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Fault Tolerance Using AutoScaling in Amazon Web Services 1

Fault Tolerance Using AutoScaling in Amazon Web Services

引用

1st IEEE International Conference on Computing and Data science, ICCDS 2024

作者： Nanthini, N. Shanmuga Prabha, P. Vidhyasri, R. Anand, Vruthi V. Sathyabama Institute of Science and Technology Dept. Computer Science and Engineering Tamil Nadu Chengalpattu India

ISBN: (纸本)9798350365337

This study examines the design of fault tolerance mechanisms in cloud computing infrastructure, with particular emphasis on Amazon Web Services (A WS). Fault tolerance is critical to assure the continuous availability and reliability of cloud-based systems. Auto Scaling, an A WS feature, provides a dynamic way to handle demand changes while keeping the system flexible. This article presents a fault tracking management approach using Auto Scaling in A WS based on current research and real-world concerns. The importance of monitoring fault tolerance policies is emphasized, along with practical implementation methods. Furthermore, a case study demonstrating the success of this technique in real-world situations is presented, highlighting its importance for solving current challenges. © 2024 IEEE.

关键词： Websites

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Uncertainty-Aware Deep Learning for Segmenting Ultrasound Images of Breast Tumours

Uncertainty-Aware Deep Learning for Segmenting Ultrasound Im...

引用

2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Munia, Afsana Ahmed Hossain, Ibrahim Jalali, Seyed Mohammad Tabarisaadi, Pegah Rahman, Ashikur Nahavandi, Saeid Deakin University Institute for Intelligent Systems Research and Innovation VIC3216 Australia Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350337020

Precise image segmentation is one of the dominant factors in disease diagnosis. A typical application is the segmentation of breast ultrasound images, allowing radiologists to suggest what to do next. After emerging deep learning technology especially convolutional neural networks (CNNs), the image segmentation model achieved state-of-the-art performance in various medical applications such as cancer detection and classification, lung node segmentation, cell segmentation and so on. However, despite these successes, a big question arises: to what extent is the model certain about the predicted result? Generally, most deep learning models focus on high accuracy but not on uncertainty of predicted results, which is not enough to make a critical real-life decision such as a disease diagnosis, where a wrong decision can be life-threatening. Hence for making a crucial decision, it is essential that the predicted result will provide not only accuracy but also estimate model uncertainty. Our contribution to this research is to build a system that predicts pixel-wise semantic segmentation and provides uncertainty estimation of the predicted results. It is achieved by adding a dropout layer during training and using Monte Carlo dropout in inference. We evaluate our model with the breast ultrasound image dataset (BUSI) and compare the results with a few other state-of-the-art methods where our method outperforms others in terms of IoU. © 2023 IEEE.

关键词： Breast cancer Deep learning Semantic segmentation Ultrasound images Uncertainty quantification

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ILog 2.0: A Novel Method for Food Nutritional Value Automatic Quantification in Smart Healthcare 8

ILog 2.0: A Novel Method for Food Nutritional Value Automati...

引用

8th IEEE International Symposium on Smart Electronic systems, iSES 2022

作者： Mitra, Alakananda Goel, Sarang Mohanty, Saraju P. Kougianos, Elias Rachakonda, Laavanya University of North Texas Dept. of Computer Science and Engineering United States University of North Texas Texas Academy of Mathematics and Science United States University of North Texas Computer Science and Engineering United States Dept. of Electrical Engineering United States Univ. of North Carolina at Wilmington Dept. of Computer Science United States

ISBN: (纸本)9798350399226

In order to be healthy and well-nourished, one must consume a nutritious diet. Many chronic noncommunicable diseases, such as heart disease, diabetes, and cancer, can be prevented by taking healthy and balanced diet. Dietary diversity and moderation in salt, sugar, saturated fat, and trans fat consumption are needed for a balanced diet. The proposed system iLog 2.0 aims for estimating nutritional values of food. It uses state-of-the-art object detector to detect the food object. Food quantification has been performed. It makes the estimation of nutritional values more accurate. A high success rate has been achieved. This preliminary research shows promise in estimating nutritional value of the food. © 2022 IEEE.

