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A short review on environmental impacts and application of iron ore tailings in development of sustainable eco-friendly bricks
Increased mining activity of iron ore has led to the generation of voluminous wastes of various nature, especially during the different stages of its extraction and production. The improper disposal of such waste causes negative impact on the environment. One such waste which is generated during the beneficiation process of iron ore is waste iron ore tailings, which is also termed as IOT. Further, dumping of IOT on open ground creates huge dumping sites. This dumping sites have been a concern to the environment and human population in its close vicinity. Therefore, a need to effectively use IOT has become one of the subjects of interest for many researchers. This article provides a short review of environmental problems caused due to improper disposal of IOT, and also reviews on the reuse methods of IOT in the construction sector, which helps to alleviate the environmental pollution associated with improper disposal of IOT. Furthermore, reuse of IOT in construction sector reduces the exploitation of the virgin materials for production of construction material, and thus reducing depletion of natural resources. Based on the existing literatures and findings it was observed that the use of IOT to develop stable building blocks using unconventional methods showed great potential and improved performance, when compared with conventional materials such as clay fired bricks. 2021 -
GNSS Signal Obstruction Removal Tool for Evaluating and Improving Position Accuracy in Satellite Networks
The positioning accuracy of Global Navigation Satellite System (GNSS) is largely affected by the site's surroundings. However, the methods to simulate GNSS signal obstruction and the nature of signal obstruction have not yet been explored fully. In this research, we investigated a way to remove the signals received from a specific region by specifying azimuth and elevation from GNSS observation files and evaluating how the removal of signals affects GNSS positioning accuracy. In addition, we also investigated the signal blockage for buildings of certain dimensions and a mountain. Python was used as a programming language to develop a program for the signal removal. RTKPOST was used for the GNSS data processing, and RTKPLOT was used for the visualisation of processed data and analysis of positioning accuracy. We successfully developed a Python shell script to remove the signals in GNSS data file from specific region by specifying azimuth and elevation. It was also found that removing signals from azimuth 0 to 100 degree and elevation 0 to 30 degree increased the positioning accuracy within a low multipath dataset. However, when the maximum elevation angle was increased to 45 degrees, positioning accuracy degraded, indicating that the signal from certain elevations have a positive or negative impact on positioning accuracy. Further research avenues are explored as an extension of work done here. 2023 IEEE. -
Artificial intelligence (AI) governance in organizational decision-making: balancing autonomy, accountability and transparency
Purpose This study aims to investigate the ethical and practical implications of delegating decision-making to AI systems, focusing on the necessity for a robust governance framework. Specifically, it examines how autonomy, transparency and accountability within AI governance influence organizational decision-making. Design/methodology/approach Employing a quantitative survey methodology, this study gathered data from 452 business owners and managers in Indian IT companies. The questionnaire was disseminated using online platforms and departmental communication channels. Structural equation modelling (SEM) was utilized for data analysis, allowing for the examination of relationships among autonomy, transparency, accountability and decision-making. Findings The findings indicate that autonomy, transparency and accountability significantly impact organizational decision-making processes. Specifically, autonomy and accountability were found to directly influence decision-making, while transparency also played a crucial role. Additionally, social innovation was identified as a significant moderating factor, enhancing the relationship between AI governance and decision-making outcomes. Originality/value This research contributes to the existing literature on AI governance by elucidating the critical role of ethical frameworks in organizational decision-making. By incorporating social innovation as a moderating variable, the study offers novel insights into how AI governance can be optimized to enhance decision-making processes. The application of SEM provides a rigorous analytical approach, facilitating a deeper understanding of the interplay between governance dimensions and decision-making outcomes. The findings have practical implications for organizations seeking to implement effective AI governance strategies in their operations. 2025 Emerald Publishing Limited -
3D face recognition based on symobolic FDA using SVM classifier with similarity and dissimilarity distance measure /
International Journal of Pattern Recognition and Artificial Intelligence, 31, Issue 4, ISSN: 1793-6381. -
A computer vision based system for stenosis detection and recognition in coronary angiogram image and a method thereof /
Patent Number: 202241013759, Applicant: Kavipriya K.
