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Policies and metrics for schedulers in cloud data-centers using CloudSim simulator
Todays cloud technology consumers must address escalating computing and storage demands for services and applications. However, decision-making on provisioning and scheduling is challenging due to varying workflow demands within Infrastructure as a Service (IaaS). This study formulates an optimization problem with multiple objectives to identify optimal policies, employing heuristic metrics through cloud simulation similar to AWS EC2 instances. Experiments involve two task scheduler types, time-shared and space-shared, aimed at minimizing execution time and cost. The study introduces two novel algorithms, SLB and MinMax, for comparison with standard algorithms. It emphasizes the importance of precise quantification of uncertainty in cloud storage allocation and highlights the state-of-the-art policies and metrics achieved through virtualization techniques. The studys novelty lies in simulating both policies at two levels and proposing a novel algorithm for multi-objective optimization while providing cost and time measurements. Contributions include experimenting with various combinations, applying heuristics to entire data center entities, proposing a novel algorithm, and offering cost and time measurements for the optimizations. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Analysis of Workloads for Cloud Services
Capturing best quality datasets for a study is the first evidence for better outcomes of research. If the analysis are based on such datasets, then the metrics, the characteristics and few factors determines proof point for well proven theories. Hence it is obvious that we rely on the best possible ways to arrive at such data acquiring sources. It can be either based on historical techniques or from the innovations in application of it to industry. This paper introduces a mapping framework for analyzing, and characterizing data previously used by research community and how they are made to fit for Cloud systems, i.e. using 'workloads' and 'datasets' as the 'refined definitions'. It was contributed in the past two decades within the scientific community setting their own workflow analysis mechanisms. The framework thus is validated by acquiring a sample workload per layer of cloud. The sources are form the literature that are available from existing scientific theories. These workloads are then experimented against the three tiers of the cloud computing ie., IaaS(Infrastructure as a Service), PaaS(Platform as a Service), & SaaS(Software as a Service). The selected data is analyzed by the authors for an offline model presented here based on the Machine Learning tool-kits. There are future studies planned for and to be experimented in a cloud auto scaled environment with online model as well. 2022 IEEE. -
Cloudsim exploration: A knowledge framework for cloud computing researchers
This paper aims to help find solutions for questions an early researcher may have to set up experiments in their development environment. Simultaneously, while identifying the steps required for experimenting, the authors narrowed on an experimenting toolkit for Cloud Computing as an area of their study. Because of such simulators, the cloud computing environment itself is available easily at the comfort of ones desktop resources instead of visiting an actual physical data center to collect trace and log files as data sets for real workloads. This paper acts as an experience sharing to naive researchers who are interested in how to go about to start cloud computing setups. A new framework called Cloud Computing Simulation Environment (CCSE) is presented with inspiration from Procure Apply Consider and Transform (PACT) model to ease the learning process. The literature survey in this paper shares the path taken by researchers for understanding the architecture, technology, and tools required to set up a resilient test environment. This path also depicts the introduced framework CCSE. The parameters found out of the experiments were Virtual Machines (VMs), Cloudlets, Host, and Cores. The appropriate combination of the values of the parameters would be horizontal scaling of VMs. Increasing VMs does not influence the average execution time after a specific limit on the number of VMs allocated. Nevertheless, in vertical scaling, appropriate combinations of the cores and hosts yield better execution times. Thereby maintaining the optimal number of hosts is an ultimate saving of resources in case of VM allocations. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021. -
International Financial Reporting Standards and Their Impact on Financial Performance of Mindtree Ltd: A Case Study
Indian Journal of Social Science Research, Vol-1 (2), pp. 44-55. ISSN-2321-208X -
Policies and metrics for schedulers in cloud data-centers using CloudSim simulator
