检索结果-内蒙古大学图书馆

3rd international conference on intelligent Communication, Control and Devices, ICICCD 2018

作者： Ambigavathi, M. Sridharan, D. Department of Electronics and Communication Engineering Anna University CEG Campus Chennai India

ISBN: (纸本)9789811386176

The large volume of healthcare data continues to mount every second, making it harder and very difficult to find any form of useful information. Recently, big data is changing the traditional way of the data delivery system into valuable insights, especially in the healthcare industry. It provides a lot of benefits in the healthcare sector to detect critical diseases at the initial stage and deliver better healthcare services to the right patient at the right time. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured vital data rapidly produced by the various healthcare information storage systems. However, there are several issues to be addressed in the current health data analytics platforms that offer technical methods such as vital data collection, aggregation, process, analysis, visualization, and sharing. Due to lack of detailed analysis in the existing research works, this paper examines the most significant characteristics of big data analytics in health care, various data sources and its data types, five R’s of big data analytics, and then briefly discusses the recent open research challenges with future directions. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

An intelligent Traffic Light Control System Based on Dual Mode Special Vehicle Identification 22

An Intelligent Traffic Light Control System Based on Dual Mo...

引用

22nd IEEE international conference on High Performance computing and Communications, 18th IEEE international conference on smart City and 6th IEEE international conference on data Science and Systems, HPCC-smartCity-DSS 2020

作者： Cui, Beilei Ren, Erxiang Luo, Li University of Electronic Science and Technology of China Chengdu China Beijing Jiaotong University Dept. of Ee Beijing China

ISBN: (纸本)9781728176499

smart transportation is a major aspect of smart city which aims at improving traffic operation level, dispatching and overall supervision. How to alleviate traffic congestion, which is particular severe in large cities, is a cardinal facet of transportation. Special vehicles refer to vehicles dedicated to special tasks, like police cars, ambulances and are very dependent on road patency. It could be a life matter if a special vehicle on a mission encounters traffic congestion. Most of the existing traffic control systems do not target on special vehicles. Existing traffic control systems for special vehicle have weaknesses like unable to precisely detect the condition of special vehicles. In this paper, we proposed a traffic light control system based on dual mode identification, which aims at providing priority for special vehicles in a crowded city. By using dual mode identification, the condition of vehicles can be more precisely defined and accuracy performance is improved. In addition, we applied control and compensate time for the intersection to prioritize special vehicles and restore original state. In the system simulation and evaluation results, the proposed traffic light control system achieves 29% of time saving for special vehicles to get through an intersection and the intersection requires 4 cycles to fully recuperate to original condition. © 2020 IEEE.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

SBDC: smart building data center for iot, EDGE, and 5G

SBDC: Smart building data center for iot, EDGE, and 5G

引用

2020 Spring Simulation Multiconference, SpringSim 2020

作者： Rajaei, Hassan Kanumuri, Bhargav Narreddi, Nishitha Computer Science Department Bowling Green State University Bowling GreenOH43403 United States

ISBN: (数字)9781565553705

ISBN: (纸本)9781713812883

Internet of Things (IoT) targets smart devices and applications to better assist the supported domains with intelligent technologies to increase the utilization of resources and users. smart buildings constitute one such domain, where millions of devices generate terabytes of data demanding ultrahigh-speed computation and communication power for monitoring and analytical purposes. Latency in computation and communication is thus paramount. To meet such demand, this paper proposes a new architecture called smart Building data-Center (SBDC), an edge cloudlet node, furnishing high computing power and storage generated for vast IoT data in the building. In addition, this datacenter integrates a Mobile Edge computing (MEC) of the Fifth Generation (5G) for all 5G wireless devices used in the building. Each SBDC is further connected to nearby smart buildings, cloud datacenters, and other networks in a smart City. This paper describes the design, architecture, and network connectivity of the proposed system. © 2020 Society for Modeling & Simulation international (SCS)

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Mining and analyzing behavior patterns of smart home users based on cloud computing 2nd

Mining and analyzing behavior patterns of smart home users b...

引用

2nd EAI international conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020

作者： Lu, Xing-hua Mo, Chang-shen Wang, Xiao-qi Ma, Qing-qing Huali College Guangdong University of Technology Guangzhou511325 China

ISBN: (纸本)9783030510992

Aiming at the problem of poor robustness of traditional user behavior pattern mining analysis method, a cloud computing-based intelligent home user behavior pattern mining analysis method is designed. intelligent household IoT from using cloud computing method and data mining the user behavior patterns, establish a two-layer neural network level of data is divided into 2 kinds, the user behavior mode by setting the input weight vector calculation after classifying data correlation between user behavior model, using Apriori algorithm, input minimum support and minimum confidence, on the basis of analyzing the correlation between data, and establish the user behavior mode decision tree, on the basis of complete analysis of cloud computing smart home user behavior patterns mining method design. Through the comparison experiment with the traditional method, it is concluded that the designed mining analysis method based on cloud computing has higher robustness, the proposed cloud computing-based intelligent home user behavior pattern mining method has good application space. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Effect Monitoring of Physical Education Curriculum Based on Wearable Sensor in intelligent Environment 2

Effect Monitoring of Physical Education Curriculum Based on ...

