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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 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 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 and analysis of quality in e commerce (B2C Website) /
There has been a phenomenal growth in Ecommerce in the last few years and it is still growing. As the market is expanding, more and more organizations want to have web presence. Due to sudden and rapid demand in Ecommerce website, website development companies are ignoring or skipping the quality factor. Apart from this, due to popularity of Internet, more and more consumers are buying products and services through ecommerce websites. The software development companies want to delivery the products quickly, to make fast money. To meet the deadlines, usually the quality of the product is not taken as a priority, resulting in a product full of bugs, being shipped to the customers. Once the software becomes live, more and more bugs keep coming resulting in loss of business and credibility of the organization is affected. Lack of quality Ecommerce websites result in consumers moving back to the alternate methods of shopping or switching to another website. With the increase in the competition, companies have started studying the consumer behavior and determining the factors that affect the quality of Ecommerce websites form the consumers perspective. During these years, several lessons have been learned about the technology, business and economy of Ecommerce. -
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. -
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 role of soil EPS in modifying the toxicity potential of the mixture of polystyrene nanoplastics and xenoestrogen, Bisphenol A (BPA) in Allium cepa L.
The coexistence of emerging pollutants like nanoplastics and xenoestrogen chemicals such as Bisphenol A (BPA) raises significant environmental concerns. While the individual impacts of BPA and polystyrene nanoplastics (PSNPs) on plants have been studied, their combined effects are not well understood. This study examines the interactions between eco-corona formation, physicochemical properties, and cyto-genotoxic effects of PSNPs and BPA on onion (Allium cepa) root tip cells. Eco-corona formation was induced by exposing BPA-PSNP mixtures to soil extracellular polymeric substances (EPS), and changes were analyzed using 3D-EEM, TEM, FTIR, hydrodynamic diameter, and contact angle measurements. Onion roots were treated with BPA (2.5, 5, and 10 mgL-1) combined with plain, aminated, and carboxylated PSNPs (100 mgL-1), with and without EPS interaction. Toxicity was assessed via cell viability, oxidative stress markers (superoxide radical, total ROS, hydroxyl radical), lipid peroxidation, SOD and catalase activity, mitotic index, and chromosomal abnormalities. BPA alone increased cytotoxic and genotoxic parameters in a dose-dependent manner. BPA with aminated PSNPs exhibited the highest toxicity among the pristine mixtures, revealing increased chromosomal abnormalities, oxidative stress, and cell mortality with rising BPA concentrations. In-silico experiments demonstrated the relationship between superoxide dismutase (SOD), catalase enzymes, PSNPs, BPA, and their mixtures. EPS adsorption notably reduced cyto-genotoxic effects, lipid peroxidation, and ROS levels, mitigating the toxicity of BPA-PSNP mixtures. 2024 Elsevier B.V. -
Evaluating the Role of Economic Factors in Sustainable Consumption Behaviour
The research paper investigates the intricate nexus between economic factors and sustainable consumption behaviour, providing a nuanced exploration of how such considerations shape an individuals choice in the realm of environmental responsibility. Drawing on established theories of consumer behaviour and sustainability, this study employs a positivist approach encompassing quantitative surveys and analysis. It scrutinises the effects of prices, expectations and other broader economic conditions on the adoption of sustainable practices. The findings contribute significantly to the existing body of knowledge by providing a holistic understanding of the economic levers instrumental in driving towards sustainable consumption like taste and preferences and price or hindering the shift towards sustainable consumption like societal behaviour and availability of alternatives. This research aims to inform policymakers, businesses and consumers alike, facilitating the development of targeted interventions and initiatives that foster a harmonious convergence of economic and ecological goals. 2024 IOS Press BV. All rights reserved. -
Evaluating the Pertinence of Pose Estimation model for Sign Language Translation
