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Establishing the effectiveness of intervention module on positive youth development among adolescent in India
Purpose: Positive Youth Development (PYD) originated in the west as a pragmatic approach to teaching youth skills and attributes to develop into healthy, productive, and engaged adults. This approach proposes that youth with more developmental resources experience increased academic success, better economic prospects, are more civically engaged, and experience optimal well-being and functioning in the long term. Over time, the need for administering evidence-based interventions was felt by practitioners, researchers, and policymakers. With this background and the absence of research in PYD in India, the present research was carried out to develop and test an intervention module for its effectiveness in bringing about a positive change among youth. Approach: The present research is quantitative in nature with pre-test post-test control group design. The PYD intervention program included activities, non-profit visits, community building exercises, and mentoring programs, creating self-actualizing youth. The paper deliberates on the findings of a six-month interventional program based on the Six Cs model of Learner (2005). Findings: The independent sample t-test was significant, for overall PYD, t (98) = 3.45, p <. 001. and on all the dimensions of PYD, indicating that intervention was effective as there are statistically significant differences among experimental and control groups. Value: The intervention was experientially positive for the students, valued, and commended by the school authorities. The paper recommends enhancing psychological intervention research in school settings, including multiple approaches to address holistic student development, facilitating peer relationships and mentoring, developing resources, and enhancing growth opportunities. 2021 RESTORATIVE JUSTICE FOR ALL. -
Cipher Block Chaining Support Vector Machine for Secured Decentralized Cloud Enabled Intelligent IoT Architecture
The growth of internet era leads to a major transformation in a storage of data and accessing the applications. One such new trend that promises the endurance is the Cloud computing. Computing resources offered by the Cloud includes the servers, networks, storage, and applications, all as services. With the advent of Cloud, a single application is delivered as a metered service to numerous users, via an Application Programming Interface (API) accessible over the network. The services offered via the Cloud are such as the infrastructure, software, platform, database and web services. The main motivation of this application model is to provide computationally secure key generation to protect the data via encryption. This key generation in the cryptography process falls into three categories in this research work. In the first part, SVM based encryption service model is constructed for which the key generation is from the conventional encryption operation mode with some improvements. To make the process more complex, the optimization techniques are taken into account for the key generation in descendant two methods application model that acts computationally more secure specifically for Cloud environment. The results of security analysis confirm the effectiveness of the proposed application model withstands potentially against various attacks such as Chosen Cipher Attack, Chosen Plain text Attack indistinguishable attacks for files. In case of images, it resists well against statistical and differential attacks. Comparative Analysis shows evidence of the efficiency of the developed pioneering application model quality and strength compared with that of the existing services. 2013 IEEE. -
A comparative study on the effect of HNT and nano-alumina particles on the mechanical properties of vacuum bag moulded glass-epoxy nanocomposites
In the present work, the mechanical properties of the Halloysite nanotube (HNT) and Nano-Alumina particle additions in glass-epoxy nanocomposites are investigated experimentally. The composite specimens for tensile, flexural, interlaminar shear strength (ILSS) and impact tests are prepared by vacuum bag moulding process and tested in accordance with the ASTM standards. HNT/Nano-Alumina particle contents are varied from 0 to 4 wt. %, while the weight fraction of glass fiber is kept constant at 60%. The strength values of the respective tests are obtained and compared graphically to study the effect of nanoparticle type and content on the mechanical properties. From the experimentation and subsequent result analysis, considerable improvements in the mechanical properties are observed with the addition of nanoparticles as compared to neat composites. The 3 wt.% addition of HNT in the nanocomposites resulted in increase in tensile strength, elastic modulus, flexural strength, flexural modulus, ILSS and impact energy values by 12.7%, 6.96%, 5.46%, 4.49%, 7.44% and 119.3% respectively in comparison with the same weight percentage of Nano-Alumina. HNT modified composites reveal an improvement in mechanical properties, hence qualifying it as a most promising cost-effective reinforcing filler for glass-epoxy composites. Further, the SEM micrographs of fractured surfaces are analyzed to study the failure mechanisms and fracture morphologies of higher loaded composites (4 wt.%) and understand the reason for decline in mechanical properties. 2021 Published by Semnan University Press. All rights reserved. -
