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Evaluating the usability of mhealth applications on type 2 diabetes mellitus using various mcdm models
The recent developments in the IT world have brought several changes in the medical industry. This research work focuses on few mHealth applications that work on the management of type 2 diabetes mellitus (T2DM) by the patients on their own. Looking into the present doctor-to?patient ratio in our country (1:1700 as per a Times of India report in 2021), it is very essential to develop self?management mHealth applications. Thus, there is a need to ensure simple and user-friendly mHealth applications to improve customer satisfaction. The goal of this study is to assess and appraise the usability and effectiveness of existing T2DM?focused mHealth applications. TOP? SIS, VIKOR, and PROMETHEE II are three multi?criteria decision?making (MCDM) approaches considered in the proposed work for the evaluation of the usability of five existing T2DM mHealth applications, which include Glucose Buddy, mySugr, Diabetes: M, Blood Glucose Tracker, and OneTouch Reveal. The methodology used in the research work is a questionnaire?based evaluation that focuses on certain attributes and sub?attributes, identified based on the features of mHealth applications. CRITIC methodology is used for obtaining the attribute weights, which give the pri-ority of the attributes. The resulting analysis signifies our proposed research by ranking the mHealth applications based on usability and customer satisfaction. 2021 by the authors. Licensee MDPI, Basel, Switzerland. -
Evaluating the Use of White Board Animation in the Learning Process; [Evaluaci del uso de la animaci de pizarra en el proceso de aprendizaje]
A big challenge for the present-day trainers and teachers is to attract and retain the attention of the students and participants. In the era of social media and smartphones, students have several things that can distract them during the learning process and the responsibility to find ways to engage them effectively falls on the teacher. Based on a review of literature on technological developments, the researchers of the current study propose the use of whiteboard animation multimedia as a tool to enhance the learning experience. In the current study, the effectiveness of this technique is evaluated through a pre-test post-test control group design and the sample comprised of students of the masters in business administration course. The findings provide empirical evidence supporting the use of whiteboard animation videos to supplement classroom learning. 2022 Authors. All rights reserved. -
Evaluation and applying feature extraction techniques for face detection and recognition
Detecting the image and identifying the face has become important in the field of computer vision in recognizing and analyzing, reconstructing into 3D, and labelling the image. Feature extraction is usually the first stage in detection and recognition of the image processing and computer vision. It supports the conversion of the image into a quantitative data. Later, this converted data can be used for labelling, classifying and recognizing a model. In this paper, performance of such feature extraction techniques viz. Local Binary Pattern (LBP), Histogram of Oriented Gradients (HOG) and Convolutional Neural Network (CNN) technique are applied to detect and recognize the face. The experiments conducted with a data set addressing the issues like pose variation, facial expression and intensity of light. The efficiency of the algorithms was evaluated based on the computational time and accuracy rate. 2018 Institute of Advanced Engineering and Science. All rights reserved. -
Evaluation of a gamified learning experience: Analysis of factors that impact the effectiveness of a gamified experience; [Avaliao de uma expericia de aprendizagem gamificada: Anise dos fatores que afetam a eficia de uma expericia gamificada]
Gamification has gone through a faddish cycle. It first gained prominence around 2012 and was quickly abandoned, as practitioners did not achieve the outcomes they expected. According to Gartner's Hype Cycle, Gamification is at a point at which one might expect wide scale adoption. However, if history is not to repeat itself and results are to be achieved as theoretically predicted, a deeper understanding of the concept is essential. In the current study, the researchers attempt to evaluate a gamified learning experience. The participants were students of a Master in Business Administration course. The students were asked to participate in a gamified module and relevant data was collected, before and after the intervention. Based on a review of literature, the researchers identified the exogenous variables of Valence, Attitude towards use of Technology and Experience with Technology. The endogenous variables identified included Reaction and Learning. The findings of the study suggest that the gamified module resulted in increase in knowledge and that Attitude, Experience and Valence significantly predicted the Learner's reaction to the experience. The findings of the study provide support to key theories in the area of gamification and insights for practitioners, on the factors to be considered before using a gamifiedlearning intervention. 2021 UNIVERSIDADE FEEVALE All rights reserved. -
