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A microstructure exploration and compressive strength determination of red mud bricks prepared using industrial wastes
The consensual view among researchers concerning building with industrial by-products is that the utilization of by-products represents green technology and sustainable development. The current investigation focuses on the utilization of an assortment of by-products for the production of bricks. The by-products include Red Mud (RM), Fly ash (FA), and Ground Granulated Blast Furnace Slag (GGBS) combined in different proportions with lime. The Red Mud employed ranged from 100% to 60% with a decrement of 10%, whereas Fly ash and GGBS varied between10% and 40% with an increment of 10%. Bricks produced from two methods namely, ambient curing and firing methods, were tested as per IS standards/ASTM norms, on both the materials and the composites of bricks. XRD, XRF, and SEM focused on both the raw materials and the composites. Because geopolymer materials are partially amorphous materials with complex composition, understanding the structural characteristics of geopolymers is opined as intricate. The results of the investigation show that the compressive strength of the bricks increased with the increment in the percentage of Fly ash and GGBS. The compressive strength of Red Mud-GGBS fired bricks attained maximum strength of 7.56 MPa. 2021 Elsevier Ltd. All rights reserved. -
A mini review on recent advancements in inclined solar still
Water shortage is a global problem, and the demand for fresh water is growing at an ever-increasing rate. The only method to meet the demand for water is via water filtration. Water purification may be done in a variety of methods, including cleaning saltwater or holding rainfall and then releasing it into the environment. There are still several kinds of solar still are available, which may be utilized to improve the amount of water that is generated. The inclined solar still (ISS) is a particularly successful option because it has a large outer water surface to supplement the normal potable water production, as well as because it has a shallow depth of water to increase the overall efficacy of the inclined solar still. Increasing the water's surface area has been the subject of much investigation. As a result of this study, an evaluation was conducted on the present state of various ISS designs in order to make advanced adjustments and research to increase the productivity of the ISS in order to meet the rising need for potable water. According to this analysis, active ISS and hybrid ISS are shown to be the most successful ISS methods. 2022 The Author(s) -
A Mini Review on the Multicomponent Synthesis of Pyridine Derivatives
Multicomponent reactions (MCRs) have emerged as key green tool in organic synthesis for their methodological simplicity. MCRs have made heterocycle synthesis more versatile. The most crucial molecule among the most often used heterocycles is pyridine, which is widely used in biological, industrial, and pharmaceutical sectors. In light of this, our mini-review highlights the literature on substituted pyridine synthesis published from the year 2016 to early 2022 via multicomponent approach. 2022 Wiley-VCH GmbH. -
A miniaturized antenna array for direct air-to-ground communication of aircrafts
In this paper, a miniaturized, high directivity low-cost antenna array is presented. The uniqueness of the proposed array (PA) exists in the feed mechanism designed using Dolph-Chebyshev non-uniform excitations. Authors simulated the designed antenna array using ANSYS EM 18.2 (HFSS) software and characterization is carried out in a fully established anechoic chamber. The simulated array antenna is operating at 2.4 GHz with a gain of 8.12 dB and a reflection coefficient of -28.45 dB having a bandwidth of 110 MHz. On contrast with the traditional array (TA), PA exhibits enhanced resonance characteristics by maintaining the same radiation characteristics. The bandwidth is increased by 37.5%, maintaining the same gain of 8.12 dB. In contrast, there is a remarkable reduction in the size compared to the traditional corporate feed array antenna with non-uniform excitation. The overall size of the PA antenna is 242.5 mm 58.8 mm, which is 33.73% less compared to the TA. Published under licence by IOP Publishing Ltd. -
A Mixed methods study of psyhosocial factors in career decision making in adolescents
Career choice is an important developmental task in adolescence and is influenced by many factors. Using a mixed methods research design, this study aimed to understand career decision making and factors influencing the same in adolescents. In the quantitative phase the relationship between career maturity and perceived parenting style, personality traits, metacognition, socio- economic status, gender, college type, stream of study and decision status was studied in students studying in II Year Pre- University in Bangalore, India. Career decisions, personal and family factors in career decision making were explored in the qualitative phase. Informed consent was obtained from the participants and parents of the participants of the study. newlineQuantitative data was collected from 548 students studying in Arts, Science and Commerce stream in second year Pre- University in Bangalore. Students from eight private and seven government colleges were recruited for the study. Quantitative data was collected using a socio- demographic data sheet, Career Maturity Inventory, Parental Authority Questionnaire, Neo Five Factor Inventory and Metacognitive Awareness Inventory. The scales were translated to Kannada and back translated. In the qualitative phase, data was collected through a semi- structured interview schedule designed for this study. 30 students who were a part of the quantitative phase took part in this phase. The interviews were audio-recorded and transcribed for analysis. Statistical analysis was done to analyze quantitative data. Descriptive statistics, correlation, regression analysis, t tests and one-way ANOVA was done. Qualitative data was analyzed by template analysis and themes were derived from the data. The results revealed associations between personality traits neuroticism, openness and conscientiousness and specific aspects of career maturity attitude and competence. -
A mixed methods study on factors associated with relapse of alcohol use disorder