A hybrid level set based approach for surface water delineation using landsat-8 multispectral images
The detection and delineation of surface water is a crucial step in change detection studies on water bodies using satellite images. Single band methods, spectral index methods, classification using machine learning and spectral un-mixing methods are the widely used strategies for surface water mapping from multi-spectral images. Level set theory based algorithms have been successfully employed in image segmentation problems and are proven to be effective. This study presents a hybrid level set theory based segmentation algorithm which is a combination of edge based and region based approaches to detect and delineate surface water bodies in Landsat 8 images. Level set algorithms were applied in combination with Modified Normalized Difference Water Index (MNDWI) to further improve the delineation accuracy. Robustness of the proposed approach was established by successfully applying the algorithm to delineate water bodies of different sizes, ranging from 0.5 km2 to 298 km2 in surface area. The proposed algorithm was also compared with established machine learning based delineation methods and found to be faster than the algorithms those produced comparable delineation outputs. As the ground truth was not available for accuracy measurement, the output image of the proposed method was compared with the outputs of the machine learning algorithms using Pearsons correlation co-efficient, Structural Similarity Index (SSIM) and Dice Similarity Index. The proposed algorithm was subsequently applied to multi-temporal Landsat data for water body change detection and analysis. 2021, International Association of Engineers. All rights reserved. -
Theorizing race, marginalization, and language in the digital media
Digitization of the communication medium has transformed the mute, marginalized audience into a heterogeneous and credible content producer. Drawing on this dynamics and operation of the digital media, it has urged the need to re-theorize marginalization and race. Hence, this paper critiques the digital-media tool, blogs, using a rhetoric-textual analysis method and critical discourse analysis method for the fictional text, Americanah. These methods employ the psychoanalyticalAlthusserian critique of Adichies fictional narrative, Americanah. In the psychoanalytical sense, blog-writing can qualify as a mechanism of sublimation in the post-modern world. In the Althusserian sense, blogs become persuasive mechanisms for a subjects interpellation into non-dominant ideology. Among the plethora of marginalized global communities, African-Americans are enormously embracing the virtual communication trends for socio-political motives. This paper theorizes the correlations between race-related blogging, psychoanalytic sublimation, and the socio-political repudiation of power structure by employing the literary text as material evidence. Accordingly, the literary study has concluded that digital-mediums (i.e., in this case, political blogs) can depose the power vested in the ideologicalstate-apparatuses and impose a high potential for expression of unrestrained, credible, and democratic voice of the marginalized. It also validates that blogs/blogging influences and moulds national/political/racial discourses by lending a liberated voice and context-independent perspective to the racially oppressed. 2021 Communication & Society. -
Probiotic properties of bacillus subtilis isolated from dried anchovies (Stolephorus indicus) and evaluating its antimicrobial, antibiofilm and growth-enhancing potential in danio rerio
The study was aimed at isolating and characterising a potential probiotic bacterium from dried anchovies (Stolephorus indicus) and evaluating its antibacterial, antibiofilm and growth enhancing potential in Danio rerio. The isolate was identified as Bacillus subtilis using 16S rRNA sequencing and phylogenetic analysis. Probiotic properties were characterised based on the ability of the isolated strain to survive in simulated gastric juice and trypsin. Isolated strain was further subjected to varying pH, temperature, different concentrations of organic solvents to evaluate its potential to tolerate stress. Biofilm inhibition against Vibrio harveyi (31.54.6%), Escherichia coli (28.84.2 %), Pseu-domonas aeruginosa (34.83.1%) and Staphylococcus aureus (34.43.75%) was noted. The study showed that the isolate improved the survival rate of Danio rerio against Vibrio harveyi and Escherichia coli. The weight (12.770.06) and length (11.4130.18) gain percentage was numerically (p> 0.05) improved in probiotic supplemented groups as compared to control. The use of probiotics from non-conventional sources can improve the diversity of the available probiotics for aquaculture practices. 2021 Ali L et al. -
Psychological Problems Among Children Three Years After the Earthquake in Nepal
