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Optical Spectroscopy of Classical Be Stars in Old Open Clusters
We performed the optical spectroscopy of 16 classical Be stars in 11 open clusters older than 100 Myr. Ours is the first spectroscopic study of classical Be stars in open clusters older than 100 Myr. We found that the H? emission strength of most of the stars is less than 40 in agreement with previous studies. Our analysis further suggests that one of the stars, [KW97] 35-12, might be a weak H? emitter in nature, showing H? equivalent width of ?0.5 Interestingly, we also found that the newly detected classical Be star LS III +47 37b might be a component of the possible visual binary system LS III +47 37, where the other companion is also a classical Be star. Hence, the present study indicates the possible detection of a binary Be system. Moreover, it is observed that all 16 stars exhibit a lesser number of emission lines compared to classical Be stars younger than 100 Myr. Furthermore, the spectral type distribution analysis of B-type and classical Be stars for the selected clusters points out that the existence of CBe stars can depend on the spectral type distribution of B-type stars present in these clusters. 2023. National Astronomical Observatories, CAS and IOP Publishing Ltd. -
Indexing of exoplanets in search for potential habitability: application to Mars-like worlds
Study of exoplanets is one of the main goals of present research in planetary sciences and astrobiology. Analysis of huge planetary data from space missions such as CoRoT and Kepler is directed ultimately at finding a planet similar to Earththe Earths twin, and answering the question of potential exo-habitability. The Earth Similarity Index (ESI) is a first step in this quest, ranging from1 (Earth) to0 (totally dissimilar to Earth). It was defined for the four physical parameters of a planet: radius, density, escape velocity and surface temperature. The ESI is further sub-divided into interior ESI (geometrical mean of radius and density) and surface ESI (geometrical mean of escape velocity and surface temperature). The challenge here is to determine which exoplanet parameter(s) is important in finding this similarity; how exactly the individual parameters entering the interior ESI and surface ESI are contributing to the global ESI. Since the surface temperature entering surface ESI is a non-observable quantity, it is difficult to determine its value. Using the known data for the Solar System objects, we established the calibration relation between surface and equilibrium temperatures to devise an effective way to estimate the value of the surface temperature of exoplanets. ESI is a first step in determining potential exo-habitability that may not be very similar to a terrestrial life. A new approach, called Mars Similarity Index (MSI), is introduced to identify planets that may be habitable to the extreme forms of life. MSI is defined in the range between 1 (present Mars) and 0 (dissimilar to present Mars) and uses the same physical parameters as ESI. We are interested in Mars-like planets to search for planets that may host the extreme life forms, such as the ones living in extreme environments on Earth; for example, methane on Mars may be a product of the methane-specific extremophile life form metabolism. 2017, Springer Science+Business Media B.V. -
Data journalists perception and practice of transparency and interactivity in Indian newsrooms
Data journalism research recorded exponential growth during the last decade. However, the extant literature lacks comparative perspectives from the Asian region as it has been focused on select geographies (mainly Europe and the US). In this backdrop, the present study examined data journalism practices in the Indian media industry by conducting intensive interviews with 11 data journalists to investigate their perception of transparency and interactivity which are two of the core aspects of data journalism practice. Further, a content analysis of data stories published by two Indian news organizations for two years was conducted to assess the status of transparency and interactivity options in these stories. The findings showed that Indian data journalists acknowledge the importance of transparency and interactivity, but exhibit a cautious approach in using them. There is general apathy in practicing transparency among journalists in legacy organizations, drawing a stark contrast with their counterparts in digitally-native organizations. 2022 Asian Media Information and Communication Centre. -
Numerical modeling of novel cage-like cross-linked membranes for enhanced proton conductivity in a high temperature-polymer electrolyte membrane fuel cell
Phosphoric acid (PA)-doped polybenzimidazole (PBI) membranes have encountered several problems associated with high cost, chemical instability, poor solubility in organic solvents, and higher doping level which results in poor mechanical properties and faster degradation of the membrane. Alternative membranes with high proton conductivity and mechanical strength for high-temperature applications are of great interest, one such membrane being cPBI-IL X. The cage-like cross-linked structure of these membranes shows a dual proton transport path due to which proton conductivity is elevated. The ionic liquid content of these membranes improves the PA absorbing capability and shortens the proton transfer path. These membranes exhibit the highest proton conductivity of 13.3 S/m and better durability compared to existing PBI Membranes. A mathematical model is developed and validated versus published experimental results to account for the proton conductivity of these membranes. The developed model is further investigated for a detailed understanding of polarization phenomena and species distribution. 2023 Wiley Periodicals LLC. -