引用

2nd international conference on computing and data Science, CONF-CDS 2021

作者： Liang, Feng Shan, Zhouxiang Wang, Dongle School of Leisure and Health Guilin Tourism University Guilin China Sport and Military Teaching Department Anhui University Hefei China

Reasonable amount of exercise is the premise of physical education teaching. On this premise, in the process of students' physical education teaching, the appropriate degree of actual exercise amount will affect the effect of motor skill learning and physical exercise to a great extent. Through monitoring the amount of exercise and then evaluating the quality of physical education teaching is the focus of the implementation of physical education. Looking for simple and effective monitoring equipment has important practical significance. In this paper, through the analysis of the current situation of wearable sensor in the development of physical education teaching, put forward the effect monitoring of sports curriculum based on wearable sensor in intelligent environment. In this paper, 258 freshmen and sophomores who use wearable devices are selected for monitoring and analyzing, and the pertinence, accuracy and data of wearable sensor physical education course and traditional physical education course are compared and analyzed, and the results are discussed and analyzed. It is concluded that wearable sensor can promote physical education curriculum, not only can improve the teaching pertinence, strengthen the accuracy, but also can In order to improve the scientificity of physical education curriculum effect monitoring. The research in this paper has important practical significance for monitoring the effect of wearable sensors in physical education curriculum. © Published under licence by IOP Publishing Ltd.

关键词： Curricula

来源：评论

学校读者我要写书评

暂无评论

Call data analytics Using Big data 3rd

Call Data Analytics Using Big Data

引用

3rd international conference on Advanced computing and intelligent Engineering, ICACIE 2018

作者： Manaswini, V.N.S. Krishnam Raju, K.V. Computer Science Engineering S.R.K.R.Engineering College Bhimavaram534204 India

ISBN: (纸本)9789811514821

One of the important strategies that can increase the business success rate is "customer monitoring" in which customer service representatives (CSRs) measure the satisfaction of customers. Here, the only way to know about customer’s experience (CX) is conducting the surveys which are either through phone calls or sending emails. The main challenge of customer monitoring is to know about customer’s experience, and the customer service representatives record their phone calls and analyze those recorded calls by converting them into text files. They maintain a large amount of memory to store a huge number of audio files and text files. This results in data tempering, corruption of data, unauthorized access to tables, columns and rows and burden of managing the data. In this paper, we replace the recorded files with direct phone calls. Now, we can convert the phone calls to text files with the help of speech-to-text (STT) algorithm, then analyze a huge amount of text files using Hadoop MapReduce Framework and apply the text similarity algorithms for getting better results to improve the business. © 2020, Springer Nature Singapore Pte Ltd.

关键词： data analytics

来源：评论

学校读者我要写书评

暂无评论

Web-Based Electricity Cost Modeling for Bangladesh Power Sector to Improve Capacity and Transparency

Web-Based Electricity Cost Modeling for Bangladesh Power Sec...

引用

Future Technologies conference, FTC 2020

作者： Shamsul Alam, M. Zaman, Marzia Razzaque Rupom, M.A. Mondal, Alam Hossain Department of Electrical and Electronics Engineering Daffodil International University Dhaka Bangladesh e-POWER Walter Light Hall Room 108 19 Union Street KingstonONK7L 3N6 Canada OS CLiCKS 160 Lake Circus Kalabagan Dhaka1205 Bangladesh

ISBN: (纸本)9783030631277

A study project undertaken for developing a web-based electricity cost model (WECM) is presented in this paper. The project targets to complete by five years that includes development of a prototype application, followed by a pilot phase with various cost analysis of real-life data and finally a nation-wide implementation of the model in the power sector of Bangladesh. The overall objectives of this study project are: (i) design and develop a well-structured, scalable database and a web application (ii) capacity building in Web and mobile app development and (iii) integrate machine learning based analytics using real-life data. This paper discusses the detailed methodology used for the web application development and capacity building. In addition, the first prototype application developed, and future scope are also presented. Finally, the expected outcome of this ongoing study and benefit of WECM are discussed. The proposed model for migrating the operation of one of the vital sectors i.e. the energy sector in Bangladesh to cloud is a bold step towards "Digital Bangladesh". Upon successful completion of this study project, it is expected that about 90% of the energy sector’s data can be automatically captured and reported for management and operation using WECM. © 2021, Springer Nature Switzerland AG.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A 65-nm 8-to-3-b 1.0-0.36-V 9.1-1.1-TOPS/W Hybrid-Digital-Mixed-Signal computing Platform for Accelerating Swarm Robotics

