Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
8,553
result(s) for
"Garima"
Sort by:
Secure VM Migration in Cloud: Multi-Criteria Perspective with Improved Optimization Model
Distributed computing has risen as a well-known worldview for facilitating an assortment of online applications and services. The present business distributed computing stages utilize a semi concentrated design, where cloud resources, such as servers and storage are hosted in a few large global data centers. Virtualization in computing is a creation of virtual (not real) of something such as hardware, software, platform or an operating system or storage, or a network device. Further, Virtual Machine (VM) technology has recently emerged as an essential building block for data centers and cluster systems, mainly due to its capabilities of isolating, consolidating, and migrating workload. Migration of VM seeks to improve the manageability, performance, and fault tolerance of systems. In a virtual cloud computing environment, a set of submitted tasks from different users are scheduled on a set of Virtual Machines (VMs), and load balancing has become a critical issue for achieving energy efficiency. Thus to solve this issue and to achieve a good load balance, a new improved optimization algorithm is introduced namely Dual Conditional Moth Flame Algorithm (DC-MFA) that takes into account of proposed multi-objective functions defining the multi-constraints like CPU utilization, energy consumption, security, make span, migration cost, and resource cost. The performance of the proposed model will be analyzed by determining migration cost, energy consumption, and response time, and security analysis as well.
Journal Article
Linking Lichen Metabolites to Genes: Emerging Concepts and Lessons from Molecular Biology and Metagenomics
Lichen secondary metabolites have tremendous pharmaceutical and industrial potential. Although more than 1000 metabolites have been reported from lichens, less than 10 have been linked to the genes coding them. The current biosynthetic research focuses strongly on linking molecules to genes as this is fundamental to adapting the molecule for industrial application. Metagenomic-based gene discovery, which bypasses the challenges associated with culturing an organism, is a promising way forward to link secondary metabolites to genes in non-model, difficult-to-culture organisms. This approach is based on the amalgamation of the knowledge of the evolutionary relationships of the biosynthetic genes, the structure of the target molecule, and the biosynthetic machinery required for its synthesis. So far, metagenomic-based gene discovery is the predominant approach by which lichen metabolites have been linked to their genes. Although the structures of most of the lichen secondary metabolites are well-documented, a comprehensive review of the metabolites linked to their genes, strategies implemented to establish this link, and crucial takeaways from these studies is not available. In this review, I address the following knowledge gaps and, additionally, provide critical insights into the results of these studies, elaborating on the direct and serendipitous lessons that we have learned from them.
Journal Article
IoT and AI technologies for sustainable living : a practical handbook
\"This book brings together all the latest methodologies, tools and techniques related to the Internet of Things and Artificial Intelligence in a single volume to build insight into their use in the sustainable living. The applications include areas such as agriculture, smart farming, healthcare, bioinformatics, self-diagnosis system, body sensor network, multimedia mining, multimedia in forensics and security. It provides a comprehensive discussion of modeling and implementation in water resource optimization, recognizing pest pattern, traffic scheduling, web mining, cyber security and cyber forensics. It will help develop an understanding of the need of AI and IoT to have a sustainable era of human living Tools covered include genetic algorithms, cloud computing, water resource management, web mining, machine learning, block chaining, learning algorithm, sentimental analysis and NLP. It is a valuable source of knowledge for researchers, engineers, practitioners, and graduate and doctoral students working in the field of cloud computing. It will also be useful for faculty members of graduate schools and universities\"-- Provided by publisher.
Book
Star Wars : Sith wars
Introduces the dark world of the evil Sith, describing their powers and ruthless plots to take over the galaxy.
Book
Antiviral Peptides: Identification and Validation
Despite rapid advances in the human healthcare, the infection caused by certain viruses results in high morbidity and mortality accentuate the importance for development of new antivirals. The existing antiviral drugs are limited, due to their inadequate response, increased rate of resistance and several adverse side effects. Therefore, one of the newly emerging field “peptide-based therapeutics” against viruses is being explored and seems promising. Over the last few years, a lot of scientific effort has been made for the identification of novel and potential peptide-based therapeutics using various advanced technologies. Consequently, there are more than 60 approved peptide drugs available for sale in the market of United States, Europe, Japan, and some Asian countries. Moreover, the number of peptide drugs undergoing the clinical trials is rising gradually year by year. The peptide-based antiviral therapeutics have been approved for the Human immunodeficiency virus (HIV), Influenza virus and Hepatitis virus (B and C). This review enlightens the various peptide sources and the different approaches that have contributed to the search of potential antiviral peptides. These include computational approaches, natural and biological sources (library based high throughput screening) for the identification of lead peptide molecules against their target. Further the applications of few advanced techniques based on combinatorial chemistry and molecular biology have been illustrated to measure the binding parameters such as affinity and kinetics of the screened interacting partners. The employment of these advanced techniques can contribute to investigate antiviral peptide therapeutics for emerging infections.
Journal Article
ISHA’S WAIT
Isha waits in her low-income parents’ home for her estranged husband, charged for dowry and domestic violence, to pay her the legally mandated maintenance money. I listen to her as she talks about pyaar, or love, and domestic violence as arising from the absence of its ehsaas, or feeling/realization, by the abusive husband. The awaited money is infused with the hopeful imagination that it will generate both pyaar and its ehsaas. I argue that money becomes a substance of kinship assigned an agentive role in engendering the ethical transformation of a “bad” husband to create “good” kinship. Exploring the ways in which the tenuous legal promise of money sustains imaginations of reformed kinship futures, I outline how centrally money shapes the experience of domestic violence and its aftermath.
Journal Article
Load Balancing in Cloud Environment Using Opposition Based Spider Monkey Optimization
Using cloud computing, user can pool resources in a distributed environment. These resources can be accessed wherever and whenever the provider permits. There can be various virtual machines (VMs) present at the backend to handle the requests. Whenever task requests are submitted by the user’s application on the cloud, they must be scheduled appropriately. Scheduling algorithms determine how well the system performs and the shortest response time must be the goal of the algorithm. A scheduling algorithm must distribute tasks evenly across all VMs in order to balance the load among all the available VMs. Scheduling of tasks with an optimal solution is a challenging work due to the dynamic nature of the problem in real time. This paper proposes opposition based spider monkey optimization algorithm to improve the performance of system. For every VM evaluation of load factor is done. The task has been scheduled with the VM with less load factor in comparison to the threshold value. The selection of optimal VM will be done by proposed optimization algorithm. According to simulation results, proposed algorithms perform better than existing algorithms in terms of load balancing, response time, makespan, and resource utilization.
Journal Article