检索结果-内蒙古大学图书馆

Communication, Computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： Krishnaraj Rao N S Smitha GL P. S. Ramesh Nandhini T J P. Nagaveni A Balaji Assistant Professor Department of Information Science and Engineering Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT) Nitte Karnataka India Department of CSE Saveetha School of Engineering Saveetha Institute of Medical and Technical Science (SIMATS) Chennai India Department of CSE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science and Engineering Saveetha School of Enginnering Saveetha Institute of Medical and Technical Science – SIMATS Saveetha University Chennai India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore Department of IT Panimalar Engineering College

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

The study of artificial intelligence focuses on the principles that guide all human intellectual endeavors. The integration of several academic disciplines, including as computer science, philosophy, politics, linguistics, systems engineering, neurophysiology, and behavioral science, has allowed it to grow. This article will describe how to build an intelligent machine, consisting of both hardware and software, that can replicate and exceed the abilities of the human brain in order to handle complicated issues that need specialized knowledge. It will specifically examine how to more effectively use artificial intelligence support systems into piano instruction. An Introduction, an oral language and music-assisted education system based on the ARM and SA algorithm, is proposed by this study in order to ascertain the implementation principle guiding the functioning of the piano automation recording system. It also delves deeply into the theory and operation of automated music recording systems, compiling and evaluating data that these systems generate via internal databases. is an effort to improve music education via the use of artificial intelligence support systems. The results of the experiment show that the training system for the automated notation algorithms for playing the piano and songs has a 56.81 and fast growing machine learning auxiliary technology utilization rate. Thus, we may infer that using an AI support system is necessary while teaching performance piano and automated notation.

关键词： Training Machine learning algorithms Education Music Machine learning Software Recording Multiple signal classification Telecommunication computing Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Medical Data Classification Using Velocity Enhanced Whale Optimization Algorithm

Medical Data Classification Using Velocity Enhanced Whale Op...

引用

Advances in Computing and Future Communication Technologies (ICACFCT), International Conference on

作者： Soumya Das Monalisa Nayak Manas Ranjan Senapati Jeetamitra Satapathy Asst. Professor Computer Science Engineering Government College of Engineering Kalahandi Kalahandi India Asst. Professor Electronics and Telecommunication Engineering Indira Gandhi Institute of Technology Sarang Dhenkanal India Information Technology Veer Surendra Sai University of Technology Burla Sambalpur India Principal SD &amp Technical Education GOVT. ITI Bhubaneswar Bhubaneswar India

ISBN: (数字)9781665420761

ISBN: (纸本)9781665420778

Early diagnosis of the disease helps the patients to get through the disease. Diagnosis of medical datasets are carried out by different machine learning approaches. In this paper, Velocity Enhanced Whale Optimization Algorithm (VEWOA) is taken as classification algorithm to predict three different varieties of medical datasets like Heart disease, Echocardiogram and Hepatitis and then compared with Whale Optimization Algorithm (WOA). The classification accuracy of VEWOA-NN is 97.2 percentage in heart disease dataset, 96 percentage in echo-cardiogram dataset and 92.5 percentage in Hepatitis dataset. The performance validation is done with the help of Root Mean Square Error (RMSE) and time.

关键词： Support vector machines Heart Liver diseases Machine learning Communications technology Classification algorithms Root mean square

来源：评论

学校读者我要写书评

暂无评论

college students' Network behavior Using data mining and feature analysis

引用

Journal of Physics: Conference Series 2021年第1期2089卷

作者： Thatiparthi Sravani Srinivasa Rao Madala Sk HeenaKauser M. Tech. Scholar Department of Computer Science and Engineering Professor & HOD Department of Computer Science and Engineering Asst. Professor Department of Computer Science and Engineering PACE Institute of Technology and Sciences

