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Future prospects and challenges of renewable energy: A case study of Nepal 1

Future prospects and challenges of renewable energy: A case ...

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1st IEEE international conference on advances in Electrical, computing, Communications and Sustainable technologies, ICAECT 2021

作者： Rajkarnikar, Neesha Cheng, Jianjie Tao, Hanzhong Ye, Jilei van Ree, Teunis Wu, Yuping School of Energy Science and Engineering Nanjing Tech University Nanjing China College of Urban Construction Nanjing Tech University Nanjing China Department of Chemistry University of Venda Thohoyandou South Africa

ISBN: (纸本)9781728157900

Energy has become one of the most important drivers of socio-economic growth. However, situations in developing countries are almost overlooked. Here Nepal is taken as one example, and is found that the results are of great importance to the sustainable of human being. Nepal is a country with a tremendous potential for different types of energy but it relies heavily on imported fossil fuel for its energy needs. Being rich in water resources and with a diverse geography, renewable resources such as hydroelectric, solar and biomass have become relatively reliable substitutes for fossil fuels. This study traces Nepal's current energy requirements and builds a data model to forecast future demands. It further depicts the role of renewable energy in Nepal to supplement its energy needs. Both qualitative and quantitative data analysis are utilized to highlight the prospects for renewable energy in Nepal. It also focuses on the prospects and constraints for the advancement of renewable energy technologies (RETs). It is also recommended for the advancement, growth and implementation of RETs in Nepal. © 2021 IEEE

关键词： Fossil fuels

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Process of Adapting a Local Laboratory to Connect to an Online Laboratory System Based on Standard Definitions and Open Source technologies 17th

Process of Adapting a Local Laboratory to Connect to an Onli...

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17th Annual conference of the international-Association-of-Online-Engineering (IAOE) and the Global-Online-Laboratory-Consortium (GOLC) on Remote Engineering and Virtual Instrumentation (REV) - Cross Reality and data science in Engineering

作者： Zapata-Rivera, Luis Felipe Larrondo-Petrie, Maria M. Sahinbeyoglu, Brsar Argun, Serhan Latin Amer & Caribbean Consortium Engn Inst LACCE Boca Raton FL 33431 USA Florida Atlantic Univ Dept Comp & Elect Engn & Comp Sci Boca Raton FL 33431 USA Acrome Robot San Francisco CA USA

ISBN: (纸本)9783030525750;9783030525743

Local educational laboratories are evolving from isolated resources into a more accessible, shareable and interoperable resources. Due to the flexibility of desktop, and mobile software development tools, developers can now easily add to the educational laboratory experiments;multimedia content such as: videos, text, animation, simulation, among others. Companies such as: Acrome, Quanser, Labs Land, among others, offer flexible educational Laboratory solutions for schools and universities in which the professor or laboratory manager can make a content selection and, in some cases, they can add their own content to the student's laboratory interface. This paper develops a methodology for extending the educational local laboratories with online capabilities that enables the interoperability and integration within a e-learning ecosystem and presents a real case of adaptation of a local laboratory into a fully functional online remote laboratory.

关键词： Online laboratories Educational laboratories industry Control laboratories

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Simulation of the cloud computing network security intrusion detection model based on the data mining technology

Simulation of the cloud computing network security intrusion...

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Networking, Communications and Information Technology (NetCIT), international conference on

作者： Yuxiang Hou Guangdong University of Science and Technology Dongguan Guangdong China

Under the background of the continuous improvement of Chinese social modernization and development level and the comprehensive popularization of information technology, data mining technology is becoming more and more widely used, but the corresponding network security problems occur frequently, which causes serious constraints to the improvement of data mining technology level. Therefore, this paper analyzes the simulation measures of cloud computing network security intrusion detection model based on data mining technology, to ensure that under the cloud computing environment, network intrusion effectively prevents concealment, degeneration, unpredictable, effectively realize the real-time monitoring network intrusion target, and improve the application value of relevant technologies.