Sign Language is the natural language used by a community that is hearing impaired. It is necessary to convert this language to a commonly understandable form as it is used by a comparatively small part of society. The automatic Sign Language interpreters can convert the signs into text or audio by interpreting the hand movements and the corresponding facial expression. These two modalities work in tandem to give complete meaning to each word. In verbal communication, emotions can be conveyed by changing the tone and pitch of the voice, but in sign language, emotions are expressed using nonmanual movements that include body posture and facial muscle movements. Each such subtle moment should be considered as a feature and extracted using different models. This paper proposes three different models that can be used for varying levels of sign language. The first test was carried out using the Convex Hull-based Sign Language Recognition (SLR) finger spelling sign language, next using a Convolution Neural Network-based Sign Language Recognition (CNN-SLR) for fingerspelling sign language, and finally pose-based SLR for word-level sign language. The experiments show that the pose-based SLR model that captures features using landmark or key points has better SLR accuracy than Convex Hull and CNN-based SLR models. 2023 World Scientific Publishing Europe Ltd. -
Evaluating the performance of machine learning using feature selection methods on dengue dataset
Dengue fever is a mosquito-borne disease transmitted by the bite of an Aedes mosquito infected with a dengue virus. The bites of an infected female Aedes mosquito which gets the virus while feeding on the infected persons blood, transmits the virus to others. Dengue transmission is climate sensitive for several reasons such as temperature, humidity, rainfall, etc. Areas having higher vapor pressure and rainfall rate are most vulnerable to the spreading of the dengue disease. So to find the important features responsible for spreading the dengue we have used the classification algorithms. Machine learning is one of the key methods used in modern day analysis. Many algorithms have been used for medical purposes. Dengue disease is one of the serious contagious diseases. To find the features related to spreading of dengue disease, we have used popular machine learning algorithms. This proposed work focuses on evaluating the performances of the various machine learning techniques like-Random Forest Classifier (RFC), Decision Tree Classifier (DTC) and Linear Support Vector Machine (LSVM). Predictive Mean Matching is applied for preprocessing of the data and percentage split is applied for resampling of the data. Information gain values for each of the attributes are calculated. The attributes are sorted on the basis of information gain values. Feature selection methods (FSMs) such as Forward Selection (FS) and Backward Elimination (BE) are applied to choose the finest subset of the attributes, so that the algorithm runs more efficiently with a lower run time. It also results in the improvement of the accuracy. The attributes selected by the Feature Selection Methods are the main attributes which results in the probable effects of global weather change on human healthiness. BEIESP. -
Evaluating the performance of indian banks: Eagles model approach
Sound financial health of a bank is the guarantee not only to its depositors but is also equally significant for the shareholders, employees and whole economy as well. Various steps and policies have been made from time to time, to measure the financial position of each bank and manage it efficiently and effectively. The introduction of new banking policies and technological advances put banks into more complex and risky situations. CAMEL model is widely used tool for measuring the efficiency and performance of banks which has been proved to be outdated. EAGLES model is a proper tool to measure the financial performance as well as the soundness of banks in a more determinate, objective and consistent manner, as the banks are being analyzed on the output ratios. The present study aimed at finding out the financial performance and soundness of selected Indian commercial banks, analyzing six major parameters which are key success factors of every bank today. Indian Institute of Finance. -
Evaluating the performance of Cr-Soc-MOF Super-Adsorbents for CO2 capture from flue gas under humid condition through molecular simulation
One of the major criticisms for gas separation by utilizing Metal Organic Framework (MOF) porous material for all classes of adsorbents is their very poor performance under humidified gas streams. Very few MOFs show better CO2 separation from N2 mixture in the presence of moisture. Conversely, plenty of MOFs demonstrated good CO2 capture from dry gas streams. In order to explore the potential characteristics of gas separation under humid conditions by coordinatively unsaturated metal organic framework (CUS-MOF) with square octahedral (Soc) topology were exercised single component (CO2, N2) adsorption and co-adsorption (CO2/N2) in the presence of moisture at 298 K with pressure ranging from 0 to 10 bar. Herein, we investigated five exceptional Cr-Soc-MOFs similar to the experimentally established iso-structural topology by differing the polynuclear aromatic ring size and N-heteroatom to their pore wall. The specific interaction of guest molecules to the coordinatively unsaturated metal site (CUS), i.e., rigid ?3-oxygen-centered tri-nuclear metal carboxylate, of Cr-Soc-MOF-n series were identified with Density Functional Theory (DFT) calculations, this energy profile was used to derive specific force field. Further, Grand canonical Monte Carlo (GCMC) simulation was employed with DFT-derived force field to identify suitable CO2 capture for Cr-Soc-MOFs in the presence of moisture. Interestingly, the Cr-Soc-MOFs with larger pore volume were retained not only CO2 uptake in the range of 23 35 wt% but also selectivity about 20 50 range even up to 70% of RH. Importantly, we introduced a mathematical tool to theoretically analyze the dynamic co-adsorption in the form of breakthrough curve measurement from CO2/N2 simulated co-adsorption by mimicking the real flue gas condition, also working capacity (?N), Regenerability (R%) and Adsorbent Performance Indicator (API) of Cr-Soc-MOF-n series were investigated. The CO2 separation performances of Cr-Soc-MOF-n series suggested that the polynuclear aromatic ring to their pore wall withstand CO2 uptake in the presence of humidity rather than N-heteroatom decorated Cr-Soc-MOF due to its high pore volume and the accommodation of extra aromatic ring in their pore channels. 2022 Elsevier B.V. -
