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Smart Technologies, Communication and Robotics (STCR)

作者： A Pandiaraj N Vinothkumar R Venkatesan Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamil Nadu India Department Computer Science and Bussiness Systems BIET Sathyamangalam Tamil Nadu India Department of Information Technology BIET Sathyamangalam Tamil Nadu India

ISBN: (纸本)9781665460484

Cloud computing has the ability to work in a predestined manner. The main technology is virtualization. This generalizes the physical infrastructure. This helps us to manage easily. In this work, based on the needs the allocated resources are used. It supports the green computing concept. Dealing with the clients request is difficult for the interest of asset allotment. Virtual Machine is utilized for asset provisioning. By utilizing the virtualization climate will lessen the jib reaction time as well as it executes the undertaking as per the accessibility of assets. The viable and dynamic usage of the assets. This would help to balance the load and situations. The implementation uses the co-location approach. It is used to combine the small spaces and improve the performance of server. To reduce the wrong data based on time to live property. We use self-destruction approach. By developing the online prediction model we can estimate the sizes to reduce the task at run time.

关键词： Cloud computing Predictive models Green computing Virtual machining Servers Virtualization Task analysis

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KartalOl: Transfer learning using deep neural network for iris segmentation and localization: New dataset for iris segmentation

arXiv

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arXiv 2021年

作者： Khiarak, Jalil Nourmohammadi Nasab, Samaneh Salehi Jaryani, Farhang Moafinejad, Seyed Naeim Pourmohamad, Rana Amini, Yasin Noshad, Morteza Institute of Control and Computation Engineering Warsaw University of Technology Warsaw Poland School of Engineering Lorestan University Aleshtar Campus Aleshtar Iran Faculty of Engineering Arak University Arak Iran Department of Physics Shahid Beheshti University Tehran Iran School of Computing Informatics and Decision Systems Engineering Arizona State University AZ United States Faculty of Electrical and Computer Engineering University of Kharazmi Iran Stanford University Stanford United States

Iris segmentation and localization in unconstrained environments is challenging due to long distances, illumination variations, limited user cooperation, and moving subjects. To address this problem, we present a U-Net with a pre-trained MobileNetV2 deep neural network method. We employ the pre-trained weights given with MobileNetV2 for the ImageNet dataset and fine-tune it on the iris recognition and localization domain. Further, we have introduced a new dataset, called KartalOl, to better evaluate detectors in iris recognition scenarios. To provide domain adaptation, we fine-tune the MobileNetV2 model on the provided data for NIR-ISL 2021 from the CASIA-Iris-Asia, CASIA-Iris-M1, and CASIA-Iris-Africa and our dataset. We also augment the data by performing left-right flips, rotation, zoom, and brightness. We chose the binarization threshold for the binary masks by iterating over the images in the provided dataset. The proposed method is tested and trained in CASIA-Iris-Asia, CASIA-Iris-M1, CASIA-Iris-Africa, along the KartalOl dataset. The experimental results highlight that our method surpasses state-of-the-art methods on mobile-based benchmarks. The codes and evaluation results are publicly available at https://***/Jalilnkh/KartalOl-NIR-ISL2021031301. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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Plenary session 1: engineering leadership & cognitive computing

Plenary session 1: Engineering leadership & cognitive comput...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Nicos M. Timotheou Matthias Reumann Jovica V. Milanovic L. Gene Kornegay Ralph Stübner Julio Hernandez-Castro Pedro A. Amado Assunção Julius Georgiou Moritz Riede NAN Strategic Change Consultants Ltd Cyprus Sustainable Resilient Health Systems Research IBM Research - Zurich Switzerland School of Electrical and Electronic Engineering at the University of Manchester UK Republic of Cyprus Noble Energy COST Association EU School of Computing University of Kent (UK) Electrical and Computer Engineering Electronics and Multimedia Communication Systems at the Polytechnic Institute of Leiria Portugal University of Cyprus Cyprus University of Oxford Oxford UK

Business success equals creation and DELIVERY of value to all stakeholders. Engineers and especially engineering Leaders ask themselves: • Who are my stakeholders and what value do they expect from me? • How will I lead and manage so as to create and deliver the maximum value to my stakeholders in an optimum, sustainable way? • To what should I primarily devote my energy: Formulating and executing my unit's/my own value proposition and delivery, in the context of my unit's/own Mission or formulating and executing my unit's/my own strategy, in the context of my unit's/my own Vision? • Which are my main duties and in what mix and balance?

