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Performance of DSSC with green synthesized and thermodynamically sintered Bi-phase TiO2 with various sensitizers
The production of green and clean energy in the current era is heavily reliant on light harvesting through the use of solar cells. A successful fabrication of any of the components of Dye-sensitized solar cells (DSSC) through an easy, environmental, and economic-friendly method would be an added advantage in promoting the production of green and clean energy. With this in mind, this paper highlights the green synthesis of materials for the preparation of photo-anodes as well as sensitizers. Apart from the routine synthesis method, this paper presents a new perspective that enhances inter-particle connections by providing an optimum calcination temperature (thermodynamic sintering) during the preparation procedure. The best calcination temperature for the preparation of photo-anode material is initially optimized by comparing the device output performance between synthetic and natural dyes. Further improvement in device performance is achieved through TiCl4 (Titanium tetrachloride) post-annealing treatment on the optimized photo-anodes. The improvement in performance of these optimized photo-anodes is checked and confirmed with different natural, synthetic, and cocktail sensitizers. The best natural dye-sensitized solar cell (NDSSC) device showed an efficiency of 4.65 % and the dye-sensitized solar cell (DSSC) device showed an efficiency of 5.78 %. This confirms the suitability of these green-synthesized TiO2 nanopowders as a promising material for photo-anode preparation that could work well for both NDSSC and DSSC. 2024 Elsevier B.V. -
Enhancing the stability of DSSC by Co-activation of microwave synthesized TiO2 with biomass derived carbon dots
Dye-sensitized solar cells (DSSCs) that utilize natural dyes have garnered interest due to their low cost, eco-friendly manufacturing process, and competitive photovoltaic performance. However, their efficiency and stability issues have hindered their widespread implementation. To enhance their performance, this paper proposes a novel approach of modifying the photoanode with carbon dots (CDs) to align the band gap for easier carrier collection. The material properties were thoroughly characterized by examining their structural, morphological, optical, and electrical properties. In this study, titanium dioxide (TiO2) was synthesized using the microwave-assisted solvothermal method, while nitrogen-doped CDs derived from Citrus medica fruit juice were prepared using a simple hydrothermal treatment. Three sets of Natural Dye Sensitized Solar Cells (NDSSC) devices were created using co-activated photoanode (CD/TiO2) and unmodified photoanode (TiO2) with Platisol T/sp coated ITO serving as the counter electrode. Hibiscus (Hibiscus rosa-sinensis) and Onion (Allium cepa) peel extracts were utilized as sensitizers and Iodolyte HI-30 as the electrolyte. The most efficient device attained an efficiency of 3.5 % with Voc = 0.81 V and Jsc = 6.57 mA/cm2. This marks the highest efficiency reported using Hibiscus as a sensitizer with the current configuration, accompanied by prolonged device stability. This study showcases the potential of Citrus medica-derived nitrogen-doped CDs in achieving durable device stability. 2024 Elsevier B.V. -
FUZZY SEMI-ESSENTIAL SUBMODULES AND FUZZY SEMI-CLOSED SUBMODULES
In this paper, we prove some properties of fuzzy semi-essential submodules and fuzzy semi-closed submodules I??k University, Department of Mathematics, 2023; all rights reserved -
Isolation, Characterization and Evaluation of Potential Plant Growth-Promoting Bacteria From The Rhizosphere of Coffea arabica L. From Kodagu District, Karnataka
Agriculture is fundamental to food security and economic stability. The utilisation of newlineplant growth-promoting rhizobacteria (PGPR) an eco-friendly alternative to chemical newlinefertilisers is particularly promising as these microorganisms enhance nutrient newlineavailability, stimulate plant growth, and improve resistance to biotic and abiotic newlinestresses. This study aimed to isolate and characterise PGPR from the rhizosphere of newlineCoffea arabica L. in the Kodagu District of Karnataka, focusing on their potential as newlinebiofertilizers. Soil samples collected from ten different locations within Kamath Coffee newlineEstate led to the isolation of fourteen distinct bacterial colonies, labelled NJ01 to NJ14. These isolates were evaluated for various plant growth-promoting (PGP) traits like indole-3-acetic acid (IAA) siderophore and ammonia production, nitrogen fixation, newlinephosphate, and zinc solubilization and hydrogen cyanide (HCN) production. Further newlinestudies were carried out using 3 isolates with significant PGP traits. Enzyme activity newlineassays indicated that NJ01, NJ04, and NJ14 had positive results for protease, cellulase, newlineamylase, and catalase activity. These strains also displayed varying degrees of newlinehalotolerance, with NJ01, NJ04 and NJ14 tolerating up to 8%, 10% and 11% NaCl, newlinerespectively. Heavy metal tolerance tests revealed that NJ01 tolerated Pb up to 250 newlineg/mL, NJ04 tolerated Pb up to 1500 g/mL and Cd up to 50 g/mL, and NJ14 tolerated Pb up to 1000 g/mL and Hg up to 100 g/mL. Polyhydroxyalkanoate (PHA) production was confirmed in all isolates, with NJ01 yielding the highest amount (6.4 g/L). The isolates exhibited significant antifungal and the 16S rRNA sequencing identified NJ01 as Bacillus albus (OP784795), NJ04 as Bacillus licheniformis (OM780221), and NJ14 as Bacillus subtilis (OM780222). A consortium was prepared after confirming the plant growth promoting abilities of these PGPR strains by carrying out an initial plant growth studies. The optimisation of media parameters was by using a two-factor interaction model. -
