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

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SHRD: improving spatial locality in flash storage accesses by sequentializing in host and randomizng in device 17

SHRD: improving spatial locality in flash storage accesses b...

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Proceedings of the 15th Usenix conference on File and storage Technologies

作者： Hyukjoong Kim Dongkun Shin Yun Ho Jeong Kyung Ho Kim Sungkyunkwan University Korea Samsung Electronics Korea

ISBN: (纸本)9781931971362

Recent advances in flash memory technology have reduced the cost-per-bit of flash storage devices such as solid-state drives (SSDs), thereby enabling the development of large-capacity SSDs for enterprise-scale storage. However, two major concerns arise in designing SSDs. The first concern is the poor performance of random writes in an SSD. Server workloads such as databases generate many random writes; therefore, this problem must be resolved to enable the usage of SSDs in enterprise systems. The second concern is that the size of the internal DRAM of an SSD is proportional to the capacity of the SSD. The peculiarities of flash memory require an address translation layer called flash translation layer (FTL) to be implemented within an SSD. The FTL must maintain the address mapping table in the internal DRAM. Although the previously proposed demand map loading technique can reduce the required DRAM size, the technique aggravates the poor random performance. We propose a novel address reshaping technique called sequentializing in host and randomizing in device (SHRD), which transforms random write requests into sequential write requests in the block device driver by assigning the address space of the reserved log area in the SSD. Unlike previous approaches, SHRD can restore the sequentially written data to the original location without requiring explicit copy operations by utilizing the address mapping scheme of the FTL. We implement SHRD in a real SSD device and demonstrate the improved performance resulting from SHRD for various workloads.

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22.6 A 25Gb/s 4.4V-swing AC-coupled Si-photonic microring transmitter with 2-tap asymmetric FFE and dynamic thermal tuning in 65nm CMOS

22.6 A 25Gb/s 4.4V-swing AC-coupled Si-photonic microring tr...

引用

IEEE International conference on Solid-State Circuits (ISSCC)

作者： Hao Li Zhe Xuan Alex Titriku Cheng Li Kunzhi Yu Binhao Wang Ayman Shafik Nan Qi Yang Liu Ran Ding Tom Baehr-Jones Marco Fiorentino Michael Hochberg Samuel Palermo Patrick Yin Chiang Oreqon State University Corvallis OR University of Delaware Newark DE Texas A&M University College Station TX Hewlett-Packard Palo Alto CA Conant Advanced Technology Group New York NY Fudan University Shanghai China

Silicon photonic microring modulators (MRMs) offer a promising approach for realizing energy-efficient wavelength-division multiplexing (WDM) optical interconnects. For data-rates greater than 10Gb/s, depletion-mode MRMs are generally preferred over their injection-mode counterparts due to their shorter carrier lifetimes and resulting higher bandwidths. Unfortunately, these depletion-mode MRMs typically exhibit low PN junction tunability, thereby requiring higher modulation voltages in order to provide >6dB extinction ratios (ER). Furthermore, negative DC-biasing of the MRMs is necessary to maintain reverse-biased depletion-mode operation. In this work, a 5×25Gb/s hybrid-integrated MRM WDM transmitter is demonstrated that incorporates the following key advances: 1) an AC-coupled differential output driver that applies a 4.4V pp-diff output-swing on the MRM while providing a tunable on-chip negative DC-bias; 2) a 2-tap non-linear digital FFE that compensates for optical-dynamics-induced bandwidth limitations; 3) a dynamic thermal tuning loop that stabilizes the MRM by minimizing thermally-induced wavelength fluctuations.

关键词： optical transmitters Integrated optics Nonlinear optics Wavelength division multiplexing optical modulation Tuning

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Evolvable and Scalable System of Content Servers for a Large Digital Preservation Archives

Evolvable and Scalable System of Content Servers for a Large...

