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A study on women benificiaries of national rural health mission with special a reference to barwani district madhya pradesh
Regardless of several growth-orientated policies implemented by the government, the widening economic, regional and gender disparities are posing challenges for the health sector. The health status of Indians, especially women is still a cause for serious concern, especially that of the rural population. The National Rural Health Mission (NRHM) was launched by Government of India with a view to bring about dramatic improvement in the health system and health status of the people, especially those living in rural areas. The study aimed to understand the knowledge level of women beneficiaries on NRHM related services. The study further focussed on understanding the extent of availability and accessibility, challenges faced and the benefits received by women. The research work was carried out in three Village Panchayats of Barwani district in the state of Madhya Pradesh. Multi stage sampling method was adopted to select the sample group for the study. The study was conducted among 278 women beneficiciaries of NRHM. The researcher used 120 item semi structured and validated interview schedule for collecting the data. The study results show that there is a need to strengthen the grass root level interventions in terms of strengthening the sub-centres and involvement of Gram Panchayat in fulfilling the health mission objectives of the country. test indicated significant association between Caste and electricity at home and Knowledge about NRHM among women. The Correlation between the knowledge scores and benefits scores was significant (r = .705, Pgt.001). The study suggests having effective monitoring and evaluation mechanisms at all levels with clearly designed indicators and means of verification to ensure the success of the programme. newline -
A Model for the Secured Data Transfer of Healthcare Data by Image Steganography and Cryptography Techniques
Health care domain and related issues have evoked a lot of attention from researchers in the recent past. Ensuring the Security and Privacy of data of patients having classified disease is of utmost importance to the health care sector. From time immemorial cryptography and steganography techniques were used to provide data security. In health care domain, classified disease is the area of investigation as the patients having classified disease always prefer more security and privacy. The objective of this research work is to extract the benefits of cryptography and steganography techniques and to apply the combination of these security mechanisms to develop an algorithm that gives more security and privacy than existing techniques. The proposed algorithm builds on Rivest, Shamir and Adleman (RSA)algorithm which is considered to be one of the classical algorithms in cryptography. RSA is widely used in the encryption-decryption process for data transfer in internet which ensures the security of data in transit. The data encrypted using RSA is provided with one more layer of protection by calculating the message digest of the same. The message digest of encrypted data is calculated using message digest (MD5) algorithm. The steganographic approach of spread spectrum gives better security as it is always robust against statistical attacks and provides added security to the cryptographic protected data. Finally the Discrete wavelet transform (DWT) method is used for transformation. Combination of cryptographic technique and steganographic techniques offers higher level security to the data dealt in health care domain. Image type is a major factor contributing to the performance of the proposed algorithm. In recent years the open sources such as internet shows rapid usage of images especially Joint Photographic Experts Group (JPEG) image format as it occupies comparatively less space and provides better image quality even after applying image transformation. So medical image format type selected for the discussed research work is of JPEG format. Medical images of patients like X-ray of lung, bilateral section of face etc. are taken as cover image for the developed algorithm. Patients personal data is very confidential which is in the textual format is encrypted using RSA algorithm, then message digest is incorporated to keep the encrypted data homogeneous and then it is embedded in the cover image using DWT technique. The performance of the algorithm developed is measured on the basis of peak signal to noise which is a statistical method. The peak signal to noise ratio measurement is used as a visual quality measurement to simulate human perception as the difference between original image and embedded image seems to be identical as per developed algorithm. PSNR ratio is measured for various medical images selected. Noise ratio is also measured for Lena image as it is considered as a standard cover image in the steganography. Noise ratio of the selected medical images are measured and compared against cropped medical images. The results of the above research exercise presented in the thesis, infers that the proposed algorithm Raster Data protection algorithm provides enhanced security to the embedded medical images dealt within the health care sector, with minimal side effect on the quality of the image. KEYWORDS: Cryptography, Steganography, Health care, Security, JPEG, PSNR. -