Teachers may use advanced analytics to rapidly and correctly understand undergraduate behavior trends, especially when it comes to identifying undergraduate groupings that need to be focused on at a later time. This study uses data mining cluster analysis to analyze the constituent behavior of 3,245 undergraduates in a specific level 'B' institution's college network. According to the data, there are four different undergraduate groups with different Web access features, with 350 participants using the accomplishments and other variables of their success have an influence on these students. As a result of this research, we were able to collect data on undergraduate college network activity, which may be used to aid in the development of academic advising management.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Glimpse on Key Applications of Smart City under M2M Communication

引用

IOP Conference Series: Materials science and engineering 2021年第1期1022卷

作者： Sonam Kaushik Gaurav Aggarwal Sanjay Tejasvee Asst. Professor/Research Scholar Dept. of Engineering & Technology Gurugram Univ. Gurugram -122001-India Professor Dept. of Computer Science JIMS Bahadurgarh-124507-India Asst. Professor Computer Application Dept. Govt. Engineering College Bikaner 334004-India

In India, It is very necessary to make normal cities as smart cities near future. So, Develop a smart city is one of the most recent fields in today's digital era to researches. Machine to Machine (M2M ) communication is the latest innovative-fangled type of communiqué that enables full automation with the help of integrated applications to make a normal city to a smart city. Many devices are connected in a smart city to monitoring many tasks and it is a very challenging task to integrate and manage these connected devices. Interconnection of several devices and machines using the internet to form an M2M Area Network (M2MAN) provides controlling and monitoring smart applications like smart-metering, weather, environment, home, air quality, water supply with quality management, power supply with bill monitoring, traffic, and healthcare, etc. under M2M communication and integrated single level umbrella structured applications. Out of several M2M monitoring and controlling applications towards smart cities, few key applications are presented in this paper with their basic approach, workflow, and concerning issues and used technologies for the implementation with the brief growth analysis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Vision based Detection and Categorization of Skin lesions using Deep Learning Neural networks

引用

Procedia computer science 2020年 171卷 1726-1735页

作者： V. Srividhya K. Sujatha R.S. Ponmagal G. Durgadevi L. Madheshwaran V. Asst. Professor Dept. of EEE Meenakshi College of Engineering India Professor Dept. of EEE Dr. MGR Educational & Research Institute India Dept. of CSE SRM Institute of Science and Technology India Dept. of ECE New Prince Shri Bhavani College of Engineering and Technology India Dept. of EEE Dr. MGR Educational & Research Institute India

Melanoma is the deadly form of skin cancer. The melanocyte serves as the cause for the development of a malignant tumor on the skin. The dermatological photographs are used to detect the skin cancer. The objective of this project is to develop a structurized scheme to analyze and evaluate the probabilities of melanoma with the help of a typical user friendly camera. The novelty of this project is that it has a well developed strategy for skin cancer detection using high performance image based machine learning algorithms to execute intensity level adjustment at the preprocessing stage followed by segmentation and feature extraction from the region of interest, the lesion on the skin surface. This method uses images from the open source data base like DermIS and DermQuest. The preprocessing includes filtering and edge detection. For this purpose, convolution is used to remove the noise present followed by extraction of Highly Perceptive Features (HPF) like colour, irregularity, boundaries, shape and diameter. The correlation coefficients play an important role to determine the effectiveness in identifying the skin tumor and serves as a unique measure to identify the distinct input feature set for training the Convolutional Neural Network (CNN) so as to identify the malignant tumor on the skin surface. The Identification Efficiency (IE) is found to be 95% with a sensitivity of 93.3%.

