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Elementary Methods for Generating Three-Dimensional Coordinate Estimation and Image Reconstruction from Series of Two-Dimensional Images
The increase in computational power in recent years has opened a new door for image processing techniques. Three-dimensional object recognition, identification, pose estimation, and mapping are becoming popular. The need for real-world objects to be mapped into three-dimensional spatial representation is greatly increasing, especially considering the heap jump we obtained in the past decade in virtual reality and augmented reality. This paper discusses an algorithm to convert an array of captured images into estimated 3D coordinates of their external mappings. Elementary methods for generating three-dimensional models are also discussed. This framework will help the community in estimating three-dimensional coordinates of a convex-shaped object from a series of two-dimension images. The built model could be further processed for increasing the resemblance of the input object in terms of its shapes, contour, and texture. 2021 Naived George Eapen et al. -
Model Selection Strategies for Identifying Effective Energy Storage Systems
Energy is present in various forms in and around us. Capturing and storing energy from various sources have diverse challenges. Designing and developing energy storage systems are challenging, as various techniques are used to distribute energy from sources and to store for diverse use cases. Identifying the optimal and effective energy storage system requires the application of various model selection strategies. The success and adoption of effective energy storage systems can be identified with numerous factors, which include the systems efficiency, reliability, cost-effectiveness, and scalability. Various model selection strategies are available to compute and determine the effective energy storage mechanisms. Various researchers are planning and designing energy storage systems based on the insights from the data with the support of optimisation algorithms, mathematical models, and Artificial Intelligence (AI) and Machine Learning (ML) technologies. The chapter discusses the various model selection strategies for identifying effective models for energy storage systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Model Selection Strategies for Identifying Effective Energy Storage Systems
Energy is present in various forms in and around us. Capturing and storing energy from various sources have diverse challenges. Designing and developing energy storage systems are challenging, as various techniques are used to distribute energy from sources and to store for diverse use cases. Identifying the optimal and effective energy storage system requires the application of various model selection strategies. The success and adoption of effective energy storage systems can be identified with numerous factors, which include the systems efficiency, reliability, cost-effectiveness, and scalability. Various model selection strategies are available to compute and determine the effective energy storage mechanisms. Various researchers are planning and designing energy storage systems based on the insights from the data with the support of optimisation algorithms, mathematical models, and Artificial Intelligence (AI) and Machine Learning (ML) technologies. The chapter discusses the various model selection strategies for identifying effective models for energy storage systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
A Worldwide Test of the Predictive Validity of Ideal Partner Preference Matching
Ideal partner preferences (i.e., ratings of the desirability of attributes like attractiveness or intelligence) are the source of numerous foundational findings in the interdisciplinary literature on human mating. Recently, research on the predictive validity of ideal partner preference matching (i.e., Do people positively evaluate partners who match vs. mismatch their ideals?) has become mired in several problems. First, articles exhibit discrepant analytic and reporting practices. Second, different findings emerge across laboratories worldwide, perhaps because they sample different relationship contexts and/or populations. This registered reportpartnered with the Psychological Science Acceleratoruses a highly powered design (N = 10,358) across 43 countries and 22 languages to estimate preference-matching effect sizes. The most rigorous tests revealed significant preference-matching effects in the whole sample and for partnered and single participants separately. The corrected pattern metric that collapses across 35 traits revealed a zero-order effect of ? =.19 and an effect of ? =.11 when included alongside a normative preference-matching metric. Specific traits in the level metric (interaction) tests revealed very small (average ? =.04) effects. Effect sizes were similar for partnered participants who reported ideals before entering a relationship, and there was no consistent evidence that individual differences moderated any effects. Comparisons between stated and revealed preferences shed light on gender differences and similarities: For attractiveness, mens and (especially) womens stated preferences underestimated revealed preferences (i.e., they thought attractiveness was less important than it actually was). For earning potential, mens stated preferences underestimatedand womens stated preferences overestimatedrevealed preferences. Implications for the literature on human mating are discussed. 2024 American Psychological Association -
A worldwide test of the predictive validity of ideal partner preference matching.
