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Containerized architecture for edge computing in smart home : AAA consistent architecture for model deployment 10

Containerized architecture for edge computing in smart home ...

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10th international conference on Computer Communication and Informatics, ICCCI 2020

作者： Gupta, Nitu Anantharaj, Katpagavalli Subramani, Karthikeyan Things Platform Samsung Research Institute Bangalore India

ISBN: (纸本)9781728145136

Network bandwidth and high latency are the main bottlenecks of cloud computing. To combat such scenarios, new paradigm Edge computing is used. Edge computing shifts the computation of resources from centralized cloud closer to the devices which generates data. Edge computing reduces the response time, latency and improves the battery life while maintaining data safety and privacy. The distributed architecture of edge computing makes resource management an important aspect of edge computing. In such a resource constrained environment edge devices should be capable of processing all types of request coming from IoT devices. With the advancement in data science and Machine learning models in different domains, many intelligent services have emerged to provide better user experience. These deep learning models have frequent updates to adapt to new hardware and software requirements. These models also have some installation dependencies and requirement of cross platform compatibility for training and prediction. In home edge environment, these issues are more important due to resource constraint in terms of memory and computing power. Also, due to the availability of extensive list of deep learning models for different service, it is difficult to maintain an environment supporting such models across various devices in the smart home to support all services. To solve this issue in smart home environment, this paper proposes architecture, using containerization techniques to deploy and manage the deep learning models. This paper also explains about the steps to convert the existing model into containers. Minimal space requirement on the edge device, data privacy, low latency along with device independence for deep learning models are prime benefits of the architecture proposed. To test the performance of the architecture, deep learning model was containerized and compared with the actual model deployed in the same edge environment. The experimental results demonstrated the

关键词： Containers

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THE METHOD OF HYBRID FUNCTIONS FOR THE NUMERICAL SOLUTION OF THE HODGKIN-HUXLEY MODEL 7th

THE METHOD OF HYBRID FUNCTIONS FOR THE NUMERICAL SOLUTION OF...

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7th international conference on Advances in Control and Optimization of Dynamical Systems (ACODS)

作者： Ganguly, Anindita Saha, Manika Ghosh, Aniruddha Maity, Ursa Kucera, Jan P. Raha, Soumyendu Indian Inst Sci Dept Computat & Data Sci Bangaluru 5600012 India Sister Nivedita Univ Dept Robot & Automat Kolkata 700150 India Indian Inst Technol Dept Elect Engn Dhanbad Bihar India Univ British Columbia Sch Biomed Engn Vancouver BC Canada Univ Bern Dept Physiol Bern Switzerland

Background and objective: The Hodgkin-Huxley framework of equations represent the generation of the nerve action potential. It is a fairly complex biophysical model that is non-linear in nature. It has four sets of coupled differential equations representing the membrane voltage and the gate variables. The conventional way of solving such systems is usually the forward Euler method. Some other computational methods are the Rush-Larsen (RL) method and, Runge-Kutta (RK) methods. In MATLAB, a popular method used is the ODE45 solver, which is actually 4th order Runge Kutta method. Method: In this paper, a new and simplified computational method is proposed which is called the Hybrid Functions (HF) method. To solve these differential equations representing a complex biological model, we present a detailed derivation of the proposed algorithm. Results: A detailed comparative study based on computational speed, absolute error and Integral Timed Squared Error (ITSE) was then conducted on the aforementioned algorithms. Conclusion: The results show that, due to the simplification of steps because of approximations considered in solving the system of equations, the HF method is quite effective for computing solutions of complex biophysical models with ease. Copyright (C) 2020 The Authors.

关键词： Hodgkin-Huxley model Hybrid function Biophysical model Numerical methods Membrane potential

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international conference on Cyber Security Intelligence and analytics, CSIA 2019

International Conference on Cyber Security Intelligence and ...

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international conference on Cyber Security Intelligence and analytics, CSIA 2019

ISBN: (纸本)9783030152345

The proceedings contain 202 papers. The special focus in this conference is on Cyber Security Intelligence and analytics. The topics include: Design of the In-depth Intelligence Education System Based on the Intercultural Communication;an Improved Load Balancing Algorithm Based on Neural Network;research on international Logistics Supply Chain Management Mode from the Perspective of Cross-border E-commerce;optimization of Logistics Warehouse Location Based on Genetic Algorithm;application of intelligent Algorithms in System Integration Design;research on Obstacle Avoidance of Mobile Robot Based on Multi-sensor Fusion;interaction Steady State Transportation Network and Planning Optimization Model;fatigue Damage and Creep Modeling of Combined Rotor and Its Application;Electromagnetic Force of Power Transformer with Different Short Circuit Current Based on FEM;analysis and Research of Dynamic data Path Selection Algorithm in Heterogeneous Networks;contribution Title Graphical Language Transmission Mechanism in Visual Communication Design Based on data Abstraction;design of the Network Security Intrusion Detection System Based on the Cloud computing;deep Learning Approaches for Voice Activity Detection;a State Observer Design for Dual Lipschitz Nonlinear System;research on Speech Enhancement Algorithms Based on Blind Source Separation in Outdoor Environment;an Improved Apriori Algorithm Research in Massive data Environment;research on the Development Trend of Online Education Industry Considering the Influence of Big data and Artificial Intelligence;feature Analysis and Selection in Acoustic Events Detection;prediction of Dollar Exchange Rate Based on Wavelet Neural Network;computer Performance Determination System Based on Big data Distributed File;optimization and Improvement of Lucene Index Algorithm.