The Future Warfare with Multidomain Applications of Artificial Intelligence: Research Perspective
We live in a period when historical fiction has become current reality. With our future being automated, using AI on a daily basis will only get more convenient. Making military weapons to detect, monitor, and engage a human being with attacks may all be done in the privacy of one's own garden. There is a plethora of AI software out there that can be readily integrated into combat weapons. The automobile industry is already incorporating AI into vehicles to assess driving circumstances and give augmented reality to drivers via heads-up displays in order to assist avert accidents. Similarly, artificial intelligence will be utilized to study the battlefield and give soldiers with augmented reality information via heads-up displays and weapon control systems. Since AI is not a single technology, it has been argued that it might be used by the military in a variety of ways. Intelligence, surveillance, and reconnaissance (ISR) activities, as well as processing and interpreting sensor data and geographic imaging analysis, are all examples of AI. Artificial intelligence has the potential to reduce human involvement in conflict, whether it is employed for combat robots or data analysis. AI has the potential to profoundly alter the nature of war. The article mainly focussed on warfare technologies and applications. The main aim of this review is to understand the current applications being used in armed forces and proposed technologies of artificial intelligence. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Experience and Agency of Children with Intellectual Disabilities in Schools : An Ethnographic Study in Haryana, India
India currently has more than 24 million children within the age group of 0-18 years experiencing some form of disability. Among them, India has the highest population of children at risk of developmental disabilities (UNICEF, 2011). However, there is a significant dearth of knowledge regarding their lived experiences. Surprisingly, qualitative understandings of the lives of children with intellectual disabilities within their school environments are lacking in India. Thus, this research aims to fill this gap by focusing on comprehending the lived experiences and agency of these children within their schools, families, and neighborhoods. Recognizing them as social agents has the potential to challenge the marginalized status often attributed to them. The objective of this research was to understand the lived experiences of children with intellectual disabilities across various school setups, including government schools, private schools, and mainstream schools. Furthermore, it seeks to understand the values and perspectives of the schools, school authorities and teachers, and the manner in which children with intellectual disabilities employ their agency in their day- to-day lives within different educational structures. Ethnographic research was, therefore, conducted in four government schools, two private schools and two special schools in Karnal district, Haryana, India. Haryana was chosen due to the existence of previous research on the cultural understanding of disability in the state. A total of 25 children with intellectual disabilities and 44 school teachers were interviewed and observed. Classroom observations and shadowing also served as important methods of data collection. The findings reveal that policies, school structures and processes, as well as teachers' practices and attitudes, continue to perpetuate exclusionary practices for children with intellectual disabilities. The notion of "inclusive schooling" remains superficial within the Indian context. However, within these exclusionary systems and processes, a diverse range of differences were noted in terms of the experiences, beliefs, and preferences of children. These differences are influenced by a complex interplay of their social environment (school and home), cultural norms and personal attributes. Academic aspirations and experiences of personal friendship emerged as dynamic and intricate aspects of their lives. Evaluating these elements presents challenges as children's academic achievements and friendships are continually evolving, forming, and dissolving. Data analysis also demonstrates that children with intellectual disabilities not only actively construct meanings but also possess an awareness of the cultural context in which they exist. Their interactions with others, including the researcher, were heavily influenced by these cultural contexts. Their actions contribute differently to social and relational networks, depending on the barriers they encounter within each institution. The performativity of their agency was explored through an understanding of their "silences," which proved to be an essential element in analyzing their agency.Additionally, their agency was examined through their utilization of digital technologies which was actively used by children to maintain friendships with old friends, to develop new friendships and for entertainment purposes. This research, therefore, aims to integrate the notions of agency, culture, and structure in order to gain a comprehensive understanding of the experiences of children with intellectual disabilities in various educational environments in an Indian state. -
