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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. -
Analysis of zoochemical from Meretrix casta (Mollusca: Bivalvia) extracts, collected from Rameswaram, Tamil Nadu, India and their pharmaceutical activities
The marine ecosystem's diverse animal species offer a unique opportunity to discover marine-derived natural products. While numerous invertebrates have been studied, research on Indian marine invertebrates, especially Meretrix casta, remains limited. This study explores the zoochemical composition of ethyl acetate and methanolic extracts from Meretrix casta off Rameswaram, Tamil Nadu, India, and evaluates their bioactive potential, focusing on antioxidant properties, glucose uptake in yeast cells, and alpha-amylase activity. The results reveal the presence of alkaloids, flavonoids, polyphenols, sterols, terpenoids, and cardiac glycosides in both extracts, highlighting their bioactive potential. Although their antioxidant capacity is slightly lower than ascorbic acid, the extracts demonstrated significant alpha-amylase inhibition, suggesting their potential in blood sugar regulation and diabetes management. These findings underscore the therapeutic potential of M. casta in developing anti-diabetic compounds, warranting further pharmacological exploration. Authors. -
Analysis on emotion-aware healthcare and Google cloud messaging
Cloud computing has the potential to get integrated with the healthcare sector. It provides functionality for managing data in a distributed environment. The concept of Healthcare services is becoming popular in the Healthcare sector as it helps the patients to get immediate access regarding his/her health related information whenever needed and wherever needed using cloud computing technology. The Big Data Application in Emotion-aware Healthcare system [BDAEH], gives attention to both the emotion factor and logical reasoning of the user. The basic functions of this system are collecting health-related data, transmitting the collected data, analyzing the received data, storing them and making it available to a user in order to perform diagnosis and predict medications. Mobile devices are becoming an essential tool in our day to day lives. By integrating the concept of Google Cloud messaging alongside BDAEH system, numerous tasks can be done efficiently. 2017 IEEE. -
Analysis on techniques used to recognize and identifying the Human emotions
Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwins work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on various recognition techniques used to identify the complexity in recognizing the facial expression is presented. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved. -
Analysis on thermal sensitivity of 2D Profilometer used for TMT Glass Polishing
TMT adopts Stressed Mirror Polishing (SMP) technology for the polishing of mirror segments. In this process, the meniscus type spherical shape glass blanks are converted in to a desired aspheric shape by spherical grinding and polishing in the stressed condition. After each grinding and polishing activity metrological measurements are done using different metrology tools. The metrology tool named as 2D-Profilometer is used for low frequency error/foam measurements. It consists of 61 high precision length gauges attached to Carbon Fiber Reinforced Polymer (CFRP) sandwiched Aluminum panel of diameter 1.6 meter in spiral direction. The coefficient of thermal of CFRP is very low however, a small delta temperature variation between the top and bottom sheet of CFRP of the panel will lead to panel bowing which will result in increasing power error. Hence, the objective this work is to analyse the thermal sensitivity of the 2D Profilometer. 2024 SPIE. -
ANALYSIS, ASSESSMENT, AND MANAGEMENT OF ENVIRONMENTAL AIR POLLUTION USING ENVIRONMENTAL ENGINEERING IN DEVELOPING COUNTRIES
Recent studies underscore the value of contemporary technology and gas emissions mitigation while overlooking the necessity of optimal fuel in Developing Countries (DC). DC's historical economic expansion has significantly depended on fossil fuels, resulting in severe environmental air pollution (EAP) challenges. The separation of economic progress from pollution has been the central emphasis in advancing environmental civilization in emerging countries. This study presents an analysis, assessment, and management of EAP using environmental engineering (EE) in DC. This work has examined the evolution of EAP regulations in DC, emphasizing a strategic shift from emission regulation to Air Quality Management (AQM). The regulation of Sulfur dioxide (SO2) emissions addressed the worsening of acid rain in DC. Since 2015, regulatory measures across several sources and industries have aimed to decrease the total amount of Fine Particulate Matter (FPM2.5), signifying a shift towards an AQM-focused policy. Escalating ozone (O3) pollution necessitates integrated management measures for O3 and FPM2.5, focusing on their intricate photochemical reactions. Significant enhancement of AQM in DC, as a crucial metric for the efficacy of sustainable economic development, necessitates the profound carbon reduction of the DC's energy infrastructure and the establishment of more integrated strategies to tackle EAP and climate change in DC concurrently. 2024, Rotherham Academic Press Ltd. All rights reserved. -
Analytical Estimation and Experimental Validation of the Bending Stiffness of the Transmission Line Conductors
