Security Enhancement in Image Steganography

Steganography helps in communication of secured data in several carries like images, videos and audio. It undergoes many useful applications and well known for ill intentions. It was mainly proposed for the security techniques in the increase of computational power, in order to have security awareness like individuals, groups, agencies etc. The factors that are separated from cryptography and water making are data is not detectable; capacity of hidden data is unknown and robustness of medium. The steganography provides different methods existing and guidelines. The current technology of image steganography involves techniques of LSB in image domain but once the attacker acknowledges that medium is containing embedded data he will attack the medium and breaks into the secured content. In this paper we are discussing how to protect the steganography image by embedding it into another medium using mat lab. Here we work on image matrices to perform the steganography. Lightness adjustment on the matrix is done to reduce the brighter pixels in image. The lightness decreased image then embedded into another cover image by matrix difference technique (will be discussed in detail)

COST-EFFICIENT RESOURCE PROVISIONING FOR CLOUD-ENABLED SCHEDULERS

Since the last decade, public cloud platforms are rapidly becoming de-facto computing platform for our society. To support the wide range of users and their diverse applications, public cloud platforms started to offer the same VMs under many purchasing options that differ across their cost, performance, availability, and time commitments. Popular purchasing options include on-demand, reserved, and transient VM types. Reserved VMs require long time commitments, whereas users can acquire and release the on-demand (and transient) VMs at any time. While transient VMs cost significantly less than on-demand VMs, platforms may revoke them at any time. In general, the stronger the commitment, i.e., longer and less flexible, the lower the price. However, longer and less flexible time commitments can increase cloud costs for users if future workloads cannot utilize the VMs they committed to buying. Interestingly, this wide range of purchasing options provide opportunities for cost savings. However, large cloud customers often find it challenging to choose the right mix of purchasing options to minimize their long-term costs while retaining the ability to adjust their capacity up and down in response to workload variations. Thus, optimizing the cloud costs requires users to select a mix of VM purchasing options based on their short- and long-term expectation of workload utilization. Notably, hybrid clouds combine multiple VM purchasing options or private clusters with public cloud VMs to optimize the cloud costs based on their workload expectations. In this thesis, we address the challenge of choosing a mix of different VM purchasing options in the context of large cloud customers and thereby optimizing their cloud costs. To this end, we make the following contributions: (i) design and implement a container orchestration platform (using Kubernetes) to optimize the cost of executing mixed interactive and batch workloads on cloud platforms using on-demand and transient VMs, (ii) develop simple analytical models for different straggler mitigation techniques to better understand the cost of synchronization in distributed machine learning workloads and compare their cost and performance on on-demand and transient VMs, (iii) design multiple policies to optimize long-term cloud costs by selecting a mix of VM purchasing options based on short- and long-term expectations of workload utilization (with no job waiting), (iv) introduce the concept of waiting policy for cloud-enabled schedulers, and show that provisioning long-term resources (e.g., reserved VMs) to optimize the cloud costs is dependent on it, and (v) design and implement speculative execution and ML-based waiting time predictions (for waiting policies) to show that optimizing job waiting in the cloud is possible without accurate job runtime predictions

EFFECTS OF PRANAYAMA AND SURYANAMASKAR YOGIC PRACTICE ON COGNITIVE PERFORMANCE IN MEDICAL STUDENTS

Background: Recent studies have suggested that yoga reduce stress levels and anxiety accordingly reducing stress increases cognitive performance. The present study attempted to determine the combined yoga practice is associated with higher cognitive performance in medical students. Materials & Methods: All the instructions were given to the participants, they were asked to Unscramble 20 scrambled words in 5 minutes of time. The score was noted and were asked to perform yoga for four weeks. The same score was collected after yoga session and was compared with the previous values. Result: Analysis showed that the yoga group (M=15.2, SD=4.25) and the pre yoga group (M=09.49, SD=3.11) did not differ significantly on cognitive performance, p=<0.005. Conclusion: Combined effect of Pranayama and suryanamaskar are beneficial effect on improving cognitive function but it was statically insignificant.KEYWORDS:  Pranayama, suryanamaskar; Yoga; Cognitive functions

Surfaces with Patterned Wettability: Design and Applications.