Ideal partner preferences (i.e., ratings of the desirability of attributes like attractiveness or intelligence) are the source of numerous foundational findings in the interdisciplinary literature on human mating. Recently, research on the predictive validity of ideal partner preference matching (i.e., Do people positively evaluate partners who match vs. mismatch their ideals?) has become mired in several problems. First, articles exhibit discrepant analytic and reporting practices. Second, different findings emerge across laboratories worldwide, perhaps because they sample different relationship contexts and/or populations. This registered reportpartnered with the Psychological Science Acceleratoruses a highly powered design (N = 10,358) across 43 countries and 22 languages to estimate preference-matching effect sizes. The most rigorous tests revealed significant preference-matching effects in the whole sample and for partnered and single participants separately. The corrected pattern metric that collapses across 35 traits revealed a zero-order effect of ? =.19 and an effect of ? =.11 when included alongside a normative preference-matching metric. Specific traits in the level metric (interaction) tests revealed very small (average ? =.04) effects. Effect sizes were similar for partnered participants who reported ideals before entering a relationship, and there was no consistent evidence that individual differences moderated any effects. Comparisons between stated and revealed preferences shed light on gender differences and similarities: For attractiveness, men's and (especially) women's stated preferences underestimated revealed preferences (i.e., they thought attractiveness was less important than it actually was). For earning potential, men's stated preferences underestimatedand women's stated preferences overestimatedrevealed preferences. Implications for the literature on human mating are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved) 2024 American Psychological Association All rights, including for text and data mining, AI training, and similar technologies, are reserved. -
Sustainability and Gender Equality: SDG5Gender Differences in Bargaining in the Housing Market
This chapter investigates whether gender differences exist in bargaining behaviour in the housing market. The impact of personality dispositions, location preferences and other such variables on the individuals willingness and ability to bargain and obtain a concession is studied. The variables were estimated using a 5-point Likert scale, and the final dataset was analysed by implementing logistic regression model. Findings suggest that gender, product knowledge, bargaining disposition, role of agent and reference price significantly impact bargaining behaviour. The study validates the need to attain the fifth Sustainable Development Goal, i.e. Gender Equality. The current emphasis is to ensure full participation of women in decision-making capabilities by 2030 (UN Women, Progress on the sustainable development goals: the gender snapshot, UN Women, New York, 2022), but it is found that men bargain more than women in the rental housing market. The chapter contributes to existing literature by studying gender differences in the rental housing market and justifies the findings with the help of primary data analysis. 2024 The Author(s). -
Spectroscopic Study of Late-type Emission-line Stars Using the Data from LAMOST DR6
Low-mass emission-line stars belong to various evolutionary stages, from pre-main-sequence young stars to evolved stars. In this work, we present a catalog of late-type (F0 to M9) emission-line stars from the LAMOST Data Release 6. Using the scipy package, we created a Python code that finds the emission peak at H? in all late-type stellar spectra. A data set of 38,152 late-type emission-line stars was obtained after a rigorous examination of the photometric quality flags and the signal-to-noise ratio of the spectra. Adopting well-known photometric and spectroscopic methods, we classified our sample into 438 infrared (IR) excess sources, 4669 post-main-sequence candidates, 9718 Fe/Ge/Ke sources, and 23,264 dMe sources. From a crossmatch with known databases, we found that 29,222 sources, comprising 65 IR excess sources, 7899 Fe/Ge/Ke stars, 17,533 dMe stars, and 3725 PtMS candidates, are new detections. We measured the equivalent width of the major emission lines observed in the spectra of our sample of emission-line stars. Furthermore, the trend observed in the line strengths of major emission lines over the entire late-type spectral range is analyzed. We further classified the sample into four groups based on the presence of hydrogen and calcium emission lines. This work presents a large data set of late-type emission-line stars, which can be used to study active phenomena in late-type stars. 2024 National Astronomical Observatories, CAS and IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved. -
Machine Learning Algorithms for Predictive Maintenance in Hybrid Renewable Energy Microgrid Systems
The rapid expansion of hybrid renewable energy microgrid systems presents new challenges in maintaining system reliability and performance. This paper explores the application of machine learning algorithms for predictive maintenance in such systems, focusing on the early detection of potential failures to optimize operational efficiency and reduce downtime. By integrating real-time data from solar, wind, and storage components, the proposed models predict the remaining useful life (RUL) of critical components. The results demonstrate significant improvements in predictive accuracy, offering a robust solution for enhancing the reliability and longevity of renewable energy microgrids. The Authors, published by EDP Sciences. -