Todays cloud technology consumers must address escalating computing and storage demands for services and applications. However, decision-making on provisioning and scheduling is challenging due to varying workflow demands within Infrastructure as a Service (IaaS). This study formulates an optimization problem with multiple objectives to identify optimal policies, employing heuristic metrics through cloud simulation similar to AWS EC2 instances. Experiments involve two task scheduler types, time-shared and space-shared, aimed at minimizing execution time and cost. The study introduces two novel algorithms, SLB and MinMax, for comparison with standard algorithms. It emphasizes the importance of precise quantification of uncertainty in cloud storage allocation and highlights the state-of-the-art policies and metrics achieved through virtualization techniques. The studys novelty lies in simulating both policies at two levels and proposing a novel algorithm for multi-objective optimization while providing cost and time measurements. Contributions include experimenting with various combinations, applying heuristics to entire data center entities, proposing a novel algorithm, and offering cost and time measurements for the optimizations. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. -
An Efficient Localized Route Recommendation Scheme using Fusion Algorithm for VANET based Applications
The evolution of vehicles has led to the need for improved and advanced techniques to solve traffic related problems. The improvement related to cooperative vehicles has been a recent focus in dealing with such difficulties. The most popular application of co-operative vehicles is the route planning for travelers. In this paper, an innovative module namely Localized Route Recommendation with Fusion Algorithm (LR2FA) is proposed to enumerate a localized route recommendation system to communicate to co-operative vehicles. Traffic parameters such as vehicle speed and density information collected from the centralized location and used as decision factor to provide suggestions of routes using a novel Fusion Algorithm (FA). To evaluate the factors for route suggestion, FA uses a combination of genetic and heuristic-based approaches. The performance of the proposed localized route references is analyzed using simulated values of vehicle speed and density. It is seen from the results that the proposed LR2FA provides top fitting routes compared to greedy based route suggestion. 2022 IEEE. -
Thermoelectric effects in graphene
Graphene, owing to its unique electronic properties, has become one of the active areas of condensed matter research with promising applications in future efficient thermoelectric (TE) and energy storage devices. The present work reviews the status of thermoelectric power (TEP) of graphene systems, including single-layer, bilayer, and nanoribbons. The theory of TEP, based on the Boltzmann transport formalism in 2D systems, is given. An analysis of the experimental data, in terms of the diffusion and the phonon-drag contributions to TEP, with regard to the various scattering mechanisms operative in graphene systems, is presented. The outlook on TEP for better understanding of the TE properties of graphene is discussed. 2016 by Taylor & Francis Group, LLC. All rights reserved. -
Thermoelectric effects in graphene
Graphene, owing to its unique electronic properties, has become one of the active areas of condensed matter research with promising applications in future efficient thermoelectric (TE) and energy storage devices. The present work reviews the status of thermoelectric power (TEP) of graphene systems, including single-layer, bilayer, and nanoribbons. The theory of TEP, based on the Boltzmann transport formalism in 2D systems, is given. An analysis of the experimental data, in terms of the diffusion and the phonon-drag contributions to TEP, with regard to the various scattering mechanisms operative in graphene systems, is presented. The outlook on TEP for better understanding of the TE properties of graphene is discussed. 2016 by Taylor and Francis Group, LLC. -
Identification of Superclusters and Their Properties in the Sloan Digital Sky Survey Using the WHL Cluster Catalog
Superclusters are the largest massive structures in the cosmic web, on tens to hundreds of megaparsec scales. They are the largest assembly of galaxy clusters in the Universe. Apart from a few detailed studies of such structures, their evolutionary mechanism is still an open question. In order to address and answer the relevant questions, a statistically significant, large catalog of superclusters covering a wide range of redshifts and sky areas is essential. Here, we present a large catalog of 662 superclusters identified using a modified friends-of-friends algorithm applied on the WHL (Wen-Han-Liu) cluster catalog within a redshift range of 0.05 ? z ? 0.42. We name the most massive supercluster at z ? 0.25 as the Einasto Supercluster. We find that the median mass of superclusters is ?5.8 1015 M ? and the median size ?65 Mpc. We find that the supercluster environment slightly affects the growth of clusters. We compare the properties of the observed superclusters with the mock superclusters extracted from the Horizon Run 4 cosmological simulation. The properties of the superclusters in the mocks and observations are in broad agreement. We find that the density contrast of a supercluster is correlated with its maximum extent with a power-law index, ? ? ?2. The phase-space distribution of mock superclusters shows that, on average, ?90% of part of a supercluster has a gravitational influence on its constituents. We also show the mock halos average number density and peculiar velocity profiles in and around the superclusters. 2023. The Author(s). Published by the American Astronomical Society. -