Injective edge coloring of graphs
Three edges e1, e2 and e3 in a graph G are consecutive if they form a path (in this order) or a cycle of lengths three. An injective edge coloring of a graph G = (V, E) is a coloring c of the edges of G such that if e1, e2 and e3 are consecutive edges in G, then c(e1) ? c(e3). The injective edge coloring number ?? i (G) is the minimum number of colors permitted in such a coloring. In this paper, exact values of ?? i(G) for several classes of graphs are obtained, upper and lower bounds for ?? i (G) are introduced and it is proven that checking whether ?? i (G) = k is NP-complete. 2019, University of Nis. All rights reserved. -
Relevance for demographic factor: Level of financial literacy
The study assesses the level of Financial Literacy of residents of Puducherry and investigates the impact of demographic characteristics on their Financial Literacy. A total of 637 residents residing in seven different blocks of Puducherry constituted the sample of the study. Multinomial regression model was used to see the impact of demographic variables on the levels of Financial Literacy. The results indicated that the level of Financial Literacy was affected by factors including gender, marital status, work status, level of education and number of financial dependents in a family. These statistically significant results suggested that male respondents who are married and have 3 financial dependents having self employment or salaried job living in rural areas tend to have high level of financial literacy. 2018 SCMS Group of Educational Institutions. All rights reserved. -
A Semiotic Analysis of Political Cartoons in Malayalam Newspapers during the 2016 Assembly Election
I am immensely grateful for the everlasting love and grace of the Almighty God for granting me wisdom and guiding me to complete this study successfully. I would like to thank Dr (Fr) Abraham V M, Vice- Chancellor, Christ University, Bengaluru for giving me the opportunity to pursue research and facilitating me to complete my study. I thank Mr. Padmakumar, Head of the Department of Media Studies for being always approachable, understanding and infusing positivity that motivated me to persist in my endeavours with conviction that has enabled me to complete my thesis. I express my sincere thanks to my guide and supervisor Dr. Pradeep Thomas J.A Department of Media studies, Christ University, Bengaluru for his constant supervision, mentoring and valuable inputs throughout the course of my study. I thank the department of Media Studies for taking time out and guiding my thesis at every stage. I have been able to build my thesis with all your valuable insights. I sincerely thank all my M.Phil. professors for their constant help and guidance. I express my heartfelt gratitude to Mr. Sukumaran Potti (Chairman, Kerala Cartoon Academy), Mr. Baiju Paulose (Staff Cartoonist, Malayala Manorama), Unnikrishnan K (Chief Sub Editor, Mathrubhumi), V R Rajesh (cartoonist, Madhyamam), T.K Sujith (staff cartoonist, Keralakaumudi) and Satish Acharya, renowned Indian cartoonist for taking part in the study and giving valuable contribution for the study. Finally, I am thankful to my parents, brother and my friends for their constant encouragement, moral support, continuous inspiration and prayers to carry out this dissertation successfully. -
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Automatic Measurement and Differentiation of Traffic Volume Count
Traffic volume in India is growing drastically over the past few decades. This leads to an increased need of constructing more highways and underpasses. In order to have the definite knowledge of traffic volume, and to design the width and thickness of the pavements, periodical conduction of traffic census is necessary. At present, the evaluation of traffic volume is conducted manually. This system is tiresome and lacks accuracy. The data obtained from the traffic census decides the sanction of new highways, underpasses, or flyovers which involves huge investments. Hence, the accuracy of this data is very critical. In this paper, we propose an automatic tool that helps to measure the traffic volume and differentiate the vehicles using video processing tools in MATLAB. The proposed algorithm consists of the following steps: i Foreground Detection ii Blob Detection iii Blob Analysis iv Vehicle differentiation Counting. 2018 IEEE. -
Securing Automated Systems with BT: Opportunities and Challenges
The use of automated systems is becoming increasingly prevalent in various industries; however, they pose significant security risks. In order to enhance the security of these systems, Blockchain Technology (BT) provides a promising solution. This chapter discusses the opportunities and challenges associated with using BT to secure automated systems. The role of BT in securing automated systems is discussed, emphasizing its ability to improve security and transparency. Additionally, BT-based systems with enhanced security are examined, such as decentralized data management, immutable and transparent ledgers, reduced cyber-attacks, and secure data sharing. Despite these opportunities, challenges such as high computational power requirements, integration challenges, BT scalability, and regulatory challenges must be addressed. Utilizing BT can create a more secure and transparent system that can help to prevent fraud, hacking, and other forms of cyber-attacks, ultimately enhancing the reliability and safety of automated systems. In conclusion, this paper highlights the potential of using BT for securing automated systems and the need for continued research and development to overcome the challenges associated with its implementation. 2024 selection and editorial matter, Nidhi Sindhwani, Rohit Anand, A. Shaji George and Digvijay Pandey; individual chapters, the contributors. -