关键词： Cloud computing Analytical models Computational modeling Neural networks Intrusion detection Network security data models

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Real Time Pothole Detection using Machine Learning and Edge computing

Real Time Pothole Detection using Machine Learning and Edge ...

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international conference on advances in Electronics, Computers and Communications (ICAECC)

作者： Rakshith Gowda G Revathi G P Computer Science and Engineering PES University Bengaluru India

ISBN: (数字)9798350305449

ISBN: (纸本)9798350305456

Vehicle owners in every region of the globe face a significant challenge in the form of potholes. They result in property damage to cars, lengthen the time it takes to get from place to place and present a threat to the safety of motorists, cyclists, and pedestrians. This paper suggests a refreshing approach for detecting potholes using machine learning and edge computing technologies. The YOLOv7 model architecture is employed for pothole detection by applying transfer learning techniques. On the edge Raspberry Pi device, the trained model is deployed. Our proposed system consists of a camera module that is connected to a Raspberry Pi. The camera is affixed to the vehicle's dashboard and transmits live footage of the road surface to the edge device. The Raspberry Pi conducts inference on the stream of road surface data captured by the camera, detecting and preserving images of identified potholes. The efficacy of the suggested method has been demonstrated through experimental findings, exhibiting a notable degree of precision and expediency in the identification of potholes. The amalgamation of machine learning and edge computing presents a pragmatic resolution that can be implemented on low-energy consumption devices, such as Raspberry Pi, thereby rendering it both scalable and economical for extensive deployment. The research introduces a pothole detection system that operates in near real-time. The system's implementation is expected to enhance proactive road maintenance, resulting in a reduction of infrastructure damage and an improvement in road safety.

关键词： Image edge detection Computational modeling Transfer learning Streaming media Cameras Real-time systems Road safety

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Sensitivity Analysis of an Air Pollution Model with Using Innovative Monte Carlo Methods in Calculating Multidimensional Integrals 10th

Sensitivity Analysis of an Air Pollution Model with Using...

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10th international conference on Numerical Methods and Applications, NMA 2022

作者： Ostromsky, Tzvetan Todorov, Venelin Dimov, Ivan Georgieva, Rayna Department of Parallel Algorithms Institute of Information and Communication Technologies Bulgarian Academy of Sciences Acad. G. Bonchev Str. Block 25 A Sofia1113 Bulgaria Department of Information Modeling Institute of Mathematics and Informatics Bulgarian Academy of Sciences Acad. Georgi Bonchev Str. Block 8 Sofia1113 Bulgaria

ISBN: (纸本)9783031324116

Large-scale models are mathematical models with a lot of natural uncertainties in their input data sets and parameters. Sensitivity analysis (SA) is a powerful tool for studying the impact of these uncertainties on the output results and helps to improve the reliability of these models. In this article we present some results of a global sensitivity study of the Unified Danish Eulerian Model (UNI-DEM). A large number of heavy numerical experiments must be carried out in order to collect the necessary data for such comprehensive sensitivity study. One of the largest supercomputers in Europe and the most powerful in Bulgaria, the petascale EuroHPC supercomputer Discoverer is used to perform efficiently this huge amount of computations. One of the most important features of UNI-DEM is its advanced chemical scheme, called Condensed CBM IV, which considers a large number of chemical species and all significant reactions between them. The ozone is one of the most harmful pollutants, that is why it is important for many practical applications to study it precisely. Stochastic methods based on Adaptive approach and Sobol sequences are used for computing the corresponding sensitivity measures. We show by experiments that the stochastic algorithms for calculating the multidimensional integrals under consideration are one of the best stochastic techniques for computing the small in value sensitivity indices. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Sensitivity analysis

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Wireless sensor networks communication protocols

Wireless sensor networks communication protocols

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international conference on Information science and Communications technologies (ICISCT)

