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检索条件"主题词=distributed databases"

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Large Scale Machine Translation Language Model Training System Based on Spark

Large Scale Machine Translation Language Model Training Syst...

引用

Mobile Networks and Wireless Communications (ICMNWC), IEEE International Conference on

作者： Yan Hu Department of English Education Shandong Vocational College of Light Industry Zibo Shandong China

ISBN: (数字)9798331528348

ISBN: (纸本)9798331528355

When faced with large language datasets, machine translation language models are difficult to process, resulting in low accuracy and efficiency of translation. Therefore, this study constructs a framework based on Firstly, by installing Apache Spark and configuring its integration with Hadoop distributed File System (HDFS), a distributed computing environment capable of parallel data processing is established to support rapid processing of large-scale data. Then, the distributed storage system HDFS is adopted to optimize data access efficiency and reduce IO (Input/Output) bottlenecks. Finally, a new iterative training strategy is implemented to gradually improve the translation accuracy of the model through incremental learning. Under the optimal configuration, the combination of a learning rate of 0.1 and batch processing of 2048 achieves a BLEU score of up to 30.8%, with training lasting only 4 hours. This study demonstrates the effectiveness of a large-scale machine translation language model training system based on Spark in improving translation efficiency and accuracy.

关键词： Training Translation Accuracy Computational modeling distributed databases Cluster computing Parallel processing Data models Machine translation Sparks

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Fingerprinting Network Device Based on Traffic Analysis in High-Speed Network Environment

Fingerprinting Network Device Based on Traffic Analysis in H...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Yiting Zhang Ming Yang Xiaodan Gu Peilong Pan Zhen Ling School of Computer Science and Engineering Southeast University Nanjing China

The identification of network device is of vital importance to strengthen network identity management and maintain cyberspace security. However, traditional device identification technologies based on the MAC address, IP address or other explicit identifiers can be deactivated if the identifier is hidden or tampered. Meanwhile, the existing device fingerprinting technology is also restricted by its limited performance and excessive time lapse. In order to realize device identification in high-speed network environment, PFQ kernel module and Storm are used for high-speed packet capture and online traffic analysis, respectively. On this basis, a novel device fingerprinting technology based on runtime environment analysis is proposed, which employs logistic regression to implement online identification with a sliding window mechanism, reaching a recognition accuracy of 77.03% over a 60-minute period. Moreover, performance test results show that the proposed technology can support over 10Gbps traffic capture and online analysis, and the system architecture is justified in practice because of its practicability and extensibility.

关键词： Object recognition Protocols Fingerprint recognition Storms distributed databases High-speed networks Data communication

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Arrhythmia Classification Using EFFICIENTNET-V2 with 2-D Scalogram Image Representation

Arrhythmia Classification Using EFFICIENTNET-V2 with 2-D Sca...

引用

TRON Symposium (TRONSHOW)

作者： Muhammad Furqon Supeno Mardi Susiki Nugroho Reza Fuad Rachmadi Arief Kurniawan I Ketut Eddy Purnama Mpu Hambyah Syah Bagaskara Aji Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9781665410540

Cardiovascular disease is part of global death's main cause. It is the term for all types of diseases that affect the heart or blood vessels. Heart disease is a type of cardiovascular disease. It can be detected early by examining the arrhythmia presence. Arrhythmia is an abnormal heart rhythm that is commonly diagnosed and evaluated by analyzing electrocardiogram (ECG) signals. In classical techniques, a cardiologist/ clinician used an electrocardiogram (ECG) to monitor the heart rate and rhythm of patients then read the journal activity of patients to diagnose the presence of arrhythmias and to develop appropriate treatment plans. However, The classical techniques take time and effort. The development of arrhythmias diagnosis, toward computational processes, such as arrhythmias detection and classification by using machine learning and deep learning. A convolutional neural network (CNN) is a popular method used to classify arrhythmia. Dataset pre-processing was also considered to achieve the best performance models. MIT-BIH Arrhythmia Database was used as our dataset. Our study used the EfficientN et- V2 which is a type of convolutional neural network to perform the classification of five types of arrhythmias. In pre-processing, the ECG signal was cut each 1 second (360 data), signal augmentation is applied to balance the amount of data in each class, and then the Continues Wavelet Transform (CWT) is employed to transform the ECG signal into a scalogram. The dataset is then distributed into subsets by using modulo operation to get variants of data in each subset. The colormap is applied to convert scalograms into RGB images. By this scheme, our study achieved superior accuracy than the existing method, with an accuracy rate of 99.97%.