Psychological experiences and travel Adversities: A Mixed-Method study of the regular commuters in traffic congestion
This study investigated the psychological experiences and consequences of travel adversities during traffic congestion using a three-phase sequential exploratory mixed-methods design. Phase 1 explored the travel adversities, psychological experiences, and consequences of a sample of ten (four women and six men) regular commuters of Bangalore's congested roads using semi-structured interviews. In phase 2, a checklist was developed listing the fundamental themes from phase 1 with Likert-type responses ranging from 0 (never) to 5 (always). Phase 3 gathered data in the checklist and tested the statistical validity of the thematic model in a sample of 190 (81 women and 103 men) regular commuters. Attride-Stirling model thematic network was established with 57 fundamental themes categorized and assigned under the organizing themes of travel adversities (n = 6), negative affect (n = 28), fight (n = 7), flight (n = 6), and negative road occurrences (n = 10), in the global theme, psychological experiences and consequences. Structural equation modeling indicated that (1) negative affect significantly predicted fight and flight, (2) fight is a significant predictor of negative road occurrences, and (3) psychological experiences and consequences create a self-perpetuating cycle, with travel adversity triggering negative emotions, which results in fight responses leading to negative road occurrences, further intensifying travel adversity. A mathematical model is established based on this statistical validation, which holds potential applications in real-time traffic algorithms. 2024 -
Bioinformatics applications for evaluating health and pharmacological properties of tea: Use of computer-assisted drug discovery tools
Bioinformatics has emerged as a crucial tool in tea research, enabling the exploration of the genetic and molecular intricacies underlying tea cultivation, quality, and health benefits. By leveraging bioinformatics, researchers have extensively explored, inferred, and evaluated the pharmacological properties of tea. This groundbreaking approach has unveiled a myriad of possibilities for utilizing the bioactive compounds present in tea. Metabolomics studies have unraveled the intricate metabolic pathways within tea plants, providing insights into the synthesis and accumulation of bioactive compounds. Bioinformatics in tea research opens new avenues for the tea industry, benefiting both producers and consumers worldwide. These advancements not only deepen our understanding of tea biology but also hold immense potential for sustainable tea production, the discovery of novel bioactive compounds, and the optimization of tea flavors and health benefits. This chapter explains the bioinformatic tools used to identify various therapeutic properties of tea biocompounds. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Multivariate statistical optimization of phenolics and antioxidants from nutmeg seeds (Myristica fragrans Houtt)
The present study aimed to optimize the phenolic and antioxidant-rich extract from the nutmeg (Myristica fragrans Houtt) by using a two-factor 26-run central composite design-based response surface methodology tool. The selected parameters were extraction period (2 to 5days), solvent-to-water ratio (v/v) (50100%), and type of solvent (acetone or ethanol). The optimized extract at conditions of 3.14days incubation and 68% (v/v) acetone showed total phenolic content (TPC), total flavonoid content (TFC), and DPPH antioxidant assay as 376.38mg GAE/g DW, 34.40mg QUE/g DW and 842.46mg AAE/g DW, respectively. Among the nineteen (19) compounds identified by the LCMS, myristicin (37.74%) was found to be the highest. Nine (9) alkane-fatty acyl compounds were determined by the GCMS analysis, as well. Additionally, SEM and XRD revealed sheet-like anatomy with the presence of Carbon (C), Oxygen (O) and Potassium (K). The study presented a unique approach to optimizing phenolic-rich antioxidant extracts from nutmeg using response surface methodology, offering valuable insights for more efficient extraction of bioactive compounds with minimal resource waste and potentially enhancing the utilization of nutmeg's nutraceutical properties. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
On the zero forcing number of graphs and their splitting graphs
In [10], the notion of the splitting graph of a graph was introduced. In this paper we compute the zero forcing number of the splitting graph of a graph and also obtain some bounds besides finding the exact value of this parameter. We prove for any connected graph ? of order n ? 2, Z[S(?)] ? 2Z(?) and also obtain many classes of graph in which Z[S(?)] = 2Z(?). Further, we show some classes of graphs in which Z[S(?)] < 2Z(?). Journal Algebra and Discrete Mathematics. -
