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Developing anticipatory and cognitive skills for sustainable management
This chapter's subject is integrating cognitive and anticipatory abilities, systems thinking proficiency, and social and emotional intelligence into sustainable management practices. The chapter examines the significance of proactive strategies in tackling the intricacies of economic, environmental, and social systems. Suggestions centre on frameworks for skill development, cultural alignment, and individual, team, and organizational progress to cultivate a dynamic learning environment. By adopting these principles, organizations can effectively navigate uncertainties, cultivate ethical leadership, and achieve sustainable outcomes. 2024 by IGI Global. All rights reserved. -
Developing authentic thought leaders through the DREAMS model of social action
DREAMS is a three-year curriculum-based after-school intervention program for enhancing leadership qualities among the underprivileged and college/university youngsters. It is an innovative model providing a platform for the mentors and the mentees to share their thoughts and knowledge and create a future generation with a growth mindset. The current world is expecting authentic thought leadership among its workforces. This leadership would help the constantly changing world to guide and lead the followers effectively for a better outcome. This study explores the impact of the DREAMS intervention program by Christ University in entrenching authentic thought leadership among its undergraduates. The study employs a qualitative approach to explore the perceptions among Christ University undergraduates about the contributions the DREAMS has made to their leadership development. The study finds evidence that DREAMS initiatives at Christ University have transformed undergraduates into authentic thought leaders. 2024 Nova Science Publishers, Inc. -
Developing Critical Thinking Skills Among Secondary School Students: Need of the Hour
Golden Research Thoughts, Vol-3 (2), pp. 1-3. ISSN-2231-5063 -
Developing employment capacity: The impact of academic student organization on the students core competencies
The purpose of this research is to understand the relationship between developing employment capacity with the enhanced core competencies by participating in student body organizations while pursuing their undergraduate degree program. This research aims at understanding the Communication Skills of the Students Core Competencies that are affected by their participation in the student organizations. This research aims at understanding the overall Character Development of the student by their participation in the student organizations. This research aims at understanding the Critical Thinking skills of the students core competencies that are affected by their participation in the student organizations. This research aims at understanding the Career Development skills of the students core competencies that are affected by their participation in the student organizations. This research aims at understanding how the development in the students core competencies help in improving the students employment capacity. This is an empirical study carried out using primary and secondary methods of data collection. Literature of relevant topics were gathered and studied to assist in the study. A questionnaire was circulated to 350 respondents in order to gather information. This study shows that the students who are actively involved in student organizations develop core competencies that help them during employment. The study has proved the students develop better skills which are very useful for their life. The limitations of the study are that all the students do not develop similar skills because they play various different roles in the student organizations. Some students are less involved and the research does not take into consideration the degree of involvement. The study aims to ultimately create a system that measures the students performance and involvement in the organizations. The university can motivate students and encourage them to be more enthusiastic about participating in student organizations. 2020, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Developing mathematical models to analyze economic growth patterns in emerging market dynamics
A key factor in determining national development and directing successful market strategies is economic growth. Making better judgements in developing countries is facilitated for investors and policymakers by having a better understanding of the main drivers of growth. The purpose of this paper is to use mathematical models to explain how economic growth patterns vary among the major growing nations. It examines the effects of inflation, foreign investment, trade, and current account balances on the GDP growth of five major economies India, China, Russia, Brazil, and South Africa between the year 2005 to 2025. The study presents how these variables connect to growth and vary among nations using techniques like logistic regression, linear regression, and ANOVA. TARU PUBLICATIONS. -
Developing the assessment questions automatically to determine the cognitive level of the e-learner using NLP techniques