The bending stiffness of transmission line conductors can vary significantly, ranging from maximum stiffness when behaving monolithically to minimum stiffness when wires behave loosely. This large range makes it challenging to estimate stiffness accurately at intermittent bending stages. To address this issue, a mathematical model that accounts for both frictional forces between wires in the same layer and the clenching effects of helical wires from preceding layers is proposed in this paper. The proposed model estimates cable bending stiffness as a function of axial load and curvature for multilayered strands by considering slip caused by wire behavior. To evaluate the bending stiffness, experiments were conducted on Panther and Moose Indian Power Transmission line conductors. The proposed slip model considers Coulomb frictional effects and clenching effects caused by Hertzian contact forces, filling the void in the estimation procedure. Additionally, the model considers the wire stretch effect, a parameter not previously accounted for in cable research. The predicted numerical results of the proposed model were found to vary within a maximum of 7% from the experimental tests. The proposed mathematical model thus offers a more accurate and comprehensive way of estimating the bending stiffness of transmission line conductors, addressing the existing limitations in the estimation procedure. 2024 College of Engineering, Universiti Teknologi MARA (UiTM), Malaysia. -
ANALYTICAL METHODS FOR TRAMADOL IN PHARMACEUTICAL AND FORENSIC CONTEXT A REVIEW
Tramadol is a centrally-acting weak opioid recept or analgesic and is a racemic mixture of (+)-tramadol and ()-tramadol enantiomers. Tramadol does not show many adverse severe effects without any dependency potential in therapeutic doses, as seen in other opioids only if not used for extended periods in doses higher than recommended. Symptoms of tramadol intoxication are similar to those of other opioid analgesics but may include serotonergic and noradrenergic components. Fatal intoxications are rare and appear synergetic with other drugs and alcohol. There is growing evidence of abuse of tramadol in many countries. Due to its extensive use in the medical field as an analgesic of choice, pharmaceutical analysis in both process and quality control is essential. Due to its abuse and overdose cases, forensic toxicological analysis of tramadol in body fluids and tissues is also vital in medico-legal practice. Tramadol and its metabolites are found in wastewater also. This analytical review (from 2016-2021) focuses on identifying and determining t ramadol in bulk dr ugs, formulations, forensic drug seizures, forensic toxicological specimens, and wastewater. The analytical methods covered include UV/Visible/IR spectrophotometric methods, thin-l ayer, gas and li quid chromat ographic met hods, electrochemical methods, GC-MS, LC-MS, LC-MS-MS methods, and electrochemical methods. The review will i nt eres t phar maceut i cal chemi st s, pharmacol ogis ts, biochemists, forensic chemists, forensic toxicologists, and environmental scientists. 2023, Medico Legal Society. All rights reserved. -
Analytical Methods of Machine Learning Model for E-Commerce Sales Analysis and Prediction
In the commercial market, E-commerce sales show a significant trend and have attracted many consumers. Ecommerce sales forecasting has a significant role in an organization's growth and aids in improved operation. Many studies have been conducted in the past using statistical, fundamental, and data mining techniques for better analysis and prediction of sales. However, the current scenario calls for a better study that combines the available information to propose different machine-learning techniques. The sole motive of the study is to analyze and determine different machine learning models to predict accurate results. The research observed that the Extreme Gradient Boosting model outperformed all other models and brought a good result. It produced an RMSE value of 0.0004 and Explained Variance score of 0.99. Decision Tree algorithm also shows an exemplary result. 2023 IEEE. -
Analytical modeling of reconfigurable transistors
A functionally enhanced transistor is a potential candidate for further advancing electronics and Moore's law beyond the classical scaling. This chapter discusses these kinds of multifunctional transistors called reconfigurable field-effect transistor (RFET) and reconfigurable tunnel field-effect transistor (RTFET). The RFET works on the principle of Schottky barrier tunneling, and the RTFET works on the principle of band-to-band tunneling. Both devices can be configured as an n-type and p-type device based on the biasing. This chapter explains the working and performance comparison of RFET and RTFET in detail with the help of technology computer-aided design (TCAD) simulations. Further, the potential and current models of a single-gated RFET and double-gated RTFET are presented in this chapter. The presented analytical models are compared and verified with TCAD simulations. The potential in the channel regions of RFET and RTFET is modeled by solving a two-dimensional (2D) Poisson's equation. Because the working principle of both devices is different, two different formulas are utilized for modeling the current in the device. The current model for the RFET is developed by integrating Landauer's formula, whereas the current model for RTFET is obtained by integrating band-to-band generation rate over the tunneling volume. The procedure, technique, and assumptions followed to obtain the potential and current models of RFET and RTFET are detailed in this chapter. 2022 selection and editorial matter, Ashish Raman, Deep Shekhar and Naveen Kumar; individual chapters, the contributors. -
Analytical Results of Heart Attack Prediction Using Data Mining Techniques
In the modern era of living a fast lifestyle, people are not more conscious of their food eating and lifestyle. Due to these reasons, the chances of having a cardiac-related disease have risen drastically. This paper has studied the various supervised and unsupervised machine learning algorithms in comparative methods with best accuracy. Models like classification algorithms, regression algorithms, and clustering algorithms have been used for this paper. This research paper majorly focuses on patients with certain medical attributes that indicate a higher risk of heart disease. The model almost gives a good accuracy for all the regression and classification models when compared to the clustering models. Among all the algorithms, random forest and decision tree gives better accuracy 2023 IEEE. -
