Browse Items (5511 total)
Sort by:
-
An Adaptive Cluster based Vehicular Routing Protocol for Secure Communication
In todays scenario, Vehicular Ad-hoc Network (VANET) is one of the modern fields in vehicle communication; it includes a large number of nodes that can be changed arbitrarily with the ability to link or exit the system anytime. Moreover, it has various complexities because of the attacks model in the transmission and communication channel. Besides, most of the attacks are known as black hole attack and wormhole attack. The presence of these attacks causes large damage in the data broadcasting region that ends in data drops or collapses. To defeat these problems, a novel Clustered Vehicle Location protocol for Hybrid Krill Herd and Bat Optimization (CVL-HKH-BO) technique is proposed. Thus, the proposed mechanism of hybrid krill herd and bat optimization is to detect and prevent attacks based on the fitness function. Moreover, secure communication can be enhanced by the proposed technique. Consequently, the solution to energy consumption and packet delay issues are solved using the CVL protocol. The projected strategy is implemented in the Network simulator (Ns-2) platform, and the outcomes show the node energy, overload and delay are minimized by increasing the quantity of packets transmitted in the network. Sequentially, the proposed technique is compared with existing techniques in terms of throughput, packet loss, delay time and data broadcasting ratio. Therefore, the duration of the node can be enhanced and can attain high energy capable data transmission. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Gender Differences in Social Capital and Job Search Methods in the Information Technology Industry in Bangalore
The Indian Journal of Economics Vol. 55, No. 3, pp 501-917, ISSN No. 0971-7927 -
Job search methods in the software industry in Bangalore: Does social capital matter? /
The Indian Journal of Labour Economics, Vol.61, Issue 4, pp.681-699, ISSN No: 0971-7927. -
Patriarchy and Wifehood: A Feminist Reading of One Part Woman and Singarevva and the Palace
Marriage is a socially approved relationship between a man and a woman that binds each other into a permanent, official relation of husband and wife. In a patriarchal culture, the husbands personify dominance and liberty, whereas the wives are expected to be the epitome of fidelity, fecundity and chastity. In the Indian context, the intense devotion of wives towards their husbands defines married women as pativratas. The present study intends to analyze the various aspects that contribute to and shape the formation of the identity of a wife in a marital space through Ponna and Singarevva, the female protagonists of the novels One Part Woman and Singarevva and the Palace, respectively. The paper demonstrates how these female protagonists identity as wives gets suppressed over a period of time and how they succeed in reconstructing their identities, sailing against all odds stacked against them. The paper views these issues through the feminist theoretical lens. 2024 IUP. All Rights Reserved. -
Influence of hydrothermal synthesis conditions on lattice defects in cerium oxide
Cerium oxide makes one of the most promising materials for chemical transformations in environmental and energy applications. Herein, the influence of hydrothermal conditions on the physico-chemical characteristics of cerium oxide prepared from salt solution via ammonia precipitation is analyzed. The systems are well characterized using SEM, TEM, XRD analysis, photoluminescence spectra, Raman spectra, TPR study. and XPS analysis. Normal aqueous conditions lead to particles of size ~8 ?nm, with truncated octahedral geometry, closer to spheroid shape (RT-Ce) bound by {111} and {100} planes. Elevated temperature facilitated preferential exposed {100} plane bounded cubic ceria structures of size ~15 ?nm (HT-Ce), which are stabilized by more number of anion vacancies. Low temperature synthesis yielded smaller sized particles with less crystallinity and higher surface area, when compared to hydrothermal route. Lattice defects, represented in terms of Ce3+ ions and associated lattice oxygen vacancies are seen in higher amounts in ceria synthesised via hydrothermal path, as supported by various characterization results. CeO2 achieved via hydrothermal path exhibited higher catalytic oxidation activity, which is examined using a model oxidation reaction, vis., CO oxidation. The enhanced activity of HT-Ce is explained through the defect structure induced facile redox shift in the system. 2021 Elsevier Inc. -
ANALYSIS, ASSESSMENT, AND MANAGEMENT OF ENVIRONMENTAL AIR POLLUTION USING ENVIRONMENTAL ENGINEERING IN DEVELOPING COUNTRIES