关键词： Nutrition

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Compression method for ECU software updates 10

Compression method for ECU software updates

引用

10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017

作者： Onuma, Yutaka Terashima, Yoshiaki Sumika Nakamura Kiyohara, Ryozo Dept. of Information and Computer Science Graduate School of Kanagawa Institute of Technology Atsugi Japan Dept. of Science and Engineering Soka University Hachioji Japan Dept. of Information and Computer Science Kanagawa Institute of Technology Atsugi Japan

ISBN: (纸本)9784907626310

Bugs in electrical control units (ECUs) in vehicles are increasing in accordance with the increasing complexity and scale of the ECU software. Thus, manufacturers need to recall their products. Moreover, upgrade functions for the ECU software or security functions will be required for connected vehicles. Therefore, a software function for reprogramming ECUs over the air (OTA) will be required after shipment. The most important issue in OTA updating is to reduce the update time. In many cases, differential compression technology is applied to the update data. However, it is difficult to apply this technology for some ECUs in which the RAM size is smaller than the size of the erase block unit. In this case, compression technology should be applied. We evaluated the many compression technologies for application to this type of ECU, proposed a suitable algorithm, and discuss improvements to it to reduce the update time for these ECUs. © 2017 IPSJ.

关键词： Flash memory

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Identifying masses in mammograms using template matching

Identifying masses in mammograms using template matching

引用

2nd International Conference on Communication Software and Networks, ICCSN 2010

作者： Lochanambal, K.P. Karnan, M. Sivakumar, R. Dept. of Computer Science Mother Theresa University Kodaikkanal India Department of Computer Science and Engineering Tamilnadu College of Engineering and Technology Coimbatore India

ISBN: (纸本)9780769539614

This paper introduces a novel segmentation scheme based on the template-matching method is used for identifying cancerous part in the mammogram image. These templates are defined according to the shape, and brightness of the masses or micro calcifications. Earlier to template matching, median filtering enhances the mammogram images, Edge detection operators such as Sobel, Prewitts, Laplacian and Laplacian of Guassian masks are enhances and detect the edges and then edge detection is used to detect the shape of the cancerous part. In the template matching, the threshold is set for the calculated values of the cross-correlation. Then the percentile method is used to set an overall threshold for each mammogram image. The segmentation accuracy is increased as the proposed scheme is more robust to noise and hence, it prevents over segmentation in final segmented images. It is exposed that, this method of template matching for identifying early stage cancerous parts gives considerably better detection results. © 2010 IEEE.

关键词： Median filters

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Matching fingerface based on area under the highest peaks curve

Matching fingerface based on area under the highest peaks cu...

引用

International Conference on computer and Communication engineering, ICCCE'10

作者： Elmadani, Ahmed B. Ramli, Abd R. Department of Computer Science Faculty of Science University of Sebha Sebha Libya Dept. of Computer and Communication Systems Eng. Faculty of Engineering University Putra Malaysia 43400 Serdang Selangor Malaysia

ISBN: (纸本)9781424462346

Passwords are no longer valid for accessing personal resources, because it is easy to forge them, in either small or big systems. Today's challenge is to find other alternatives for passwords. Biometric is one of the ways, by mean of using human characteristics in accessing system resources. Fingerprint and face can be used to secure systems, because fingerprint is a unique, un-repeatable. Using it with face it can be widely acceptable. This paper present a model of fingerprint and face recognition to gain access to sensitive information for only authorized person. The method is based on recognition of the concatenated fingerprint and face images known as fingerface. A small size of fingerface images are used to extract information. Area under the curve resulted from connecting highest peaks are used in matching parameter. Other parameters are used to ensure a perfect matching. Our method takes into account a minimum image size and minimum number of searches. As a result we get fast in matching process. © 2010 IEEE.

关键词： Face recognition

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Model trees for classification of hybrid data types

Model trees for classification of hybrid data types

引用

6th International Conference on Intelligent Data engineering and Automated Learning - IDEAL 2005

作者： Pao, Hsing-Kuo Chang, Shou-Chih Lee, Yuh-Jye Dept. of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan

In the task of classification, most learning methods are suitable only for certain data types. For the hybrid dataset consists of nominal and numeric attributes, to apply the learning algorithms, some attributes must be transformed into the appropriate types. This procedure could damage the nature of dataset. We propose a model tree approach to integrate several characteristically different learning methods to solve the classification problem. We employ the decision tree as the classification framework and incorporate support vector machines into the tree construction process. This design removes the discretization procedure usually necessary for tree construction while decision tree induction itself can deal with nominal attributes which may not be handled well by e.g., SVM methods. Experiments show that our purposed method has better performance than that of other competing learning methods. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Classification (of information)

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Deconstructing complex search tasks: A Bayesian nonparametric approach for extracting sub-tasks 15

Deconstructing complex search tasks: A Bayesian nonparametri...

