performed well and further optimized using Adam, with high accuracy of 94 in the test dataset. 7%. The strength of our results can be seen through evaluation metrics in detail like confusion matrices and classification reports. The model can distinguish various cases of retinal degeneration accurately which proves to have high precision and recall for mild and normal degeneration. Interpolation analysis of the model using Grad-CAM and occlusion sensitivity, giving the clue about the model's decision making process, setting a precedent for clinical interpretation. The enhanced cross-validated model on an independent dataset also arrays the model in a representational where it will be able to generalize in a diverse population and in different imaging conditions. The systematic approach which proved to be more accurate and resilient than the other techniques was the one which was compared to the mentioned ones. In conclusion, our study shows the possibility for application of the Deep Faster CNNs in identifying the early signs of retinal degeneration; the tool therefore becomes an important tool for enhancing patient outcomes and prevention of vision loss in the world at large.

关键词： Training Analytical models Technological innovation Accuracy Systematics Coherence Tomography Retina data models Diseases

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Fast Polygons Proximity Detection for ICs Multiple Patterning Lithography

Fast Polygons Proximity Detection for ICs Multiple Patternin...

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IEEE NW Russia Young Researchers in Electrical and Electronic Engineering conference (EIConRusNW)

作者： Dmitry A. Bulakh Andrey V. Korshunov Vladimir A. Bespalov National Research University of Electronic Technology Zelenograd Moscow Russia

ISBN: (数字)9781665404761

ISBN: (纸本)9781665446426

Multiple Patterning Lithography (MPL) is one of the main solutions to manufacture ICs with scale less than 32 nm using 193nm optical lithography. This approach is based on layout decomposition according to the topology of IC layout geometries. The main difficulty for its application is the huge amount of calculations aimed to determine proximity of IC layout polygons. In this article a new approach to minimize the amount of calculations during proximity evaluation is proposed. It is based on implementation of special data structure for storing the geometries of an IC with the sparse matrices storage format used to minimize the memory usage. Experimental results show that proposed approach gives an advantage in terms of memory usage and evaluation speed. Funding: the reported study was funded by RFBR, project number 20-07-00556.

关键词： Integrated circuits Geometry Lithography Layout data structures Topology Task analysis

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Improving the Table Boundary Detection in PDFs by Fixing the Sequence Error of the Sparse Lines

Improving the Table Boundary Detection in PDFs by Fixing the...

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International conference on Document Analysis and Recognition

作者： Ying Liu Kun Bai Prasenjit Mitra C. Lee Giles College of Information Sciences and Technology Pennsylvania State University University Park PA USA

ISBN: (纸本)9781424445004

As the rapid growth of PDF documents, recognizing the document structure and components are useful for document storage, classification and retrieval. Table, a ubiquitous document component, becomes an important information source. Accurately detecting the table boundary plays a crucial role for many applications, e.g., the increasing demand on the table data search. Rather than converting PDFs to image or HTML and then processing with other techniques (e.g., OCR), extracting and analyzing texts from PDFs directly is easy and accurate. However, text extraction tools face a common problem: text sequence error. In this paper, we propose two algorithms to recover the sequence of extracted sparse lines, which improve the table content collection. The experimental results show the comparison of the performance of both algorithms, and demonstrate the effectiveness of text sequence recovering for the table boundary detection.

关键词： data mining Information analysis Image converters HTML optical character recognition software Image analysis Filtering Text analysis Computer errors Educational institutions

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Capacity Planning of Distributed Photovoltaic Generation and Energy storage Systems for the Traction Power Supply System of Electric Railway

Capacity Planning of Distributed Photovoltaic Generation and...

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IEEE International conference on Energy Internet (ICEI)

作者： Li Huang Ying Wang Weizhi Liu Yingtao Ma Shenglin Li School of Electrical Engineering Beijing Jiaotong University Beijing China Beijing Zongheng Electromechanical Technology Co. Ltd. State Key Laboratory for Traction and Control System of EMU and Locomotive China Academy of Railway Sciences Corporation Limited Beijing China School of Electronic Information and Electrical Engineering Shanghai Jiaotong University Shanghai China

ISBN: (数字)9798331523558

ISBN: (纸本)9798331523565

Although the current power industry distributed photovoltaic development for many years, how to integrate photovoltaic into the railway system existing power supply infrastructure is still not a consensus in the industry, how to determine the railway energy system planning of photovoltaic energy storage access needs to be studied. Taking the traction power supply system connected with distributed photovoltaic power generation and energy storage system as the research object, this paper explores the capacity planning method of optical storage system along railway line, which takes into account the whole life cycle cost of photovoltaic and energy storage equipment. On the basis of consulting data, this paper first defines the influence factors of the system required for capacity planning, including access method of PV and ESS, the Solar radiation conditions, the types of photovoltaic and energy storage equipment used, etc. Then, the system is modeled according to the selected parameters and constraints of equipment in planning stage and operation stage. Finally, the necessity is illustrated by comparing the difference of power purchase cost of railway system before and after introducing PV and ESS along the railway line, and the further evaluation of the role of the system is obtained by comparing the effect of different access methods, different electricity tariff policies and different light levels.

关键词： Photovoltaic systems Costs Electricity Tariffs Rail transportation Traction power supplies Planning Solar radiation Energy storage Capacity planning

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Distortion correction method in the high-precision and high-speed CCD measurement system

Distortion correction method in the high-precision and high-...

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Chinese Control conference (CCC)

作者： Jing Li Junzheng Wang Renjian Hao Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology 100081 China

In the high-precision and high-speed measurement system, the distortion of CCD pixes will give a greater margin of error to measurement results. According to the characteristic of noise leading to the image distortion, this article establishes the image transformation model. data fitting based method is used for correcting image distortion. For the distortion caused by camera installation, the perspective transformation is used to correcting the image. And then the four points calibration method is adopted to calibrating the measurement system. Experiments adopt the high speed area array CCD to gather images with the circular facula in the target area launched by the laser, and calculate the real position of the facula in the target area, adopt the high accurate displacement sensor to give the true displacement of the target which is used to verify the real position of the facula in the target area. The results show that the algorithm can reduce the influence of image distortion, which advances the measurement accuracy efficiently.

关键词： Charge coupled devices Distortion measurement optical distortion Cameras Measurement uncertainty Calibration Real-time systems

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