作者： Halim Khujamatov Bakhtiyor Maxkamov Nurshod Akhmedov Amir Lazarev Jamshid Khoshimov Data transmission networks and systems department Tashkent University of Information Technologies Tashkent Uzbekistan Rector of Tashkent University of Information Technologies named after Muhammad al-Khorazmi Tashkent Uzbekistan The Ministry for Development of Information Technologies and Communications of the Republic of Uzbekistan Tashkent Uzbekistan

Modern technological advances allow remote monitoring of all social and production-related processes. It is important to ensure network resources and choose a network protocol based on the requirements during the monitoring process. The focus is on wireless communication protocols. When conducting a comparative analysis of wireless communication protocols, it is necessary to study based on several indicators. The network size, transmission time, power and transmission distance, power consumption, including the power consumption of microcircuits and coding efficiency of these protocols are important parameters in choosing a protocol. In this paper, the communication protocols used in the process of remote monitoring are studied on the example of the healthcare system.

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Maritime vessel route extraction and automatic information system (AIS) spoofing detection 1

Maritime vessel route extraction and automatic information s...

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1st IEEE international conference on advances in Electrical, computing, Communications and Sustainable technologies, ICAECT 2021

作者： Prasad, Priank Vatsal, Vishesh Chowdhury, Rajarshi Roy Data Science Intern Dfy-Graviti Bangalore India CTO Dfy-Graviti Bangalore India Application Developer Dfy-Graviti Bangalore India

ISBN: (纸本)9781728157900

Automated Identification System (AIS) comprises of a global real-time network of maritime vessels, transmitters, and satellite or ground-station receivers, which are used to track and record time-stamped static (vessel-id, type, etc.) and dynamic (location, course, speed, etc.) information of all maritime vessels. Traditionally, this data feed has been used by vessel traffic services to avoid vessel collisions, however increasingly, marine researchers and data scientists have shown interest in developing algorithms on historical AIS data-dumps with diverse objectives such as estimating trends in global ocean-currents, maritime logistical planning, fishing fleet monitoring and enhancing maritime security. This paper aims to propose a novel shipping-route extraction algorithm to process historical AIS data (running into tens of gigabytes of daily data, from more than a hundred thousand maritime vessels), to effectively characterize global shipping route behaviour and capture its seasonal trends. This is done by formulating a sigmoid based turning waypoint identification, which does not solely depend on the change in the course of a vessel, derived from AIS message. The AIS data is further processed to excerpt the vessel's distance from the nearest port and nearest shore with resolution of about 1 km, which forms a handy metric for the identification of suspicious ports. Several other use cases are also explored, which include detecting various anomalies in individual vessel behaviour such as intentional or unintentional switching off AIS transmission, shipping-lane deviations, spoofing transmission messages. To tackle spoofing anomaly, various spoofing identification methods are discussed. A region-based spoofing identification algorithm is developed to identify spoofing points under multiple categories using a clustering algorithm. All the results are visualized through an open-source map overlay. The results contribute to a growing body of fast shipping route analys

关键词： Python

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12th international conference on High-Performance computing Systems and technologies in Scientific Research, Automation of Control and Production, HPCST 2022

12th International Conference on High-Performance Computing ...

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12th international conference on High-Performance computing Systems and technologies in Scientific Research, Automation of Control and Production, HPCST 2022