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Annual IEEE International Systems conference

作者： Quyen L. Nguyen Alia Lake Mark Huber US National Archives and Records Administration

ISBN: (纸本)9781424458820

Building a large-scale digital preservation archives system (LDPAS) for long-term access is a challenging endeavor. The three most significant system requirements contributing to that challenge are the scalability of the system, accommodation of heterogeneous digital holdings, and the evolvability of both the constituting technologies and the data formats in storage. The amount of digital-born materials requiring long-term preservation and access is overwhelming due to the fast pace of information technology and its widespread utilization in government, business corporations, academic institutions, and the general public. Compounding to the data volume challenge is the heterogeneity of the data, which range from the products of office automation and geospatial images, to multimedia artifacts. Storing and preserving digital objects must be accomplished in a way that allows access to the objects independently of the platform technology and software applications used to create these objects. As the technologies change rapidly, the LDPAS must accommodate the changes to its benefit, while also increasing in scale. A successful LDPAS must be able to adapt to the two-fold evolutionary demands. The evolution of the system software with time is the norm in any large-scale long-term system. But, even more important is the system's capability to cope with the evolution of the very software applications that generated the digital objects archived within it. In this paper, we propose an architecture of a system of Content Servers, which can scale with the data volume growth, continually sustain evolution in the face of technological change, and provide different levels of service to the different kinds of users accessing the LDPAS. We describe the concept, components and services of a Content Server in the context of digital archiving, service-oriented architecture (SOA) and the Open Archive Information System (OAIS) reference model. Several possible deployment configurations ar

关键词： Electronic Records Digital Archives Digital preservation SOA OAIS Evolvability Content Server Semiconductor optical Amplifier office automation Service-oriented architecture Access Digital archives content server Systems software digital archiving Scalability data formats Applications software Electronic records archives

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Advanced multispectral TIR remote sensing

Advanced multispectral TIR remote sensing

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IEEE conference on Aerospace

作者： C.F. Schueler K.R. Blasius S.H. Silverman Hughes Santa Barbara Remote Sensing Goleta CA USA

Recent advances in thermal infrared (TIR) detection offer design options for space sensors requiring temperature sensitivity in the 0.1-0.5 K range. A cost vs. performance trade-off is illustrated with two "reference" sensor concepts. Both systems use all reflective front optics designed for low cost "bolt-together" assembly-alignment. Cooled HgCdTe detection is illustrated by a reference hyperspectral concept using a 320/spl times/210 element cooled focal-plane array (FPA), offering /spl sim/0.15 K noise-equivalent temperature difference (NEDT) at 50 K FPA temperature for 60 meter pixels from a 705 km Earth orbit. Less expensive uncooled 1 /spl mu/m bandwidth multi-spectral imaging is illustrated by a reference concept using silicon microbolometers. Test data from a 320/spl times/240 element microbolometer array suggest 0.2-0.5 K system accuracy. NEDT improvements are expected over the next two years. Improvements in the design of radiative coolers are also expected to lower the cost of cooled TIR sensor systems. A Mars mission imager now under development illustrates application of the uncooled technology to planetary exploration.

关键词： Remote sensing Temperature sensors Hyperspectral sensors Costs Infrared sensors Infrared detectors Thermal sensors Temperature distribution optical sensors optical design

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LLM-centric pipeline for information extraction from invoices

LLM-centric pipeline for information extraction from invoice...

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Foundation and Large Language Models (FLLM), International conference on

作者： Faiza Loukil Sarah Cadereau Hervé Verjus Mattéo Galfre Kavé Salamatian David Telisson Quentin Kembellec Olivier Le Van LISTIC University Savoie Mont Blanc Annecy-le-Vieux France Cegedim Lyon France

ISBN: (数字)9798350354799

ISBN: (纸本)9798350354805

Extracting information from digital documents is an evolving area of research, especially with the recent advances in artificial intelligence and computer vision. Recently, Large Language Models (LLMs) have shown remarkable performance in various natural language processing tasks, including data extraction from documents. However, the accuracy of these models can be significantly affected when dealing with large or complicated documents due to the inherent complexity and variability of rich formats. In this paper, we target a specific type of complex document: financial *** technology extracts editable and searchable data from different types of documents transformed into an image, e.g., scanned documents, and PDFs. However, OCR is highly sensitive to noise and image mis-alignment that frequently results into wrong extraction of texts. Moreover, OCR cannot understand the structure of a document, and leverage it to understand the semantic of the document’s content to extract structured information from document. OCR is therefore considered as a preprocessing step that need to be completed with further processing. In this paper, we use text-based LLMs to enrich the outputs of optical Character Recognition (OCR) applied to documents to extract structured information from financial invoices. We show here, that by fusing OCR engines, including Tesseract and DocTR, with the two open-source LLM models, Llama3 and Mistral, we significantly improve the accuracy and reliability of information extraction operations on two datasets featuring business documents: SROIE and FATURA datasets.