Disproportionate impact of climate change: Housing crisis and displacement among the transgender community in India
India is a nation that is threatened by climate change. Climate change and the housing crisis are inextricably linked, they are associated with exacerbated mental and physical health conditions. It often affects individuals differently based on various factors shaped by social norms. So, marginalized sections like transgender persons are disproportionately affected. Individuals with inadequate housing are significantly affected by natural disasters. However, most transgender individuals cannot rent due to a lack of documents and unemployment. Thus, housing is an essential social determinant of physical and mental health. The book chapter discusses the various intersecting identities and the geographical and ecological contexts. The current revised climate laws in India have emphasized incorporating gender but there is a need to focus on gender beyond the binary to formulate more sensitive and equitable methods to address climate change. It also discusses the psycho-social impact on the community and the unique challenges they face as extreme weather events increase. 2024, IGI Global. All rights reserved. -
Semantic image annotation using convolutional neural network and WordNet ontology
Images are a major source of content on the web. The increase in mobile phones and digital cameras have led to huge amount of non-textual data being generated which is mostly images. Accurate annotation is critical for efficient image search and retrieval. Semantic image annotation refers to adding meaningful meta-data to an image which can be used to infer additional knowledge from an image. It enables users to perform complex queries and retrieve accurate image results. This paper proposes an image annotation technique that uses deep learning and semantic labeling. A convolutional neural network is used to classify images and the predicted class labels are mapped to semantic concepts. The results shows that combining semantic class labeling with image classification can help in polishing the results and finding common concepts and themes. 2018 Jaison Saji Chacko, Tulasi B. -
MoS2-TiO2 Nanocomposites for Enhanced Photo-electrocatalytic Hydrogen Evolution
The investigation on the designing and fabrication of highly efficient electrocatalysts for hydrogen evolution reaction (HER) is critical for future applications in renewable sustainable energy. The present work reports the hydrothermal synthesis of two-dimensional MoS2 and MoS2-TiO2 nanostructures. The as-prepared nanostructures were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Raman analysis, UV-vis-NIR, and photoluminescence spectrophotometry and vibrating sample magnetometer (VSM). Systematic electrochemical measurements for HER were performed and MoS2-TiO2 nanocomposites demonstrated the lowest onset potential in comparison with MoS2. The results suggest that the nanofusion interface between MoS2 nanoflakes and TiO2 nanoparticles induced an efficient charge transfer from the conduction band of MoS2 to TiO2 and favored the reduction of H+ at active sites. We believe the present work can open up new possibilities that would provide deep insights for the rational design of 2D materials-based catalysts for energy storage and conversion applications. 2023 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. -
Synthesis, Structure, and Physical Properties of Bulk MoS2
With the discovery of graphene by Novoselov and Geim in 2004, two-dimensional (2D) materials have been extensively researched due to their bizarre promise in the fields of electronics, optics, medical, mechanics, energy conversion, and storage. Especially, 2D-layered materials consisting of atomic sheets stacked together by weak van der Waal forces have received intriguing research interest in recent years. Cutting-edge 2D materials being investigated by researchers include 2D oxides (V2O5, MoO3, LixCoO2), topological insulators (Bi2Se3, Bi2Te3, HfBr), nitrides (h-BN, MoN, Ti4N3Tx, W2N, V2N), carbides (Ti3C2, Ta4AlC3), and transition-metal dichalcogenides (MoS2, WS2). Research has proved that these materials could counterpart graphene in a variety of fields and applications. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Recent development on self-powered and portable electrochemical sensors: 2D materials perspective
Electrochemical sensors have attracted tremendous research interest due to their simplicity and compatibility to be integrated with standard electronic technologies and capability to produce electrical signals that can be effectively acquired, processed, stored, and analyzed. Due to the incredible electronic and physical properties derived from the 2D structure, two dimensional (2D) nanomaterials such as graphene, phosphorene black phosphorus, transition metal dichalcogenides (TMDCs), and others have proven to be attractive for the fabrication of high-performance electrochemical sensors. The book chapter is focused in the unique characteristics of 2D materials leading toward excellent sensing performance, the structural and molecular designing of various 2D materials, structure-property relationships, various sensing applications employing disparate 2D nanostructures with an emphasis on highlighting various prototypical and prominent research paths. 2023 Elsevier Inc. All rights reserved. -