Background: Frequent disasters and weak mental health system pose a risk to psychological health in Nepal. In 2015, a massive earthquake of 7.6 magnitude occurred in Nepal, which caused large scale destruction to human life and property. Limited research in children after disasters in Nepal prevent health professionals from implementing new evidence-based trauma treatments. Aim: The study aimed to identify the long term emotional problems experienced by earthquake-affected children in Nepal. The role of gender, severity of exposure, socioeconomic status and type of family in relation to emotional problems were also examined in the selected group. Methods: A purposive sampling was used to select 454 children (4th and 5th standard) from two highly affected wards in Kathmandu Metropolitan City. Information about exposure to the earthquake was collected from children using the Level of Exposure Scale while the parents completed the Nepali version of the Strengths and Difficulties Questionnaire (SDQ/ 4-17). Results: The effect of exposure to the earthquake was identified in the children even after three years. Boys had higher conduct, hyperactivity-inattention and peer problems while girls had high pro-social behaviour. Emotional problems were greater for those belonging to a lower socio-economic status. Among the variables, gender was a better predictor of emotional problems in earthquake-affected children. Conclusions: Emotional problems such as conduct problems, hyperactivity-inattention, peer problems are present in the earthquake-affected children in Kathmandu. Future researchers and clinicians need to monitor the children affected by the earthquake to recognise vulnerable groups and implement appropriate trauma-focused interventions. 2021, Indian Association for Child and Adolescent Mental Health. All rights reserved. -
Engagement Detection through Facial Emotional Recognition Using a Shallow Residual Convolutional Neural Networks
Online teaching and learning has recently turned out to be the order of the day, where majority of the learners undergo courses and trainings over the new environment. Learning through these platforms have created a requirement to understand if the learner is interested or not. Detecting engagement of the learners have sought increased attention to create learner centric models that can enhance the teaching and learning experience. The learner will over a period of time in the platform, tend to expose various emotions like engaged, bored, frustrated, confused, angry and other cues that can be classified as engaged or disengaged. This paper proposes in creating a Convolutional Neural Network (CNN) and enabling it with residual connections that can enhance the learning rate of the network and improve the classification on three Indian datasets that predominantly work on classroom engagement models. The proposed network performs well due to introduction of Residual learning that carries additional learning from the previous batch of layers into the next batch, Optimized Hyper Parametric (OHP) setting, increased dimensions of images for higher data abstraction and reduction of vanishing gradient problems resulting in managing overfitting issues. The Residual network introduced, consists of a shallow depth of 50 layers which has significantly produced an accuracy of 91.3% on ISED & iSAFE data while it achieves a 93.4% accuracy on the Daisee dataset. The average accuracy achieved by the classification network is 0.825 according to Cohens Kappa measure. 2020, Intelligent Engineering & System. All rights reserved. -
A Deep Learning Model for Information Loss Prevention from Multi-Page Digital Documents
World Wide Web has redefined almost all the business models in the past twenty-five to thirty years. IoT, Big Data, AI are some of the comparatively recent technologies which brought in a revolution in the digitization and management of data. Along with the revolution arose the need for data security and consumer privacy protection, primarily concerning financial institutions. The data breach of Equifax in 2017 and personal information leaks from Facebook in 2021 led to general skepticism among the customers of large corporations. The GLBA, 1999, also known as the Financial Modernization Act, was implemented by US federal law to enforce the financial institutions to protect their private information. Built upon the GLBA, guidelines are paved by FTC for all financial institutions of the United States of America, including TI companies. In this paper, an ANN-based content classification technique using MLP architecture in combination with n-gram TF-IDF feature descriptor is proposed to detect and protect the customers' sensitive information of a reputed TI company securing it's one of the digital image-document stores. The proposed technique is compared with other state-of-the-art strategies. Data samples from the digital document store of the company have been taken into consideration in the study, and the prediction accuracy metrics obtained are found to be substantially better and within the acceptable range defined by the organization's information security monitoring team. 2013 IEEE. -
Hierarchically nanostructured ZnO with enhanced photocatalytic activity
