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ARIMA time Series Model vs. K-Means Clustering for Cloud Workloads Performance

ARIMA time Series Model vs. K-Means Clustering for Cloud Wor...

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Emerging Trends in Industry 4.0 (ETI 4.0)

作者： Vishnu Kumar Mishra Megha Mishra Sunil Tekale T Naga Praveena Rachakonda Venkatesh Bhupesh Kumar Dewangan Department of Computer Science and Engineering Shri Shankaracharya Technical campus CSVTU University Bhilai Chhattisgarh India Department of Computer Science and Engineering Malla Reddy College of Engineering Secunderabad Telangana India Department of Computer Science and Engineering OP Jindal University Raigarh India

To develop a thriving ability plan and protect the observable of Internet service providers of cloud environment, the increased heterogeneity brought on by various Cloud workloads, such as Business data analytics, Big data, IoT and calls for exact sensors. Although K-Means is an easy and quick clustering technique, it might not fully account for the heterogeneity present in Cloud platform workloads. The Multiple patterns can be found using ARIMA time series Models, which is trained for data prediction on cloud be combined into cohesive, homogenous components that closely resemble the data set’s actual patterns. In order to assess the cluster suggest the two different approaches for heterogeneity in resource utilization of Cloud infrastructure, this study compares ARIMA time series Model and K- Means. Clusters generated using K-Means yield significantly abstracted information, according to Bitbrains’ experiments using Google cluster trace and business-critical workloads. A more accurate clustering with discrete usage boundaries is provided by the ARIMA time series Model. Even though the ARIMA time series Model takes longer to compute than K-Means, it can be employed when a finer-grained characterization and study of the workload is needed.

关键词： Cloud computing Computational modeling Time series analysis Predictive models Probabilistic logic Behavioral sciences Central Processing Unit

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Research on Service Evaluation Improvement of Hot Pot Restaurants Based on data Mining

Research on Service Evaluation Improvement of Hot Pot Restau...

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Information and computing Research (iCORE), international conference in

作者： Lei Liu Qingyu Liu School of Computer Science Huainan Normal University Huainan Anhui China College of Computing and Information Technologies National University Manila Philippines

The development of big data technology has promoted the digitalization of social resources and opened up new areas of value for various industries. In recent years, China's hot pot industry has developed rapidly, but with the increase of users, the industry has also faced the development bottleneck of improving personalization and precision services. Relying on the online ordering website, we use data mining technology to obtain online ordering and evaluation data of users. By modeling these data and analyzing the correlation between dishes and user evaluation, it is found that hot pot restaurants will have a great impact on users' satisfaction in terms of dishes taste, type of dishes, and service quality. The research results based on this article can provide reference for the quality of the restaurant to improve the quality of service, and it is also expected to promote the orderly development of the hot pot industry.

关键词： Industries Analytical models Correlation Quality of service Big data data models data mining

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A Taxonomy towards fog computing Resource Allocation

A Taxonomy towards fog computing Resource Allocation

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international conference on Innovative Sustainable Computational technologies (CISCT)

作者： V. Vasuki Rohinidevi Prabhat Kumar Srivastava Nilesh Dubey Shivam Tiwari Sweeti Ashish Tiwari B V Raju Institute of Technology Narsapur India IMS Engineering College Ghaziabad U.P India Devang Patel Institute of Advance Technology and Research Charotar University of Science and Technology India G L Bajaj Institute of Technology and Management Greater Noida India CSE Department BBD University Lucknow India CSE Department Amity University Lucnkow India

ISBN: (纸本)9781665474177

Fog computing is the opportunity of an exercise floor that stretches from the exterior edges of the spot information are made to the spot it will in this manner be dealt with, whether that is in the cloud or in a client's server farm. Fog is an more layer of a dissipated undertaking's shut surroundings and is unfalteringly related with apportioned enlisting and the internet of troubles of the Internet of Things (IoT). Public basis as an assist (IaaS) cloud outlets must be seen at a simple level, the normal endpoint for information. The locale of the affiliation is the spot data from IoT contraptions made.