Analytical study of BrinkmanBard convection in a bidisperse porous medium: Linear and weakly nonlinear study
Linear and weakly nonlinear stability analyses of BrinkmanBard convection of a Newtonian fluid saturating a bidisperse porous medium (BDPM) are made. Local-thermal-non-equilibrium (LTNE) is assumed between the fluid and the porous spheres (micro-pores) that make up the macro porous medium. Two coupled linear momentum equations are considered one each for the macro- and micro-pores. Results of mono-disperse porous medium (MDPM) with solid spheres are recovered as a limiting case of the present study. Further, in the case of both types of porous media considered the results of DarcyBard and BrinkmanBard convection are extracted under suitable limiting procedures. To keep the work analytical, we reduce the intractable hexa-modal Lorenz model with four quadratic nonlinearities into the tractable mono-modal StuartLandau equation (SLE) with cubic and quintic nonlinearities. Subcritical instability is discounted in the study thereby suggesting that cubic SLE and cubicquintic SLE both expound similar results qualitatively. The concept of a BDPM is shown to be meaningful only when the pores are not large, and when they are very small, then the MDPM assumption applies. Similar observation can be made when the ratio of permeabilities is large. The presence of micro-pores does not alter the size of the convective cell significantly at the onset. The present study reiterates the findings of several earlier works. 2023 Elsevier Ltd -
Analytical Study of Security Enhancement Methods on Diverse Cloud Computing Platforms
Cloud storage is a convenient and virtually limitless storage option for the bulk of data technology is producing in recent times. Data security in cloud is not so robust as data owners need to depend upon the service providers for the safe storage. In this paper, we have identified few broadly used cloud computing paradigms: mobile cloud, cloud-based IoT and multi-tenant cloud. Mobile cloud helps reduce the data storage overhead on the mobile device and give users access to their personal data as and when required through cloud access. Cloud-based IoT helps the network of IoT devices, which is growing exponentially, to create on-demand cloud repositories. Multi-tenant cloud platforms are cloud environment accessed by more than one user. Few recent and related research work which aims at enhanced security from all these three paradigms is discussed and analysed. Encryption and similar network securing methods are used for mobile cloud and cloud-based IoT. For multi-tenant cloud, the objective is to keep the user spaces separate to keep their resources confidential. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analytical study of triple diffusive convection in a bi-viscous Bingham fluid layer using Ginzburg-Landau model
In this paper, considering bi-viscous Bingham as the base fluid, we study the thermophysical-properties (such as density, specific heat, thermal conductivity, thermal diffusivity, and thermal expansion) with different combinations of salts among NaCl, KCl, CaCl2, and NaCl2 of triple diffusive convection in a bi-viscous Bingham fluid layer with heat as one of the diffusing components. A weakly non-linear case is formulated to facilitate a solution to the problem using a series solution Ginzburg-Landau model. With regard to single, double, and triple diffusive convection, the tables are made to record the actual values of thermophysical-properties together with the critical Rayleigh-number for each combination of aqueous-salt solutions. This computation calculates the mean Nusselt and Sherwood numbers to quantify the systems heat- and mass-transfers for various aqueous-solutions. The effect of the bi-viscous Bingham fluid parameter, for small and large values, for different aqueous-solutions, in single, double, and triple diffusive convection has been captured via 2-dimensional (2D) and 3-dimensional (3D) figures and the results are recorded and compared. The investigation reveals that the heat- and mass-transfers increase with an increase or decrease in the bi-viscous Bingham fluid parameter, which in turn depends on the values of (Formula presented.) and (Formula presented.) The results confirm that the heat- and mass-transfers are least for the combination of KCl with CaCl2 and maximum for the combination of NaCl with other salts. 2024 Taylor & Francis Group, LLC. -
Analytics Enabled Decision Making
Analytics is changing the landscape of businesses across sectors globally. This has led to the stimulation of interest of scholars and practitioners worldwide in this domain. The emergence of big data, has fanned the usages of machine learning techniques and the acceptance of Analytics Enabled Decision Making. This book provides a holistic theoretical perspective combined with the application of such theories by drawing on the experiences of industry professionals and academicians from around the world. The book discusses several paradigms including pattern mining, clustering, classification, and data analysis to name a few. The main objective of this book is to offer insight into the process of decision-making that is accelerated and made more precise with the help of analytics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Analytics Enabled Decision Making Tracing the Journey from Data to Decisions