Revisiting the Nexus Between Suicides and Economic Indicators: An Empirical Investigation
In India, as of 2021, there was a 7.2% increase in suicides. With the economic burden inflicted by the pandemic and increasing suicides, a systematic investigation needs to be done. This empirical investigation uses the Autoregressive Distributed Lag (ARDL) model to obtain long and short-term estimates for the relationship between suicides and prominent economic indicators. The findings suggest that economic indicators like GDP per capita growth, age dependency ratio, and unemployment rate have a significant dynamic relationship with suicides. In this regard, preventive measures can be formulated and implemented in such a way that focuses on improving the countrys economic scenario which will in turn reduce suicides. Organizations and governments can plan training and mental health care programs for farmers, workers, and students. Mental health care services require attention from the government so that at a macro level the problem of increasing suicides can be handled. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
Mapping Fire, Earthquake and Bio-hazard in Delhi: A Micro-level Study
Delhi, being Indias capital territory, is a massive metropolitan area that is extremely vulnerable to various types of disasters because of the widely spread built-up area that houses the population from all over the country. Delhi lies in Seismic Zone IV14, which makes the area sensitive to disasters. Another major problem that Delhi is currently facing is of proper garbage disposal, since the density of the population is high, tons of waste is generated. A fair share of the waste generated also includes biomedical waste. Delhi generates more biomedical waste than it can process. The area chosen for the present study is Chirag Delhi and Sheikh Sarai, located in south Delhi. This area is urbanized, and a home to a large number of people. The area is populated, poorly managed and highly vulnerable to disasters. The study area also has two colleges situated near the residential area because of which the area is subjected to a lot of traffic jam. The purpose of choosing this area for this study is its vulnerability to disasters like fire, earthquake and biohazard. The study area has pockets with high rise buildings or ill-designed high-risk areas without specific consideration for earthquake resistance. Moreover, the area lacks proper waste management. It has been identified that the area is a highly vulnerable place when it comes to hazards like fire, earthquake and biohazards. The people living there are in a constant threat for their lives. One of the major problems is that the community lacks dedication and determination, which has been tested through a schedule and observation method, to change their circumstances and bring about a change in the area that would benefit them and their families. The Editor(s)(ifapplicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
The relationship between density of drug outlets, crime hot spots and family factors on the consumption of drugs and delinquent behaviour of male adolescent Mexican students
This study examined the relationship between community risk factors (drug outlets density and crime hot spots) and family factors on the risk behaviours (drugs consumption and delinquent behaviour) of male adolescent Mexican students. Results were obtained based on data bank analysis and direct collection of information regarding family factors and risk behaviours of adolescents attending school. Spatial and statistical analysis was performed. The final sample was composed of 1450 male adolescents, from 11 secondary and high schools located in marginal and violent areas of Mexico. Spatial analysis revealed that when considering only the prevalence of the risk behaviours of the adolescents, the area of highest risk was the northwestern area of the city. However, after performing conjunct analysis of all evaluated variables using density point risk (aside from confirming that the northwestern area is still the one with the greatest risk), results indicated that the southern area has a high-density point risk. All densities of the variables showed a statistically significant positive association (p < 0.05). However, the results of the structural equation model indicated than only the family factors influenced the risk behaviours of adolescents (p < 0.05). The spatial distribution of the risk behaviours in male adolescent students and community risk variables surrounding the area where schools are located allows for the description of patterns and hotspot detection that facilitate the prioritization of where interventions must be directed. Besides, the interventions should target family factors. 2021 Elsevier Ltd -
