Data Mining - Concepts and Techniques.

Containers as a lightweight technology to virtualise applications have recently been successful, particularly to manage applications in the cloud. Often, the management of clusters of containers becomes essential and the orchestration of the construction and deployment becomes a central problem. This emerging topic has been taken up by researchers, but there is currently no secondary study to consolidate this research. We aim to identify, taxonomically classify and systematically compare the existing research body on containers and their orchestration and specifically the application of this technology in the cloud. We have conducted a systematic mapping study of 46 selected studies. We classified and compared the selected studies based on a characterisation framework. This results in a discussion of agreed and emerging concerns in the container orchestration space, positioning it within the cloud context, but also moving it closer to current concerns in cloud platforms, microservices and continuous development.

Cloud Container Technologies: A State-of-the-Art Review

Over the past few decades, interest in theories and algorithms for face recognition has been growing rapidly. Video surveillance, criminal identification, building access control, and unmanned and autonomous vehicles are just a few examples of concrete applications that are gaining attraction among industries. Various techniques are being developed including local, holistic, and hybrid approaches, which provide a face image description using only a few face image features or the whole facial features. The main contribution of this survey is to review some well-known techniques for each approach and to give the taxonomy of their categories. In the paper, a detailed comparison between these techniques is exposed by listing the advantages and the disadvantages of their schemes in terms of robustness, accuracy, complexity, and discrimination. One interesting feature mentioned in the paper is about the database used for face recognition. An overview of the most commonly used databases, including those of supervised and unsupervised learning, is given. Numerical results of the most interesting techniques are given along with the context of experiments and challenges handled by these techniques. Finally, a solid discussion is given in the paper about future directions in terms of techniques to be used for face recognition.

https://www.mdpi.com/1424-8220/20/2/342/pdf

Face Recognition Systems: A Survey

The recent development of nanotechnology led to the concept of using suspended nanoparticles in heat transfer fluids to improve the heat transfer coefficient of the base fluids. Specifically, numerical studies are reviewed in this study to get a clear view and detailed summary of the influence of several parameters such as type of nanoparticle and host liquid, particle volume concentration, particle size, particle shape, Brownian diffusion and thermophoresis effect on hydrodynamic and thermal characteristics of convective heat transfer using nanofluids. In addition, the paper provides detailed information about the most of commonly-used correlations which are utilized to predict the effective thermophysical properties of nanofluids. Finally, the main aim upon which the present work is based is to give a comprehensive review on different CFD approaches employed in numerical simulation of nanofluid flow, address the pros and cons of each approach, and find the suitable technique which gives more credible results as compared to experimental results.

Numerical study of convective heat transfer of nanofluids: A review

Advances in imaging technology have made the capture and display of digital images ubiquitous. A variety
of displays are used to view them, ranging from high-resolution computer monitors to low-resolution mobile
devices, and images often have to undergo changes in size and aspect ratio to adapt to different screens. Also,
displaying and printing documents with embedded images frequently entail resizing of the images to comply with
the overall layout. Straightforward image resizing operators, such as scaling, often do not produce satisfactory
results, since they are oblivious to image content. In this work, we review and categorize algorithms for contentaware
image retargeting, i.e., resizing an image while taking its content into consideration to preserve important
regions and minimize distortions. This is a challenging problem, as it requires preserving the relevant information
while maintaining an aesthetically pleasing image for the user. The techniques typically start by computing an
importance map which represents the relevance of every pixel, and then apply an operator that resizes the image
while taking into account the importance map and additional constraints. We intend this review to be useful to
researchers and practitioners interested in image retargeting.

A survey of image retargeting techniques

It is well known that the images, often used in variety of computer applications, are difficult to store and transmit. One possible solution to overcome this problem is to use a data compression technique where an image is viewed as a matrix and then the operations are performed on the matrix. Image compression is achieved by using Singular Value Decomposition (SVD) technique on the image matrix. The advantage of using the SVD is the property of energy compaction and its ability to adapt to the local statistical variations of an image. Further, the SVD can be performed on any arbitrary, square, reversible and non reversible matrix of m x n size. In this paper, SVD is utilized to compress and reduce the storage space of an image. In addition, the paper investigates the effect of rank in SVD decomposition to measure the quality in terms of MSE and PSNR.

Image Compression Using SVD

Face Recognition Using Gabor Wavelet Features with PCA and KPCA - A Comparative Study☆

Image interpolation has many applications in computer vision, image processing and biomedical applications. Resampling is required for discrete image manipulations, such as geometric alignment and registration, to improve image quality on display devices or in the field of lossy image compression wherein some pixels are discarded during the encoding process and must be regenerated from the remaining information for decoding. The comparison is done for different interpolation techniques such as nearest neighbor, bilinear and bicubic interpolation and the comparison is done for different interpolation schemes using universal image quality index. In this paper an attempt is made to highlight the universal quality index by comparing with error measures such as MSE and PSNR.

Image Scaling Comparison Using Universal Image Quality Index

In this paper we attempt to provide unified security and privacy multilateral security architecture for cloud services stack, using key latest technology via LxC in general and Docker containers in specific. Docker is one of the first to use LxC at such a large scale, but LxC is not a very new concept, it is around for quite some time. Docker container service is a key Platform as a Service (PaaS) based engine. Unified layered cloud computing multilateral security implementation addresses the potential risks associated with cloud computing environment. It also specifies when, at what time, where, and how to apply security controls. Unified Design includes the structured connection between the components of cloud ecosystem for basket and bucket of unified cloud-based hybrid services using micro service oriented venture architectural services realized in terms of PAAS using Docker container as a service. We surveyed various industry/academic professionals and based on our experience we tried to understand the challenges they faced while using the cloud system. We tried to understand the security challenges, incidents, story pieces, accidents, experience they faced while designing, implementing and using the cloud services/resources virtually via online. This work helps to assess the security design and architecture quality using multilateral security framework for Docker container. We try to present the architecture using OSI/TCP/IP stack model with reference to Cloud service stack model and deployment stack model and try to propose the balanced multilateral security prototype with reference to Docker Container security architecture.

Docker container security via heuristics-based multilateral security-conceptual and pragmatic study

https://cyberleninka.org/article/n/567557.pdf

K. N. Balasubramanya Murthy

Papers

Image Compression Using SVD

Face Recognition Using Gabor Wavelet Features with PCA and KPCA - A Comparative Study☆

Image Scaling Comparison Using Universal Image Quality Index

Docker container security via heuristics-based multilateral security-conceptual and pragmatic study

Two Novel Detector-Descriptor Based Approaches for Face Recognition Using SIFT and SURF