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11th IEEE International Conference on Cloud computing in Emerging Markets, CCEM 2023

作者： Yaamini, H.S. Gowri Swathi, K.J. Sindhu, H.R. Vidya, K. Manohar, N. Jipeng, Tian Department of Computer Science School of Computing Mysuru Amrita Vishwa Vidyapeetham India Computer Science College Zhongyuan University of Technology Henan Province Zhengzhou China

ISBN: (纸本)9798350360059

Food being an inseparable part of human's life, it is difficult for people to recognize and to find the recipe of traditional snacks descended by their ancestors. In this paper, a food recognition system is proposed where it recognizes the specific Karnataka snack inclusive of challenges like inter-class similarities, intra-class dissimilarities, diverse background, noise, and etc. using ResNet50 transfer learning model which has achieved a training accuracy of 99.8% and testing accuracy of 94.5%. Karnataka snacks are prepared through similar techniques which makes identification based on texture, color and pattern more challenging as well as the use of artificial intelligence techniques in recognizing snacks originated in Karnataka region needs exploration. The dataset consists of twelve classes with 150 images in each has been collected manually from various platforms. ©2023 IEEE.

关键词： Convolutional neural networks

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Dynamic Spray and Wait routing protocol for delay tolerant networks

Dynamic Spray and Wait routing protocol for delay tolerant n...

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9th IFIP International Conference on Network and Parallel computing, NPC 2012

作者： Zhang, Longbo Yu, Chen Jin, Hai Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9783642356056

Delay Tolerant Networks (DTN) is one of the mobile wireless networks that cannot set up the end-to-end communication path between the source and destination nodes pair in most of time. In this paper, we propose an improved routing protocol named as Dynamic Spray & Wait (DS&W), which is based on Spray and Wait routing strategy attempting to gain the higher delivery ratio benefits of replication-based routing as well as the lower resource utilization benefits of forwarding-based routing. But different from S&W, DS&W routing strategy focus on dynamic control to reduce the scale of the messages' flooding by calculating the delivery success probabilities to destinations. DS&W routing protocol can dramatically reduce the overhead ratio in DTNs. Simulation results also evident that DS&W protocol outperforms other existing DTN routing protocols. © IFIP International Federation for Information Processing 2012.

关键词： Wireless networks

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A novel clustered MongoDB-based storage system for unstructured data with high availability

A novel clustered MongoDB-based storage system for unstructu...

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作者： Jiang, Wenbin Zhang, Lei Liao, Xiaofei Jin, Hai Peng, Yaqiong Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

More and more unstructured data are produced and consumed over network. How to maintain these data and improve the availability and scalability of the storage systems has become a considerable challenge. Although some NoSQL systems such as Dynamo, Cassandra, MongoDB have provided different advantages for unstructured data management, no one can provide flexible query functions like MongoDB, meanwhile guarantee the availability and scalability as Cassandra simultaneously. This paper presents a new high available distributed storage system called MyStore based on an optimized clusteredMongoDB for unstructured data. Consistent hash is used to distribute data on multiple MongoDB nodes by applying virtual node method. NWR mode is applied to provide automatic backup operation and guarantee data consistency. And a gossip protocol is taken for exchanging information of failures in the system. Moreover, a user-friendly interface module and an efficient cache module are designed for improving the usability of the system. Based on above strategies, the system can realize high availability for unstructured data storage, while providing complex query functions like rational databases. Moreover, it is applied in a multi-discipline virtual experiment platform named VeePalms that has run practically. Experimental evaluation shows that the methodology is powerful enough not only to enhance the data availability, but also to improve the server's scalability. © Springer-Verlag Wien 2014.

关键词： Scalability

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Detection and Recognition of Vehicles Using Indian Driving Datasets 11

Detection and Recognition of Vehicles Using Indian Driving D...

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11th IEEE International Conference on Cloud computing in Emerging Markets, CCEM 2023

作者： Padukote, Yathish H.S. Suresha, R. Manohar, N. Jipeng, Tian Department of Computer Science School of Computing Mysuru Amrita Vishwa Vidyapeetham India Computer Science college Zhongyuan University of Technology Henan Province Zhengzhou China

ISBN: (纸本)9798350360059

Vehicle identification and recognition are essential computer vision tasks with important applications in autonomous driving, traffic management, and surveillance systems. The Indian Driving Dataset (IDD) dataset used in this work was compiled from a variety of driving scenarios in the Indian environment, and it includes a thorough investigation on vehicle detection and recognition. The dataset is meticulously chosen to reflect the difficulties brought on by the state of Indian roads, traffic patterns, and vehicle kinds. In this study, a Faster RCNN method for precise and effective vehicle detection and recognition deep learning approaches by enhancing images using power-law transformation. The collection consists of annotated IDD dataset images taken in a range of lighting situations, urban-rural locales, and camera angles. The testing results demonstrate the effectiveness of the recommended approach, which achieves competitive performance with 79.5% detection accuracy and 76% recognition accuracy. Additionally, the performance of the model is impacted by elements like various lighting situations and various vehicle models. This research offers insightful information about the model's ability to generalise in realistic situations. ©2023 IEEE.

关键词： Image annotation

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Evolutionary selection for regression test cases based on diversity

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Frontiers of computer science 2021年第2期15卷 201-203页

作者： Baoying MA Li WAN Nianmin YAO Shuping FAN Yan ZHANG School of Health Management Mudanjiang Medical UniversityMudanjiang157011China Department of intelligence and Computing Tianjin UniversityTianjin300350China School of Computer Science and Technology Dalian University of TechnologyDalian116024China School of Computer and Information Technology Mudanjiang Normal UniversityMudanjiang157011China

1 Introduction Regression testing refers to retest code after modification to ensure that changes will not introduce new faults or cause faults in other lines of code[1].Regression test selection(RTS)is one of the predominant *** identifies test cases that are relevant to test recent changes in an application and seeks to reduce the number of test suite while preserving the capability to reveal faults[2].