Surfaces with patterned wettability have well-defined domains containing both wettable and non-wettable regions. One of the key features of the surfaces with patterned wettability is their ability to localize wetting of liquids preferentially within the patterned wettable regions. This ability of the patterned surfaces has been widely explored as a simple route to pattern both liquids, as well as, solids for various applications such as microfluidics, electronic and optical devices, surfaces with enhanced heat transfer properties, etc. However, most of the patterned surfaces exhibit wettability contrast only with high surface tension liquids such as water, thereby limiting the applications of the patterned surfaces to only aqueous systems. Herein, we utilize the design principles of superomniphobicity (repellency towards all liquids) to develop the first-ever patterned superomniphobic-superomniphilic surfaces that exhibit extremely wettability contrast with both high and low surface tension liquids. Utilizing these patterned surfaces, we demonstrate site-selective self-assembly of various liquids including: oils, alcohols, polymer solutions and solid dispersions. We also demonstrate site-selective condensation and boiling with low surface tension liquids, which is crucial when designing surfaces with significantly enhanced, phase-change, heat-transfer properties. We have further utilized surfaces with patterned wettability as templates for fabricating monodisperse, multi-phasic micro- and nano-particles. The developed technique termed WETS (Wettability Engendered Templated Self-assembly) provides us with an unprecedented ability to manufacture multi-phasic particles, on a large-scale, with precise control over the size (down to 25 nm), shape, chemistry and surface charge of the particles. We further demonstrate the utility of the WETS technique in developing amphiphilic building blocks for self-assembly and multi-functional cargo carriers. Finally, we have also studied stimuli-responsive shape reconfigurations of the multi-phasic WETS particles. Overall, this dissertation puts forward design principles for developing surfaces with patterned wettability that are universal to almost all liquids, thus enabling novel applications for the patterned surfaces, such as the WETS technique reported here.PhDMacromolecular Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116726/1/saireddy_1.pd

EFFECTS OF PRANAYAMA AND SURYANAMASKAR YOGIC PRACTICE ON COGNITIVE PERFORMANCE IN MEDICAL STUDENTS

Background: Recent studies have suggested that yoga reduce stress levels and anxiety accordingly reducing stress increases cognitive performance. The present study attempted to determine the combined yoga practice is associated with higher cognitive performance in medical students. Materials & Methods: All the instructions were given to the participants, they were asked to Unscramble 20 scrambled words in 5 minutes of time. The score was noted and were asked to perform yoga for four weeks. The same score was collected after yoga session and was compared with the previous values. Result: Analysis showed that the yoga group (M=15.2, SD=4.25) and the pre yoga group (M=09.49, SD=3.11) did not differ significantly on cognitive performance, p=<0.005. Conclusion: Combined effect of Pranayama and suryanamaskar are beneficial effect on improving cognitive function but it was statically insignificant.KEYWORDS:  Pranayama, suryanamaskar; Yoga; Cognitive functions

Studies on mechanical behavior of glass epoxy composites with induced defects and correlations with NDT characterization parameters

Degradation in mechanical properties (compression, flexural and ILS) of glass epoxy composite laminates with induced defects (simulating delaminations) was studied. The defects were characterized by using the A-scan ultrasonic pulse-echo technique. The two A-scan parameters, viz. the back wall echo amplitude and time of flight, were followed respectively, as functions of the defect size (diameter) and its location in the laminate thickness. The mechanical properties of laminates were evaluated destructively for different defect sizes and locations. An attempt has been made to express the mechanical properties in terms of the two NDT scan parameters characterizing the defects and empirical equations presente