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Towards a smart irrigation scheduling system through massive data and predictive models 2nd

Towards a smart irrigation scheduling system through massive...

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2nd international conference on Advanced intelligent Systems for Sustainable Development, AI2SD 2019

作者： El Mezouari, Asmae Najib, Mehdi Fazziki, Abdelaziz El LISI Semlalia Faculty of Science Marrakech Morocco TICLab International University of Rabat Salé Morocco

ISBN: (纸本)9783030366636

The development of new systems for the governance of water resources in agriculture is at the keen interest of precision agriculture field. These systems combine the advances of various fields such as machine learning, massive data and IoT for building new innovative solutions. Therefore, the integration of forecasting methods is an important component for anticipating changes and guaranteeing its adaptation trough an accurate prediction of environment features. In this paper, we present the architecture of a smart irrigation system with a focus on the integration of two prediction methods auto regressive moving average and the extreme gradient boosting. These represented methods are used for forecasting of soil moisture parameter which is considered as the main parameter for estimating irrigation requirements. The results are discussed for assessing the accuracy of these methods in different conditions. © Springer Nature Switzerland AG 2020.

关键词： intelligent systems

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Development and Design of Hospital Labor Union Information Management System under the Background of Big data 5

Development and Design of Hospital Labor Union Information M...

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5th international conference on smart Grid and Electrical Automation (ICSGEA)

作者： Han, Xiuli Qiqihar Med Univ Affiliated Hosp 2 Qiqihar 161000 Peoples R China

ISBN: (纸本)9781728182780

To improve the management level of trade union in large enterprises such as hospitals, this paper constructs a set of trade union information management system based on Web. Starting from the actual work requirements of existing trade union management, the overall process of system requirements analysis, system design and database design is described in detail. Then the system is analyzed and designed by UML modeling technology, and the functional structure diagram, IPO table and processing flow chart of the specific module design are provided. We adopt entity relation E-R diagram and SQL Server to design the table structure of the database. In the operation of information data, HDFS distributed file storage system is used to store data, and the spark distributed file computing engine is also used to analyze and process data. The test and analysis of the system show that the scheme has the advantages of high reliability, fast query speed and strong expansibility. It basically solves the shortcomings of the current system, such as weak expansibility, lack of data query and analysis speed.

关键词： labor union information management HDFS MSSQL J2EE

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Automated detection of social roles in online communities using deep learning 20

Automated detection of social roles in online communities us...

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3rd international conference on Software Engineering and Information Management, ICSIM 2020 - and its Workshop 2020 the 3rd international conference on Big data and smart computing, ICBDSC 2020

作者： Wijenayake, Piyumini De Silva, Daswin Alahakoon, Damminda Kirigeeganage, Saliya Research Centre for Data Analytics and Cognition La Trobe University Melbourne Australia Electrical and Computer Engineering University of Louisville Louisville United States

ISBN: (纸本)9781450376907

Online communities are an increasingly important aspect in the digital age, for business organizations, diverse industry sectors and overall, in modern society. The social role of each end-user, influencers to followers, and content providers to receivers is a primary consideration when evaluating the purpose and contribution of any online community. Most existing research on the detection of social roles in online communities is based on manual observations and analysis. This paper introduces a technique for automating the detection and extraction of social roles from online communities. Given the large volume of text and value of content, it is no longer viable to manually encode and detect social roles and contributions. The machine learning approach is based on a deep recurrent neural network and a word embedding model. A dataset consisting of over 1.2 million textual posts extracted from an online community on higher education in Australia was used to demonstrate the technique. This technique can be applied to any online community to automatically identify social roles, their influence and interactions. © 2020 Association for computing Machinery.