Hierarchical nanostructures of ZnO are integrated architectures comprising well-ordered nanoscale subunits and excellent photocatalytic properties. In this study, synthesis of ZnO nanoparticles using methods such as co-precipitation, hydrothermal, thermal decomposition, and electrochemical precipitation yielded microsphere, nanorod, pyramid, and nanopetal-like morphologies, respectively. The catalysts obtained were characterized using XRD, IR, SEM-EDX, UVDRS, TGA, PL, and Zeta potential analysis. The XRD spectra confirmed that all the different morphologies of ZnO have hexagonal wurtzite structures The photocatalytic activity of these nanostructures was determined using a dye degradation study on a model pollutant Methylene Blue (MB) under simulated visible light. The kinetic study of the dye degradation reveals that it obeys pseudo-first-order kinetics with a maximum rate constant of 0.01503 min-1. The nanorod structured ZnO particles prepared by the hydrothermal method showed the best catalytic activity. 2021 The Electrochemical Society ("ECS"). Published on behalf of ECS by IOP Publishing Limited. -
Mindfulness: An emotional aid to the glass ceiling experiences
We have progressed to a phase where there is very little difference between men and women, but the reality in many countries is that women are looked down as the inferior gender and not given career opportunities to explore. They are not let into the decision-making roles at the organization even when they have an equal qualification, experience and skill. They are placed low in the hierarchy which allows them to witness the functions at the higher level of the organization but restricts them from participating in them. There are a lot of factors like cultural, socio-demographic factors and society itself that influence this disparity in the organization. These contributory factors create the glass ceiling phenomenon at the workplace, thereby generating emotional and psychological imbalances in women employees. This is a conceptual paper aiming to explore the concept and impact of mindfulness, and various concepts of mindfulness could be used as an emotional aid to treat the psychological effects of the glass ceiling. It further explains some of the mindful concepts like mindful walking, mindful life and mindfulness-based stress reduction technique in treating some of the psychological and emotional issues like depression, anxiety, frustration, traumatic experiences, adjustment issues, addiction, stress, low self-esteem, low self-confidence and aggression. It also elucidates adopting mindfulness techniques in real organizational scenarios where women are constantly discriminated because of their gender and opportunities are taken away. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
A Novel Threshold based Method for Vessel Intensity Detection and Extraction from Retinal Images
Retinal vessel segmentation is an active research area in medical image processing. Several research outcomes on retinal vessel segmentation have emerged in recent years. Each method has its own pros and cons, either in the vessel detection stage or in its extraction. Based on a detailed empirical investigation, a novel retinal vessel extraction architecture is proposed, which makes use of a couple of existing algorithms. In the proposed algorithm, vessel detection is carried out using a cumulative distribution function-based thresholding scheme. The resultant vessel intensities are extracted based on the hysteresis thresholding scheme. Experiments are carried out with retinal images from DRIVE and STARE databases. The results in terms of Sensitivity, Specificity, and Accuracy are compared with five standard methods. The proposed method outperforms all methods in terms of Sensitivity and Accuracy for the DRIVE data set, whereas for STARE, the performance is comparable with the best method. 2021. All Rights Reserved. -
Integrated Home-Based Palliative Care in Motor Neuron Disease: A Case Report from Low- Middle Income Country
In many international care guidelines, multidisciplinary palliative care forms a key to optimum management in Motor Neuron Disease (MND). We describe the home-based palliative care interventions for a client with MND and his family from a Low and Middle-income country context. This report also discusses the advantages and challenges of the same with suggestions for sustaining the quality of care for neuro palliative conditions. 2021 Taylor & Francis Group, LLC. -
Optimization of Biodiesel Production from Waste Cooking Oil by Box Behnken Design Using Response Surface Methodology
Interest in Biodiesel production has grown over the years due to concerns related to the environment, and the solutions include deriving energy from waste as the replacement for diesel, a petroleum-derived fuel. Biodiesel has been accepted as a "green fuel" as it is a renewable, non-toxic, safe and biodegradable energy material. The utilisation of waste cooking oil (WCO) by converting it into biodiesel is one of the promising alternatives to diesel. An attempt to optimise the biodiesel production from WCO (a waste material) has been made via this study. The process adopted was Trans-esterification of pretreated WCO, and the optimization of biodiesel production was carried out by Box-Behnken method using a response surface methodology. The variations between the analytical and experimental results were within acceptable limits. The response surface methodology resulted in an optimum yield of 96.88% (analytical), which was validated through an experiment within an acceptable error of 0.58%. 2021,International Journal Of Renewable Energy Research.All rights reserved. -
Has Indias Employment Guarantee Program Achieved Intended Targets?