Background: Alcohol use disorder (AUD) is one of the most concerning mental health issues in India. According to the recent survey, Magnitude of Substance Use in India, 2019, 160 million of the countrys population consumes alcohol. About 35.6% are problem drinkers among those who drink, of which 18% are alcohol dependent. Despite the greater understanding of alcohol use disorder (AUD) and the scientific advancements in treatment, relapse remains to be the main challenge in managing AUD. This study aimed at investigating various factors associated with relapse of AUD and presenting an in-depth understanding of it. Methods: A Sequential Explanatory Mixed Methods design was used. In the quantitative phase, 72 relapsed individuals with AUD currently undergoing treatment were compared with 72 individuals previously treated for AUD who maintain total abstinence for a minimum period of one year. Relapsed participants were selected from three private de-addiction centers in Bangalore and abstaining participants were recruited from various Alcoholics Anonymous meetings in Bangalore. The relapsed and sober groups were matched on gender, AUD diagnosis, and previous inpatient alcohol de-addiction treatment. Cloninger's Temperament and Character Inventory-Revised was used to assess the personality profiles of the participants. A sociodemographic and clinical information form was also used to collect data. Six participants were selected purposively from the same sample for in-depth interviews. Data analysis was conducted using SPSS and NVivo for quantitative and qualitative data, respectively. The study protocol was approved by the institutional ethics committee. Results: Bivariate analyses showed a significant difference in Novelty Seeking, Persistence, Self-Directedness, and Self-Transcendence traits between the relapsed and sober participants. Results also suggested that reported use of other substances, post- discharge follow-ups, and living with drinking or drug-using individuals are significantly associated with relapse. Logistic regression displayed incomplete treatment, use of other substances, and no post-discharge follow-up as predictors of relapse. The qualitative thematic analysis revealed preparedness, motivation, personal exceptionalism, meaning and purpose, and social and interpersonal as the main relapse-related themes. Conclusions: The findings highlight the importance of treatment engagement, discharge planning, aftercare, and special attention to those presenting with multiple substance use. It also displays a few culture-specific aspects to be considered during treatment, such as preparing the individuals entering treatment to effectively engage, assessing and working with their motivation, and addressing the relationship dynamics. -
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A Mixed-Methods Study of Training in Evidence-Based Practice in Psychology Among Students, Faculty, and Practitioners in India and the United States
The current mixed-method study in India and the United States assessed understanding of what evidencebased practice in psychology (EBPP) is, how EBPP training and implementation occurs, and perceived barriers and needs related to EBPP training. Graduate students (India, n = 282; United States, n = 214), faculty (India, n = 24; United States, n = 67), and practitioners (India, n = 24; United States, n = 49) were surveyed, and focus groups with students (India, n = 31; United States, n = 12), faculty (India, n = 10, United States, n = 9), and practitioners (India, n = 28; United States, n = 17) were held. Individuals across countries and across the professional continuum were only somewhat aware of EBPP, largely equating it to just using empirically supported treatments. In both the United States and India, EBPP training was largely infused across the curriculum, though a sizable percentage of participants did report only limited exposure to EBPP training. Participants perceived themselves as engaging in EBPP. The biggest barriers to EBPP training (largely shared across countries) were hesitancy about EBPP, investing the time in training, and being wedded to a single school of thought. Indian participants also noted a limitation in primarily relying on data from Western countries. EBPP training needs identified included desire for greater flexibility within EBPP, receiving more theoretical foundation in EBPP, and more applied EBPP training. Results demonstrated advances in EBPP training in the past 15 years since the release of American Psychological Associations task force report but also provide areas for growth in training, specifically surrounding balancing research evidence with clients cultural context as well as ways to promote lifelong EBPP learning. 2024 American Psychological Association -
A Mixed-Methods Study on Experiencing in Indian Couples During Gottman's Intervention of Dreams-Within-Conflict
In Gottman Couple Therapy (GCT), the intervention of Dreams-within-Conflict (DWC) helps break down a gridlocked issue between couples through deeper emotional expression and experiencing (in-counseling exploration of emotions). The current study examined experiencing in a single session of DWC for N = 30 individuals (15 couples) using multiple methods such as self-assessment questionnaires, observation rating and coding of the video recording, and feedback interviews. The before and during DWC best experiencing video segments were selected and rated by two raters independently on the experiencing scale (ES) for partners. The changes in experiencing mode and peak scores (ESM and ESP) during DWC were investigated in the presence of individual characteristics of attachment (anxiety and avoidance) and relationship mindfulness traits. A paired-samples t-test showed a significant increase in experiencing for both partners. Hierarchical linear modeling analysis indicated that gender (women) significantly and positively predicted ESM. ESP was predicted positively by gender (women) and negatively by avoidance, though the results were not conclusive. Thematic analysis was used to look at the Indian couples' experiencing as shared by them in order to better grasp the therapeutic implications. The qualitative findings confirm the quantitative results that couples outside of intervention utilized experiencing levels 13 predominantly and moved to 34 levels during best experiencing segments of intervention. Couples reviewed positively to the emotional experiencing techniques used during the DWC intervention. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