A novel security framework for healthcare data through IOT sensors
The Internet of Things (IoT) has played a crucial role in the distribution of health records and poses security issues to the patient-specific health information needed for remote hospital attention. The majority of publicly accessible security mechanisms for health information do not concentrate on the flow of information from IoT different sensors installed upon the person's blood through networking devices to primary health care centers. In this paper, we investigated the potential risks of unprotected transmission data, particularly among IoT sensor systems and network gateways. The study encourages the transmission of health insurance data to hospitals remotely. The proposed health care information model would encode immediately so that the sensing element before even being transferred to cryptographic techniques. To use a laboratory configuration with two-stage cryptography at the IoT sensor and two-stage decoding at the physician's surgery receptor, the prototype system was validated. The test results for a complete safety system for IoT - based on the transmission of healthcare data seem good. The study opens up new avenues for information security on IoT devices. 2022 The Authors -
Research Trends on Workplace Criminal Behaviour: A Bibliometric Analysis
This study presents a comprehensive bibliometric analysis of the research landscape surrounding Workplace Criminal Behaviour (WCB), examining its evolution over time. By focusing on thematic areas, research trends, and patterns of scholarly output, the study offers a systematic overview of scientific contributions in this field. A total of 767 peer-reviewed publications were retrieved from the scientific database and analyzed using bibliometric techniques. The findings indicate that scholarly interest in WCB began to gain momentum in 1989, marking a significant turning point in the field. The analysis also highlights the most prominent institutions, journals, and influential scholars contributing to the field. Keyword mapping revealed closely related areas of inquiry, including white-collar crime, workplace theft, and corporate crime, reflecting the multidimensional nature of WCB research. This study offers a valuable resource for emerging scholars, outlining key areas of focus, frequently used methodologies, high-impact publication outlets, and potential collaborators. By mapping the intellectual structure of the field, the findings contribute to shaping future research directions and fostering more targeted and impactful scholarly efforts in workplace criminal behaviour. (2026), (South-West University "Neofit Rilski"). All rights reserved. -
Tool wear and tool life estimation based on linear regression learning
Tools have remained an integral part of the society without which stimulation of certain aspects of human evolution would not have been possible. In recent times the modern tools are used in the manufacturing of high precision components. We know that the accuracy and surface finish of these components can be achieved only by the usage of accurate tools. Sharp edged tools may loosen their sharpness due to repeated usage and machining parameters. Hence to address this issue we propose a system to monitor tool wear by using the captured image of cutting tool tip. We used vision system since it is the primitive method of predicting tool wear and two main machining parameters feed rate and depth of cut. The image of flank wear cutting edge at tool tip is captured by examining under profile projector. The system uses linear regression model to calculate tool wear which is mapped onto continuous 2-D coordinates with feed rate and depth of cut as axis from a captured digital image. Thus the proposed intelligent system uses profile projector and digital image processing methods to estimate tool wear continuously and predictively like humans rather than using strict rules. By estimating tool wear continuously the machine can better perform and machine components accurately by using the resultant values of feed rate and depth of cut as a threshold which are arrived as a result. 2015 IEEE. -
Comparative Analysis of Prediction Algorithms for Heart Diseases
Cardiovascular diseases (CVDs) are the leading source of demises universally: More individuals perish yearly from heart disease than due to any other reason. An estimated 17.9 million humans died from CVDs in 2016, constituting 31% of all global deaths. [1] Such high rates of death due to heart diseases have to cease. This idea can be accelerated by the prediction of risk of CVDs. If a person can be medicated much earlier, before they have any symptoms that can be far more beneficial in averting sickness. The paper strives to communicate this issue of heart diseases employing various prediction models and optimizing them for better outcomes. The accuracy of each algorithm guides to a relative enquiry of these prediction models, forming a solid base for further research, finer prognosis and detection of diabetes. 2021, Springer Nature Singapore Pte Ltd. -