Big Data Analytics Tools and Applications for Modern Business World
In the modern world, data is the unavoidable word. The digital environment in almost all our day to day life is linked with digital data. Effective data management is one of the important tasks. The gradual growth of technology in recent years, the generation of data has increased exponentially. Everything, ranging from sending a mail to simply browsing the internet generates data and this is collected and stored. This data has countless uses in various fields such as medicine, business, agriculture and marketing, but most of the time it goes unused. Business intelligence is a key factor in the current business world. Business growth is purely depending on technology. Technology is not only used in manufacturing it is applied to getting the customer. The data analytics is still in its earlier stages and has a long way to go before it yields favourable results. It is a good time as any to start working in this domain to utilize its prowess. This article has discussed the opportunities and growth of data analytics in the research domain. It can face soon when it reaches its advance stages. The big data is handling a larger amount of data in a conventional and non-conventional manner. Technology is playing a vital role to handle larger data from the database. This article is to discuss data analytics application in modern industry. In the technical perspective, big data Map-reduce is an advanced tool and for simulation part, R tool is used. 2020 IEEE. -
Towards Smarter Warehouse Layouts: Simulation-Driven Insights on Congestion and Forklift Flow Patterns
In high-mix, make-to-order warehouse environments, slotting decisions in constrained warehouse settings affect flow dynamics, yet their behavioral implications remain underexplored. This study employs discrete event simulation (DES) using the software FlexSim to evaluate three slotting strategies: baseline reflecting current operations, a benchmark informed by heuristic frequency-based clustering, and a proposed layout based on a learned configuration within a forklift-operated warehouse characterized by narrow aisles, unidirectional traffic, and spatial contention. Instead of emphasizing throughput alone, the study takes a closer look at how forklifts operate on a day-to-day basis, specifically how their time is divided between active movement, waiting due to blockages, and idling with no task assigned. Each strategy was tested over 20 simulation replications. Notably, the proposed layout cut blocked time by more than 30% and allowed forklifts to remain idle (and ready) more often, without reducing overall utilization. These patterns held consistently across runs. Statistical analysis confirmed that the differences in forklift behavior were significant, and Levenes tests showed that performance didnt become more erratic. These findings demonstrate that the improvements are systematic, not random. The work presents a simulation-based method for diagnosing layout effectiveness by looking at behavior, not just outputs, connecting slotting choices to real operational flow and system stability. This approach supports more resilient warehouse designs in settings with limited space and high product mix. 2025 IEEE. -
Pluronic f127 encapsulated titanium dioxide nanoparticles: Evaluation of physiochemical properties for biological applications
The infections caused by bacteria that are resistant to drugs are very bad for human health and kill thousands of people every year. Also, both human actions and natural processes make surface waters more likely to have drug-resistant bacteria grow and spread in the environment. Because of this, researchers need to find new ways to treat bacterial infections quickly becoming resistant to drugs as soon as possible. Drug delivery systems based on nanoparticles have enhanced biocompatibility, biocidal properties, pharmacokinetics, tumor targeting, and stability while exhibiting non-toxicity to normal cells and overcoming drug resistance. In the present work, the pluronic-F127 encapsulated titanium dioxide (PF127/TiO2) nanoparticles (NPs) were prepared by a green process using Morinda citrifolia leaf extract. X-ray diffraction patterns (XRD) revealed that synthesized NPs exhibit an anatase structure. FESEM and TEM images of synthesized PF127/TiO2 NPs showed a polymorphic structure and an average particle size of 5060 nm. The chemical composition of the prepared NPs, which included elements like carbon, titanium, and oxygen, was identified using the EDAX spectrum. With the DLS spectrum, the hydrodynamic sizes of PF127/TiO2 NPs were 176 nm. In the FTIR spectrum, the metal oxide stretching bands like O-Ti-O were located at 664 cm?1 for PF127/TiO2 NPs. The surface defects, including Ti and O vacancies, were studied using the photoluminescence spectrum. The prepared PF127/TiO2 NPs exhibited significant microbial activity for inhibiting hospital pathogenic bacterial and fungal strains, specifically (Staphylococcus aureus) S. aureus, (Streptococcus pneumoniae) S. pneumonia, (Klebsiella pneumoniae) K. pneumonia, (Shigella dysenteriae) S. dysenteriae and (Candida albicans) C. albicans. In addition, PF127/TiO2 NPs had highly anti-cancer properties against human blood cancer (MOLT-4) cell lines. Furthermore, we found that synthesized PF127/TiO2 NPs exhibited anti-inflammatory activity. 2023 -