关键词： Cloud computing Taxonomy Internet of Things Servers Resource management Floors Edge computing

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Decentralized Voting System

Decentralized Voting System

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

作者： Sachin Kumar Shoaib Akhtar Soumalya Ghosh Kavita Saini School of Computing Science and Engineering Galgotias University Delhi NCR India

The evolution of Blockchain has given way to a Smart World where there is improved security and integration of devices, systems, and processes with humans through all-pervasive connectivity. There are numerous secure applications using Blockchain like smart cities, Cloud computing, Smart Management of the Environment and Healthcare, etc.A decentralized voting system is an option for the paper ballot system and EVM (Electronic Voting Machines). Democracies need a decentralized voting system that offers security, integrity, immutability, transparency, and privacy to voters. Blockchain is an emerging technology that offers integrity, immutability, and decentralization of data. Moving our traditional voting system to Blockchain technology can increase voter confidence. This paper describes an attempt to influence the advantages of Blockchain, such as cryptography and transparency, to accomplish an efficient scheme for a decentralized voting system using the Ethereum network. Smart contracts are profound chunks of codes, which are included in the Blockchain and then execute written code as planned in each stage of Blockchain updates. Decentralized voting is one of the trending topics, but is yet to be significant, compared to the other e-services.

关键词： Privacy Cloud computing Codes Electronic voting systems Smart cities Smart contracts Process control

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Query-Based Image Retrieval Using SVM 5th

Query-Based Image Retrieval Using SVM

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5th international conference on Emerging technologies in Computer Engineering: Cognitive computing and Intelligent IoT, ICETCE 2022

作者： Janu, Neha Gupta, Sunita Nawal, Meenakshi Choudhary, Pooja Department of Computer Science and Engineering Swami Keshvanand Institute of Technology Management and Gramothan Jaipur India Department of Information Technology Swami Keshvanand Institute of Technology Management and Gramothan Jaipur India Department of Electronics and Communication Engineering MNIT Jaipur India Department of Electronics and Communication Engineering Swami Keshvanand Institute of Technology Management and Gramothan Jaipur India

ISBN: (纸本)9783031070112

In today’s world, images are used to extract information about objects in a variety of industries. To retrieve images, many traditional methods have been used. It determines the user’s query interactively by asking the user whether the image is relevant or not. Graphics have become an important part of information processing in this day and age. The image is used in image registration processing to extract information about an item in a variety of fields such as tourism, medical and geological, and weather systems calling. There are numerous approaches that people use to recover images. It determines an individual’s query interactively by asking users whether the image is relevant (similar) or not. In a content-based image retrieval (CBIR) system, effective management of this image database is used to improve the procedure’s performance. The study of the content-based image retrieval (CBIR) technique has grown in importance. As individuals, we have studied and investigated various features in this manner or in combinations. We discovered that image Registration Processing (IRP) is a critical area in the aforementioned industries. Several research papers examining color feature and texture feature extraction concluded that point cloud data structure is best for image registration using the Iterative Closest Point (ICP) algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Feature extraction

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Comparison of Augmentation and Preprocessing Techniques for Improved Generalization Performance in Deep Learning based Chest X-Ray Classification

Comparison of Augmentation and Preprocessing Techniques for ...

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Trends in Quantum computing and Emerging Business technologies (TQCEBT), international conference on

作者： Shubhra Prakash B Ramamurthy Computer Science Department CHRIST (Deemed to be University) Bengaluru India

ISBN: (纸本)9781665453622

Convolutional Neural Network (CNN) models are well known for image classification; however, the downside of CNN is the ineffectiveness to generalize and inclination towards over-fitting in case of a small train dataset. A balanced and sufficient data is thus essential to effectively train a CNN model, but this is not always possible, especially in the case of medical imaging data, as often patients with the same disease are not always available. Image augmentation addresses the given issue by creating new data points artificially with slight modifications. This study, investigates ten different methods with various parameters and probability and their combined effect on the test dataset’s generalization performance and F1 Score. For the study, three pre-trained CNN models, namely ResNetl8, ResNet34, and ResNet50, are fine tuned on a small training dataset of 500 Pneumonia and 160 Non-Pneumonia(Normal) Images for each augmentation setting. The test accuracy, F1 Score, and generalization performance were calculated for a test dataset consisting of 50 Pneumonia and 16 Non-Pneumonia(Normal) Images.

关键词： Deep learning Training Pulmonary diseases Transfer learning data models Convolutional neural networks Reliability

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IPFS-Based Image Sharing Using Perceptual Hash Code with Digital Right Management 2nd

IPFS-Based Image Sharing Using Perceptual Hash Code with Dig...