Evaluating the impact of microlearning and micro-lessons and implications for general education
The educator training approach known as microteaching, which is used now all over the world, offers teachers the chance to sharpen their teaching abilities by enhancing the many straightforward activities referred to as teaching skills. Microteaching supports the growth of in-person teaching experiences thanks to its success with both beginners and older students. The fundamental abilities of microteaching, such as exposition and reinforcing abilities, aid new instructors in mastering the craft of instruction with ease and to the fullest. This method's effects have been widely observed in a variety of educational settings, including the biological sciences, health sciences, and other fields. The chapter reflects upon the basic concepts of microteaching, microlearning, and micro lessons. The study discusses the fundamental teaching techniques, implementation issues, and the effects of microlearning on education. The study also throws light on the impact and advances of technology on microlearning in the context of the digital age. 2024, IGI Global. -
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EVALUATING THE ELEMENTS IN THE RECREATIONAL SPACE OF AN INSTITUTION
The concept of 'Recreation' justifies the human need for satisfaction, leisure, and a state of pleasure. The elements involved in a recreational space impact the activities of the user in that space. Recreational spaces act as the in-between sojourns for formal pedagogy or andragogy. Spaces of recreation are essential, especially in educational institutions, where students spend most of their time. Public, semi-public, and private spaces are all included in the institutional design, with a large percentage used by students. Open public spaces, including recreational places, are measured in terms of their physical characteristics and connections to nature. The components of a recreational area influence the activities that users engage in there. This paper seeks to list and assess the many components that are present in a recreational space. This study will evaluate those elements and their types. Informal outdoor areas or other breakout areas promote interaction and provide the students with refreshments and leisure. The focus of this paper is to draw out the quality of leisure space synonymous with a productive environment for the student, where they feel rejuvenated. Five recreational spaces of CHRIST University were studied, and the elements that combine to form this place were also observed. A survey among the students who are frequent users of these spaces was conducted, and their responses were evaluated. The elements that majorly help students go to a place were assessed, and the element's significant role was concluded. The result of this study to design professionals is to understand the need to incorporate recreational spaces while designing an educational institution and design a student-oriented space. ZEMCH Network. -
Evaluating the Effectiveness of a Facial Recognition-Based Attendance Management System in a Real-World Setting
Face recognition technology has been extensively used in multiple verticals of security, surveillance, and human-computer interaction. Conventional techniques including manual sign-ins, identity cards, or biometric verification have been used by traditional attendance systems. Face recognition systems have, however, become a popular way to track attendance, thanks to developments in computer vision and machine learning. The construction of an attendance registration application is the main topic of this research study, which also offers a thorough overview of facial recognition attendance systems. This study seeks to provide light on the benefits, drawbacks, and potential applications of these fast-developing technologies. Face recognition technology may be integrated into attendance systems to increase productivity, accuracy, and user comfort. However, issues like privacy worries and technological constraints must be resolved. With predicted future improvements in machine learning algorithms and hardware capabilities, face recognition attendance systems look to have a bright future. This research article adds to a deeper understanding and successful application of facial recognition technology in attendance systems by examining these features. 2023 IEEE. -
Evaluating the effect of different ligands on the supercapacitance and hydrogen evolution reaction studies of Zn-Co MOF