The key objective of the teaching-learning process (TLP) is to impart the knowledge to the learner. In the digital world, the computer-based system emphasis teaching through online mode known as e-learning. The expertise level of the learner in learned subjects can be measured through e-assessment in which multiple choice questions (MCQ) is considered to be an effective one. The assessment questions play the vital role which decides the ability level of a learner. In manual preparation, covering all the topics is difficult and time consumable. Hence, this article proposes a system which automatically generates two different types of question helps to identify the skill level of a learner. First, the MCQ questions with the distractor set are created using named entity recognizer (NER). Further, based on blooms taxonomy the Subjective questions are generated using natural language processing (NLP). The objective of the proposed system is to generate the questions dynamically which helps to reduce the occupation of memory concept. 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. -
Developing the Skill Set of Generation Alpha through Toy Engagement: Building a Novel, Toy-Based Pedagogy (TBP)
Toy-Based Pedagogy (TBP) is a relevant, recognized teaching approach adopted by educational institutions to enhance the learning curve of children. Toys help Generation Alpha children develop skills, and the current paper underlines the need to include these skills into Indias Toy-Based Pedagogy (TBP) and suggest revisions. The data for the current study is directly elicited from Generation Alpha which is a novel intervention in pedagogical research. Educational pedagogies should be constantly revised and updated catering to the needs of the current generation. The findings of the study are highly relevant, as they highlight what Generation Alpha seeks and values in the current Toy-Based Pedagogy (TBP). The data was collected directly from primary school children aged 6 and 7 years. The paper adopts qualitative methodology and purposive sampling technique to obtain data from children through one-on-one interviews using an interview schedule. Thematic analysis employed suggested that children developed different skills through toy engagement. Furthermore, the study gives deep insights on the revisions required for the existing TBP to better suit the educational needs of Generation Alpha. 2025 by the authors. -
Development and Analysis of Current Collectors for Proton Exchange Membrane Fuel Cells
Hydrogen fuel cells are gaining popularity in power-consuming devices due to their zero-emission characteristics. However, ohmic resistance, which arises from the resistance to electron flow through the electrodes and external circuit, can cause reduced efficiency and voltage drops in a fuel cell. This research aims to develop current collector plates for proton exchange membrane fuel cells with optimal design, high electrical conductivity, and thermal conductivity to mitigate ohmic resistance. Six different designs and five different materials-copper, brass, aluminum, stainless steel 316, and stainless steel 304 were considered for this purpose. The study involved experimental electrical conductivity and fuel cell performance tests to identify the best material and design for the current collector. Results indicated that brass and copper exhibited the least resistivity and favorable material characteristics. Consequently, all six current collector plate designs were developed using brass and copper with various machining and finishing processes. Performance testing on a fuel cell test station revealed that brass current collector plate design 5, featuring open ratios, demonstrated superior performance. Ultimately, the optimum design and material selection of the current collector plates have led to the development of fuel cells with reduced ohmic resistance and improved overall performance. 2024, Politechnika Lubelska. All rights reserved. -
Development and characterization of carbon fiber reinforcement in Aluminium metal matrix composites
Carbon fibers (CF) possess exceptional mechanical properties and the highest degree of chemical stability. However, carbon reinforcement in metal matrix composites is extremely scarce due to production difficulties, particularly in obtaining a uniform distribution. Carbon fiber reinforced composites are typically made using high temperature processing processes. However, the fibers must be coated with Ni or Cu in order to achieve effective particle dispersion; otherwise, there is a larger likelihood of intermetallic compound formation, which reduces the chances for enhanced properties. In this work, the metallurgical, mechanical, and tribological characteristics of the carbon fiber reinforcement in AA 7050 are examined. Uncoated carbon fibers are reinforced into the Aluminium matrix using a low temperature processing technique known as powder metallurgy. The AA 7050 matrix reinforced with carbon fibers at various weight percentages between 0 and 1.5. The samples undergone mechanical and metallurgical testing in accordance with ASTM guidelines. The findings indicate that the 0.25 weight percent carbon fiber reinforcement in the matrix increased the material's hardness by 30% over the monolithic alloy, making it an excellent alternative for structural applications. Published under licence by IOP Publishing Ltd. -