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On the scalability of particle swarm optimisation

On the scalability of particle swarm optimisation

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Congress on Evolutionary Computation

作者： Sebastien Piccand Michael O'Neill Jacqueline Walker Department of Computer Science ' Information Systems University of Limerick Limerick Ireland Natural Computing Research ' Applications group School of Computer Science ' Informatics University College Dublin Dublin Ireland Department of Electronic and Computer Engineering University of Limerick Limerick Ireland

Particle swarm has proven to be competitive to other evolutionary algorithms in the field of optimization, and in many cases enables a faster convergence to the ideal solution. However, like any optimization algorithm it seems to have difficulties handling optimization problems of high dimension. Here we first show that dimensionality is really a problem for the classical particle swarm algorithms. We then show that increasing the swarm size can be necessary to handle problem of high dimensions but is not enough. We also show that the issue of scalability occurs more quickly on some functions.

关键词： Benchmark testing Topology Particle swarm optimization Scalability Evolutionary computation Optimization Convergence

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On the ideal interpolation operator in algebraic multigrid methods

arXiv

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arXiv 2017年

作者： Xu, Xuefeng Zhang, Chen-Song LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China LSEC & NCMIS Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

Various algebraic multigrid algorithms have been developed for solving problems in scientific and engineering computation over the past decades. They have been shown to be well-suited for solving discretized partial differential equations on unstructured girds in practice. One key ingredient of algebraic multigrid algorithms is a strategy for constructing an effective prolongation operator. Among many questions on constructing a prolongation, an important question is how to evaluate its quality. In this paper, we establish new characterizations (including sufficient condition, necessary condition, and equivalent condition) of the so-called ideal interpolation operator. Our result suggests that, compared with common wisdom, one has more room to construct an ideal interpolation, which can provide new insights for designing algebraic multigrid algorithms. Moreover, we derive a new expression for a class of ideal interpolation operators.65F10, 65F15, 65N55 Copyright © 2017, The Authors. All rights reserved.

关键词： Coarsening

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Design and Comparison of Collaborative Filtering Technology for Product Suggestions in E-Commerce 1

Design and Comparison of Collaborative Filtering Technology ...

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1st IEEE International Conference on Automation, computing and Renewable systems, ICACRS 2022

作者： Rajasekar, P. Mohanraj, B. Padhi, S.N. Sivakumar, N. Lavanya, J. Charles Prabu, V. Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Tamil Nadu Chennai603203 India Department of Information Technology Karpagam College of Engineering Tamil Nadu Coimbatore641032 India Department of Mechanical Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Department of Computer Science and Engineering Panimalar Engineering College Chennai City Campus Tamil Nadu Chennai600029 India Department of Fashion Designing SRM Institute of Science and Technology CSH Kattankulathur campus Tamil Nadu Chennai603203 India Department of Computer Science Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai600 062 India

ISBN: (纸本)9781665460842

E-commerce websites and internet purchasing have never been more necessary. Product recommendations are a key tactic employed by online buying platforms. This study compares two different filtering algorithms that are used in product recommendationson websites like Amazon and Flipkart. Reviews of electrical devices, user data, and timestamps were all gathered from Kaggle and put into a dataset. These specifics then undergo several preprocessing steps. The steps are data visualization, duplicate value analysis, missing value analysis, and datatype analysis. The exhibited data is then used to train and test the machine learning models. For this purpose, two machine learning models are developed using two different algorithms. The algorithms K-Nearest Neighbor(KNN) and Support Vector Decomposition (SVD) are employed. The models are then trained to acquire used in the prediction procedure after that. The best models for the prediction process are then determined by scrutinizing the results of both models. The Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Error (MAE) values are located and compared because the findings of the analysis weren't *** erroneous data are plotted into a graph and evaluated to further demonstrate the point. As the SVD method is discovered to be the best of the group, the algorithm's greatest and worst predictions are discovered and examined. Even the poorest model constructed for the study's predictions turned out to be superior to several other prediction algorithms used for product suggestions. This algorithm can be deployed into the backend of any e-commerce website making it more effective. © 2022 IEEE

关键词： Value engineering

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Cyber-Physical -Social systems for Smart Cities: An Overview

Cyber-Physical -Social Systems for Smart Cities: An Overview

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Noreen Anwar Gang Xiong Wanze Lu Peijun Ye Hongxia Zhao Qinglai Wei The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation and with The Cloud Computing Center Chinese Academy of Sciences China School of Artificial Intelligence and Automation Beijing University of Technology Beijing China

Cyber-physical social systems (CPSS) include cyberspace, physical space, and social space. Since the introduction of CPSS, human relationships with machinery and the physical world have altered as a new paradigm. Recent estimates indicate that approximately 60 percent of the world's population will live in cities by 2030. Large, dense cities can be highly productive, innovative, and very green per capita, hence ideal for our future. However, the huge influx of new people poses enormous challenges to their administrations. Smart cities are becoming a reality, therefore, to achieve higher efficiency, optimum use of resources, management and to strengthen several features of modern towns, several elements of modern cities are automated and integrated into Information and Communications Technology (ICT). Cities and infrastructure are growing all over the world, in providing end-users with increased performance, comfort, visibility and convenience, the Smart Cities concept is critical. This paper will discuss smart cities and the CPSS concept intensively with some of its key technologies, challenges, and further development by using CPSS.