This paper explores the performance of the worlds largest employment guarantee program, the Mahatma Gandhi National Rural Employment Guarantee Schemes in India, both nationally and through a sub-national-level comparison based on key performance indicators viz. (i) financial indicators, (ii) physical performance indicators, and (iii) inclusiveness indicators. The paper is based on administrative data taken from the Ministry of Rural Development from 2006 to 2019. Despite sharp increases in fund allocation, total expenditures, and utilization rates, there was deceleration in majority of physical performance indicators after 2016, including total person-days employment and person-days of employment per household, with wide variation in sub-national level implementation capabilities. The finding also rejects the falsity of saturation of MGNREGA work in the rural areas, which is reflected in a strong positive correlation between fund allocation and employment generation. Its broader objective of social safety net for vulnerable people in rural areas shows an achievement, although with some gaps in implementation. JEL classification: H53, J43, P25 The Author(s) 2021. -
Nexus Between Interest Rate Risk and Economic Value of Equity of Banks
This analytical study looks to provide recommendations to the banking sector on different policies and regulations by examining certain aspects of the Basel III accord, which was designed to manage specific operational, capital and market risks of banks. A review of extant literature reveals that only a few papers have been written on simulation-based approaches, using basis and re-pricing risks. We look to connect this as a source while attempting to define and measure the impact of interest rate risk (IRR) on the economic value of equity (EVE) of banks. We propose to use the driverdriven method, wherein interest rate shocks are derived through prime lending rate (PLR) for the period of 20162019 in the context of India. Monte Carlo Simulation and OLS regression was performed to predict the IRR; Granger causality was used to examine the cause and effect relationship; the impulse response function (IRF) was used for sensitivity analysis; and the vector error correction model (VECM) technique was used for co-integrating relationships. Notably, the EVE movement caused due to shocks in interest rates had to be traced as it envisages probable EVE losses. Importantly, our study is among the first few to show the relationship between IRR and EVE of banks, especially after the deregulation of Indian banking sector. 2021 International Management Institute, New Delhi. -
An empirical analysis of ICT tools with gamification for the Indian school education system
Information and communication technologies (ICTs) are used as a part of different fields, for example, training, business, and healthcare. The main objective of this paper is to introduce ICT as a better method to teach and test student's performance so it can become a part of the school curriculum and enhance learner's experience. To accomplish this objective, multiple kinds of literature were studied to get insights into the factors associated with ICT and gamification. Based on the findings, a survey was conducted on teachers to know the favourability of ICT in modern schools. Based on the response, two application prototypes are developed for students to get their performance and results that support the study. Most importantly, similar concepts were taught to students using both, traditional and ICT based approaches. A test was conducted via both methods. It was discovered that the performance of the students increased by 13% when the modern approach was followed to conduct the test. Copyright 2021 Inderscience Enterprises Ltd. -
A Novel Approach for Linguistic Steganography Evaluation Based on Artificial Neural Networks
Increasing prevalence and simplicity of using Artificial Intelligence (AI) techniques, Steganography is shifting from conventional model building to AI model building. AI enables computers to learn from their mistakes, adapt to emerging inputs, and carry out human-like activities. Traditional Linguistic Steganographic approaches lack automation, analysis of Cover text and hidden text volume and accuracy. A formal methodology is used in only a few Steganographic approaches. In the vast majority of situations, traditional approaches fail to survive third-party vulnerability. This study looks at evaluation of an AI-based statistical language model for text Steganography. Since the advent of Natural Language Processing (NLP) into the research field, linguistic Steganography has superseded other types of Steganography. This paper proposes the positive aspects of NLP-based Markov chain model for an auto-generative cover text. The embedding rate, volume, and other attributes of Recurrent Neural Networks (RNN) Steganographic schemes are contrasted in this article between RNN-Stega and RNN-generated Lyrics, two RNN methods. Here the RNN model follows Long Short Term Memory (LSTM) neural network. The paper also includes a case study on Artificial Intelligence and Information Security, which discusses history, applications, AI challenges, and how AI can help with security threats and vulnerabilities. The final portion is dedicated to the study's shortcomings, which may be the subject of future research. 2013 IEEE. -
An IoT-based tracking application to monitor goods carrying vehicle for public distribution system in India
Designing a secured transportation system to handover food items to various fair price shops is one of the objectives of smart city development in India. In this paper, an IoT-based tracking solution for moving goods carrying vehicle is proposed. A hardware prototype model is developed using different sensors with GPS/GPRS tracking module and is attached to the vehicle. An alarm is raised to make decision in case of trouble or malfunction. The data generated by the model during the movement of vehicle is encrypted using RSA algorithm and sent to cloud for monitoring by an application developed using PHP and analysis using MapReduce programming model. Experiments are conducted to study the feasibility of the developed model during deployment. From the experiment it is observed that, the developed hardware model and the application meet the objective of monitoring vehicle, safer recovery in case of malfunction and secured delivery of items. Copyright 2021 Inderscience Enterprises Ltd. -
A collaborative defense protocol against collaborative attacks in wireless mesh networks
Wireless mesh network is an evolving next generation multi-hop broadband wireless technology. Collaborative attacks are more severe at the transport layer of such networks where the transmission control protocol's three-way handshake process is affected with the intention to bring the network down by denying its services. In this paper, we propose a novel collaborative defense protocol (CDP) which uses a handshake-based verification process and a collaborative flood detection and reaction process to effectively carry out the defense. This protocol presents a group of monitors that collaboratively entail in defending the attack; thus reduces the burden on a single monitor. Moreover, this paper proposes a novel transport layer post-connection flooding attack that occurs after establishing a TCP connection and we show that CDP can detect and mitigate this attack. The CDP protocol has been implemented in Java and its performance has been evaluated using essential metrics. We show that CDP is efficient and reliable and it can identify the attack before any major damage has occurred. Copyright 2021 Inderscience Enterprises Ltd.