Coronary artery disease is becoming one of the most common heart diseases recently because of the unhealthy lifestyle from past few decades. The coronary artery supplies the oxygenated blood and nutrient to the heart muscle. If the artery is blocked or narrowed by the stenosis deposit on the wall of the artery it led to coronary artery disease. If the block is high it will lead to heart attack or stroke. Doctors do an Angiogram test to diagnosis the stenosis. -
A system for human face detection and recognition using feature fusion and a method thereof /
Patent Number: 202141031566, Applicant: Manjunatha Hiremath.
Biometric systems have become a vital role in the process of authenticating an individual based on physical or behavioral features/ traits of human beings. Biometric systems are categorized into two types namely Physiological and Behavioral systems. Face recognition, Fingerprint, Iris recognition, Hand geometry, and DNA fingerprint traits are considered as physiological biometrics which are essentially fixed and are relatively stable whereas voice recognition, signature and keystroke recognition are considered behavioral biometrics that can vary over a period of time due to some factors like aging, mood and behavior of the person. -
3D face recognition based on symbolic FDA using SVM classifier with similarity and dissimilarity distance measure
Human face images are the basis not only for person recognition, but for also identifying other attributes like gender, age, ethnicity, and emotional states of a person. Therefore, face is an important biometric identifier in the law enforcement and human-computer interaction (HCI) systems. The 3D human face recognition is emerging as a significant biometric technology. Research interest into 3D face recognition has increased during recent years due to availability of improved 3D acquisition devices and processing algorithms. A 3D face image is represented by 3D meshes or range images which contain depth information. In this paper, the objective is to propose a new 3D face recognition method based on radon transform and symbolic factorial discriminant analysis using KNN and SVM classifier with similarity and dissimilarity measures, which are applied on 3D facial range images. The experimentation is done using three publicly available databases, namely, Bhosphorus, Texas and CASIA 3D face database. The experimental results demonstrate the effectiveness of the proposed method. 2017 World Scientific Publishing Company. -
Segmentation and Recognition of E. coli Bacteria Cell in Digital Microscopic Images Based on Enhanced Particle Filtering Framework
Image processing and pattern recognitions play an important role in biomedical image analysis. Using these techniques, one can aid biomedical experts to identify the microbial particles in electron microscopy images. So far, many algorithms and methods are proposed in the state-of-the-art literature. But still, the exact identification of region of interest in biomedical image is a research topic. In this paper, E. coli bacteria particle segmentation and classification is proposed. For the current research work, the hybrid algorithm is developed based on sequential importance sampling (SIS) framework, particle filtering, and Chan–Vese level set method. The proposed research work produces 95.50% of average classification accuracy. 2019, Springer Nature Singapore Pte Ltd. -
Integrating Renewable Energy in Airports: A Roadmap Towards Carbon-Neutral Aviation Hubs
This chapter explains how one of the means of achieving carbon-neutral airports is by the airports integrating renewable energy. It examines how solar, wind, geothermal and hydropower technology can be used to curb carbon emission, reduce energy costs, and make the aviation industry environmentally sustainable. It lists the best practice, the impediments to the implementation, and the policy recommendations to the successful implementation based on the world case studies such as San Diego, Amsterdam Schiphol, and Denver airports. The discussion notes financial, technological and regulatory challenges, and predicts future trends of smart grids, energy storage, and electric ground equipment that can turn airports to sustainable energy centers that will support low-carbon aviation. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Measuring employee attrition intention in an auto-component manufacturing organisation
Orientation: The auto-component manufacturing sector, a critical contributor to industrial growth, faces persistent challenges related to employee attrition, affecting operational efficiency and workforce stability. This study examines the influence of job satisfaction, work-life balance, and job stress on attrition intention among employees in Indian auto-component manufacturing organisations. Research purpose: To identify the key factors contributing to employee turnover and evaluate their relative impact on attrition intention. Motivation for the study: Amid rising concerns over attrition in the manufacturing industry, this research aims to explore how work-life balance and job stress influence employees intentions to leave their organisations. Research approach/design and method: Data were collected from 192 employees across 10 auto-component manufacturing companies in