关键词： Accuracy Large language models optical character recognition Semantics Pipelines Noise Information retrieval data mining Reliability Engines

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RAI4IoE: Responsible AI for Enabling the Internet of Energy

RAI4IoE: Responsible AI for Enabling the Internet of Energy

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IEEE International conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

作者： Minhui Xue Surya Nepal Ling Liu Subbu Sethuvenkatraman Xingliang Yuan Carsten Rudolph Ruoxi Sun Greg Eisenhauer CSIRO's Data61 Australia CSIRO’ s Energy Australia Georzia Institute of Technology USA Monash University Australia

This paper plans to develop an Equitable and Re-sponsible AI framework with enabling techniques and algorithms for the Internet of Energy (IoE), in short, RAI4IoE. The energy sector is going through substantial changes fueled by two key drivers: building a zero-carbon energy sector and the digital transformation of the energy infrastructure. We expect to see the convergence of these two drivers resulting in the IoE, where renewable distributed energy resources (DERs), such as electric cars, storage batteries, wind turbines and photovoltaics (PV), can be connected and integrated for reliable energy distribution by leveraging advanced 5G-6G networks and AI technology. This allows DER owners as prosumers to participate in the energy market and derive economic incentives. DERs are inherently asset-driven and face equitable challenges (i.e., fair, diverse and inclusive). Without equitable access, privileged individuals, groups and organizations can participate and benefit at the cost of disadvantaged groups. The real-time management of DER resources not only brings out the equity problem to the IoE, it also collects highly sensitive location, time, activity dependent data, which requires to be handled responsibly (e.g., privacy, security and safety), for AI-enhanced predictions, optimization and prioritization services, and automated management of flexible resources. The vision of our project is to ensure equitable participation of the community members and responsible use of their data in IoE so that it could reap the benefits of advances in AI to provide safe.. reliable and sustainable energy services.

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Fast Matching of Astronomical data within data Warehouse Architecture

Fast Matching of Astronomical Data within Data Warehouse Arc...

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2014 International conference on advances in Materials Science and Information Technologies in Industry(AMSITI 2014)

作者： Hailong Zhang Wu Chen Jun Nie Xinjiang Astronomical Observatory Chinese Academy of Sciences University of Western Australia

The data volume in astronomical digital sky surveys has reached hundreds of PB per *** to efficiently manage the massive astronomical data in explosive growth,how to achieve the integration on multi-wavelength observation data,and how to rapidly release the huge amounts of data generated by the larger telescopes are urgent problems need to be *** main purpose of this paper is to put forward an astronomical data warehouse architecture design to manage and publish massive astronomical *** the proposed architecture data servers deal with the raw data obtained from telescopes based on a predefined integration strategy,save the standardized meta-data structure and *** build a multi-level data storage model,extracting the different levels of data sets from the raw *** multi-level data asset is formed by constructing an object-based database and data warehouse management system,where all data is centralized in a reliable *** with huge number of objects have not yet had an efficient cross matching algorithm to achieve data integration from different band *** the implementation of this data warehouse architecture,we were able to adopt a parallel computing model to evaluate the matching method of massive astronomical catalogue *** improving the speed of matching,this method could potentially pave a way for the development of large-scale astronomical data of future larger telescopes and gain experience.

关键词： Astronomy Massive data Matching Catalogue data Warehouse

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Efficient Jobs Dispatching in Emerging Clouds

Efficient Jobs Dispatching in Emerging Clouds

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IEEE Annual Joint conference: INFOCOM, IEEE Computer and Communications Societies

作者： Shimon Bitton Yuval Emek Shay Kutten Industrial Engineering and Managment Technion - Israel Institute of Technology Haifa Israel