Broad spectrum antibacterial activity of nanostructured Cu oxide thin films grown via glancing angle sputtering deposition
The demand for antibacterial surfaces has intensified since the recent pandemic, underscoring the need to prevent microbial adhesion on high-contact surfaces. Metallic and metal oxide nanostructures exhibit intrinsic antibacterial properties, motivating the development of scalable, cost-effective fabrication routes for functional coatings. In this study, copper oxide (CuO) thin films were deposited by magnetron sputtering and further nanostructured via glancing angle deposition (GLAD). The films exhibited pronounced antibacterial efficacy, inactivating Escherichia coli (Gram-negative) and Staphylococcus aureus (Gram-positive) with efficiencies over 98% after 8h of exposure. Increasing the deposition angle enhanced surface roughness and hydrophobicity, which directly correlated with higher bacterial inactivation. Longer exposure further improved antibacterial performance, demonstrating time-dependent activity. These results establish GLAD-fabricated CuO thin films as a promising, industrially scalable strategy for next-generation antimicrobial surface coatings. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026. -
Electrochemical behaviour of optically transparent, nanoporous LiFePO4cathodes grown via RF magnetron sputtering
The rapid growth of smart technology has accelerated the need for compact and durable microbatteries. Fabrication of thin-film microbatteries is effective to address the requirements of the evolving technology. In the present work, pristine, optically transparent, nanoporous LiFePO4 (LFP)is synthesized via RF magnetron sputtering. The effect of nanoporosity on the electrochemical properties and charge storage mechanisms of LFP is explored. The galvanostatic studies revealed an initial discharge capacity of 32 Ah cm2?m1 and stabilised to 17.5 Ah cm2?m1 after 100 cycles. The capacity fading can be attributed to the increased formation of SEI caused by the enhanced interaction between the cathode and electrolyte due to the nanoporosity. The films demonstrate good rate capability and reversibility. Optical studies reveal a bandgap of 3.74eV, highlighting the potential for usage in optically transparent microbatteries. This work provides key insights into the intrinsic electrochemical behaviour of pristine nanoporous LFP thin films, creating a pathway for its implementation in microbatteries. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2026. -
Automated Detection Model (ADM) for Glaucoma, Exudate and Diabetic Retinopathy (DR) Diagnosis Using Fundus Images
A total of 15 million people in India suffer from blindness yet statistical analysis shows 75% of these cases can be treated. The research shows DR and Glaucoma lead to blindness in India. Long-term diabetes mainly causes diabetic retinopathy which stands as the primary cause of blindness. Glaucoma damages the optic nerve until blindness develops. The digitized format of fundus images provides useful diagnostic information about infected retinas for proper eye disease detection. Eye defect diagnosis at an early stage enables medical care that greatly decreases patient vision loss risk. An ophthalmologist conducted the disease screening process through examination of fundus image abnormalities. Higher rates of DR and glaucoma prevalence do not affect the number of available ophthalmologists for evaluating fundus images so the prevention of diseases has been delayed. An automated analytical system should be developed presently to help ophthalmologists enhance their diagnostic process efficiency. The paper introduces an artificial learning methodology that utilizes concatenate systems to detect input fundus images in three categories namely ND and GI and EI and DRI. No Diseases (ND), ii. Glaucoma (GI) iii. The classification groups include Exudate infected Images (EI) along with two other categories namely Glaucoma (GI) and DR Images (DRI). The proposed model Automated Detection Model (ADM) starts by analyzing input samples with histogram-based model and employs DenseNet121 and Inception-ResNetV2to facilitate further processing. The Convolution Neural Networks (CNN) function gathers and sorts the feature extraction data obtained from both models. The proposed approach demonstrates improved accuracy and recall plus average precision when used instead of a solitary model. The proposed machine-learning approach using fundus images proves successful for Glaucoma, Exudate and DR diagnosis according to this experiment. 2025 IEEE. -
AADS: An Automated Accident Detection and Nighttime Surveillance System Using Fine-Tuned YOLOv10 Deep Learning Techniques