Recent studies underscore the value of contemporary technology and gas emissions mitigation while overlooking the necessity of optimal fuel in Developing Countries (DC). DC's historical economic expansion has significantly depended on fossil fuels, resulting in severe environmental air pollution (EAP) challenges. The separation of economic progress from pollution has been the central emphasis in advancing environmental civilization in emerging countries. This study presents an analysis, assessment, and management of EAP using environmental engineering (EE) in DC. This work has examined the evolution of EAP regulations in DC, emphasizing a strategic shift from emission regulation to Air Quality Management (AQM). The regulation of Sulfur dioxide (SO2) emissions addressed the worsening of acid rain in DC. Since 2015, regulatory measures across several sources and industries have aimed to decrease the total amount of Fine Particulate Matter (FPM2.5), signifying a shift towards an AQM-focused policy. Escalating ozone (O3) pollution necessitates integrated management measures for O3 and FPM2.5, focusing on their intricate photochemical reactions. Significant enhancement of AQM in DC, as a crucial metric for the efficacy of sustainable economic development, necessitates the profound carbon reduction of the DC's energy infrastructure and the establishment of more integrated strategies to tackle EAP and climate change in DC concurrently. 2024, Rotherham Academic Press Ltd. All rights reserved. -
The Impact of Artificial Intelligence on Digital Employee Engagement
Purpose: This study aimed to investigate the impact of artificial intelligence (AI) on digital employee engagement, focusing on the roles of job autonomy and digital learning orientation. It sought to understand how these factors influenced employee engagement in a digital environment and the extent to which the meaningfulness of work mediated these relationships. Design/Methodology/Approach: Data were collected from 527 individuals performing administrative jobs in the private service sector. The study utilized partial least squares structural equation modeling (PLS-SEM) to test the proposed relationships among job autonomy, digital learning orientation, and digital employee engagement with mediation of meaningfulness of work. Findings: The findings indicated that job autonomy and digital learning orientation significantly and positively predicted digital employee engagement. However, the meaningfulness of work did not mediate the relationship between job autonomy, digital learning orientation, and digital employee engagement. The results of this study found that there was no significant relationship between the meaningfulness of work and digital employee engagement. This study also found that when the employees used digital tools, they often experienced feelings of loneliness and insecurity. Practical Implications: The study suggested that the organizations role should always be focused on promoting digital tools. Organizations should emphasize enhancing job autonomy and encourage employees to engage in digital learning orientation, boosting digital employee engagement in the workplace. Originality/Value: This study contributed to the literature considering the role of AI applications that directly influenced digital employee engagement by addressing the significant roles of job autonomy and digital learning orientation. It also emphasized the need for future research to explore the impact of the meaningfulness of work and the dependence on digital tools for employee performance. 2024, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Effect of heavy metal stress on biochemical and antioxidant efficacy of Chamaecostus cuspidatus
Chamaecostus cuspidatus, commonly known as insulin plant is medicinally important and a rich source of several secondary metabolites which exhibit pharmacological properties. In the present study, three different heavy metals (Pb, Cu and Cr) with different concentrations (Pb and Cr-50, 100, 150, 200 and 250 ppm and for Cu 25, 50, 75, 100 and 125 ppm) was used for heavy metal treatment and its impact on several biochemical and antioxidant parameters was measured of the test plant along with control. Current study mainly focuses on the biochemical and antioxidants estimation of root and rhizome of C. cuspidatus. Protein, proline and carbohydrate content was increased in the treated groups. Total phenol and total flavonoid content were also found to be increased in all the treated groups. Both enzymatic (SOD, CAT, APX) and nonenzymatic antioxidants (DPPH, FRAP and total antioxidant activity) was measured. Antioxidant activity was also high in the treated groups. Highest DPPH activity was found in Cu 25 treated rhizome 91.8030.157 and lowest was observed in Pb 50 treated root 4.5530.240. Highest reducing power activity (FRAP) was observed in Cr 100 treated rhizome 0.75860.0008 and least was found in control root 0.2090.0005. Heavy metals accumulation was also measured and maximum heavy metal accumulation was found in soil following by root and rhizome of all the treated groups. 2024, Indian journals. All rights reserved. -