Enhancing Human-Computer Interaction with a Low-Cost Air Mouse and Sign Language Recognition System
The purpose of this study is to investigate the development of assistive technologies that are designed to empower people with disabilities by increasing their level of freedom and accessibility. Voice assistants, air mice, and software that recognizes sign language are some of the topics that are specifically covered in this. Those who have impaired fine motor skills can benefit from using air mice since they allow controls to be made by hand gestures. Using machine learning algorithms, sign language recognition software is able to decipher signs with an accuracy rate of over 90 percent, making it easier for people who are deaf or hard of hearing to communicate themselves. By relying solely on vocal instructions, voice assistants like Alexa make it possible to control devices without using your hands. Not only do these technologies have the potential to be revolutionary, but they also confront obstacles in terms of improving identification accuracy and integrating them into common gadgets. In this study, the development and impact of voice assistants, sign language software, and air mice are discussed. More specifically, the paper highlights the potential for these technologies to help millions of people with disabilities all over the world. Additionally, it examines potential enhancements that could be made to these technologies in the future in order to further improve accessibility and inclusivity. This research integrates computer vision and machine learning to create a multimodal system blending air mouse functionality with real-time sign language translation. Achieving 95% accuracy in gesture recognition for air mouse control and 98% accuracy in sign language letter classification using a basic webcam, the system promotes accessible interaction without specialized hardware. Despite limitations in vocabulary and lighting sensitivity, future efforts aim to broaden data training and explore mobile deployment. These advancements hold promise for enhancing natural human-computer interaction, particularly for users with disabilities, by enabling intuitive, hands-free control and communication. 2024 IEEE. -
A study on the factors affecting usage of voice assistants and the interface transition from touch to voice
The interface simplicity has always been one of the most important factors which makes any new technology or device successful. Once an individual gets attached to a particular interface it becomes easy for them to use any devices which follows the same interface pattern. But to adapt to a new interface for the same device or the same need it will take a lot of effort from both the user and the companies which advances those to support each other to make the interface shift happen. The timespan required for this interface shift depends on the mindset of each individual and the simplicity of the proposed interface. Voice Assistants (VA) are an important achievement, which have become an inseparable and integral part of many smart devices. The mobile penetration in India has allowed rapid acceleration among metropolitan Indian adults in the usage of the wearable devices and other such smart technologies. Voice as an interface is going to improve the next generation of social conversation, content searches and medium of commerce. The rapidly increasing competition in this segment has led to several improvements. We already have many such voice-enabled devices that help us to set routines, automate the home appliances and provides us on-demand information. Also, the smart speakers category in Indiagrew 43 per cent in the second quarter of 2018.Many big corporates like Amazon, Apple, Google and Microsoft offers an entire digital platform infrastructure that can be controlled by voice assistants. The future of Voice Assistants depends to a large extent on how natural and fluid the communication with the user can take place. The interface transition from touch to voice has several factors involved in it. This study is majorly to find out what are the major factors which are influencing this transition and how relevant are these identified factors for the transition to happen in Indian market. 2020 SERSC. -
Deep learning-driven correction of motion-induced artifacts in microfluidic on-chip fluorescence microscopy for robust cell classification