Evaluation of physicochemical and biological properties of SnO2 and Fe doped SnO2 nanoparticles
In recent decades, nanoparticle synthesis has been used for various physical and chemical methods. However, different toxic chemicals are used during this synthesis process to address these concerns, which has multiple effects on environmental toxicity and high cost. To avoid these problems, we need a cost-effective and environmentally friendly approach. In this study, green synthesis was used to make tin oxide (SnO2) and ferrous doped tin oxide (SFO) nanoparticles (NPs) from Morinda citrifolia leaf extracts. The X-ray diffraction patterns of SnO2 and SFO NPs reveal a tetragonal crystalline structure. From the FESEM image of synthesized SnO2 and SFO NPs, their spherical structure and chemical composition were identified by EDX spectrum. Through the DLS spectrum, the hydrodynamic size was observed at 66 and 61 nm for SnO2 and SFO NPs, respectively. In the FTIR spectrum, the OSnO stretching vibration peak arises at (606 & 509 cm?1 for SnO2 NPs) and (613 & 538 cm?1 for SFO NPs). Photoluminescence is used in materials to detect surface defects and impurity levels. The antibacterial activity of the SnO2, SFO NPs, and conventional antibiotics like amoxicillin NPs is effectively inhibited against S. aureus and E. coli bacterial strains. SFO NPs exhibit a higher antibacterial activity as compared to SnO2 and amoxicillin. The anticancer efficacy of increased SFO NPs compared to SnO2 NPs was tested against (MDA-MB-237) human breast cancer cells. These results suggest that Fe ions modified SnO2 NPs could be used in healthcare industrial applications to improve human health. 2022 Elsevier Ltd and Techna Group S.r.l. -
Salutogenesis: A Paradigm for Organizational Health And Sustainability- A Metaphorical analysis.
Volume .5, Issue - 2, P# 43-22 ISSN: 0974-908x -
Mediation of Perceived Innovation Characteristics on ERP Adoption in Industrial Cluster
An industrial cluster, due to its close network of institutions, will experience various pressures that force the industry to have a homogeneous structure, norms, and practices. These pressures can also lead to adoption of innovative technologies. Enterprise Resource Planning (ERP) is perceived as a sophisticated technology and diffuses across the cluster by its innovative characteristics. However, firms in the industrial cluster will have different rate of adoption of technologies due to the varying level of knowledge spillover and a heterogeneous absorptive capacity. This study empirically tests how absorptive capacity mediates the institutional forces and the perceived innovation characteristics towards the ERP adoption in an industrial cluster. Mediation effect and the model validity are tested using SEM technique. The results show that absorptive capacity complements the forces of institutional pressure and the perceived innovation characteristics on ERP adoption. The implications of managing the absorptive capacity for better ERP adoption are discussed. 2016 World Scientific Publishing Company. -
Adapting Case Study Pedagogy for Non-Residential Business Schools: Strategies for Implementation
Case study pedagogy is widely recognized as a powerful teaching approach in business education programs. However, its implementation in non-residential business schools poses distinct challenges. Optimizing case study pedagogy to the unique needs and circumstances of non-residential students necessitates a specific strategy. This chapter delves into various strategies essential for the effective implementation of case study pedagogy in non-residential business schools. First, an overview of 2024 by IGI Global. All rights reserved. -
Influence of Business Analytics Usage on Operational Efficiency of Information Technology Infrastructure Management
Organizations today depend and thrive on timely, accurate and strategically relevant information. Business analytics (BA) holds the key to many of these issues. This paper validates a model on how the usage of BA leads to operational efficiency. We identified the factors of basic analytical usage from the Business Capacity Maturity Model (BCMM). The scope of the study is restricted to the Information Technology Infrastructure and Application management domain. A survey was conducted among the managers of the IT companies in Bengaluru, India. The results showed a significant influence of data-oriented culture and BA tools and infrastructure on BA usage. We found a significant influence of BA usage and pervasive use on operational efficiency. The speed to insight is still not practised in organizations. The awareness level of analytical skills in organizations is very low. 2022, Asia Pacific Journal of Information Systems. All Rights Reserved. -
Navigating the doctoral programme: A journey metaphor in heutagogical context
The journey towards a doctoral degree, the highest academic degree, is challenging. It is a journey full of emotions and experiences that provides a feeling of achievement and fulfilment. The doctoral research process is sometimes overwhelming, and scholars are lost in the wilderness of the activities. Navigating a social science doctoral programme, including the business and management streams, requires understanding the pathways and the nuances. This paper presents metaphors of the doctoral journey that helps scholars in developing a better mindset and plan an enriching journey. The methodology used is a qualitative-conceptual metaphor analysis. The study considers the heutagogical framework and develops analogies from the travel and tour domain and applies it to the doctoral programme. The paper compares self-guided tours, Driver Vs Passenger, Roller coaster, pilgrimage model and self-experience that the scholars need to take up in their doctoral journey 2024, IGI Global. All rights reserved. -