Textile tourism and the challenges of the indigenous handloom sector in Northern Kerala
This study investigates the functioning of indigenous handloom enterprises and their relationship with textile tourism. It also explores the regional textile industry and the challenges weavers encounter in promoting their goods to visitors and exporters. Data was collected using a purposive sampling method, and a structured questionnaire was administered to 120 weavers from four textile weaving centers in Kozhikode, Kerala. The most significant obstacle for weavers and independent producers is the lack of direct communication with customers and the limited access to information provided by manufacturers, corporations, and gallery owners. Firstly, handcrafted items are becoming more accessible and affordable; secondly, the interest of the younger generation is gradually fading, which reduces the number of skilled professionals. The result of this study provides insight into how Khadi Textiles has the potential to contribute positively to socioeconomic achievements and enhance weaver's and destination image. 2024, IGI Global. All rights reserved. -
Potential, prospects, and problems of textile tourism in Kerala
Tourism in the textile industry has tremendous potential for future growth and development of local economies and rural communities, building upon the services provided by local governments. This study focuses on Khadi textile business operations, with a particular emphasis on textile-based businesses, and provides visitor perceptions of textile tourism. It discusses the possibilities and challenges in the local textile industry, including the dificulties faced by the weavers in marketing their goods to tourists and exporters. The questionnaire survey applied to 120 visitors from three different khadi shops in Kozhikode, Kerala. According to the study's findings, textile business centres require strategic promotional approaches to boost textile tourism. The major hurdle for weavers and independent producers is a lack of direct access to visitors, as well as access to information controlled by producers, commercial interests, and gallery owners. more in the future to expand the reach of this type of tourism. The potential role that the government and tourism authorities may play an important role in designing policies that may grant this form of tourism increased visibility. 2022, Universidade de Aveiro. All rights reserved. -
Copper oxide modified biphasic titania for enhanced hydrogen production through photocatalytic water splitting
Recently, TiO2(B) has been extensively used in catalytic and energy fields owing to its exceptional crystal structure. But being a metastable state, TiO2(B) is transformed easily into other stable crystalline forms like anatase or rutile phase, and the low crystallinity limits the application of the material in catalysis. A combination of TiO2(B) with anatase, which is benefitted by a homojunction, is proven to be blessed with high activity. Herein, hydrogen production via photocatalytic water-splitting is presented using Cu modified biphasic titania nanotubes achieved by a facile hydrothermal procedure. The systems are well characterized using SEM, TEM, XRD analysis, N2 adsorption study, FTIR, DR-UV, Raman, Photoluminescence, and X-ray photoelectron spectral analysis. The homo-junction developed in titania due to anatase TiO2 (B), as well as the heterojunction created by the co-catalyst, tune the photocatalytic activity of TiO2 nanotubes positively, as evident from the enhanced hydrogen production over the system. 2023 -
Despeckling of Ultra sound Images using spatial filters - A Fusion Approach
Ultra sound images are normally affected by speckle noise which is typically multiplicative in nature. This study proposes different fusion based despeckling methods for ultra sound images. The output of existing spatial domain despeckling methods viz. Lee filter, Bayesian Non Local Means (BNLM) filter and Frost filter are fused pairwise. Fusion is implemented in two steps, first an inter-scale stationary wavelet coefficient fusion followed by an intra-scale wavelet coefficient fusion. Analysis of these projected despeckling strategies are conducted using metrics like Peak Signal to Noise Ratio (PSNR), Equivalent Number of Looks (ENL), Structural Similarity Index (SSIM) and Universal Image Quality Index (UIQI). The results show that the performance of fusion based methods is better than the respective individual filters for despeckling ultra sound images. 2019 IEEE. -
Directional Vector-Based Skin Lesion Segmentation - A Novel Approach to Skin Segmentation