Child mental health: The role of different attributional styles
Background: High prevalence of mental health issues in the twenty-first century accounts for a lion share in the worldwide burden of disease. There is an alarming decrease in the onset of half of the mental health problems. Hence, it is necessary to explore the current situation and figure out the causes and preventive measures as well as the appropriate mental health enhancement measures. Individual characteristics, such as thinking patterns and perception, have an impact on the mental health. Attributional style is one source of cognitive vulnerability which influences mental health disorders. Therefore, the present study examines whether there are any variations in the mental health of children with different attributional styles. Methods: The current research adopted a cross-sectional research design and selected 150 school going students [74 males and 76 females] between 10-13 years of age as participants. The Child Attributional Style Questionnaire [CASQ], Satisfaction with Life Scale-Children [SWLS-C], Brief Resilience Scale, and Revised Child Anxiety and Depression Scale [RCADS] are used to gather information. Results: The results indicated that children with a pessimistic attributional style experienced more depression and generalized anxiety than children with other two attributional styles. In terms of gender differences in mental health, female students with pessimistic attributional style significantly differed from their counterparts on depression [?2 [2] = 10.131, p = 0.006] and separation anxiety [?2 [2] = 6.456, p = 0.040]. Conclusion: Attributional style seems to have a significant role in depression and anxiety in female children. Although male children did not show any statistically significant results, they were more likely to be pessimistic in terms of their attributional style, which makes them vulnerable to mental health issues. 2020, Indian Association for Child and Adolescent Mental Health. All rights reserved. -
Grey Wolf Optimization Guided Non-Local Means Denoising for Localizing and Extracting Bone Regions from X-Ray Images
The key focus of the current study is implementation of an automated semantic segmentation model to localize and extract bone regions from digital X-ray images. Methods: The proposed segmentation framework uses a pre-processing stage which follows convolutional neural network (CNN) obtained segmentation stage to extract the bone region from X-ray images, mainly for diagnosing critical conditions such as osteoporosis. Since the presence of noise is critical in image analysis, the X-ray images are initially processed with a grey wolf optimization (GWO) guided non-local means (NLM) denoising. The segmentation stage uses a Multi-Res U-Net architecture with attention modules. Findings: The proposed methodology shows superior results while segmenting bone regions from real X-ray images. The experiments include an ablation study that substantiates the need for the proposed denoising approach. Several standard segmentation benchmarks such as precision, recall, Dice-score, specificity, Intersection over Union (IOU), and total accuracy have been used for a comprehensive study. The proposed architectural has good impact compared to the state-of-the-art bone segmentation models and is compared both quantitatively and qualitatively. Novelty: The denoising using GWO-NLM adaptively chose the denoising parameters based on the required conditions and can be reused in other medical image analysis domains with minimal finetuning. The design of the proposed CNN model also aims at better performance on the target datasets. 2023 Biomedical & Pharmacology Journal. -
Transfer Learning-Based Osteoporosis Classification Using Simple Radiographs