In the current business environment, which is greatly dynamic and competitive, business organizations are continually striving for expanding their competence and financial performance through improving almost every facet of their business--product/service quality, customer satisfaction, customer retention, productivity, line filling strategies, and others. In this sense, success and failure of organizations depend on the extent of precision of their decisions. Organizations are engaged with data to extract insights, identify trends and make decisions at different levels; and also, many of them learn how to utilize the power of data. Analytics can enable them to derive conclusions, make predictions, and ascertain actionable insights in a contextual and time-bound manner. It helps to examine data from multiple perspectives and gives visualizations by using different frameworks and platforms such as IBM Watson, Tableau, and R. The chapter presents the role of analytics in decision-making processes and assess the effectiveness of decisions upon their implementation, so the corrective measures can also be inserted. As decision making is a continuous business process, analytics accelerates it and gives organizations a pace to keep updated with changing business scenarios. Thus, this chapter presented a decision-making framework exhibiting how decision-making functions as an ongoing process. Different contexts and cases have been used to establish the relevance of each step of the framework. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Analytics in e-learning
Predictive analytics play an important role in the evolving dynamics of higher education. There has been a steady up rise in use of technology in the field of education. e-learning is seen as a futuristic approach of learning. Hence, the study of factors influencing success in e-learning courses is relevant to the current scenario. Use of predictive analytics in virtual learning environment would provide insight on learning patterns of students. The learning data available in the traditional teaching environment is different from the one, which is available from virtual learning. This paper tries to identify various attributes associated with e learning which can help in making the learning process effectual. International Research Publication House. -
Analyzing and optimizing the usability of website access
The world wide web (WWW) plays a significant role in information sharing and distribution. In web-based information access, the speed of information retrieval plays a critical role in shaping the web usability and determining the user satisfaction in accessing webpages. To deal with this problem, web caching is used. The problem with the present web caching system is that it is very hard to recognize webpages that are to be accessed and then to be cached. This is forced by the fact that there are broad categories of users and each one having their own preferences. Hence, it is decided to propose a novel approach for web access pattern generation by analyzing the web log file present in the proxy server. Further, it tries to propose a novel hybrid policy called popularity-aware modified least frequently used (PMLFU) that best suits for the current proxy-based web caching environment. It combines features such as frequency, recency, popularity, and user page count in decision-making policy. The performance of the proposed system is observed using real-time datasets, empirically using IRCACHE datasets. 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. -
Analyzing blockchain-based supply chain resilience strategies: resource-based perspective
Purpose: This research tries to find the blockchain-based resilience strategies that can help the supply chains of micro, small, and medium-sized enterprises (MSMEs) to recover from the disruptions and work effectively in a resource-based view perspective. Design/methodology/approach: Eight broad strategies and 32 sub-strategies are identified from the literature review. Delphi study was carried out, and detailed discussion with 16 experts helped in finalizing these strategies. Further, the best-worst method (BWM) prioritized these strategies. Findings: The findings suggests that building social capital, improving coordination capabilities, sensitivity towards market, flexibility in process and production, reduction in process and lead time,and having a resource efficiency and redundancy are the top strategies on which the top management should focus to overcome the situations of disruptions and enhance performance of MSMEs. Practical implications: The blockchain-based strategies will enable the companies in tracing the products from the company to customers. Further, the customers will be able to identify their manufacturers, the raw materials used in manufacturing, and the life and quality of raw used materials. Altogether the textile industry will become more sensitive toward environmental practices. Originality/value: The previous research has not identified and evaluated the blockchain-based resilience strategies, and therefore this study tries to fill this gap. This study used a smaller sample from the experts, so the results may vary if the larger data set is used and hypothesis testing can be done. 2023, Emerald Publishing Limited. -
Analyzing Dual-Stage Inverter Performance for Solar Grid Integration
This paper presents a comprehensive analysis of the performance of dual-stage inverters in the context of solar grid integration through simulation. Dual-stage inverters are increasingly recognized for their potential to enhance the efficiency and reliability of solar power systems by mitigating grid disturbances and optimizing energy extraction. Through detailed simulation studies, this research evaluates key performance metrics such as grid stability, power quality, and energy conversion efficiency. The simulation environment enables the exploration of various operational scenarios and system configurations to assess the versatility and robustness of dual-stage inverter solutions. Furthermore, the study investigates the impact of control strategies and parameter variations on the overall performance of dual-stage inverters, providing valuable insights for system optimization and design. 2024 IEEE.