Efficient skin lesion segmentation algorithms are required for computer aided diagnosis of skin cancer. Several algorithms were proposed for skin lesion segmentation. The existing algorithms are short of achieving ideal performance. In this paper, a novel semi-automatic segmentation algorithm is proposed. The fare concept of the proposed is 8-directional search based on threshold for lesion pixel, starting from a user provided seed point. The proposed approach is tested on 200 images from PH2 and 900 images from ISBI 2016 datasets. In comparison to a chosen set of algorithms, the proposed approach gives high accuracy and specificity values. A significant advantage of the proposed method is the ability to deal with discontinuities in the lesion. 2020 World Scientific Publishing Company. -
Automatic Skin Lesion SegmentationA Novel Approach of Lesion Filling through Pixel Path
Abstract: Lesion segmentation is a vital step in a melanoma recognition system. Many algorithms were developed for the efficient skin lesion segmentation. Most of them fails to realize a perfect segmentation. This paper proposes a novel, fully automatic system, for the lesion segmentation in dermatograms. The proposed approach executes in two steps. Selection of root seed is the first step. All the lesion pixels in the dermatogram are identified during the second step. Traversal through a predefined lesion pixel path ensures the reachability of all lesion pixels irrespective of the possible lesion discontinuity. The proposed algorithm is tested with two publically available dataset, PH2 and images of ISBI2016 challenge. Out of the six evaluation parameters, the proposed method shows the best values for specificity, accuracy, Hammuode distance and XOR. This confirms the merit of the proposal with respect to existing popular methods. 2020, Pleiades Publishing, Ltd. -
Evaluating the Effectiveness of a Facial Recognition-Based Attendance Management System in a Real-World Setting
Face recognition technology has been extensively used in multiple verticals of security, surveillance, and human-computer interaction. Conventional techniques including manual sign-ins, identity cards, or biometric verification have been used by traditional attendance systems. Face recognition systems have, however, become a popular way to track attendance, thanks to developments in computer vision and machine learning. The construction of an attendance registration application is the main topic of this research study, which also offers a thorough overview of facial recognition attendance systems. This study seeks to provide light on the benefits, drawbacks, and potential applications of these fast-developing technologies. Face recognition technology may be integrated into attendance systems to increase productivity, accuracy, and user comfort. However, issues like privacy worries and technological constraints must be resolved. With predicted future improvements in machine learning algorithms and hardware capabilities, face recognition attendance systems look to have a bright future. This research article adds to a deeper understanding and successful application of facial recognition technology in attendance systems by examining these features. 2023 IEEE. -
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A Study on emotional labour and job embeddedness amongst the frontline employees in hotel industry in bangalore
In various studies, researchers have pointed out that there exists a high turnover in the hotel industry. It is also found that employees in the hotel industry practice high emotional labor. However, the researcher, wanted to understand if people leave the industry or the organisation and how emotional labor plays positively in this phenomena. It was also curious to understand if Pride in work and Social Intelligence plays a role between Emotional Labor and Job newlineEmbeddedness. The present study investigated the emotional labor along with pride in work and social intelligence, experienced by employees of different hotels as a factor affecting their Job Embeddedness. A descriptive study was conducted using self-administered questionnaires among 341 frontline employees of different five-star and five-star deluxe hotels of Bangalore. newlineThe results exhibited a significant impact of Emotional Labor, Pride-in-Work, Social Intelligence on Job Embeddedness as well as significant differences in perceptions of variables based on demographic factors of the employees. The implications and suggestions for the hotel industry were discussed in the study. -
Artificial Intelligence Based Computational Framework for Identification and Classification of Interstitial Lung Diseases Using HRCT Images
