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检索条件"丛书名=Learning and Analytics in Intelligent Systems"

共 229 条记录，以下是61-70 订阅

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The Mechanism of Generating the Automated Java Unit Test Cases by Achieving Maximum Code Coverage 1

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作者： Avadhani, Bindu Giri, Saumya Ranjan Pulipati, Venkateswara Rao VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad India ITC Infotech Ltd. Bengaluru India

ISBN: (数字)9789811592935

ISBN: (纸本)9789811592928;9789811592959

The code coverage, being the factor of focus on unit testing that tells us which part of the source code is tested or untested. If the code consists of abstract classes or interfaces, they are also to be tested to ensure the maximum code coverage as generating the high coverage test suites play an important role in realistic systems like airbag systems, autopilot systems, etc. Thus, the correctness in the functionality is properly tested. Mocking is the process of constituting an imitation of the object. It is the technique of unit testing where the virtual objects are created to mock the behavior of the actual object, which helps us to bypass faults to some other class or system like database operation, REST API calls, etc. Hence, this proposed work has been designed to generate highly covered test cases in the aspects of Java. This work helps us to produce the test cases along with the skeleton, which forms a syntactically correct JUnit. It helps to test the subclasses implementing the Abstract class’s methods and classes implementing interfaces, to generate the test cases for no access modifier methods. The generated test cases support mocking as well. Mockito framework is being used to do so. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Java programming language

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Surface Wear Rate Prediction in Reinforced AA2618 MMC by Employing Soft Computing Techniques 1

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作者： Mathan Kumar, N. Mohanraj, N. Sendhil Kumar, S. Daniel Das, A. Sabareesaan, K.J. Adwan, Omar Akshaya College of Engineering and Technology Coimbatore India Sri Krishna College of Technology Coimbatore India Karpagam Academy of Higher Education Coimbatore India University of Technology and Applied Science Nizwa Oman Al-Ahliyya Amman University Amman Jordan

ISBN: (数字)9783030654078

ISBN: (纸本)9783030654061;9783030654092

As a result of the enhancement of mechanical and thermal properties, Metal matrix Composites (MMC) has shown enormous potentials as a likely material for various aerospace and automotive applications. Thermomechanical wear properties of Aluminium Alloy (AA 2618) is reinforced with Silicon Nitride (Si3N4), Aluminium Nitride (AlN) and Zirconium Boride (ZrB2) have been investigated in the proposed work. For the fabricated MMC, the prediction of wear features can be developed by the regression model and employing Statistical and Data Analysis named Minitab. The predicted response was found to be a linear with the actual responses. Utilizing the Support Vector Machine (SVM) and Artificial Neural Networks (ANN), prediction of the wear characteristics is performed with the developed regression model. The statistical performance parameter through ANN exhibits the minimization of the Mean Absolute Error (MAE) when compared to other approaches. The % of MAE through the soft computing techniques such as ANN, SVM, LR are 10%, 26% and 29% respectively. Predicted values obtained by means of the proposed approaches through the optimized ANN model are having sustained consistency on par with the conventional values. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Reinforcement

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Privacy and Data Protection Challenges in the Distributed Era 1st ed. 2022

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丛书名： learning and analytics in intelligent systems

2022年

作者： Eugenia Politou Efthimios Alepis Maria Virvou Constantinos Patsakis

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Digital Cities Roadmap: IoT-Based Architecture and Sustainable Buildings

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丛书名： Advances in learning analytics for intelligent cloud-IoT systems

2021年

作者： Solanki

ISBN: (数字)9781119792055;9781119792062

ISBN: (纸本)9781119791591

DIGITAL CITIES ROADMAP This book details applications of technology to efficient digital city infrastructure and its planning, including smart *** urbanization, demographic changes, environmental changes, and new technologies are changing the views of urban leaders on sustainability, as well as creating and providing public services to tackle these new dynamics. Sustainable development is an objective by which the processes of planning, implementing projects, and development is aimed at meeting the needs of modern communities without compromising the potential of future generations. The advent of Smart Cities is the answer to these *** Cities Roadmap provides an in-depth analysis of design technologies that lay a solid foundation for sustainable buildings. The book also highlights smart automation technologies that help save energy, as well as various performance indicators needed to make construction easier. The book aims to create a strong research community, to have a deep understanding and the latest knowledge in the field of energy and comfort, to offer solid ideas in the nearby future for sustainable and resilient buildings. These buildings will help the city grow as a smart city. The smart city has also a focus on low energy consumption, renewable energy, and a small carbon *** information provided in this book will be of value to researchers, academicians and industry professionals interested in IoT-based architecture and sustainable buildings, energy efficiency and various tools and methods used to develop green technologies for construction in smart cities.