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2nd international conference on Emerging technologies for computing, Communications, and Smart Cities, ETCCS 2021

作者： Geethanjali, D. Priya, R. Bhavani, R. Department of Computer Science and Engineering Annamalai University Tamilnadu Chidambaram India

ISBN: (纸本)9789811902833

In the current scenario, a large amount of information is exchanged over the Internet. An unauthorized user access may cause the information to be modified, disseminated, misused, detected, and used. Digital rights management (DRM) is a method of preserving copyrights in digital media. It often requires more elements than simply restricting or prohibiting copies of the content. This strategy includes the deployment of technologies that limit the copying and use of copyrighted works as well as proprietary software. The proposed approach has two modules. They are hash code generation of an image and Store and retrieve the data from IPFS. First, select the watermarked image. The different types of perceptual hashes are average hash, perceptual hash, difference hash, and wavelet hashing. The perceptual hash codes are generated for the selected watermarked image. Then, the watermarked image and created copyright text files are shared through the IPFS system. The goal of this proposed system is to compare the perceptual hashes by using the hamming distance, size of the image, and calculation time. Based on the evaluation, difference hash algorithm provides a better result. So, it is used to check whether the send and retrieve files of IPFS are similar or not. In the IPFS file system, hash codes are used to find the location of a file effectively and securely. This paper proposes, how IPFS and perceptual hashes are preventing unauthorized user access to the system while sharing the images over the Internet. Genuine image authors’ copyrights are protected by using perceptually identical images on a decentralized blockchain IPFS store. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Copyrights

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A Sliding Window Blockchain Architecture for the Internet of Things

A Sliding Window Blockchain Architecture for the Internet of...

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advances in science and Technology (ICAST), international conference on

作者： Shelke Kavita Dakshayani G Department of Computer Engineering Fr. C. Rodrigues Institute of Technology Vashi Navi Mumbai India

ISBN: (纸本)9781665492645

The Internet of Things is a concept that allows people to connect to the Internet and access services through new, unconventional computing and communication practices. But there are two issues in the Internet of Things. These are security and data protection. Due to the limited processor, storage, and energy resources of IoT devices existing security frameworks are unable to meet the essential security requirements. Centralized security is not good for IoT as they tend towards a single point of failure and are more expensive for protecting centralized resources against attacks. Therefore, decentralized IoT security must be adapted. Blockchain is a a decentralised security system that can be used to secure many different things. Blockchain is not currently appropriate technology for IoT because it is too complicated and poorly scalable. This paper shows research on and implementation of Sliding Window Blockchain (SWBC), a conventional blockchain architecture used in Internet of Things applications. SWBC's performance is computed using live data which is supplied by a smart home testbed.

关键词： Energy resources data protection Computer architecture Smart homes Blockchains Internet of Things Security

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Implementation of Blockchain Technology in IOT Based Smart Home

Implementation of Blockchain Technology in IOT Based Smart H...

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advances in science and Technology (ICAST), international conference on

作者： Kanad Gaikwad Kaustubh Kulkarni Surekha Kohle Pradnya Patil Department of MCA Veermata Jijabai Technological Institute Mumbai India Department of Computer Engineering Veermata Jijabai Technological Institute Mumbai India Department of Computer Engineering K. J. Somaiya Institute of Engineering & IT Mumbai India

ISBN: (纸本)9781665492645

Internet of things presents itself as an easy, effective and efficient framework for making homes smarter. Although, with its numerous advantages, it lacks a decentralized local system. The centralized cloud approach will be solved by the Blockchain, with a decentralized framework. Various safety concerns, threats, and attacks, as well as difficulties with user privacy and integrity persists in smart homes. Blockchain is being used in many IoT applications, to overcome security issues. This paper describes the three main levels of the blockchain in smart homes and how it can safeguard data and transactions while also describing IoT security assessments.

关键词： Privacy Cloud computing Protocols Authentication Smart homes Blockchains Safety

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Fusion Biometric Deep Features Blended in Its Authentication

Fusion Biometric Deep Features Blended in Its Authentication

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Advanced technologies in Intelligent Control, Environment, computing & Communication Engineering (ICATIECE), international conference on

作者： Manjula Gururaj Rao Sumathi Pawar H Priyanka K Hemant Kumar Reddy Usha Divakarala NITTE (Deemed to be University) NMAM Institute of Technology Nitte Karkala Computer Science & Engineering PES University Bangaluru Computer Science & Engineering VIT AP University AP

ISBN: (纸本)9781665493970

Information security is a key factor in a world where technology is developing quickly in terms of data and data interpretations. The most important objective is to have a secure system. Biometrics, OTP generation, iris detection, and other security-related measures are done to secure the system. One of the more established security technologies is the biometric system. In the case of getting the security from the biometrics fails if it depends on only one biometric feature. Nowadays combinations of biometric features are developed to secure the system. The proposed system can have type 1, type 2, type 3 and type 4 security to access the ITS (Intelligent Transport System). The type1 has only one biometric feature. Type 2, 3 and 4 have a blending of 2,3and 4 biometric features. The proposed system considers biometric features such as periocular, iris, fingerprint and voice modulation. We applied the different deep-learning models to get the desired result

关键词： Privacy Biometrics (access control) Smart cities Biological system modeling Transfer learning Authentication Modulation

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