Metal-Organic Frameworks (MOFs) have recently attracted a lot of interest because of their potential uses in energy storage and catalysis. In this study, we investigate the impact of various ligands on the electrochemical performance of Zn-Co MOFs for both energy storage and hydrogen evolution reaction (HER) studies. Specifically, Zn-Co MOFs are synthesized using different ligands, and their structural and electrochemical properties are characterized by a range of analytical techniques. 2,5-dihydroxybenzoic acid (DBA) and benzene-1,2,4,5-tetracarboxylic acid (BTC) are employed due to their distinct structural features and potential effects on MOF performance. Subsequently, electrochemical studies are conducted to assess the supercapattery performance and HER activity of these MOFs. The specific capacitance and overpotential value at 10 mA/cm2 of Zn-Co/DBA MOF is observed to be 1775.3 F/g and 186 mV, whereas that of Zn-Co/BTC MOF is found to be 136.6 F/g and 279 mV. The MOF synthesis using DBA as a ligand is more effective for energy-related applications. This study aims to report a multifunctional MOF composite for energy and environmental applications with better efficiency than other reported systems. Our findings provide insights into how the choice of ligand influences the structural properties and electrochemical behavior of Zn-Co MOFs, shedding light on the potential of these MOFs as versatile materials for energy storage and HER applications. 2024 Elsevier B.V. -
Evaluating the Categorical Exclusion of Khasi Women from Inheritance and Property Rights : A Case of East Khasi Hills
Customary laws govern inheritance among many tribal communities that fall within the ambit of the fifth and sixth schedules of the Indian Constitution. Under this papers scope, we shall look at the Khasi community hailing from the state of Meghalaya which is a matrilineal community. Where the Khasis draw their lineage from their mothers, there is a misnomer that women inherit and own the entire property. In light of the abovementioned background, the paper makes an analytical study of the customary inheritance rights of Khasi women, the nature of resource ownership and attempts to understand the grounds behind the claims of gender preference in the existing matrilineal system practised by the Khasis of Meghalaya. We also look at the intersection of gender and matrilineal system of inheritance in the Khasi community, the dispute between customs and legislations and examine whether there exists a need for codification. The paper also discusses the findings of the survey and focus group discussions including 90 Khasi women from East Khasi Hills and their growing consensus on equal inheritance rights but resistance towards statutory laws to govern their lives. JYOTI SINGH AND KAJORI BHATNAGAR, 2024. -
Evaluating prolonged corrosion inhibition performance of benzyltributylammonium tetrachloroaluminate ionic liquid using electrochemical analysis and Monte Carlo simulation
Corrosion inhibition performance of a newly synthesized ionic liquid Benzyltributylammonium tetrachloroaluminate [BTBA]+[AlCl4]?on carbon steel has been studied using electrochemical impedance and noise analysis in 2 N HCl medium. The synthesized product was characterized by ATR-FTIR and1H NMR spectroscopic studies. The investigation revealed that the synthesized ionic liquid, [BTBA]+[AlCl4]?showed a remarkable noise and charge transfer resistance against corrosion. The adsorption behaviour of [BTBA]+[AlCl4]- on metal surface was found to follow Langmuir adsorption isotherm. The inhibition efficiency is measured as a function of immersion time and exhibited prolonged protection against acidic corrosion. Results derived from UVVis spectra explained the complex formation between the metal surface and ionic liquid in acid medium. SEM/EDAX has been used to examine the surface protection offered by the ionic liquid. [BTBA]+[AlCl4]?ionic liquid exhibited good corrosion inhibitor property with an efficiency of 97% at the optimum concentration. Quantum chemical analysis and molecular simulation studies were performed to support the experimental data. 2019 Elsevier B.V. -
Evaluating forces associated with sentient drivers over the purchase intention of organic food products
The study proposes to find out the factors which influence awareness among the consumers towards purchasing organic food product. The study is based on primary data by using tools Chi-square test, Cronbach alpha, KMO, and Bartlett's test, ANOVA, regression, correlation, and cross-tabulation. The study found that awareness driver's nutritional information, price, certification, brand name, and logos have an essential influence on the purchase intention of the product of organic food. However, labeling and food standards do not show a noteworthy rapport between labeling and organic food products' purchase plans. The core commitment and flow to explore are to analyze purchasers with respect to organic guarantee systems (accreditation, guidelines, logo, imprints, and confirmation) so we can distinguish the genuine organic products. The independent factors of awareness like organic buying preference and buying frequency, have a significant influence on the purchase intention of organic food. The research provided evidence of consumer awareness and purchase intention of organic food that would help the organic food industry to promote their products according to the attribute of customers. 2020 Asian Economic and Social Society. All rights reserved.