Evaluation of an interprofessional collaborative practice training module for the management of children with autism spectrum disorder
Background: Protocols instituted for behavioral treatment and skills training programs for the management of autism spectrum disorder (ASD) suffer from lack of collaborative approaches. The tenets of interprofessional collaborative practice (IPCP) focus on preparing a panel of health care professionals (HCPs) from different professions who can work together to enable the common goal of ensuring that children with ASD can participate in society. This study was designed to pilot this approach through an IPCP training module on ASD for care providers from multiple professions. Methods: An interventional study with pre-post analysis began with formation of the interprofessional (IP) team, who developed an IPCP module, addressing the knowledge and skills needed for the collaborative management of neurodevelopmental issues of children with ASD. This module was delivered through an online training workshop using various teaching learning methods to the participants from seven different health professions after obtaining informed consent. Perceptions of interprofessional collaboration and competencies of IPCP were assessed using standard IP tools and reflective summaries and analyzed through a mixed-methods approach. Results: A total of 42 HCPs from seven professions, including speech and hearing, occupational therapy, clinical psychology, physiotherapy, pediatrics, nursing, and pedodontics, participated in the study. Pre-post analysis of PINCOM-Q and Dow-IPEC data and thematic analysis revealed a significant difference in the perceptions of interprofessional collaboration and competencies levels of IPCP. Conclusion: This study suggests that use of IPCP principles in the training of professionals working with ASD is a promising and feasible option to develop more competent health professionals. The training enhanced the abilities of professionals to work in field of ASD as conveyed by the participants. They also expressed confidence in the knowledge of IP core competencies after the completion of the module. 2022 -
Evaluation of Clove Phytochemicals as Potential Antiviral Drug Candidates Targeting SARS-CoV-2 Main Protease: Computational Docking, Molecular Dynamics Simulation, and Pharmacokinetic Profiling
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus can cause a sudden respiratory disease spreading with a high mortality rate arising with unknown mechanisms. Still, there is no proper treatment available to overcome the disease, which urges the research community and pharmaceutical industries to screen a novel therapeutic intervention to combat the current pandemic. This current study exploits the natural phytochemicals obtained from clove, a traditional natural therapeutic that comprises important bioactive compounds used for targeting the main protease of SARS-CoV-2. As a result, inhibition of viral replication effectively procures by targeting the main protease, which is responsible for the viral replication inside the host. Pharmacokinetic studies were evaluated for the property of drug likeliness. A total of 53 bioactives were subjected to the study, and four among them, namely, eugenie, syzyginin B, eugenol, and casuarictin, showed potential binding properties against the target SARS-CoV-2 main protease. The resultant best bioactive was compared with the commercially available standard drugs. Furthermore, validation of respective compounds with a comprehensive molecular dynamics simulation was performed using Schringer software. To further validate the bioactive phytochemicals and delimit the screening process of potential drugs against coronavirus disease 2019, in vitro and in vivo clinical studies are needed to prove their efficacy. Copyright 2022 Chandra Manivannan, Malaisamy, Eswaran, Meyyazhagan, Arumugam, Rengasamy, Balasubramanian and Liu. -
Evaluation of Consumer Experiences by Extended AIDUA Framework in the World of the Metaverse the Future of Next-Gen Hospitality