Impact of functional interdependency on employee satisfaction with performance appraisal in the real estate industry
Unbiased performance appraisal tends to bolster the performance of employees. The studies indicate several inadequacies with the current performance appraisal systems. Functional interdependence is one such factor that has been ignored. The study aims to find the factors that can improve the satisfaction with performance appraisal of employees whose deliverables are highly interdependent on other functions. Organizational justice, rater competence, inter-functional conflict, and cohesion are considered the mediating variables. To test the model, the data are collected through a survey using a questionnaire from the executives of Indian real estate companies who have undergone the appraisal process at least once. Firms with more than 500 employees are randomly selected for the list of members of the real estate developers' associations. The results show that functional interdependency has a negative impact on satisfaction with performance appraisal. Although conflict and cohesion are found to influence satisfaction with performance appraisal, they did not mediate the effect of functional interdependency on satisfaction with performance appraisal. However, the study found that rater competence and organizational justice have a mediating effect. The study provides practical implications to HR managers of real estate companies to train the raters and include the complexities of functional interdependencies in the appraisal system. A grievance mechanism should be created to address the employees' concerns, ultimately improving satisfaction with performance appraisal. Elangovan N., Sridhar Rajendran, 2020 -
Harnessing digital innovation for inclusive tourism: Role of emerging technologies in creating accessibility and equity
The rapid advancement of digital technologies has ushered in a new era for the tourism industry, presenting unprecedented opportunities to enhance inclusivity, accessibility, and equity in travel experiences. This study investigates the transformative potential of emerging technologies in fostering a more inclusive tourism landscape. Specifically, it examines how selected digital innovations such as artificial intelligence (AI), augmented and virtual reality (AR/VR), mobile applications, and wearable devices are shaping the accessibility and equity of tourism for diverse populations. This chapter begins with a comprehensive literature review, highlighting current trends, challenges, and existing studies on inclusive practices in the tourism sector. The paper delves into a detailed analysis of each emerging technology, showcasing successful integration examples from real-world cases. It evaluates the benefits and potential challenges of adopting these technologies, especially in enhancing accessibility for travelers with disabilities. The examination addresses physical, sensory, and cognitive accessibility barriers, providing insights into how technology reshapes travel experiences for diverse individuals. This chapter delves into the role of emerging digital innovations in fostering equity within the tourism sector. By facilitating cross-cultural connections and enhancing access to tech-driven travel experiences, these technologies contribute to a more inclusive landscape. The study scrutinizes socioeconomic dimensions, shedding light on the holistic impact of tech integration. While acknowledging challenges and ethical concerns, responsible technology deployment is endorsed to counterbalance drawbacks and bridge the digital divide, enabling marginalized communities to leverage the benefits of this digital transformation. The implications of this study are relevant for businesses, policymakers, and tourism stakeholders. The chapter concludes by providing practical recommendations for the responsible incorporation of emerging technologies and emphasizing the long-term sustainability of inclusive digital innovations. By shedding light on the transformative potential of these technologies and outlining guidelines for their application, this research contributes to the evolution of a more accessible, equitable, and inclusive tourism industry. 2024 Nova Science Publishers, Inc. All rights reserved. -
Method of preparing a document for survey instrument validation by experts
Validation of a survey instrument is an important activity in the research process. Face validity and content validity, though being qualitative methods, are essential steps in validating how far the survey instrument can measure what it is intended for. These techniques are used in both scale development processes and a questionnaire that may contain multiple scales. In the face and content validation, a survey instrument is usually validated by experts from academics and practitioners from field or industry. Researchers face challenges in conducting a proper validation because of the lack of an appropriate method for communicating the requirement and receiving the feedback. In this Paper, the authors develop a template that could be used for the validation of survey instrument. In instrument development process, after the item pool is generated, the template is completed and sent to the reviewer. The reviewer will be able to give the necessary feedback through the template that will be helpful to the researcher in improving the instrument. 2021 The Author(s)