关键词： Big data

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Big data analytics and artificial intelligence serving agriculture 1

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2nd international conference on Advanced intelligent Systems for Sustainable Development, AI2SD 2019

作者： Tarik, Hajji Mohammed, Ouazzani Jamil Fez Morocco

ISBN: (数字)9783030366643

ISBN: (纸本)9783030366636

Agriculture is a very important sector in the Moroccan economy. Its contribute more than 15% of Morocco’s GDP and it’s employs about 45 percent of the total workforce with a similar portion of the population living in rural areas. We find in Morocco three types of agriculture: • First, export-oriented farms, irrigated, modern and highly capitalized. • Second, the agriculture in large-scale irrigated areas. • Third, the Rain-fed agriculture with more and less favorable land in the northeast, south and east. Knowing that the digital transformation is lever of the industrial revolution 4.0 and Big data and machine learning are huge in predicting things like when you might want to use certain pesticides, we proposed in this paper an advanced intelligent systems for sustainable development applied to agriculture. We used methodological data to preventing the Cereals production rate in an area characterized by an unstable climate using artificial neural networks. We started our process by collecting, preprocessing of methodological of more than 60 years, and we stared a comparative study to find the most efficient neural architecture in terms of complicity and in terms of recognition rate. And in the end, we presented the results and prospects of the system. © Springer Nature Switzerland AG 2020.

关键词： Neural networks

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Performance Assessment of smart Electricity Meters Based on Max Margin Bayesian Classifiers 4th

Performance Assessment of Smart Electricity Meters Based on ...

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4th international conference on intelligent, Interactive Systems and Applications, IISA2019

作者： Yu, Haibo Li, Helong Zhu, Yungang Wang, Yang China Electric Power Research Institute Beijing China College of Computer Science and Technology Jilin University Changchun China China National Accreditation Service for Conformity Assessment Beijing China

ISBN: (纸本)9783030343866

There are large amount of quality and monitoring data of electricity meters, it is crucial and valuable to assess the operating performance of the smart electricity meters automatically with this data. In this paper, we propose an intelligent operating performance assessment method for smart electric meters based on selective ensemble of max margin Bayesian classifiers. The genetic algorithm is firstly used to select most relevant attributes for assessment, and max margin Bayesian classifiers is utilized to make the assessment. We use the bagging and clustering to ensemble multiple classifiers to obtain better results. The experimental results illustrate the efficiency and effectiveness of the proposed method. © 2020, Springer Nature Switzerland AG.

关键词： Genetic algorithms

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Talent Evaluation Model of College Students Based on Big data Technology

Talent Evaluation Model of College Students Based on Big Dat...

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Tan, Lei Guan, Yi Dalian Neusoft Information Institute 8 Software Park Rd Dalian China

ISBN: (纸本)9783030627454

At present, most of the talent assessment methods are expert evaluation, leaderless group discussion, psychological test, structured interview and so on. It is easy to have misunderstanding of social perception such as primacy effect and Hawthorne effect. The weak degree of control leads to more subjective influence on the evaluation results. In addition, visualization is difficult to achieve, such as large amount of data and complex statistical analysis process, which often makes the traditional personnel evaluation more difficult to achieve a high degree of fit between trend prediction and reality. In recent years, the rapid development of big data technology makes it possible to establish a talent evaluation model based on big data technology, which can comprehensively consider the aggregation and integration of multi-source data. In the study and life of college students, a large amount of data will be accumulated, which will be conducive to the prediction of future talent behavior after collection and analysis. This paper attempts to collect college students in and out of the classroom, formal and informal learning environment, learning activities and life performance, etc., to obtain the data related to the students’ comprehensive quality, carry out comprehensive data and evaluation on the comprehensive quality and ability of college students, so as to provide the basis for students’ development and enterprise classification and selection. The platform will provide reference solutions for solving the employment difficulties of college students and accurate recruitment of enterprises. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Analysis and Research of Dynamic data Path Selection Algorithm in Heterogeneous Networks

Analysis and Research of Dynamic Data Path Selection Algorit...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Pu, Zaiyi China West Normal Univ Network & Informat Management Ctr Nanchong 637009 Sichuan Peoples R China

ISBN: (纸本)9783030152352;9783030152345

The continuous development of wireless communication theory and engineering practice technology has led to the heterogeneous wireless network situation represented by 4G and wireless technology. At the same time, with the rapid development of wireless services based on mobile internet, its complex business types and high traffic demand pose a huge challenge to the resource scheduling of operators. In this paper, the current status of research and application of heterogeneous wireless networks in China is reviewed, the key technologies and promotion schemes are analyzed, the impact of existing network planning concepts is discussed, and the relevant issues are given strategic suggestions. In order to better study the resource consumption of user service models in different access networks under heterogeneous networks, a multi-QoS traffic algorithm for mixed services under heterogeneous networks is proposed. This algorithm is based on the mixed services in various access networks, and takes the guarantee of the mixed services in different access networks of heterogeneous networks as the premise to accurately evaluate the traffic from the perspective of business identification. According to the number of active users, the bandwidth requirements of different user sizes are assessed, and the network planning is guided to expand reasonably.

关键词： Heterogeneous network Four network convergence Access network data traffic channel

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