The hospitality industry is continuously exploring novel ways to enhance consumer experiences, and the advent of the metaverse presents exciting prospects for transforming guest interactions. The metaverse can provide an immersive, 3D social experience of a virtual world by using technologies like virtual reality and augmented reality, which helps bridge the gap between the real and virtual worlds. This study explores consumer experiences in the metaverse in the hospitality context. Using the extended AIDUA (artificial intelligence device usage acceptance) model, the research aims to comprehensively analyze customers willingness to accept the metaverse in the dynamic digital landscape. The objective of this study is to investigate how the metaverse revolutionizes consumer experiences in the hospitality sector, specifically in the context of room and amenity booking, in-house events, and virtual tours. In this study, a three-step cognitive appraisal process with utilitarian motivation and the attitude of the customers that determines customers willingness and objection to utilizing AI devices is evaluated through secondary data. The metaverse empowers guests to optimize in-house event participation, seamlessly navigate their stay through taking a virtual walkthrough to explore a higher-end suite, and touring the city virtually. Practical implications for industry practitioners and researchers seeking to exploit the potential of the metaverse to create an immersive and unforgettable consumer experience in the ever-evolving landscape of hospitality are explored in this chapter. 2024 selection and editorial matter, Park Thaichon, Pushan Kumar Dutta, Pethuru Raj Chelliah and Sachin Gupta; individual chapters, the contributors. -
Evaluation of Corrosion Mitigation Performance of 1-(3,4,5-Trimethoxyphenylmethylidene)-2-Naphthylamine (TMPNA) Schiffs Base on Carbon Steel Using Electrochemical, Thermodynamic and Theoretical Approaches
A novel Schiff base,1-(3,4,5-trimethoxyphenylmethylidene)-2-naphthylamine(TMPNA) has been synthesized using naphthylamine and 3,4,5-trimethoxybenzaldehyde.The effective corrosion resistance and inhibition effect of TMPNA was studied at different concentrations in water medium on carbon steel by electrochemical techniques. The protective behavior of the passive film formed by the inhibitor was characterized through electrochemical impedance spectroscopy with an increased charge transfer resistance of 954 ?.cm2. The inhibition efficiency exhibited a gradual increase up to 92% with increase in schiff base concentration. Potentiodynamic polarization studies revealed that corrosion current decreased to 0.35 10?5A/cm2 with the addition of the inhibitor, TMPNA. Through various electrochemical studies such as impedance, polarization and electrochemical noise analysis (ENA), the concentration of TMPNA was optimized to 300ppm at which the maximum corrosion resistance was observed. Inhibition efficiency was found to decrease with increase in temperature. Also, the increased activation energy (Ea) value of 27kJ/mol confirmed that the inhibitor hindered the metal dissolution reaction. Adsorption of TMPNA on carbon steel/electrolyte interface was found to obey Langmuir adsorption isotherm. Scanning electron microscope (SEM) was used to evaluate the surface morphology. The Quantum chemical analysis (QCA) revealed that there was an electron transfer between TMPNA and the metal surface at ? 6.340eV. Molecular dynamic simulation study was carried out to investigate the adsorption of TMPNA on Fe (1 1 0) surface and adsorption energy value for the gaseous form was found to be ? 4197cal/mol. 2020, Springer Nature Switzerland AG. -
Evaluation of cytotoxicity and antioxidant properties of some Zingiberaceae plants
Aim: Zingiberaceae family is widely distributed in the tropical realm of Asia. Considering its diverse applications as spices and therapeutics, the present study was undertaken to evaluate the cytotoxic and antioxidant effect of the ethanolic rhizome extracts of five plants, namely Alpinia galanga (L.) Willd., Alpinia zerumbet (Pers.) B.L. Burtt and R. M. Smith, Curcuma caesia Roxb., Zingiber officinale Rosc., and Zingiber zerumbet (L.) Smith on Allium cepa Linn. system. Materials and Methods: Cytotoxicity was evaluated by 2,3,5-triphenyltetrazolium chloride (TTC) and 2',7'-dichlorofluorescein diacetate (DCFDAH 2 ) assays. Further, in vitro DNA protection assay was performed to confirm the antioxidant potentials of the extracts. Characterization of phytochemicals was done by performing qualitative tests. Results and Discussion: TTC reduction assay revealed that the extracts (2.5, 5, and 10 g/ml) had no cytotoxic effect on A. cepa root cells. Roots treated with extracts (2.5 g/ml) were stained with reactive oxygen species-sensitive dye DCFDAH 2 and visualized under the fluorescence microscope. The result confirmed that the extracts did not exert any prooxidant effect. Further, the extracts established their substantial antioxidant potential by inhibiting oxidative DNA damage in an in vitro system. In addition, qualitative analysis showed that the rhizomes are rich in phytochemicals. Conclusion: From the current observations, it can be concluded that the selected herbs can be utilized safely for human consumption. 2019 BRNSS Publication Hub. All Rights Reserved. -
Evaluation of cytotoxicity and antioxidant properties of some zingiberaceae plants /
International Journal of Green Pharmacy Supplementary Issue, Vol.12, Issue 4, pp.870-875, ISSN No: 1998-4103. -
Evaluation of Flow Resistance using Multi-Gene Genetic Programming for Bed-load Transport in Gravel-bed Channels