关键词： Skin cancer Highly Perceptive Features Convolutional Neural Network Identification Efficiency

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Hash-Stego for Secured Message Transmission Using Stegnography

引用

IOP Conference Series: Materials science and engineering 2020年第2期981卷

作者： A. Pavan Kumar Lingam Gajjela N. Raghavendra Sai Asst. Professor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Asst. Professor Department of Computer Science and Engineering Narasimha Reddy Engineering College Assoc. Professor Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India

Steganography and cryptography is utilized together to fuse different layers security. Cryptography is a cryptographic framework and which is utilized to scramble the visual information. Cryptography is utilized in information stowing perpetually, secure the pictures, hidden picture, sight and sound and different fields. Steganography is the procedure for concealing mystery information into another information so it is basically more guaranteed about. In steganography the conundrum messages install in an innocuous looking spread, for example, a genuine picture chronicle, by then the picture is passed on. For scramble and unscramble the information we can utilize the cryptography procedure. The information are changed over into some other rubbish structure, and some time later the mixed information are passed on. Straightforwardly a days we have seen a smart improvement of correspondences security and the antonymous individual access conundrum information for the information correspondence experts. Cryptography and Steganography are the all around utilized procedures to vanquish this danger. LSB[1] method is utilized to camouflage the mixed message into annals. This undertaking is to improve another strategy for concealing riddle messages into video, the space of tending to the characters parallelly we are isolating the video chart utilizing steganalysis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detecting Faults within a Cloud Using Machine Learning Techniques

引用

IOP Conference Series: Materials science and engineering 2020年第2期981卷

作者： K. V. Daya Sagar J Kavitha Dr. Balabrahmeswara Kadaru M. Venkateswara Rao D. B. K. Kamesh Assoc. Professor Dept. of Electronics and Computer Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur Andhra Pradesh India-522502 Asst. Professor Dept. of CSE Malla Reddy Engineering College Hyderabad Telangana India Asst. Professor Dept. of CSE Gudlavalleru Engineering College Gudlavalleru Asst. Professor Dept. of ECE Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur Andhra Pradesh India-522502 Professor Dept. of Computer Science and Engineering Malla Reddy Engineering College Hyderabad Telangana India

In distributed computing, clients can get to cloud administrations using the web. In present days, in superior registering and cloud frameworks, disappointment is an inexorably significant issue. Alleviating the impact of misfortune and making stable conjectures with excellent lead time stays an overwhelming exploration issue as huge scope frameworks keep on creating in scale and multifaceted nature. Because of the advancing unpredictability of elite figuring frameworks, specific current adaptation to internal failure procedures, for Example, successive registration and replication are not adequate. It includes the significance of having a productive and useful way to deal with disappointment the executives set up to relieve the impacts of disappointment inside the framework. With the approach of AI methods, the capacity to gain from past data to anticipate future personal conduct standards makes it conceivable to foresee potential framework disappointment all the more precisely. Along these lines, in this paper, by applying a few calculations to improve the exactness of disappointment forecast, we investigate the prescient capacities of AI. We have set up an expectation of disappointment. The fundamental analysis that we have Random backwoods (RF), SVM, Classification and Regression Trees (CART) considered). Exploratory discoveries show that comparative with different calculations, the typical expectation precision of our paradigm utilising SVM while foreseeing breakdown is 92% exact and productive. This discovering implies that all likely future device and application disappointments can be viably imagined by our cycle inside.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Collaborative Filtering and Regression Techniques based location Travel Recommender System based on social media reviews data due to the COVID-19 Pandemic

引用

IOP Conference Series: Materials science and engineering 2020年第2期981卷

作者： K. V. Daya Sagar P. S. G. Arunasri Sridevi Sakamuri J. Kavitha DBK Kamesh Assoc. Professor Dept. of Electronics and Computer Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur Andhra Pradesh India-522502 Asst. Professor Dept. of Electronics and Computer Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur Andhra Pradesh India-522502 Asst. Professor Malla Reddy Engineering College Hyderabad Telangana India Professor Dept.of Computer Science and Engineering Malla Reddy Engineering College Hyderabad Telangana India