关键词： preserving predominant changes

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Dynamic switching-frequency scaling: Scheduling overcommitted domains in xen VMM

Dynamic switching-frequency scaling: Scheduling overcommitte...

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International Conference on Parallel Processing

作者： Chen, Huacai Jin, Hai Hu, Kan Huang, Jian Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769541563

Virtualization enables multiple guest operating systems run on a single physical platform. These virtual machines may host any types of application, including concurrent HPC programs. Traditionally, VMM schedulers have focused on fairly sharing the processor resources among domains, rarely consider VCPUs' behaviors. However, this can result in poor application performance to overcommitted domains if there are concurrent programs hosted in them. In this paper we review the properties of both Xen's Credit and SEDF schedulers, and show how these schedulers may seriously impact the performance of the communication-intensive and I/O-intensive concurrent applications in overcommitted domains. We discuss the origination of the problem theoretically, and confirm the derived conclusion on benchmarks. A novel approach, that dynamically scales the context switching-frequency by selecting variable time slices according to VCPUs' behaviors, is then proposed to improve the Credit scheduler more adaptive for concurrent applications. The experimental results show that this extended Credit scheduler can improve the performance of communication-intensive and I/O-intensive concurrent applications in overcommitted domains to the same magnitude as in under-committed domains. © 2010 IEEE.

关键词： Virtualization

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Detection And Tracking of Multiple Pedestrians Using Deep Learning 14

Detection And Tracking of Multiple Pedestrians Using Deep Le...

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14th International Conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Kumar, Ayush Singh, Tripty Duraisamy, Prakash Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India University of South Alabama Computer Science Department United States

ISBN: (纸本)9798350335095

Recent advancements in deep learning and computer vision have benefitted security systems. Recent object tracking algorithms, in example, have incorporated deep learning in a variety of methods to enhance tracking performance. Object tracking and security systems continue to provide a number of difficulties. This work will first identify the several challenges related to the object tracking for an autonomous system and further the object tracker system will be evaluated in a simulated environment for multiple objects like pedestrian, moving or stationary object. This research paper is all about designing the tracking algorithm for multiple pedestrians. This research employed YOLO V3 with a Deep Sort architecture. In order to get heightened accuracy different kind of scenario is used for preparing the test data. As a result, precision is 93 %, Recall is 98% and accuracy is 96%. © 2023 IEEE.

关键词： Deep learning

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Design of SaaS Overcloud for 3-Tier SaaS compatibility over cloudbased multiple boxes 17

Design of SaaS Overcloud for 3-Tier SaaS compatibility over ...

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12th International Conference on Future Internet Technologies, CFI 2017

作者： Han, Jungsu Kim, Jong Won Gwangju Institute of Science and Technology Networked Computing Systems Laboratory School of Electrical Engineering and Computer Science Gwangju Korea Republic of

ISBN: (纸本)9781450353328

With a growth in the popularity of ICT and Cloud technologies, the adoption of SaaS (Software as a Service) model is rapidly increasing. However, SaaS developers are still struggling with heterogeneities and inter-dependencies of their development and operation environments. In order to mitigate selected SaaS compatibility issues for heterogeneous underlying cloud infrastructures, we present a new approach, denoted as SaaS OverCloud, by enabling a specially-Arranged razor-Thin overlay layer and leveraging container-based on micro-services architecture. We then verify the conceptual feasibility of SaaS OverCloud model by enabling simplified 3-Tier SaaS services over small-size cloud-based boxes. © 2017 Association for computing Machinery.

关键词： Software as a service (SaaS)

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Efficient Real-time Breed Classification using YOLOv7 Object Detection Algorithm 14

Efficient Real-time Breed Classification using YOLOv7 Object...

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14th International Conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Sudharson, S. Deena, S. Reddy, Sappidi Nischinth Vellore Institute of Technology Computer Science and Engineering Chennai India Amrita Vishwa Vidyapeetham School of Computing Computer Science and Engineering Chennai India Chennai India

ISBN: (纸本)9798350335095

This work aims to develop an accurate and reliable solution for real-time breed recognition and categorisation of dogs and cats using the YOLO-v7 object detection algorithm. The Oxford IIIT pet dataset, consisting of a large number of images of different dog and cat breeds with various poses and backgrounds, is utilized for training and validation of the model. This model achieved a high F1 score of 85.6% and mAP of 82.57%, superior than other latest models. The findings illustrate the potential of using the YOLO-v7 algorithm for real-time breed detection and classification of dogs and cats, which can be used in a wide range of fields, including veterinary clinics, animal shelters, and pet stores. © 2023 IEEE.

关键词： Object detection

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Measurement study of PKTown: A P2P-based Multiplayer Online Game supporting system

Measurement study of PKTown: A P2P-based Multiplayer Online ...

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International Symposium on Parallel Architectures, Algorithms, and Programming

作者： Tu, Xuping Jin, Hai Jiang, Wenbin Liao, Xiaofei Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769543123

Recently, Multiplayer Online Game has been extremely popular, in which peer-to-peer technology has been introduced to help with the scaling. This paper presents a measurement study on a P2P-based MOG supporting system, called PKTown, which has been fully deployed over the CERNET. By leveraging a large set of traces obtained recently over a 4-month period, we study the benefit of P2P architecture applying to MOG supporting system, workload characteristics, players' behaviors and impact form a number of system parameters. We believe this provides insights in understanding the fundamental nature of MOG, which can be further explored to enhance the system design. © 2010 Crown Copyright.

关键词： Social networking (online)

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