关键词： Smart cities Digital twin Sociology Information and communication technology Security Resource management Statistics

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A SLA-Oriented Management of Containers for Hosting Stateful Web Services

A SLA-Oriented Management of Containers for Hosting Stateful...

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IEEE International Conference on e-Science and Grid computing

作者： Christoph Reich Kris Bubendorfer Matthias Banholzer Rajkumar Buyya Department of Computer Science Hochschule Furtwangen University Germany School of Mathematics Statistics and Computer Science Victoria University of Wellington New Zealand Grid Computing and Distributed Systems (GRIDS) Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia

Service-oriented architectures provide integration of interoperability for independent and loosely coupled services. Web services and the associated new standards such as WSRF are frequently used to realise such service-oriented architectures. In such systems, autonomic principles of self-configuration, self-optimisation, self-healing and self- adapting are desirable to ease management and improve robustness. In this paper we focus on the extension of the self management and autonomic behaviour of a WSRF container connected by a structured P2P overlay network to monitor and rectify its QoS to satisfy its SIAs. The SLA plays an important role during two distinct phases in the life-cycle of a WSRF container. Firstly during service deployment when services are assigned to containers in such a way as to minimise the threat of SLA violations, and secondly during maintenance when violations are detected and services are migrated to other containers to preserve QoS. In addition, as the architecture has been designed and built using standardised modern technologies and with high levels of transparency, conventional Web services can be deployed with the addition of a SLA specification.

关键词： Containers Web services Service oriented architecture Quality of service Computer science Monitoring Grid computing Conference management engineering management Mathematics

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Style Factorization: Explore Diverse Style Variation for Domain Generalization

Style Factorization: Explore Diverse Style Variation for Dom...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ting Peng Yizhi Luo Yuqi Li Chuanguang Yang Ajian Liu Ziqiao Weng School of Digital Technology and Engineering Ningbo University of Finance and Economic China Institute of Computing Technology Chinese Academy of Sciences China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences China The University of Sydney

Deep neural networks (DNNs) exhibit noticeable performance degradation when exposed to out-of-distribution samples during testing. This degradation occurs due to the fact that the statistical characteristics (mean and standard deviation) of the features reflect the domain-specific properties of the training data, causing DNNs to be biased towards unseen distributions. One prominent approach to mitigate this bias is training networks with style augmented data, which helps alleviate the reliance on specific style distributions. However, existing methods either have limitations in terms of the number of styles they can handle or rely on intricate pipelines. In this paper, we propose a novel and simple approach called Style Factorization (StylF) to generate novel styles by identifying the directions that exhibit the most significant variations in style. We formulate this problem as a constrained optimization task and decompose the feature statistics matrix of the training data to generate meaningful and diverse novel styles. Through extensive experiments conducted on three publicly available domain generalization benchmarks (PACS, OfficeHome, DomainNet), we demonstrate that our proposed method achieves SOTA performance.

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Universality, criticality and complexity of information propagation in social media

arXiv

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arXiv 2021年

作者： Notarmuzi, Daniele Castellano, Claudio Flammini, Alessandro Mazzilli, Dario Radicchi, Filippo Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Via dei Taurini 19 RomaI-00185 Italy Centro Fermi Via Panisperna 89 A Roma Italy

Information avalanches in social media are typically studied in a similar fashion as avalanches of neuronal activity in the brain. Whereas a large body of literature reveals substantial agreement about the existence of a unique process characterizing neuronal activity across organisms, the dynamics of information in online social media is far less understood. Statistical laws of information avalanches are found in previous studies to be not robust across systems, and radically different processes are used to represent plausible driving mechanisms for information propagation. Here, we analyze almost 1 billion time-stamped events collected from a multitude of online platforms – including Telegram, Twitter and Weibo – over observation windows longer than 10 years to show that the propagation of information in social media is a universal and critical process. Universality arises from the observation of identical macroscopic patterns across platforms, irrespective of the details of the specific system at hand. Critical behavior is deduced from the power-law distributions, and corresponding hyperscaling relations, characterizing size and duration of avalanches of information. Neuronal activity may be modeled as a simple contagion process, where only a single exposure to activity may be sufficient for its diffusion. On the contrary, statistical testing on our data indicates that a mixture of simple and complex contagion, where involvement of an individual requires exposure from multiple acquaintances, characterizes the propagation of information in social media. We show that the complexity of the process is correlated with the semantic content of the information that is propagated. Conversational topics about music, movies and TV shows tend to propagate as simple contagion processes, whereas controversial discussions on political/societal themes obey the rules of complex contagion. © 2021, CC BY.

关键词： Information dissemination

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