Computer vision-based surveillance is very important today's security systems to detect, track and regulate the security much better than standard cameras. However, like any other performance measurement systems they have potential pitfalls and technical, ethical, and legal implications must be well understood. The continuous rise in connection and interaction implies that safety of the public especially when navigating roads or operating in public domains is paramount. The conventional approaches to accident identification include observation or reporting from witnesses and always record slow and imprecise outcomes. With the improvement of AI and computer visions, especially with deep learning models such as YOLO, accident detection is changing. YOLO v10 which is incorporated in the surveillance systems, performs real time video analysis to provide object and pattern recognition of accidents including car accidents and incidents involving the pedestrians. When applied to the initial set of annotated accident images, the fine-tuning of the YOLO v10 model enhances its detection capability. The system is in watching the video frames that contain aberrations and issues and alarms are issued when the accidents happen and relayed to the monitoring stations or emergency departments for proper response. The optimized YOLOv10 here delivers a meaningful testing score of 72.3% mAP to outperform the regular YOLOv10 efficiency in incident detection. 2025 IEEE. -
Analysing Customer Profile, Expectations and Satisfaction with Airport Retail in Coimbatore, Insights into the Airport Environment and Decision Making Dynamics
Airport retailing has become a crucial income source and a fundamental aspect of improving traveler experiences. Nevertheless, the intricate relationship between traveler characteristics, anticipations, shopping environments, promotional tactics, purchasing choices, and contentment remains insufficiently examined. This research fills this knowledge gap by exploring the structural associations among six key factors: Customer Profile (CP), Customer Expectation (CE), Airport Retailing Environment (ARE), Retail Marketing Strategy (RMS), Customer Preference Decision (CPD), and Customer Satisfaction (CS) in the context of airport retail environments A descriptive study framework was implemented, concentrating on travelers participating in retail purchases at Coimbatore airport. Firsthand information was obtained from 203 participants using a structured survey. The collected information was assessed using Structural Equation Modeling (SEM) to determine the interconnections among these elements and their overall effect on passenger contentment. The findings reveal that Customer Expectation is significantly influenced by Customer Profile, while Airport Retailing Environment is directly shaped by Customer Expectation but not by Customer Profile. Retail Marketing Strategy is strongly impacted by Airport Retailing Environment but shows no significant relationship with Customer Expectation. These findings emphasize the significance of analyzing traveler behavior and tailoring retail strategies to enhance contentment in airport shopping environments. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Empowering Women Entrepreneurs in Trade: Challenges, Opportunities and the Role of Digital Marketplaces in Tamilnadu
In recent years, there is a revolution in the commercial sector due to digitalisation which provides an opportunity for the women entrepreneurs, especially in Tamil Nadu with unknown prospects. Nevertheless, all the women entrepreneurs do not get full advantage of these digitalised platforms like the women entrepreneurs who involved in MSME sectors with lack of access or restriction to capital, social constraints, legal constraints or lack of digital literacy. The current status of women entrepreneurship in Tamil Nadu is to identify their unique challenges they face in use of digital platforms and to overcome these challenges. The present study is to make an attempt to know how digital market places should improve women entrepreneurs in access to all the resources, opportunities and market places by evaluating the same. This current research adopts mixed-methods approach, which includes quantitative and qualitative methods. These methods are used to investigate how digital platforms helps the women entrepreneurs in removal of inequalities in reaching the market and also in elimination of financial access which in turn helps to improve the operational efficiency of women-led businesses. Based on the previous research, it is evident that digital markets help the entrepreneurs in getting connected with others and skill development along with access to a greater number of customers. This study focusses towards the interventions which has to be addressed which includes social constraints, lack of digital infrastructure, lack of training to access digital tools. The intent of this study is to focus in policy framing which promotes growth in trade that assists the women entrepreneurs. Thus, this research highlights the transformative potential of digital marketplaces in empowering women in trade, paving the way for an inclusive and dynamic entrepreneurial ecosystem in Tamil Nadu. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Role of Data Science in the Field of Genomics and Basic Analysis of Raw Genomic Data Using Python