Development and characterization of Fe2O3 nanoparticles coated with chitosan and folic acid for biomedical applications
Polymeric inorganic nanoparticles have emerged as promising nanomedicines due to their unique properties, offering enhanced antibacterial and anticancer effects. Thus, the study focus on the synthesis of Fe2O3 and Fe2O3 coated with chitosan and folic acid nanoparticles (Fe2O3-CS-FA NPs) mediated by Tagetes erecta (T. erecta) extract and assess their biological effects. The synthesized NPs are analysed by various characterisation techniques. FTIR spectroscopy of Fe2O3 and Fe2O3 -CS-FA NPs revealed characteristic peaks corresponding to Fe2O3, chitosan, and folic acid molecules. The XRD pattern confirmed the successful synthesis of Fe2O3 NPs and Fe2O3 -CS-FA NPs, indicating a rhombohedral structure. FESEM demonstrated spherical structures for both Fe2O3 and Fe2O3 -CS-FA NPs. Antimicrobial activity was assessed against various pathogens using the disk diffusion method, showing that Fe2O3-CS-FA NPs demonstrated superior antibacterial activity compared to Fe2O3 NPs. In terms of antioxidant activity, Fe2O3 -CS-FA NPs showed the highest scavenging activity against DPPH, outperforming Fe2O3 NPs. The anticancer activity of both Fe2O3 NPs and Fe2O3 -CS-FA NPs was tested against the HCT-116 human colon cancer cell line, where Fe2O3 -CS-FA NPs demonstrated greater anticancer activity with an IC50 value of 10.2 ?g/mL compared to Fe2O3 at 13.8 ?g/mL. Based on the findings of this research, there is a strong indication that Fe2O3 -CS-FA NPs hold significant potential as a nanomaterial well-suited for advanced biomedical applications in the industry. 2025 Indian Chemical Society -
Development and Evaluation of an Artificial Intelligence-Based System for Pancreatic Cancer Detection and Diagnosis
Due to its aggressive nature and late-stage manifestation, pancreatic cancer is a difficult illness to find and diagnose. The creation of a pancreatic cancer detection and diagnosis system based on artificial intelligence (AI) has the potential to increase early detection and improve treatment results. We have described the creation and assessment of an AI-based system in this paper that is intended for the identification of pancreatic cancer. A large dataset including a variety of medical pictures, including CT scans, MRI scans, and PET scans, as well as the related clinical information, was gathered for the study. With the help of the annotated dataset, a deep learning model built on convolutional neural networks was created. The proposed AI-based solution was then assessed using a separate test dataset made up of control cases and known pancreatic cancer patients. A significant effectiveness for the early diagnosis of the disease was shown by the systems excellent precision as well as sensitivity in identifying pancreatic tumors. The outcomes of this investigation demonstrate the promise of AI-based systems for pancreatic cancer detection and diagnosis. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
DEVELOPMENT AND EVALUATION OF PNEUMFC NET: A NOVEL AUTOMATED LIGHTWEIGHT FULLY CONVOLUTIONAL NEURAL NETWORK MODEL FOR PNEUMONIA DETECTION
The aim of this study is to address the challenges of pneumonia diagnosis under constraint resources and the need for quick decision making. We present the PneumFC Net, a novel architectural solution where our approach focuses on minimizing the number of trainable parameters by incorporating transition blocks that efficiently manage channel dimensions and reduce number of channels. In contrast to using fully connected layers, which disregard the spatial structure of feature maps and substantially increase parameter counts, we exclusively employ only convolutional layer approach. In the study, X-ray image dataset is used to train and evaluate the proposed Convolutional Neural Network model. By carefully designing the architecture, the model achieves a balance between parameters and accuracy while maintaining comparable performance to pre-trained models. The results demonstrate the model's effectiveness in detecting pneumonia images reliably. In addition, the study examines the decision-making process of the model using Grad-CAM, which helps to identify important aspects of radiographic images that contribute to the positive pneumonia prediction. Furthermore, the study shows that the proposed model, Pneum FC Net not only has the highest accuracy of 98%, but the total trainable model parameters is only 0.02% of the next best model VGG-16, thus establishing the potential of this new robust Deep Learning model. This research primarily addresses concerns related to mitigating significant computational requirements, with a specific focus on implementing lightweight networks. The contribution of this work involves the development of resource-efficient and scalable solution for pneumonia detection. 2024 Little Lion Scientific. All rights reserved. -
Development and evaluation of the bootstrap resampling technique based statistical prediction model for Covid-19 real time data : A data driven approach
