TABLE 7 - uploaded by Yuichi Motai
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Cloud Colonography is proposed in this paper, using different types of cloud computing environments. The sizes of the databases from the Computed Tomographic Colonography (CTC) screening tests among several hospitals are explored. These networked databases are going to be available in the near future via cloud computing technologies. Associated Mul...
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Context 1
... are examined in Section 5.1 how databases are formed into AMD, Section 5.2 computational time, Section 5.3 memory usage, Section 5.4 running cost, and Section 5.5 parallelization. Table 7 shows how databases are formed into AMD. Three databases were generated from Table 4 for the analysis of both private and public cloud environments. ...
Context 2
... 9 shows the total computational time required for growing network database sizes in the Private Cloud and Desktop environment. The total training time was measured for three uncompressed databases listed in Table 7. The total training time was increased as the number of samples in- creased. ...
Citations
... The cloud may not be the best or most cost-effective place to do development work for every project [5]. Not all cloud environments are built with mass adoption in mind [6], and not all web-based offerings should be treated as full cloud computing systems in and of themselves [7]. ...
Many technologies are being considered to enhance the productivity of Industries such as IoT enabled smart services, cloud computing empowered on-premises services and machine learning assisted techniques for predicting future risk management. These technologies are gaining and producing insights with values to the product delivery. Continues customer services are also achieved through these technologies to bridge up the gap between client’s expectation with service providers. This 4.0 evolution is aiming to create and synchronize the interconnection between entities such as man, machines, and programming devices to enable the data-driven decision-making process. The various automation software and visualization software are used to identify the pain points of the industry concerning its consumers. Cloud computing is used to create internet-based service access to globally available consumers. This cloud technique is practised for the following reasons. 1. Development of new applications and services—Multiple Language Support. 2. Storage, backup, and recovery—All the types of data. 3. Hosting Applications—File hosting and Apps deployment. 4. Prompt Launch of Software—with subscription. 5. Multimedia support—Audio & Video. The main advantages of using these cloud-assisted services are improved collaboration, ease to access, unbounded storage capacity, low cost maintenance and security mechanisms. In this book chapter, the cloud computing architecture, technology solutions, deployment models, working principles, underlying virtualization concepts with industry practices are discussed and analysed in an explained view. A research study and report are also incorporated with industry 4.0 standards with its advancements.
Healthcare data is the most sensitive information for processing through machine learning and cloud computing in the various healthcare organizations. Electronic Health Record (EHR) manipulation are now on the rise, and we need to focus on using the data generated by the healthcare applications. Many sensitive data are associated with various health care domains, particularly neurology and cardiology. Previous approaches, such as manual data records, had significant disadvantages, and hence disease prediction based on the above records was found ineffective resulting with improper diagnosis on the patients. These data records require special attention, and current frameworks focused on these areas must implement sophisticated technologies to predict specific patterns. To address the above concerns, the proposed work incorporates the integration of Neuro Fuzzy Logistic Regression (NFLR) machine learning algorithm and cloud computing storage management to solve these problems. The usage of cloud storage reduces data duplication while handling the storage of EHRs where the proposed ML algorithm accurately predict the disease. In the proposed research, the features are extracted using a specific algorithm –Self-organizing Clustering (SOC) which forms a clustered data with highest weight. To select the maximum number of features, and to predict the disease risk factors, the S2NO algorithm and NFLR algorithms are used in this work. Further, the database storage estimation with fuzzy rules, logistic analysis, and other benefits such as experimental learning of different ML tools, data privacy constraints related to healthcare are considered in this paper.
The combination of cloud computing and medicine, telemedicine, post-discharge care plan, and such virtual compliance with the drug can improve many medical-related functions. Also, to improve access to healthcare services through telemedicine. The reader to their various application types of the medical field and the processor before this. Description of peripheral equipment and tools to be used in embedded systems are also discussed here. Our focus is the medical equipment of the new era, and we, too, contains some of the existing medical equipment. A variety of bacterial infections is a significant problem for humans and a health threat. Revealing antimicrobial compounds' interactions with a biological agent has stimulated scientists to find new solutions to treat these diseases. (Personal Computer) PC, smartphone, tablet, wearable. Cloud computing technology access storage through a device connected to the Internet and files, software, and on the server to enable the user. Where the cloud computing providers store and process data are separated from the end-user. Antibiotics are rarely as long and not required to treat upper respiratory tract infections that doctors do not suspect a bacterial infection; you should generally avoid. In this way, a simple, such as to cover the surface properly wash their hand's technology, while coughing or sneezing, you can reduce the spread of respiratory infections. It will introduce some basic concepts related to antimicrobial agents. Novel compounds describe the correlation between the activity in vitro and in vivo synthetic path way and antibacterial substances specific design techniques, and polymeric materials. Mechanism of action, and efficacy in vivo, its raw data is reviewed about selecting antimicrobial resistance mechanisms most commonly used.