Evaluation of flow resistance is necessary for the computation of conveyance capacity in open channels. The significance of the friction factor in channels with bedload conditions is paramount. The response of flow resistance in gravel-bed channels in bedload transport conditions is distinct from that of a fixed bed. The paper studies the different empirical approaches in the literature to determine the friction factor under bedload transport conditions and proposes an expression by genetic programming for the same. Various hydraulic and geometric parameters affect flow resistance in the bedload transport condition. The present study includes bed slope, relative submergence depth, aspect ratio, Reynolds number, and Froude number as influencing factors for such flow conditions. A wide range of experimental datasets is employed to determine the effect of these influencing parameters and develop a customised single expression for the friction factor. The experimental data set has also been moderated for sidewall corrections. The predictability of the proposed model is compared to various empirical equations from the literature. Unlike the existing models, the proposed model provides a more extensive expression for effectively predicting the friction factor for a wide range of datasets. The conveyance capacity of a river is validated from the estimated value of friction factor, as compared to other standard models. The developed Multi-Gene Genetic Programming (MGGP) model reasonably predicts discharge in the rivers, signifying that the model can competently be applied to field study within the specified range of parameters. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Evaluation of forecasting accuracy of an equity valuation model: a case of ZEE
Investing can prove to be a very enriching and enjoyable experience if one sticks to certain principles and guidelines. The research is based on secondary data pulled out from Money Control website for ZEE Entertainment Enterprises Limited (ZEEL). The identification of target prices is important and involves precision in the price points that are forecasted. The expected growth rate for the next year is figured out to forecast the financial statement for the next year. Regression analysis has been used to estimate growth rate. Regression analysis was done on the income data for the past years for the media entertainment company, and the target prices have been identified. By taking a careful look at the forecasted prices and the prevailing prices, an investor can figure out whether the stock is under-priced or over-priced. 2023 Inderscience Enterprises Ltd. -
Evaluation of Gamified TrainingASolomon Four-Group Analysis of the Impact of Gamification on Learning Outcomes
Gamification is the application of game elements to non-game contexts. The process of gamification has been found to improve engagement levels, motivate participation and improve outcomes of activities. The primary focus of Gamification research has been on understanding how it can improve the process of learning, especially in academics or education. The impact of gamification in the organizational context is still relatively unexplored. The current study attempts to provide evidence supporting the use of gamification in organizational training. The study adopted an experimental methodology and is set in the context of organizations in India. The findings suggest that potential learners responded more positively to the gamified module and the knowledge gained was also higher through the gamified module. The gamified module also resulted in higher learner motivation. Thus, the current study provide support for the Theory of Gamified Learning that proposes that Gamification would increase Learner Motivation and thereby improve Learner reaction to the training and increase Learning. 2021, Association for Educational Communications & Technology. -
Evaluation of hydroxyapatite filler loading on dynamic mechanical properties of combined silk and basalt fabric reinforced epoxy nanocomposites
The boosting of electrical and microelectronic goods causes the continuous increase in the amount of power per unit volume of these gadgets, leading to unavoidable overheating problems that diminish their functional performance as well as life span. One of the primary aims of materials science is the creation of high-performance materials that are made from renewable resources. Multi-phase composites were recognised as an effective route to achieve a new portfolio of advanced materials with superior performance. Some of the functional fillers in polymer-based composite materials exhibit outstanding electrical insulation, chemical resistance, mechanical and processing properties, and therefore are considered to be the most promising candidates to solve the heat dissipation problem. In this research article, the thermal behavior, namely Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction Analysis (XRD), and Dynamic