关键词： Artificial Intelligence

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Smart Healthcare System Design: Security and Privacy Aspects 1

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丛书名： Advances in learning analytics for intelligent Cloud-IoT systems

2021年

作者： Islam

ISBN: (数字)9781119792239;9781119792246

ISBN: (纸本)9781119791683

SMART HEALTHCARE SYSTEM DESIGN This book deeply discusses the major challenges and issues for security and privacy aspects of smart health-care systems. The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security. The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies. Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations. Audience: Researchers and industry engineers in information tec

关键词： Artificial Intelligence

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Agricultural Informatics: Automation Using the IoT and Machine learning 1

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丛书名： Advances in learning analytics for intelligent Cloud-IoT systems

2021年

作者： Choudhury

ISBN: (数字)9781119769217;9781119769224

ISBN: (纸本)9781119768845

Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world"s economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc. Agricultural Informatics: Automation Using the IoT and Machine learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.

关键词： Artificial Intelligence

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Machine learning Techniques and analytics for Cloud Security 1

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丛书名： Advances in learning analytics for intelligent Cloud-IoT systems

2021年

作者： Rajdeep Chakraborty Anupam Ghosh Jyotsna Kumar Mandal

ISBN: (数字)9781119764113

ISBN: (纸本)9781119762256

MACHINE learning TECHNIQUES AND analytics FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine learning Techniques and analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. Audience Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography.

关键词： Artificial Intelligence

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Classification of Credit Dataset Using Improved Particle Swarm Optimization Tuned Radial Basis Function Neural Networks

Classification of Credit Dataset Using Improved Particle Swa...

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International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM)

作者： Pandey, Trilok Nath Giri, Parimal Kumar Jagadev, Alok Kumar S O Deemed Be Univ Dept Comp Sci & Engn Bhubaneswar 751030 India Fakir Mohan Univ Dept Informat & Commun Technol Balasore 756019 India KIIT Deemed Be Univ Sch Comp Sci Bhubaneswar 751020 India

ISBN: (纸本)9783030390334;9783030390327

Credit risk assessment is acting as a survival weapon in almost every financial institution. It involves an in-depth and sensitive analysis of various economic, social, demographic, and other pertinent data provided by the customers and about the customers for building a more accurate and robust electronic finance system. The classification problem is one of the primary concerns in the process of analyzing the gamut of data;however, its complexity has ignited us to use machine learning-based approaches. In this paper, radial basis function neural network (RBFNN) with particle swarm optimization (RBFNN + PSO) and improved particle swarm optimization tuned radial basis function neural network (RBFNN + IMPSO) learning algorithms have been studied and compared their effectiveness for credit risk assessment. The experimental findings draw a clear line between the proposed model and traditional learning algorithms. Moreover, the proposed method is very promising vis-a-vis of individual classifiers.

关键词： RBFN Credit risk PSO IMPSO Neural network Machine learning

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An intelligent System on Computer-Aided Diagnosis for Parkinson's Disease with MRI Using Machine learning

An Intelligent System on Computer-Aided Diagnosis for Parkin...

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International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM)

作者： Naren, J. Ramalingam, Praveena Rajeswari, U. Raja Vijayalakshmi, P. Vithya, G. SASTRA Deemed Univ Thanjavur Tamil Nadu India KL Univ Vijayawada AP India

ISBN: (纸本)9783030390334;9783030390327

Parkinson's disease (PD), an intensifying neurological disorder is predominantly because of failing dopaminergic neurons of the midbrain. Dopamine is involved in sending of messages to those parts that controls coordination and movement in brain. With the help of Machine learning approaches, it sets a base for an intelligent system that helps in computer-aided diagnosis of PD patients. Machine learning is used for early diagnosis and prediction so that it can be utilized to treat the disease quicker. In medicinal science, it is visible that outputs from the imaging devices can be incorporated for predicting a disease better. The paper specifies a brief synopsis of Machine learning techniques along with MRI data which can yield faster prediction of PD.

关键词： Parkinson's disease Machine learning MRI

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Survey of Methods Used for Differential Expression Analysis on RNA Seq Data

Survey of Methods Used for Differential Expression Analysis ...

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International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM)

作者： Joshi, Reema Sarmah, Rosy Tezpur Univ Dept CSE Tezpur Assam India

ISBN: (纸本)9783030390334;9783030390327

Gene expression indicates the amount of mRNA produced by a gene under a particular biological condition. Genes responsible for changes in biological conditions of an organism will have different gene expression values across different conditions. Gene expression analysis is useful in the domain of transcriptomic studies to analyse functions of and interactions among different molecules inside a cell. A significant analysis is that of a differential gene, that is a gene that exhibits strong change in behaviour between two or more conditions. Thus behavioural cell changes can be attributed to the differentially expressed genes. Statistical distributional properties in the read counts that constitute RNA-seq data are used for detecting the differentially expressed genes. In this paper we provide a comparison study of different tools which aid in RNA-seq based differential expression. It is important to note how the results of these tools differ and which tool provides more statistically significant results for the same.

关键词： RNa-seq Differential expression Differential gene Empirical study Differential expression tools

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