引用

15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016

作者： Mehrotra, Rishabh Bhattacharya, Prasanta Yilmaz, Emine Dept. of Computer Science University College London London United Kingdom Dept. of Information Systems National University of Singapore Singapore

ISBN: (纸本)9781941643914

Search tasks, comprising a series of search queries serving a common informational need, have steadily emerged as accurate units for developing the next generation of task-aware web search systems. Most prior research in this area has focused on segmenting chronologically ordered search queries into higher level tasks. A more naturalistic viewpoint would involve treating query logs as convoluted structures of tasks-subtasks, with complex search tasks being decomposed into more focused sub-tasks. In this work, we focus on extracting sub-tasks from a given collection of on-task search queries. We jointly leverage insights from Bayesian nonparametrics and word embeddings to identify and extract sub-tasks from a given collection of on-task queries. Our proposed model can inform the design of the next generation of task-based search systems that leverage user's task behavior for better support and personalization. ©2016 Association for Computational Linguistics.

关键词： Safety devices

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Team learning of recursive languages 4th

引用

4th Pacific Rim International Conference on Artificial Intelligence, PRICAI 1996

作者： Jain, Sanjay Sharma, Arun Dept. of Info. Systems and Computer Science National University of Singapore Singapore119260 Singapore School of Computer Science and Engineering The University of New South Wales SydneyNSW2052 Australia

ISBN: (纸本)3540615326

A team of learning machines is a multiset of learning machines. A team is said to successfully learn a concept just in case each member of some nonempty subset, of predetermined size, of the team learns the concept. Team learning of languages turns out to be a suitable theoretical model for studying computational limits on multi-agent machine learning. Team learning of recursively enumerable languages has been extensively studied. However, it may be argued that from a practical point of view all languages of interest are recursive. This paper gives theoretical results about team learnability of recursive languages. These results are mainly about two issues: redundancy and aggregation. The issue of redundancy deals with the impact of increasing the size of a team and increasing the number of machines required to be successful. The issue of aggregation deals with conditions under which a team may be replaced by a single machine without any loss in learning ability. The learning scenarios considered are: (a) Identification in the limit of accepting grammars for recursive languages. (b) Identification in the limit of decision procedures for recursive languages. (c) Identification in the limit of accepting grammars for indexed families of recursive languages. (d) Identification in the limit of accepting grammars for indexed families with enumerable class of grammars for the family as the hypothesis space. Scenarios which can be modeled by team learning are also presented. © Springer-Verlag Berlin Heidelberg 1996.

关键词： Redundancy

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Sign Language Recognition by using Spatio-Temporal Features 5

Sign Language Recognition by using Spatio-Temporal Features

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5th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2024

作者： Renjith, S. Rashmi, Manazhy Sumi Suresh, M.S. Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amritapuri690525 India Dept. of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Amritapuri690525 India Dept. of Computer Science and Engineering University at Bufalo New York City United States

The recognition of sign language has significant importance as an application that addresses the communication challenges faced by those within the Deaf and hard-of-hearing populations. This study introduces a methodology for the identification of sign language using spatio-temporal attributes, specifically concentrating on two distinct sign language datasets: the CSL (Chinese Sign Language) alphabet and the ArSL (Arabic Sign Language) alphabet. The study's objective is to create a powerful recognition system capable of reliably identifying sign language motions. A combination of spatio-temporal characteristics collected from video sequences of sign language motions is used in the suggested technique. These characteristics capture the spatial layout as well as the temporal dynamics of the motions, allowing the model to recognise signals with more precision. Experiments were carried out on the CSL and ArSL alphabet datasets to validate the method's efficacy. The findings of the trials are encouraging. The suggested system recognized CSL alphabet signs with an accuracy of 90.87% and ArSL alphabet signs with an accuracy of 89.46%. These high accuracy rates show the power of the spatiotemporal feature-based method for sign language identification. The system's success on two different sign languages implies that it is adaptable and useful in a wide variety of sign language applications. This study contributes to the evolution of assistive technology, making sign language recognition more accessible and efficient for those who communicate using sign language. Furthermore, the findings pave the way for additional research into spatiotemporal feature-based approaches in sign language recognition, with potential applications in real-world settings such as sign language interpretation and communication support. © 2024 The Authors. Published by Elsevier B.V.

关键词： Audition

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