Fluorescence microscopy combined with microfluidic platforms allows for the analysis of single cells and the whole biomedical process to be done at high speed, however, it is often a very delicate method that can be heavily affected by motion-induced distortions during the high-speed flow. These artifacts, such as motion blur, misalignment, and shape deformation significantly lower automatical accuracy of the cell classification. The suggested research suggests that on-chip fluorescence microscopy employs an AI-based framework of distortion correction using Vision Transformers (ViT) and Generative Adversarial Networks (GAN) to remove motion artifacts in real-time. The combination of the GAN-ViT architecture does not only manage to reconstruct image quality but also to preserve fine cellular features when flowing system rates increase to 200 4L/min, which provide PSNR = 38.6 dB and SSIM = 0.98. When the system was used in both synthetic and experimental microfluidic data, it was able to reach a classification accuracy of 99.9, thereby indicating consistency in the system despite varying flow rates. The speed of the framework is 950 frames per second (fps), almost equal to the 1000-fps smartphone camera acquisition rate, thereby, demonstrating its suitability to the real-time, high-throughput imaging. As opposed to the past CNN or transformer techniques, a hybrid GAN-ViT architecture offered by the authors of this study directly implements in the imaging pipeline, thus enabling the simultaneous motion correction and diagnostic classification to occur immediately. The study results highlight the fact that AI-based distortion correction not only increases the accuracy of the diagnosis, but also personnel and laboratory response in microfluidic fluorescence microscopy. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026. -
Early Detection of Cervical Cancer using Machine Learning Classifiers for Improved Diagnosis in Underserved Regions
One of the incurable diseases that affect women is cervical cancer. It is brought on by a protracted infection of the skin and the vaginal mucous membrane cells. The Human Papilloma Virus (HPV), is the main factor causing aberrant cell proliferation in the area around the cervix. There are no symptoms present when the illness first appears. Early detection of this malignancy may be used to prevent death. People in less developed countries cannot afford to periodically examine themselves due to a lack of awareness, poor medical infrastructure, and expensive medication. The EDA technique is applied to examine the data and understand its characteristics. Machine Learning algorithm has been used to diagnose cervical cancer. In order to spot the existence of cervical cancer, five machine learning classifiers are utilized, the algorithms to begin earlier. The Logistic Regression classifier's results validate the correct stage prediction. 2023 IEEE. -
Biodegradable Organic Polymers for Environmental Protection and Remediation
As the era of urbanization and industrialization progressed, non-biodegradable polymers became a severe threat to the environment and the world's rapidly growing population. These synthetic polymers possess flexible applications and cost effectiveness which makes their usage more feasible and convenient. Today they are used from simple packaging to critical biomedical tools. Although these polymers possess many merits, all come to halt when it comes to biodegradability. The inherent mechanisms in nature are unable to degrade and decompose these synthetic polymers leading to their accumulation and persistence in nature for decades causing calamitous effects. In search of solutions for the adverse effects caused by synthetic polymers, the world turned toward biologically synthesized biodegradable organic polymers. These biopolymers have a diverse set of physical and chemical characteristics that can be easily manipulated, allowing for a wide range of applications. Biopolymers like polyhydroxyalkanoates and levan have adaptable qualities that resemble those of synthetic plastics which makes them a promising alternative to synthetic plastics. However, the setback in the large-scale usage of biopolymers is their high cost of production and commercialization. The biopolymers are broadly classified into three major classes based on their origin: plant-based biopolymers (cellulose, starch), animal-based biopolymers (chitin, chitosan, keratin), and microbial biopolymers (polyhydroxyalkanoates, levan). The extraction or synthesis of these biopolymers from their biological sources varies significantly from each other; however, in order to bring out the sustainable production, these polymers should be produced by coupling with waste valorization approaches. The waste materials from plants and animals, particularly agro-industrial wastes, can be used as inexpensive substrates for the commercial manufacture of these crucial biopolymers, thereby reducing the accumulation in the environment. Another field of biopolymer usage is in remediation of pollutants. Many biopolymers are currently being used in the active removal of heavy metal, dye, and other similar pollutants. The numerous physical, chemical, and biological processes for extraction or synthesis of industrially valuable biopolymers from the waste raw materials are discussed in this chapter, along with their application in remediation of pollutants and environmental protection. 2025 WILEY-VCH GmbH, Boschstra 12, 69469 Weinheim, Germany. All rights reserved. -