The objective of the article is to develop earlyR package based novel coronavirus disease (COVID-19) forecasting model. The reported COVID-19 serial interval data is applied for obtaining maximum likelihood value of the reproduction number (R0) using maximum likelihood approach and projections package is applied for getting trajectories of epidemic curve. The minimum, median, mean and maximum projected value of R0 with 95% confidence interval (CI) is obtained by using bootstrap resampling strategy and the predicted cumulative probable count of new cases is also presented with different quantile. To validate the results with real scenario, the past COVID-19 data is considered. The % error rate ranges from -7.91% to 21.27% for the developed model for the five Indian States. 2022 Taru Publications. -
Development and Exploratory Factor Analysis of a United States Version of the International Survey of School Counselors Activities
This manuscript details the development and exploratory factor analysis of a United States version of the International Survey of School Counselors Activities (ISSCA-US), a 42-item instrument that identifies activities of school counselors. Responses were collected from 390 US school counselors. Separate EFAs were conducted for two distinct sections of the survey involving appropriateness of role activities and their actually being undertaken, both resulting in reliable 6-factor models. 2018, Springer Science+Business Media, LLC, part of Springer Nature. -
Development and Psychometric Validation of Teachers Receptivity to Change Scale
In this article, we report the development and psychometric validation of the Teachers Receptivity to Change Scale (TRCS). The sample included secondary school teachers of Kerala, India. In India, the teachers receptivity to change becomes important in the context of the newly drafted National Education Policy, (2020) which places teachers at the center of the reforms. The present study proceeded through five phases namely item analysis, exploratory factor analysis, confirmatory factor analysis, validation of the scale, and testretest reliability. The development of the tool started with the generation of a pool of items followed by item analysis. The exploratory factor analysis extracted four factors and the confirmatory factor analysis confirmed the four-factors namely individual, organizational, educational, and bridging factors. The structural equation modelling established the four-correlated factor construct of teachers receptivity to change and an additive model indexing teachers receptivity to change as the sum of the four factors. Both the model fit indices indicated an excellent fit. The validity of the TRCS established by correlating the teachers receptivity to change and its factors with multidimensional work motivation scale and engaged teachers scale indicated a moderate correlation. The final 28 item TRCS showed adequate internal consistency (Cronbachs alpha = 0.897) and discriminant validity. The test re-test reliability analysis (Cronbachs alpha = 0.884) confirmed the temporal stability of the scale. The findings recommend a psychometric reliable and valid scale for assessing teachers receptivity to change with implications for teachers, researchers, and policy makers. De La Salle University 2023. -
Development and psychometric validation of the three dimensional grit scale
This manuscript reports the development and validation of the three-dimensional Grit Scale (3-D Grit Scale). The psychometric measure developed has three factors, Perseverance-Commitment (PC), Interest-Passion (IP), and Goal-directed Resilience (GR) through a series of five studies; study 1 (n = 409) for item analysis, study 2 (n = 334) for exploratory factor analysis, study 3 (n = 514) for confirmatory factor analysis and study 4 (n = 214) and 5 (n = 107) to assess the validity. The sample included students and working professionals aged between 18 and 25, residing in different parts of India. Exploratory and confirmatory factor analyses indicated that the scale excellently fits in the three-correlated factor model and the two-level hierarchical model indexing grit as a total of three first-order factors. The final 17-item 3-D Grit Scale showed adequate internal consistency (Cronbachs ? = 0.86), and split-half reliability (Spearman-brown = 0.80, Guttman = 0.80). Validation studies showed that the scores of the 3-D Grit Scale were moderately correlated with (a) 12 item grit scale (Duckworth et al., 2007) and the brief resilience scale (smith et al., 2008), indicating good concurrent and convergent validities (b) conscientiousness revealing that both the constructs are mutually exclusive. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Development and Validation of a Framework to Identify High Potential Employees in Organizations
The present study aimed to develop and validate a multidimensional framework for identifying high-potential employees (hi-pots) to support succession planning and leadership development in organizations. A sequential exploratory mixed-methods approach was employed. In the qualitative phase, semi-structured interviews with seven organizational leaders were conducted to identify key traits and behaviors of hi-pots. The subsequent quantitative phase involved 276 managerial employees who responded to a newly developed measurement scale. The data were subjected to statistical validation to reinforce the proposed model. The validated framework comprises three dimensions: Foundation, growth, and career. The foundation dimension includes inherent traits such as optimism and sociability. The growth dimension, encompassing promotability, adaptability, and proactiveness, showed the strongest predictive power for leadership readiness. The career dimension involves performance-based competencies like technical proficiency and time management. Among these, the growth dimension emerged as the most influential for leadership potential. Organizations can utilize this framework for structured talent identification, improving leadership pipelines, and strategic HR planning. 2026 Econjournals. All rights reserved. -