Interstitial Lung Diseases (ILDs) refer to a wide array of respiratory disorders characterised via infection and scarring of the lung's interstitial tissue. These conditions affect the space within the air sacs, compromising the lungs' ability to expand and contract properly. ILDs manifest with a range of symptoms, including persistent cough, shortness of breath, and fatigue. Diagnosis of ILDs often involves imaging methods, mainly High-Resolution Computed Tomography (HRCT), to assess lung abnormalities. ILDs can have lasting effects on respiratory function, leading to progressive fibrosis. The primary obstacle in identifying ILDs lies in the diverse array of symptoms they present, making it challenging to distinguish them from other pulmonary disorders. The HRCT is a commonly employed method in ILD diagnosis. These images provide a detailed depiction of lung tissue, revealing its size, shape, and any notable abnormalities or changes. Moreover, HRCT plays a crucial role in monitoring disease progression over time. Deep Learning (DL) excels in detecting patterns in intricate medical images that may pose challenges for traditional methods. Moreover, DL algorithms exhibit the ability to identify subtle changes in medical images indicative of pathology, and they can automate object detection tasks. The application of DL in medical contexts can enrich the precision and rapidity of diagnoses. In this research aimed at improving the accuracy of artificial intelligence AI-based ILD identification, we harnessed the benefits of deep learning, employing full-training, Transfer Learning (TL), and ensemble voting techniques. Our approach involved the construction of three Convolutional Neural Networks (CNNs) from scratch for ILD detection. Additionally, we customized models named InceptionV3, VGG16, MobileNetV2, VGG19, and ResNet50 for both full-training and TL strategies. This comprehensive methodology aimed to take benefits of DL architectures to enhance the precision of ILD identification in medical imaging. Both the first dataset consisting of HRCT images and the second dataset comprising Chest X-ray were employed in our study. However, during the initial training phase of the TL models, we utilized pre-trained ImageNet weights. To enhance performance, modifications were made to the classification layers of all five models for both TL and full-training processes. To further improve training outcomes, a soft-voting ensemble approach was employed. The ensemble, combining the predictions of all three newly developed CNN models (ILDNetV1, ILDNetV2 and ILDNetV3), and ILDNetV1 achieved the highest test accuracy at 98.14%. Additionally, we incorporated machine learning (ML) models, including Logistic Regression, BayesNet, RandomForest, Multilayer Perceptron (MLP), and J48, using statistical measurements derived from HRCT images. Our study introduces a novel AI-based system for predicting ILD categories. This system demonstrated superior performance on unseen data by leveraging the results from the newly constructed CNNs, transfer learning, and ML models. This comprehensive approach holds promise for advancing ILD category prediction, providing a more robust and accurate tool for medical diagnosis and decision- making. -
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Green synthesis of silver nanoparticles using calendula officinalis and its anti-bacterial studies /
Mapana Journal of Sciences, Vol.17, Issue 2, pp.11-17, ISSN No: 0975-3303. -
Estimation of stellar parameters and mass accretion rate of classical TTauri stars from LAMOST DR6
Classical T Tauri stars (TTS) are low-mass pre-main sequence stars with an active circumstellar environment. In this work, we present the identification and study of 260 classical TTS using LAMOST Data Release 6, among which 104 stars are newly identified. We distinguish classical TTS from giants and main-sequence dwarfs based on the log g values, and the presence of H ? emission line and infrared excess that arises from the circumstellar accretion disk. We estimated the mass and age of 210 stars using the Gaia colormagnitude diagram. The age is from 0.1 to 20 Myr, where 90% of the stars have age <10 Myr and the mass ranges between 0.11 and 1.9 M? . From the measured H ? equivalent widths, we homogeneously estimated the mass accretion rates for 172 stars, with most values ranging from 10 - 7 to 10 - 10M? yr - 1 . The mass accretion rates are found to follow a power law distribution with the mass of the star, having a relation of the form M?acc?M?1.430.26 , in agreement with previous studies. 2023, Indian Academy of Sciences. -
Spectroscopic study of Herbig Ae/Be stars in the Galactic anti-centre region from LAMOST DR5
We study a sample of 119 Herbig Ae/Be stars in the Galactic anti-centre direction using the spectroscopic data from large sky area multi-object fiber spectroscopic telescope survey program. Emission lines of hydrogen belonging to the Balmer and Paschen series, and metallic lines of species such as Fe ii, O i, Ca ii triplet are identified. A moderate correlation is observed between the emission strengths of H? and Fe ii 5169 suggesting a possible common emission region for Fe ii lines and one of the components of H?. We explored a technique for the extinction correction of the HAeBe stars using diffuse interstellar bands present in the spectrum. We estimated the stellar parameters such as age and mass of these HAeBe stars, which are found to be in the range 0.1-10 Myr and 1.5-10 M, respectively. We found that the mass accretion rate of the HAeBe stars in the Galactic anti-centre direction follows the relation ?acc ? M?3.12-0.34+0.21, which is similar to the relation derived for HAeBe stars in other regions of the Galaxy. The mass accretion rate of HAeBe stars is found to have a functional form of ?acc ? t-1.10.02 with age, in agreement with previous studies. 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.