Valorization of waste chilli stalks (Capsicum annuum) as a sustainable substrate for cellulose extraction: insights into its thermomechanical, film forming and biodegradation properties
Rising global population accelerates food waste generation, thereby creating a crisis in food waste management. A solution involves deriving value-added products like cellulose biopolymer from food waste. Chilli stalk wastes are one such food waste which are generated in large quantities and are unsuitable for field use or incineration due to health and environmental challenges. A greener alternative is extracting cellulose biopolymer from chilli stalk waste. The extraction of cellulose biopolymer from chilli stalk results in a renewable, biodegradable and economically efficient biomaterial with a broad range of applications. The extraction process involving alkali treatment (NaOH) and bleaching (alkaline H2O2), resulted in a yield of 29.85% cellulose biopolymer. The extracted cellulose was subjected to quantification and functional property analysis followed by characterization (FTIR, XRD, TGA, DSC and SEM) to analyse functional groups, crystallinity, thermal properties and surface morphology. Functional property analysis resulted in higher values when compared with commercial cellulose. The characterization techniques confirmed the effective removal of impurities such as lignin, hemicellulose and pectin by the chemical treatments. Cellulose sheets, fabricated using solvent casting, exhibited exceptional biodegradability (85.36%) within 20days, surpassing conventional food packaging materials, commercial food packaging paper (15.95 0.12% [%w/w]) and plastic sheets (7.89 0.33% [%w/w]) over the same time period. The novelty of this research lies in the innovative valorization of chilli stalk waste, which often remains unused in large quantities globally. This study introduces a cost-effective method to convert it into a value-added, highly biodegradable biopolymer. The resulting cellulose sheets provide an eco-friendly substitute for traditional food packaging materials. 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
A Strategic Review on Use of Polyhydroxyalkanoates as an Immunostimulant in Aquaculture
Background and Objective: Increasing concerns over the use of antibiotics in aquaculture have emerged researchers to focus on short chain fatty acids and other biocompatible molecules as alternatives for disease prophylaxis and treatment. Polyhydroxyalkanoates well studied as biopolymeric materials for using in packaging and biomedicine were not focused much for their abilities to act as antimicrobial agents in aquaculture until recent years. Application studies of polyhydroxyalkanoates as aquafeed additives have highlighted their promising roles as ecofriendly alternatives for commercial antibiotics with strong immunomodulatory effects in fish-es and shrimps. The major aim of this review was to explore up-to-date scientific research studies on use of polyhydroxyalkanoates as aquafeed additives and their immunomodulatory effects. Results and Conclusion: Up-to-date, limited scientific literatures have been published on the use of polyhydroxyalkanoates and their copolymers as alternatives to antibiotics in aquaculture. This research field includes a great scope of development due to the promising immu-nomodulatory and antimicrobial activity of polyhydroxyalkanoates against common pathogens in aquaculture, as reported in literatures. Although several hypothesis and research data for explaining the mechanisms behind their immunostimulatory effects were suggested by various researchers, genetic and molecular bases underlying these phenomena are yet to be explored. Further research and development in this area can introduce these biopolymers as the most promising eco-friendly alternatives for antibiotics in aquaculture. Conflict of interest: The authors declare no conflict of interest. 2021. All Rights Reserved. -
Earliness of SME internationalizationand performance: Analyzing the role of CEO attributes
Purpose: The purpose of this paper is to understand the mediating effects of Chief Executive officer (CEO) attributes on the earliness of internationalization and performance in context of Indian small and medium enterprises (SMEs). Design/methodology/approach: The proposed framework is tested through analysis of a sample of 102 internationalized SMEs of the engineering industry in the Bangalore city region of India. Findings: Results highlight that CEOs age and educational background moderates between early internationalization and performance in the Indian SME context. Practical implications: Overall results facilitate in leveraging the decision-makers capabilities to successfully formulate and strategize their international marketing efforts to achieve higher performance. Originality/value: The study enriches the importance of CEO attributes in influencing the early internationalization and degree of internationalization in the context of an emerging economy where studies are limited. 2019, Emerald Publishing Limited.