Development and validation of a multi-dimensional scale to measure the factors influencing fintech firms capacity to impact digital financial inclusion
The purpose of the present study is to develop a multi-item scale to measure the factors that affect fintech firms capacity to impact digital financial inclusion. Fintech, or financial service delivery supported by advanced technology, has tremendously changed the financial services landscape. It has a potential to improve digital financial inclusion and help the poor. Digital financial inclusion is important since it ensures cost-saving digital mechanisms to provide financial services to the financially excluded and underserved populations. Following an inductive method, a qualitative study was undertaken among managerial staff in fintech firms. The scale development process involved the collection of primary data for pre-testing the questionnaire. The study identified four factors that affect a fintech firms capability of impacting digital financial inclusion: resources and capabilities, business models, networks and partnerships, and market and environment. Digital financial inclusion scale is composed of digital skills, access, and quality of access. The final scale consisted of sixty-four items. Though financial inclusion is usually measured from a demand-side perspective, this study provides a supply-side measure for digital financial inclusion. Thus, it can help in identifying and understanding the factors that may hamper fintech firms capability to attain desirable outcomes with respect to digital financial inclusion. 2024 Conscientia Beam. All Rights Reserved. -
Development and Validation of Emotion Recognition Software in the Indian Population
Though written extensively, recent debates on universality of emotions have shown that age, gender, and ethnicity have greater implications in the ability to identify expressions from faces. Facial emotion recognition deficits have been consistently shown in psychiatric conditions, which necessitates the need to construct a culturally sensitive tool. Fourteen actors depicted emotions such as happy, sad, anger, fear, surprise, disgust, and neutrality. From a total of 126 images, participants rated in terms of intensity and accuracy. Final software was developed with 28 images, and mean accuracy and reaction time were obtained. Friedmans significance test revealed a significant effect of emotion on its different dimensions. This study helped establish a culturally sensitive emotion recognition tool with the Indian population, which can be used in mental health settings for screening purposes and aid in developing rehabilitation modules. 2020, National Academy of Psychology (NAOP) India. -
Development and validation of gaming disorder and hazardous gaming scale (GDHGS) based on the WHO framework (ICD-11 criteria) of disordered gaming
This study aimed to develop and validate a brief psychometric scale for gaming disorder and hazardous gaming based on the WHO framework as defined in the ICD-11. The study was carried out among college students using face to face interview. A panel of mental health experts examined the face validity of the new Gaming Disorder and Hazardous Gaming Scale (GDHGS). An Exploratory Factor Analysis (EFA) using the principle component analysis (PCA) method with direct oblimin rotation on the five items of GDHGS was used for assessment of construct validity. The results of Kaiser Meyer Olkin (KMO) measure used for sampling adequacy and Bartlett's test (BT) of sphericity used to show the appropriateness of using factor analysis, confirmed the appropriateness of EFA for the present study sample. The factor analysis extracted single component with an eigenvalue of greater than one, which was further supported by the examination of scree plot. To examine the criterion related validity of the GDHGS, correlation between GDHGS and IGDS-SF scores was assessed. Spearman correlational analysis showed strong positive correlation of GDGHS score with IGDS-SF score (rs = 0.878, p < 0.01). Further, the sum of first four item score of GDHGS among participants diagnosed with GD (median: 15.00; IQR: 15.0015.75) was significantly greater than those without GD (median: 4.00; IQR: 3.006.50) according to the diagnostic interview based on the ICD-11 criteria (U = 0.000, p < 0.001). The internal consistency of GDHGS as measured by the Cronbach's alpha was 0.914. Further, the GDHGS did not have its reliability increased by removal of any of the five items included in the scale. Also, the threshold for significant floor and ceiling effect was not reached. In conclusion, GDHGS is a valid measurement scale for disorders involving gaming behaviour based on the ICD- 11 construct. 2020 Elsevier B.V.