Nowadays, Dynamic industries like tourism is a enhance to boost many countries economy in recent years. The hotel sector leads to a significant role among all aspects of the tourism industry. Online travel platforms, in association with hotel management, are a part of hotel E-tourism that helps users to make travel plans online, suggest precise recommendations in consideration with the earlier feedbacks upon hotel stay. From the past few months, the user roaming ratio falls rapidly due to the COVID-19 Pandemic across the globe. In a business concern, this Pandemic affects all tourism sectors, specifically in the hotels' occupancy. To retain business positions and attract the users in these problematic scenarios, hotel and travel platform management concerns about past preferences of users, which have a significant impact on gratification for a comfortable stay. The current market trends show that user reviews are playing a vital role to select a hotel based on a safe location. Our work tries to find and recommend the dimensions that contribute more towards higher satisfaction levels of users in Asian continental top tourism city hotels listed by the Master and VISA Inc survey with item collaborative filtering and regression techniques based on Tripadvisor reviews from social media in recent times. The outcome of the work is helpful for Asian continental hotel management to concentrate more on the dimensions for obtaining better reviews. From an online travel platform perspective, this work suggests the contexts for the travel recommender system to gain things effectively from users.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Energy efficient clustering and routing in a wireless sensor networks

引用

Procedia computer science 2018年 134卷 178-185页

作者： Asha G.R. Gowrishankar Asst. Professor Department of Computer Science & Engineering B.M.S. College of Engineering Bangalore and 560019 India Professor Department of Computer Science & Engineering B.M.S. College of Engineering Bangalore and 560019 India

Wireless Sensor Network (WSN) is instrumental in transferring the data gathered by Sensors mounted on the Sensors Nodes (SNs) to the Base Station (BS). Lifetime of WSN is solely depends on the energy/battery life of SNs and higher the battery life longer the lifetime of Network. The sustained operation of WSN is achieved through the efficient consumption of SNs energy. In the recent past several energy conservation mechanism were proposed and among them LEACH-WSN was the most widespread methodology [1]. Further, the work pertaining to the sustained energy conservation mechanisms which are enriched with bio inspired technique or neural computational systems such as PSO-PSO-WSN, PSO-GSO-WSN, GSO-KGMO-WSN, FCM-PSO-GSO-WSN EBC-S or RSOM-WSN are reported [2-6]. In order to conserve energy in WSN; SNs are clustered using a set of criteria and gather the data at each Cluster Head (CH) to avoid redundant transfer of data to the BS. Further, gathered data is routed to the BS efficiently using intelligent routing process. In this paper, PSO-PSO-WSN, LEACH-WSN and EBC-S are compared with PSO-GSO-WSN, GSO-KGMO-WSN, FCM-PSO-GSO-WSN and RSOM-WSN. These methods are subjected to the Performance Evaluation (PE) in terms of alive nodes, dead nodes, energy consumption, throughput and total data/packet delivered.

关键词： Wireless Sensor Networks Clustering Routing Energy Consumption Network Lifetime

来源：评论

学校读者我要写书评

暂无评论

Process Capability & Fascinating applications of Friction Stud welding

引用

IOP Conference Series: Materials science and engineering 2020年第1期923卷

作者： D.S. Samuvel Prem Kumar R. Pravin S. Kavin Raj B. Benita N.Samuel Dinesh Hynes R. Nagarajan Asst.Professor Department of Mechanical Engineering JP College of Engineering Tenkasi Under Graduate Student Department of Mechanical Engineering Mepco Schlenk Engineering College (Autonomous) Sivakasi Assistant Professor Department of Computer Science & Engineering Francis Xavier Engineering College Tirunelveli-627002 Independent Researcher & Former Part Time Lecturer Department of Computer Science & Engineering Government College of Engineering Tirunelveli-627007

In earlier days, welding only involves joining two metals of same kind and dissimilar metals were usually joined by fasteners. Friction Stud welding is a true engineering marvel of making welds between dissimilar metals without any melting or fillers involved. The friction stud welding doesn't involve heat generation from electricity and it is purely based on friction. Besides these facts the friction stud welding has numerous advantage and applications. This paper focuses on the process of stud welding, application and its limitations.

关键词：

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：