关键词： Continuous wavelet transforms distributed databases Electrocardiography Image representation Rhythm Convolutional neural networks Cardiovascular diseases

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Interactive 3-D presentation of medical images on network using VRML 2.0

Interactive 3-D presentation of medical images on network us...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： H. Sato M. Shimanuki T. Akatsuka Department of Information Engineering Faculty of Engineering Yamagata University Yonezawa Yamagata Japan

Recently many researchers have been studying the feasibility of a support system for medical diagnosis through the World Wide Web, and there have been many attempts to construct a distributed database of medical images connected by the computer network. In these cases, the efficient and easy presentation of three-dimensional (3-D) medical images should be a quite important tool. The authors made a 3-D presentation system through the World Wide Web with a practical example image. The target 3-D object is a human head reconstructed from 177 MRI cross section slices, and the data for this display are described by the VRML 2.0 format. The observer can see the 3-D head model from any viewpoint, furthermore, he can operate the model through the network in a simple manner. Now, VRML is a popular and standard language to describe 3-D object, so one doesn't need to prepare the special software or special instruments. However, one needs some procedure to use it more efficiently. Here, the authors present an interactive 3-D presentation procedure for medical images on the network using VRML 2.0, and it is mentioned the presentation procedure is quite useful for remote medial service, teaching procedure for medical students and explanation for patients.

关键词： Biomedical imaging Medical diagnostic imaging Web sites Head Medical diagnosis distributed databases Image databases Computer networks Humans Image reconstruction

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Big Spatial Data Systems - A review

Big Spatial Data Systems - A review

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International Conference on Engineering Technology and their Applications (IICETA)

作者： Noor Alsaedi Ali Sadeq Abdulhadi Jalal Information and Communication Engineering Dept. Collage of Information Engineering Al-Nahrain University Baghdad Iraq

ISBN: (数字)9781665472159

ISBN: (纸本)9781665472166

With the accelerated growth of big spatial data volume produced by various devices, a plethora of development research to handle big spatial data has been done in the past decade. This research reviews the fundamental components and characteristics included in analytic systems for effectively managing big spatial data. After that, an overview of recent researches on big spatial data is discussed using four main components: source, storage, processing, and visualization. The components are then described in detail, including examples of how they are used in existing work. Afterward, some researchers’ work on systems of big spatial data is discussed showing how they support these four components. Furthermore, a comparison between these works is given in terms of the important performance metrics. Finally, this paper addresses the future research directions.

关键词： Soft sensors Query processing Data visualization distributed databases Throughput Reliability engineering Spatial databases

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Maintaining consistency in distributed software engineering environments

Maintaining consistency in distributed software engineering ...

引用

International Conference on distributed Computing Systems

作者： J. Walpole G.S. Blair J. Malik J.R. Nicol Department of Computing University of Lancaster UK

The authors argue that immutability is a suitable base on which to build distributed software engineering environments. They discuss the various approaches to maintaining consistency in immutable object systems and compare D.P. Reed's model of time domain addressing (ACM Trans. Comput. Syst., vol.1, no.1, p.3-23, Feb. 1983), with their own model of domain relative addressing. They demonstrate the suitability of domain relative addressing for use in distributed-software engineering environments.< >

关键词： Software engineering Programming environments Database systems Concurrent computing distributed computing distributed databases Transaction databases Project management Software development management Personnel

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distributed optimal scheduling of integrated energy system based on ADMM algorithm

Distributed optimal scheduling of integrated energy system b...