ISBN: (纸本)9781538641293

This study was carried in the context of the development of technologies for a cloud that uses an optical network for internal communication. The problem addressed in this paper deals with dispatching jobs - units of work, to be performed by machines on the cloud. Sending (or migrating) a job to a machine involves establishing a lightpath (a la circuit switching); this incurs a significant setup cost, but while it exists, the lightpath's capacity is very high. Hence, moving one job is about as expensive as moving a set of jobs over the same lightpath. Our goal is to develop online network dispatching algorithms for a work conserving job scheduling. That is, consider a set of jobs the dispatcher is responsible for their executions on some set SM of machines. Any machine in the network may join or (when not executing a job) leave SM according to decisions made outside the scope of this paper. Whenever a machine joins the set or is in the set and has just finished executing a job, it issues a request for a new job to perform and the dispatcher must send this machine a job that has not been executed yet (if such exists). Every machine can perform any of the jobs, and each job is performed on a single machine. The main algorithmic challenge in this context boils down to the following questions: How many jobs should we send to a requesting machine (or to some intermediate storage to be distributed from there)? From the storage on which machine should these jobs be taken? The algorithms developed here are shown to be efficient in reducing the costs of establishing lightpaths. As opposed to related algorithms for delivering consumable resources (in other contexts), we prove that our online algorithms are fully competitive. We present randomized online algorithms for two different settings: in the first it is assumed that each message requires establishing a lightpath and thus, incurs a setup cost; in the second, we distinguish between messages that carry job sets and small

关键词： Dispatching optical fiber networks data centers Cloud computing conferences Industrial engineering Electronic mail

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Edge Computing Sleep Mode Task Scheduling Based on Deep Reinforcement Learning

Edge Computing Sleep Mode Task Scheduling Based on Deep Rein...

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International conference on Big data Computing and Communications (BIGCOM)

作者： Shengkun Tao Fanping Zeng Yufan Tao Pengcheng Xia Tong Liu School of Computer Science and Technology University of Science and Technology of China China Key Laboratory of Wireless-Optical Communications University of Science and Technology of China Chinese Academy of Sciences

In edge computing, computing, storage, and network services are provided at the edge of the network. If the edge server is configured with the appropriate virtualization services, end-device requests can be processed at the edge to save network bandwidth and reduce response time. It is necessary for edge devices to run for a long period of time in order to receive user requests, however, users do not always send requests, which may result in some edge devices being idle for a long time and causing a significant amount of idle energy *** this paper, we design a sleep-mode based edge computing architecture that uses containers as resource units. Also, based on the proximal policy optimization algorithm (PPO), we propose a task scheduling algorithm using this edge computing architecture, namely Proximal Policy Optimization Task Scheduling based on Sleep Mode (PPO-TSSM). Our goal is to minimize the total utility of the task; where the total utility is the tradeoff between completion time, energy consumption and deadline. The experimental results show that our proposed algorithm PPO-TSSM reduces the total cost by at least 3.33% (up to 62.92%) compared with the baseline algorithm, and reduces the minimum completion time by 5.37% to 157.7%, and the energy consumption by 2.95% to 8.97% compared with other baseline algorithms. Meanwhile, we set up PPO-TS-NS without sleep mode to compare with the environment using sleep mode, and find that PPO-TSSM reduces the energy consumption by 74.76% compared with PPO-TS-NS, while the minimum completion time only increases by 5.33%. Therefore, introducing sleep mode can effectively reduce the cost of the whole edge computing system.

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The Integration of HMS using IOMT and CE Through ANFIS

The Integration of HMS using IOMT and CE Through ANFIS

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Advance Computing and Innovative Technologies in Engineering (ICACITE), International conference on

作者： R. Sreelakshmy Cecil Donald Gnanajeyaraman Rajaram Prakash Putta Sadeq Khudhur Thajeel Hind Hameed Doaa Talib Zaidan Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science CHRIST (Deemed to be University) Bengaluru Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences SIMATS Chennai Department of Mechanical Engineering Mohan Babu University Tirupati Andhra Pradesh India College of Technical Engineering National University of Science and Technology Dhi Qar Iraq Al-Farahidi university Baghdad Iraq Department of Laser and Optical Electronics Engineering Kut University College Al Kut Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

advances in the IoMT-enabled cloud computing and interactive applications provide a basis for reconsidering the landscape for delivery of healthcare services. Even though the IoMT-cloud-based systems monitor patients remotely, it fails to take into account the sustainability of the healthcare systems. The paper presents the integrated framework of green healthcare under the umbrella of unique technology to enhance user interactivity. Our system is user-friendly, considering scalability and performance for both patients and doctors. Patients can send their health data to the doctor in real time with the help of the wearable sensor. We propose that in the presence of Hierarchical Clustering Algorithms and adaptive neuo-fuzzy inference system (ANFIS) for identification and analysis of the data, the applied solutions could enhance the healthcare experience interaction among all the stakeholders.

关键词： Scalability Clustering algorithms Medical services Real-time systems Inference algorithms Stakeholders Sustainable development

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