MoS2, a new perspective beyond graphene
Owing to the fascinating structural, optical, electrical, chemical properties, graphene has created new paradigm in the field of nanoscience and the common crystalline structures that can be exfoliated include the layered van der Waals (vdW) solids such as boron nitride, transition metal dichalcogenides (TMDCs), black phosphorus, and the layered ionic solids. Here, we bring forth the state-of-art-of materials dominated by their two-dimensional (2D) geometry beyond graphene. Being one of the most well-studied families of vdW layered materials, molybdenum disulphide (MoS2) belonging to TMDC family has gained considerable research interest. The present work is focused on attempts to optimize and characterize this material with unique properties for a host of applications. The work resolves the hydrothermal growth of hexagonal MoS2 nanoflakes with attracting optical and magnetic properties providing strong evidence for the spin orbit split valence bands of these nanostructures. The enhanced electrocatalytic activity, excitation wavelength dependent down-conversion and up-conversion photoluminescence, growth of structural polymorphs using simple hydrothermal method, and the efficient anticancer properties of MoS2 nanostructures providing greater insight into energy and biomedical applications are also discussed. The improved catalytic activity of MoS2-based nanostructures reveals the increasing number of accessible active sites, formation of large surface area and is greatly beneficial for accomplishing a clean, environmental-friendly, inexpensive hydrogen mission for energy storage and conversion applications. The synergistic effect of the MoS2 nanocomposites was able to impede angiogenesis, tumor growth, and epithelial to mesenchymal transition, elucidating the anticancer efficacy. Understanding and exploiting such unique properties of these 2D materials paves new horizons toward novel technological advances in electronic and medical field. 2021 Elsevier Inc. All rights reserved. -
Estimation of state of charge considering impact of vibrations on traction battery pack
Interest towards electric vehicle adoption is on the rise due to the lower running and maintenance cost it offers, along with zero tailpipe emissions. Range anxiety is one of the only concern that affects the adoption of electric vehicles. The state of charge of the traction battery pack has to be accurately determined and provided to the user to avoid range anxiety. Minute battery parameters has to be considered to improve the accuracy of the state of charge determination. In order to overcome the problem of range anxiety, an innovative strategy that takes into account how vibrations affect the performance of EV batteries is developed in this research. By doing this, the state of charge estimation precision is improved and thereby raises the drivers faith in electric vehicles. The impacts and vibrations felt on the traction battery pack during driving would lead to heat generation. The heat generated is found to be highest when the vibrations resonate at the natural frequencies of the traction battery pack. The natural frequency of the battery pack is considered when the battery is kept in the battery chamber of the two-wheeler electric vehicle. The vibrations at natural frequency produces heat which is accounted for when the state of charge is determined. To obtain accurate state of charge estimation, a Kalman filter-based approach is used. The Kalman filter-based estimation uses the conventional methods which are the open circuit voltage method and the Coulomb counting method to improve the estimation process along with the consideration of the heat component due to vibrations and impact. The vibration analysis is performed using MATLAB, while the state of charge determination is implemented in hardware and the Kalman estimation done using Python. The system is modelled on an electric two-wheeler platform and the testing is done to compare the state of charge accuracy of the open circuit voltage method, the Coulomb counting method and the Kalman filter-based estimation approach. The inclusion of the vibrational heat analysis for State of Charge estimation in the hardware testing of the electric two-wheeler provides an accurate state of charge value. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
On-board intelligent energy management system for gridable electric vehicles and a method thereof /
Patent Number: 202141037003, Applicant: Parag Jose Chacko.
The idea proposed is an Intelligent Energy Management System (1EMS) which will be on board a Gridable Electric Vehicle (GEV) for enabling Grid Integration to facilitate Grid to Vehicle (G2V), Vehicle to Grid (G2V) and Vehicle to Vehicle (V2V) active power flow. Gridable Electric Vehicles are vehicles coming under the category of Plug-in Hybrid Electric Vehicles (PHEV) and Battery operated Electric Vehicles (BEV). The interest towards alternate transportation is increasing due to the increasing fuel prices and the increased air pollution.