Pune, Maharashtra, India, using a structured questionnaire. The responses were analysed through structural equation modelling (SEM) using SPSS and AMOS. Main findings: The study reveals that work-life balance and job stress significantly impact attrition intention. Employees with poor work-life balance and high job stress are more likely to consider leaving. However, job satisfaction does not have a direct effect on attrition intention. Practical/managerial implications: Organisations should prioritise improving work-life balance and managing job stress by implementing flexible work policies, wellness programmes, and realistic workload distribution. Contribution/value-add: This study underscores the importance of addressing work-life balance and job stress in retention strategies, offering actionable insights for HR managers to mitigate attrition in the auto-component manufacturing sector. 2025. The Authors. -
An iot-based fog computing approach for retrieval of patient vitals
Internet of Things (IoT) has been an interminable technology for providing real-time services to end users and has also been connected to various other technologies for an efficient use. Cloud computing has been a greater part in Internet of Things, since all the data from the sensors are stored in the cloud for later retrieval or comparison. To retrieve time-sensitive data to end users within a needed time, fog computing plays a vital role. Due to the necessity of fast retrieval of real-time data to end users, fog computing is coming into action. In this paper, a real-time data retrieval process has been done with minimal time delay using fog computing. The performance of data retrieval process using fog computing has been compared with that of cloud computing in terms of retrieval latency using parameters such as temperature, humidity, and heartbeat. With this experiment, it has been proved that fog computing performs better than cloud computing in terms of retrieval latency. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Palm Leaf
This work is by Her Highness Pooradam Thirunal Parvati Devi Varma, daughter of His Highness Uthradam Thirunal Marthanda Varma, Former Maharaja of Travancore, Kerala. -
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. -
Factors Influencing the Quality of Internal Audits in SMEs
Internal auditors role and their quality output are one of the essential features of an organisation. But a specific internal audit department is one of the easily ignoring cost cutting method for Small and Medium-sized Enterprises (SMEs), due to their limited resources and various challenges. Based on the recent corporate governance stress, most of the listed SMEs are employing internal audit departments, but the autonomy of internal auditors which are questionable generally among all the industries are considered to be very challenging to attain in SMEs. The aim of this study is to examine how effective are the internal auditors role in listed SMEs and what are the key factors that will impact high-quality audits. Audit committee, autonomy of internal auditors and fraud risk assessment are the key factors considered to achieve the objective of study. For the comprehensive analysis of this study 71 listed SMEs are considered and quantitative research methodology is used for the collection of data. The findings shows that these key factors are crucial to improve audit quality of SMEs. The study provides valuable insights and guidance for SMEs to augment their internal control systems and achieve long-term sustainable growth as they prone to witness constant changes in the present business world. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Silenced, Scarred & Shattered: Unmasking the Wounds of Child Sexual Abuse in Select American Memoirs
The research brings to light the marginalized voices of three American women who have written about their sexual abuse in their respective memoirs Roxane Gay, Hunger: A Memoir of my Body (2017), Nikki Dubose, Washed Away: From Darkness to Light (2016) and Neesha Arter Controlled: The worst Night of my Life and its Aftermath (2015). Using these memoirs as primary data and using thematic analysis the study identified three themes which were further classified into different subthemes. Firstly, the research discovered the challenges faced by the survivors in expressing and communicating about sexual abuse due to fear and shame, the survivors do not come forward because of threats, because of rape stereotypes that permeate the society and the fear of what parents and others might think. Secondly, the research explores the various impact of trauma that is caused by sexual abuse which include shame, guilt and self blame, unworthy self, uncontrollable rage, disruption of safety and trust, isolating themselves from everyone, hostility towards body, destructive behaviours which include eating disorder from Anorexia Nervosa to Binge eating disorder, it also includes self harm and substance abuse. Thirdly, the research focuses on the recovery aspect on how the survivors learn to live with the wounds caused by sexual abuse. It focuses on how the survivors came in terms with the abuse, the conflicting feelings of forgiveness and revenge and how they sought redemption through writing their journey. 2025 Sciedu Press. All rights reserved.