mechanical analysis (DMA) of hybrid nano-sized hydroxyapatite filled hybrid fiber reinforced epoxy nanocomposites are investigated. Three important parameters were examined at 1 Hz frequency: storage modulus, loss modulus, and damping, all from room temperature to 160 C. The influence of the nHAP loading on the dynamic mechanical properties are discussed and explained with the highly relevant works from the available literature. In particular, the dependence of the hybrid composite damping on the nHAP loading was explained with regard to damping due to particleparticle and polymer-fiber interaction. The presence of nHAP is confirmed by a wider XRD curve, and the incorporation of nHAP results in the removal of the hydroxy group from the fibers as shown by FTIR. The inclusion of nHAP in a hybrid (S + B/Ep) composite enhances the synergetic effect, which raises the storage and loss modulus, decreases the damping factor, and increases the Tg of the nHAP filled hybrid nanocomposites. 2021 -
Evaluation of lime juice as potential green corrosion inhibitor using gravimetric and electrochemical studies
Lime, a vibrant fruit of citrus family is known for its antioxidant as well as anti-microbial properties. The constituents of lime juice include organic acids, polyphenols, soluble sugars, vitamins, minerals and amino acids. These details prompted to experiment lime juice as corrosion inhibitor for mild steel in 1 M HCl. The weight loss studies showed that the corrosion inhibition efficiency increased with increase in concentration of the lime juice as well as increase of temperature. The inhibition efficiency reached a maximum of 96% for an immersion period of 24 h. The best fit for the adsorption process obeyed Langmuir isotherm. The negative value of ?Gads showed the spontaneity of the corrosion inhibition process. The corrosion inhibition efficiency of the acidified lime juice was further validated by electrochemical studies namely AC impedance studies and potentiodynamic polarization studies. The surface morphology study was performed used optical profilometer. 2020 Chemical Publishing Co.. All rights reserved. -
Evaluation of machine and deep learning models for utility mining-based stock market price predictions
Considering the extreme volatility of stock market returns and hazards, accurate price prediction has attracted the attention of both financial institutions and regulatory bodies. Stocks, due to their historically strong returns, have long been considered by investors to be an excellent asset allocation strategy. Predicting stock prices has never ceased being a hot topic of study. Many early-day economists sought to foretell future stock values. In subsequent years, as computer technology has advanced rapidly and mathematical theory has been extensively studied, it has been shown that mathematical models, like the time series model, may be very effective in predicting due to their simplicity and superiority. Over time, the time series model is put into practice. Over time, the horizon widened. Support vector machines and other ML techniques have challenges when applied to stock data because of its non-linearity. In subsequent years, thanks to advancements in deep learning, models like RNN and LSTM Neural Networks were able to analyze non-linear input, remember the sequence, and remember valuable information,Stock data forecasting cannot be done without it. 2024 Author(s). -
Evaluation of machine learning algorithms for surface water delineation using landsat 8 images
Surface water detection and delineation is an important and necessary step in change detection studies on water bodies using multispectral images. Commonly used techniques for surface water delineation from multispectral images are single band density slicing, spectral index based, machine learning based classification and spectral un mixing based methods. This paper presents a comparative study of commonly used machine learning algorithms viz. ANN, SVM, Decision Tree, Random Forest and K-means clustering for their suitability and effectiveness when applied on Landsat 8 images for surface water detection and delineation. The algorithms are compared for their classification accuracy and execution time. While all the above mentioned algorithms exhibited their usefulness in water detection, Decision Tree and Random Forest algorithms were found be faster in both training phase and testing phase and also yielded better accuracy with fewer miss-classifications. Though K-means clustering with more than four clusters yielded results comparable to that of supervised classification methods, it requires appropriate post-processing to obtain the output image with only two clusters; corresponding to water pixels and non-water pixels. Pierson's correlation co-efficient and Structural similarity Index (SSIM) are computed to compare the correlation and similarity of the output images yielded by the algorithms being studied. 2020, Institute of Advanced Scientific Research, Inc. All rights reserved. -