引用

Sustainable Power and Energy Conference (iSPEC)

作者： Yi Wu Liangzhong Yao Siyang Liao Beilin Mao Institute of Electrical and Automation Wuhan University Wuhan China

ISBN: (纸本)9781665414401

With the change of energy consumption structure, the integrated energy system coupled with multiple energy flows such as electricity, natural gas and heat is developing rapidly. At present, the decision-making center of the integrated energy park is the park dispatching control center. The dispatching process involves in the collection of distributed resource data, the joint centralized scheduling of multiple data, and the allocation and distribution of dispatching tasks. However, with the expansion of the scale of the integrated energy system, the centralized control center needs to collect and process a large amount of data, this depends on the strong computing power of the park control center and the reliable communication ability with distributed resources. For the future large-scale comprehensive energy park, centralized computing has many deficiencies. In this paper, the distributed computing method is used to decompose the joint scheduling problem into electric-gas subproblems, and the strong coupling relationship between electricity, natural gas and heat is considered; In the longitudinal consideration of source and reservoir interaction, a day ahead scheduling model considering economic cost and fluctuation cost of tie line is established. Finally, an example is given to analyze the feasibility of the distributed optimization model.

关键词： Costs Processor scheduling Computational modeling distributed databases Optimal scheduling Dispatching distributed algorithms

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International workshop on hot topics in Peer-to-Peer systems - HOTP2P

International workshop on hot topics in Peer-to-Peer systems...

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International Symposium on Parallel and distributed Processing (IPDPS)

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Fuzzy conceptual-based search engine using conceptual semantic indexing

Fuzzy conceptual-based search engine using conceptual semant...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： M. NikRavesh BISC Program Computer Sciences Division EECS Department University of California Berkeley CA USA

Retrieving relevant information is a crucial component of cased-based reasoning systems for Internet applications such as search engines. The task is to use user-defined queries to retrieve useful information according to certain measures. Even though techniques exist for locating exact matches, finding relevant partial matches might be a problem. It may not be also easy to specify query requests precisely and completely - resulting in a situation known as a fuzzy-querying. It is usually not a problem for small domains, but for large repositories such as World Wide Web, a request specification becomes a bottleneck. Thus, a flexible retrieval algorithm is required, allowing for imprecise specification or search. Therefore, we envision that non-classical techniques such as fuzzy logic based-clustering methodology based on perception, fuzzy similarity, fuzzy aggregation, and FLSI for automatic information retrieval and search with partial matches are required.

关键词： Search engines Indexing Internet Information retrieval Expert systems Fuzzy logic distributed databases Web sites Multimedia databases Machine learning

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A trustworthy management approach for cloud services QoS data

A trustworthy management approach for cloud services QoS dat...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qian Tao Huiyou Chang Yang Yi Chunqin Gu Department of Computer Science Sun Yat-sen University Guangzhou China Sontan Colleague Guangzhou University Guangzhou China Department of Computer Science Zhongkai University of Agriculture and Engineering Guangzhou China

In cloud computing environments, computing power, storage, platforms, and software are abstracted and virtualized as all kind of cloud services. Meanwhile complex applications can be described as processes invoking services selected at runtime. As a nonfunctional requirement, quality-of-service (QoS) is an important selection basis of cloud services. Nevertheless, the complex network environment and illegal operations generally result in the untrustworthy QoS data in reality, and then influence the preciseness and trustworthiness of cloud services scheduling. This paper proposes a trustworthy management approach for cloud services QoS. Results of experiments demonstrate the effectiveness of the proposed trustworthy management approach.

关键词： Quality of service Clouds distributed databases Cloud computing Clustering algorithms Computational modeling Processor scheduling

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