ISBN: (纸本)9783031237430

The proceedings contain 23 papers. The special focus in this conference is on High-Performance computing Systems and technologies in Scientific Research, Automation of Control and Production. The topics include: Ontology-Based data Mining Platform for Diagnosing Sowing Quality of Wheat Seeds;algorithm for the Classification of Coronary Heart Disease Based on the Use of Symptom Complexes in the Cardiovascular Environment;business Process Designing of the Institutional Ranking System of Higher Education of the Kyrgyz Republic;evaluation of the Efficiency of the Vaccination Against Chickenpox Based on the Results of Simulation Modeling;hierarchical Volume Mesh Model of Heterogeneous Media Based on Non-Destructive Imaging data;modeling a Potential Plant Habitat by Ensemble Machine Learning;adaptive Traffic Signal Control Based on a Macroscopic Model of the Transport Network;optimization and Robustization of Angular Motion Control of an Automatic Maneuverable Aerial Vehicle;synthesis of the Rational Analyzing Function for Feature Extraction of Signals from the Electrostatic Location System;Architecture and CAD Software Solutions for PCB Design;application of Computer Numerical Control in Eddy-Current Study Methods;Open-Source Solution for Identification and Blocking of Anomalous BGP-4 Routing Information;Simulation of DDoS Attacks on LTE and LoRaWAN Protocols in the NS-3 Network Simulator;transaction-Oriented Approach to the Design of Information Systems Based on Formal Grammar;frequency-Domain Generalized Phase Transform Method in Pipeline Leaks Locating;inverse Problem Regularization of Parametric Identification of the Particle Temperature Distribution of Gas-Thermal Flow with Optimization of Its Solution;application of the Heterogeneous Multiscale Finite Element Method for Modelling the Compressibility of Porous Media.

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ReAssigner: A Plug-and-Play Virtual Machine Scheduling Intensifier for Heterogeneous Requests

ReAssigner: A Plug-and-Play Virtual Machine Scheduling Inten...

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IEEE international conference on Big data

作者： Haochuan Cui Junjie Sheng Bo Jin Yiqiu Hu Li Su Lei Zhu Wenli Zhou Xiangfeng Wang School of Computer Science and Technology East China Normal University Shanghai China Algorithm Innovation Lab. Huawei Cloud Computing Technologies Co. Xi’an China Computing Service Product Dept. Huawei Cloud Computing Technologies Co. Xi’an China

ISBN: (纸本)9781665480468

With the rapid development of cloud computing, virtual machine scheduling has become one of the most important but challenging issues for the cloud computing community, especially for practical heterogeneous request sequences. By analyzing the impact of request heterogeneity on some popular heuristic schedulers, it can be found that existing scheduling algorithms can not handle the request heterogeneity properly and efficiently. In this paper, a plug-and-play virtual machine scheduling intensifier, called Resource Assigner (ReAssigner), is proposed to enhance the scheduling efficiency of any given scheduler for heterogeneous requests. The key idea of ReAssigner is to pre-assign roles to physical resources and let resources of the same role form a virtual cluster to handle homogeneous requests. ReAssigner can cooperate with arbitrary schedulers by restricting their scheduling space to virtual clusters. With evaluations on the real dataset from Huawei Cloud, the proposed ReAssigner achieves significant scheduling performance improvement compared with some state-of-the-art scheduling methods.

关键词： Cloud computing Scheduling algorithms Big data Virtual machining Planning

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Review On Image based Coffee Bean Quality Classification: Machine Learning Approach

Review On Image based Coffee Bean Quality Classification: Ma...

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advances in computing, Communication Control and Networking (ICAC3N), international conference on

作者： Pragathi S P Lija Jacob M. Sc Data Science Christ Deemed to be University Pune Department of Data Science Christ Deemed To be University Pune

Specialty coffee’s demand is growing worldwide as coffee drinkers continue to look for the freshest and highest-quality flavors. Depending upon the quality, there are two categories in the coffee industry, that is specialty coffee and commodity/commercial coffee. Coffee beans are graded via visual inspection and cupping. A 300g sample of green coffee beans is used for visual assessment, and faulty beans are counted. As per the ‘Specialty Coffee Association of America’ (SCAA), defect can be either primary or secondary. For a coffee to be a specialty, it should have less than 5 secondary defects and zero primary defects. In this survey we have presented the coffee bean quality-related research which includes various machine learning approaches in classifying the coffee beans. The study has achieved quite promising prediction accuracies and was evaluated with test data. We have done a study on coffee bean quality classification and are willing to contribute an arabica coffee bean dataset and detection of coffee bean quality using transfer learning with higher accuracy.

关键词： Training Industries Deep learning Visualization Computational modeling Transfer learning Inspection

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