Osteoporosis is a condition that affects the entire skeletal system, resulting in a decreased density of bone mass and the weakening of bone tissues micro-architecture. This leads to weaker bones that are more susceptible to fractures. Detecting and measuring bone mineral density has always been a critical area of focus for researchers in the diagnosis of bone diseases such as osteoporosis. However, existing algorithms used for osteoporosis diagnosis encounter challenges in obtaining accurate results due to X-ray image noise and variations in bone shapes, especially in low-contrast conditions. Therefore, the development of efficient algorithms that can mitigate these challenges and improve the accuracy of osteoporosis diagnosis is essential. In this research paper, a comparative analysis was conducted Assessing the accuracy and efficiency of the latest deep learning CNN model, such as VGG16, VGG19, DenseNet121, Resnet50, and InceptionV3 in detecting to Classify Normal and Osteoporosis cases. The study employed 830 X-ray images of the Spine, Hand, Leg, Knee, and Hip, comprising Normal (420) and Osteoporosis (410) cases. Various performance metrics were utilized to evaluate each model. The findings indicate that DenseNet121 exhibited superior performance with an accuracy rate of 93.4% Achieving an error rate of 0.07 and a validation loss of only 0.57 compared with other models considered in this study. 2023, International journal of online and biomedical engineering. All Rights Reserved. -
Effectiveness of Learning Management System (LMS) in Sustainable Learning and Development among Bank Employees
Learning Management Systems in the form of E-Learning platform is currently an evolving scenario for the primary means of delivering various courses across educational, business, industries and vocational learning environments in the form of Learning and Development activities in all the sectors. LMS is a challenging and resource-intensive task requires demanding substantial knowledge, time, and effort. Consequently, there emerged a necessity in both research and practical applications to establish the personalized usage process of an LMS. Despite its significant impact on the outcomes of such an Information System (IS), the usage process has to be analysed. The researcher developed a conceptual model to delineate with set of factors to influence LMS course in Learning and Development Practices in industry context. Researcher revealed specific set of factors such as interface design, content presentation format, transfer of learning, and feedback mechanisms significantly impact learner satisfaction among Bank employees in their Learning and Development activities. Moreover, learner satisfaction depends on the application platform and content. The findings offer a valuable insight to design a corporate education system, with the quality content delivery and practical delivery. By considering these results, designers can develop more integrated and effective LMS to cater the needs and satisfaction of Learning and Development activities among Bank employees. 2024, Creative Publishing House. All rights reserved. -
Zero forcing number of degree splitting graphs and complete degree splitting graphs
A subset Z V(G) of initially colored black vertices of a graph G is known as a zero forcing set if we can alter the color of all ver- tices in G as black by iteratively applying the subsequent color change condition. At each step, any black colored vertex has exactly one white neighbor, then change the color of this white vertex as black. The zero forcing number Z(G), is the minimum number of vertices in a zero forcing set Z of G (see [11]). In this paper, we compute the zero forcing num- ber of the degree splitting graph (DS-Graph) and the complete degree splitting graph (CDS-Graph) of a graph. We prove that for any simple graph, Z[DS(G)] k + t, where Z(G) = k and t is the number of newly introduced vertices in DS(G) to construct it. 2019 Sciendo. All rights reserved. -
3-Sequent achromatic sum of graphs
Three vertices x,y,z in a graph G are said to be 3-sequent if xy and yz are adjacent edges in G. A 3-sequent coloring (3s coloring) is a function ?: V (G) ?{1, 2,...,k} such that if x,y and z are 3-sequent vertices, then either ?(x) = ?(y) or ?(y) = ?(z) (or both). The 3-sequent achromatic number of a graph G, denoted ?3s(G), equals the maximum number of colors that can be used in a coloring of the vertices' of G such that if xy and yz are any two sequent edges in G, then either x or z is colored the same as y. The 3-sequent achromatic sum of a graph G, denoted a'3s(G), is the greatest sum of colors among all proper 3s-coloring that requires ?3s(G) colors. This research initiates the study of 3-sequent achromatic sum and finds the exact values of this parameter for some known graphs. Furthermore, we calculate the a'3s(G) of corona product, Cartesian product of the graphs and some important results have been proved and a comparative study is carried out. 2021 World Scientific Publishing Company. -