The application of genomics in identifying the nature and cause of diseases has predominantly increased in this decade. This field of study in life sciences combined with new technologies, revealed an outbreak of certain large amounts of genomic sequences. Analysis of such huge data in an appropriate way will ensure accurate prediction of disease which helps to adopt preventive mechanisms which can ultimately improve the human quality of life. In order to achieve this, efficient comprehensive analysis tools and storage mechanisms for handling the enormous genomic data is essential. This research work gives an insight into the application of data science in genomics with a demonstration using Python. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
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Enhancing the confidentiality of text embedding using image steganography in spatial domain
Rapid growth in technological development, the use of the internet has grown many folds. Along with it, the sharing of privacy information in networks creates ownership issues. In order to create a high level of security for sharing private information, the concept of steganography is introduced along with encryption based invisible watermarking techniques. The proposed system hides the encrypted private messages by using onetime pad which follows the concept LSB algorithm in spatial domain. The system combines steganography and encryption for enhancing the confidentiality of the intended messages. At first, the private information of the user is encrypted by using the onetime pad algorithm. Then the encrypted text is hidden the Least Significant Bit (LSB) of the different components of the color image in such a way that as to minimize the perceived loss of quality of the cover image. The beneficiary of the message is able to retrieve the hidden back and from the stego-image and extract the cipher text and find the plaintext from using the onetime pad algorithm. The proposed algorithm will be tested and analysed against three different hiding positions of color image components. 2021 American Institute of Physics Inc.. All rights reserved. -
Assessment of composite materials on encrypted secret message in image steganography using RSA algorithm
The use of the internet in this modern era is increased many fold. The communications between different peers take place in digital form. While sharing the messages between different recipients, the confidentiality of the messages is very important. For creating the high level of security while sharing the secret messages, the cryptographic algorithms are introduced along with steganography. Image Steganography is a methodology used to hide the messages inside of the cover image. Initially, the secret information is encrypted by using the RSA Algorithm. Then the encrypted secret information is hidden in the Least Significant Bit (LSB) of the different components of the color image in such a way that the original quality of the image to be minimized. The recipient of the message is able to retrieve the encrypted secret message from the LSB bit of stego_image and then the cipher text is converted into original plain text by using the RSA algorithm. The proposed algorithm verified and analysed its performance against the different combinations of key pairs. 2021 Elsevier Ltd. All rights reserved. -
Design and Development of Terahertz Medical Screening Devices
This paper highlights the prospect of design and development of a terahertz medical screening system, giving an overview of existing devices, systems, for THz spectroscopy and imaging of biological samples (e.g., cell, tissue imaging or screening). Considering the non-ionizing nature of THz waves along with its reasonable soft-tissue sensitivity, terahertz instrumentation has opened up possibilities for medical screening devices. Some THz imaging systems presently use raster scanning for calculation of image region of interest. Here, a particular system is proposed as a medical screening device and factors like signal-to-noise ratio, image resolution, image contrast, etc., have been described and correlated with relevant clinical results for exploring possible prospects in medical applications of terahertz waves. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Towards developing an automated technique for glaucomatous image classification and diagnosis (AT-GICD) using neural networks
Glaucoma is the eye defect that has become the second leading cause of blindness worldwide and also stated as incurable, may cause complete vision loss. The earlier diagnosis of glaucoma in Human Eye is a great confrontation and very important in present scenario, for providing efficient and appropriate treatments to the persons. Though there is much advancement in Ocular Imaging that affords methods for earlier detection, the appropriate results can be obtained by integrating the data from structural and functional evaluations. With that note, this paper involves in developing automated technique for glaucomatous image classification and diagnosis (AT-GICD). The model considers both the textural and energy features for effectively diagnosing the defect. Image Segmentation is processed for obtaining the exact area of optic nerve head; histogram gradient based conversion is employed for enhancing the fundus image features. Further, Wavelet Energy features are extracted and applied to the artificial neural networks (ANN) for classifying the NORMAL and GLAUCOMA images. The Accuracy rate based comparison with other existing models is carried out for evidencing the effectiveness of the proposed model in glaucomatous image classification. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.