Evaluation of Maximum Bending Stiffness of Stranded Cables with Refined Kinematic Relations
The mechanical response of a helically stranded cable depends on the effective stiffness offered by the collective assembly of its constituent wires. This can vary between two extreme conditions, namely a monolithic state, also known as the stickslip state, wherein all the wires in the cable behave as a single unit with no relative movements among themselves, offering the maximum stiffness for the cable. In the other extreme condition, all the wires are free to move among themselves, with no frictional holding among them, thus offering the minimum stiffness. This paper reviews the various mathematical models that are available for the estimation of maximum bending stiffness and brings out the need for considering a vital parameter known as the wire stretch effect that has been neglected by many authors till date. The consequent fundamental changes that occur in the basic kinematic relations are brought out and refined expressions for the internal wire forces and moments are established for the first time in the coupled axial-bending analysis. Further, the shear displacement of the wire due to the stretch has also been included in the wire normal and binormal shear forces. A single-layered cable with core-wire contact has been considered for analysis and the numerical results are evaluated with these new inclusions and are compared with the published results. It is hoped that the refined model suggested in this paper for the accurate estimation of the maximum stiffness, will pave way for more reasonable cable analysis in the subsequent slip stages. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Evaluation of Mechanical Properties and Microstructure of Polyester and Epoxy Resin Matrices Reinforced with Jute, E-glass and coconut Fiber
Composite manufacturing is a novel branch of science and often finds numerous applications in several industries. Some of them are sport, automobile, aerospace and marine industries. Some of the properties that can be highlighted are good mechanical properties along with stiffness and comparatively lighter weight. There is a continuous research in this area is as the constant pursuit to achieve greater performance by changing various materials and the combinations of those with various resins are experimented. In the current work, polyester and epoxy resins were reinforced with coconut, E-glass and jute fibers of 5-6mm length and were prepared by hand layup method. The fiber and resin were taken in 18:82 weight percentages. Post production of the composites they were subjected to various physical mechanical and microstructural studies to determine various properties. The morphological features were analyzed through the microstructural study done through scanning electron microscope. In comparison with the composites manufactured, The artificial fiber reinforced composite, E-glass fiber reinforced epoxy composites exhibited superior tensile strength, flexural strength, impact toughness and hardness values. Among the natural fiber reinforced composite, coconut fiber reinforced composites exhibited better tensile, impact and hardness than its counterpart jute reinforced composites. Thus the resins reinforced with E-glass fiber had the highest mechanical properties when compared with jute fiber reinforced composites (JFRC) and coconut fiber reinforced composites (CFRC). The cost effectiveness of the natural fiber reinforced composites is also an added advantage over the artificial fiber reinforced composites. 2018 Elsevier Ltd. -
Evaluation of mechanical properties of e-glass and coconut fiber reinforced with polyester and epoxy resin matrices
Composite manufacturing is the novel branch of science, which finds its immense applications in various industries such as sporting, automotive, aerospace and marine industries. The superior properties of composites such as stiffness, better mechanical properties, low density and light weight make it a candidate in engineering applications. The need for seeking alternate materials with increased performance in the field of composites revived this research, to prepare fiber reinforced composites by hand layup method using E-glass and coconut fibers with length 5-6 mm. The resin used in the preparation of composites was epoxy and polyester. Fiber reinforced composites were synthesized at 18:82 fiber-resin weight percentages. Samples prepared were tested to evaluate its mechanical and physical properties, such as tensile strength, flexural strength, impact strength, hardness and scanning electron microscope (SEM). Scanning electron microscope analysis revealed the morphological features. E-glass fiber reinforced epoxy composite exhibited better mechanical properties than other composite samples. The cross linking density of monomers of the epoxy resin and addition of the short chopped E-glass fibers enhanced the properties of E-glass epoxy fiber reinforced composite. TJPRC Pvt. Ltd.