Cop-edge critical generalized Petersen and Paley graphs
Cop Robber game is a two player game played on an undirected graph. In this game, the cops try to capture a robber moving on the vertices of the graph. The cop number of a graph is the least number of cops needed to guarantee that the robber will be caught. We study cop-edge critical graphs, i.e. graphs G such that for any edge e in E(G) either c(G?e) < c(G) or c(G?e) > c(G). In this article, we study the edge criticality of generalized Petersen graphs and Paley graphs. 2023 Azarbaijan Shahid Madani University. -
Early prediction of lungs cancer by deep learning algorithms from the CT images with LBP features
The early prediction of the any type of cancer can save the lives of many especially if it is lung cancer which is one of the deadly diseases in the world. Thus the early prediction is implemented we can increase life expectancy and bring the mortality level low. Although there are various methods to detect the lung cancer cells by X-ray and CT scans, however the CT images are more preferred. The 2D images like CT scans are used to get medical results more accurate. The proposed method here will discuss how the LBP features are used to analyze the CT images with the support of Deep Learning methods. In this research work we will discuss how the image manipulation can be done to achieve better results from the CT images through various image processing methods. LBP features helps in estimating the distribution of local binary pattern of an image. A final result with 93% is achieved after the training of the processed images by LBP features. 2020 SERSC. -
Green synthesis of reduced graphene oxide using Plectranthus amboinicus leaf extract and its supercapacitive performance
A rapid, efficient, green and eco-friendly approach for the preparation of reduced graphene oxide (rGO) using Plectranthus amboinicus (Indian borage) leaves extract (PAE) is explored in this study. The improvement in the reduction process was studied by varying the concentration of graphene oxide (GO), temperature and time duration. The physical and chemical properties of rGO are studied using Raman spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction (XRD) and field emission scanning electron microscope. The result obtained from XRD analysis confirms the removal of an oxygen-containing functional group of GO significantly by PAE. Raman analysis showed a higher ID/IG ratio for rGO (1.297) than GO (1.07), which indicates a higher level of disorder in the rGO with a decrease in the average size of the sp2 domain. From the electrochemical studies, a significant specific capacitance of 92.05Fg1 (5mVs1) is obtained from the cyclic voltammetry (CV) curves and 73.20Fg1 (0.1Ag1) from the galvanostatic chargedischarge (GCD) curve. 2021, Indian Academy of Sciences. -
Quantum Algorithm: A Classical Realization in High-Performance Computing Using MPI
Volume3, Special Issue3 ISSN: 23198753 -
India Gateway Program: Transformational learning opportunities in an international context
Internationalisation is increasingly important in the social work curriculum. With globalisation and international resettlement, social workers require competencies to work locally with diverse populations as well as overseas. Study abroad experiences are used to enhance international content, cultural sensitivity and self-awareness in curricula. This article evaluates an Australian study tour focussing on students perspectives. Indications are that it was effective in enhancing cultural sensitivity, understanding of factors contributing to inequity, the lived experience of poverty, personal growth and professional identity. For students, it was a valued and transformational learning experience. 2015, The Author(s) 2015. -
Gandhiji and RSS: The Cultural Grounding of Social Representations
Exploring the cordial relationship and mutual respect between Gandhiji and the Rashtriya Swayamsevak Sangh (RSS), this article critically examines the political rhetoric against the RSS and its implications. As a nationalist cultural organisation, the RSS had been well aligned with most of the social and cultural programmes initiated by Gandhiji. When critics of the RSS like Jawaharlal Nehru were keen on crushing the RSS, the truth-seeking political philosopher Gandhiji applauded its discipline, annihilation of untouchability and the rigorous simplicity. This article demonstrates how the serious charges against the RSS that were brought to the notice of Gandhiji by a section of Congress leaders further cemented the cultural grounding of social representations between the two, instead of making Gandhiji be the stranger of the RSS. 2023 ICHR.