引用

IEEE JOURNAL OF SOLID-STATE CIRCUITS 2020年第1期55卷 49-59页

作者： Cao, Ningyuan Chang, Muya Raychowdhury, Arijit Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

Low-power edge-intelligence is leading to spectacular advances in smart sensors, actuators, and human-machine interfaces. In particular, energy efficiency is driving key advances in robotics, where low-power computation is augmented with smart control and mechanical systems to enable small-sized and intelligent drones, unmanned aerial vehicles (UAVs), micro-sized cars, and so on with applications in surveillance, disaster relief, and reconnaissance. Furthermore, for a variety of tasks, swarms of robots are often used as opposed to the individual robots. This article presents an energy-efficient computing platform that can enable a sample class of algorithms for swarm robotics. We demonstrate that both physical-model-based algorithms as well as learning-based algorithms can be supported on the same computing platform. We also demonstrate that with changing swarm sizes, the number of bits required to compute also scales. We take advantage of this observation to propose a hybrid-digital-mixed-signal computing platform, whose energy efficiency scales with the resolution of the data path and hence the swarm size. Measurements on a 65-nm CMOS test-chip demonstrate a peak energy efficiency of 9.1 TOPS/W at a 3-b resolution, and it scales down to 1.1 TOPS/W at an 8-b resolution.

关键词： Robot kinematics Mathematical model Swarm robotics Energy resolution Hardware Sensors Machine learning mixed signal robotics swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Design of Low Cost, Energy Efficient, IoT Enabled, Air Quality Monitoring System with Cloud Based data Logging, analytics and AI

Design of Low Cost, Energy Efficient, IoT Enabled, Air Quali...

引用

2020 international conference on Emerging Trends in smart Technologies, ICETST 2020

作者： Hussain, Mujahid Ghazanfar, Faisal Aleem, Sadaf Hai, Mansoor Karim, Arif Hussain, Kashif PCSIR Labs. Complex Karachi Pakistan Sharp Tel Karachi Pakistan

ISBN: (纸本)9781728171135

This paper presents a design of real-time Air Quality Monitoring System (AQMS) which incorporates Internet of Things (IoT) and cloud computing. AQMS utilizes solar panel and battery pack for independent and autonomous operation, thus, making it self-powered and sustainable. AQMS is based on AVR Microcontroller (Atmega32) and GSM modem (Sim900) for connectivity with the cloud application. The design is made low cost and scalable so that around 50nos. of such systems can be installed on roundabouts of market places, residential and industrial areas. The AQMS monitors the air quality with the help of a miniature suction pump (5volt DC) which establishes a controlled and constant stream of air-flow through a manifold that encapsulates electromechanical sensors, thus measuring the concentration of O2, CO, CO2, SO/SO2 (SOx), NO/NO2 (NOx), Hydrocarbon (CxHx), temperature, humidity and noise. By default, the air sampling is carried out once in an hour which may be changed depending on the change in air quality, i.e. making it adoptive for energy conservation and extending the sensor's life. The data collected at the cloud application will be processed using data analytics and Artificial Intelligence (AI) for getting insights of data (data mining) regarding the potential locations where the emissions are critical and disastrous for environmental, thus, leading to prevent any mishap. The design is mapped over a metropolitan city of Pakistan, i.e. Karachi, thus initiating the transformation of Karachi to a smart city. © 2020 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Advances in metagenomics based on high-throughput sequencing and big data mining

Advances in metagenomics based on high-throughput sequencing...

引用

1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Wang, Na Li, Kun Song, Yangyang Wang, Jinguo Department of Anesthesiology The First Hospital of Jilin University Changchun China Department of Urology Tengzhou Central People’s Hospital Tengzhou China Department of Urology The First Hospital of Jilin University Changchun China

ISBN: (纸本)9789811525674

The study of life science and the development of biotechnology have produced new requirements for DNA sequencing technology. Next-generation sequencing which is developed on the basis of traditional Sanger sequencing technology is widely applied in many fields for its advantages of high-throughput and low-cost. Next-generation sequencing is called high-throughput sequencing, because it is characterized by the large amount of sequence data produced in a single operation. With the improvement of sequencing technology and the development of genomics, the determination of the DNA sequence of a single species has been unable to meet the development of science, so a new research, metagenomics has been put forward. © Springer Nature Singapore Pte Ltd. 2020.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：