A mobile based remote user authentication scheme without verifier table for cloud based services
The emerging Cloud computing technology, offering computing resources as a service is gaining increasing attention of both the public and private sector. For the whole hearted adoption of Cloud, the service providers need to ensure that only valid users gain access to the services and data residing within the provider's premises. Ensuring secure access to sensitive resources within the Cloud requires a strong user authentication mechanism using multiple authentication factors. The mechanisms should also consider the increasing needs of Internet access through smart phones and other mobile devices and facilitate access through a variety of devices. Traditionally, a user needs to maintain separate user accounts for each Service Provider whose service he/she desires to use and this may cause inconvenience to users. Single Sign on (SSO) addresses this issue by permitting users to create one login credential and access multiple services hosted in different domains. In this scenario, a compromise of the single credential can result in account take over at many other sites. This points out to the requirement of strengthening the authentication mechanism by using more than one factor. This paper proposes a SSO based remote user authentication scheme for a Cloud environment. The proposed protocol uses password and mobile token and does not require the server to maintain a verifier table. The protocol is verified using automated security Protocol verification tool, Scyther and the results prove that the protocol provides protection against man-in-the-middle attack, replay attack and secrecy of the user's credentials. 2015 ACM. -
A model for analyzing the sustainability performance in educational institutions
During the past two decades innumerable international initiatives have emphasized that education is an imperative for societies to become more sustainable. Sustainable development is the current context in which higher education must begin to focus its action plans. But the present system heavily relies on archaic models which reduce learning and action to reductionist thinking and mechanistic interpretation. Campus sustainability is receiving growing attention and has become a well-established study field, even though campus sustainability itself has not become a reality yet in most universities. The paper then validates a pre-existing model using multiple regression models. The results validated the proposed model. A sustainability index could be developed for the education sector in future using this conceptual framework. The educational institutions can use the sustainability index to analyze their sustainability performance and take the necessary steps for achieving the same. This paper is an initial step in this direction which could be researched further to measure the sustainability performance in the education system. Grenze Scientific Society, 2020. -
A Model for Churn Prediction Based on Qualitative Support Interaction Features for Hotel Technology Provider
Customer retention is a significant driver of a company s growth. Machine learning has gained immense popularity as a means to predict customers at risk of churn. Churn prediction models are capable of highlighting customers who are at high risk of churn well in advance. A popular approach to improve the performance of churn prediction models is by using input variables that are mainly quantitative and structured in nature. There are limited works in literature that newlineinvestigate smart means to effectively utilize and integrate unstructured data into churn prediction models, and study the impact on model efficacy. One of the roadblocks to effectively utilize unstructured data is the associated cost of annotation which is both time consuming and requires intensive manual effort. To overcome this obstacle, researchers often adopt a semi-supervised newlineapproach called active learning that aims to achieve state-of-the-art performance using minimal number of samples. Although active learning boosts classifier performance, the underlying query strategies are unable to eliminate redundancy in selected samples for manual annotation. Redundant samples lead to increased cost and sub-optimal performance of learner. Inspired by this challenge, the study proposes a new representation-based query strategy that selects highly newlineinformative and representative subsets of samples for manual annotation. Data comprises newlinemessages of a set of customers sent to a service provider. Series of experiments are conducted to analyse the effectiveness of the proposed query strategy, called Entropy-based Min Max Similarity (E-MMSIM), in the context of topic classification for churn prediction. The foundation of E-MMSIM is an algorithm that is popularly used to sequence proteins in protein databases. The algorithm is modified and utilized to select the most representative and informative samples. The performance is evaluated using F1-score, AUC and accuracy. -
A Model for Detecting Type 2 Diabetes Using Mixed Single-Cell RNA Sequencing with Optimized Data
Diabetes is a critical disease and is crucial to personage agility. Type 2 Diabetes (T2D) accounts for 92% of epithetical cases. This paper proposes an optimized type 2 diabetes detection model using mixed single-cell RNA sequencing (scRNA-seq) technology. Diabetes is a chronic metabolic disorder affecting millions of people worldwide. Early detection of the disease can greatly improve treatment outcomes, but current diagnostic methods have limitations. Our proposed model integrates scRNA-seq data from both human pancreatic beta cells to identify gene expression patterns associated with diabetes. Our study shows that the proposed model is highly accurate in identifying diabetes, achieving an area under the curve (AUC) of 0.98. We employed an optimized model to improve the detection of diabetes at an early stage, leading to better treatment outcomes and an improved quality of life for patients. We initially incorporated optimal features from the dataset using the Monte Carlo (MC) feature selection method. This method helped us to estimate the relative importance (RI) score of each gene or feature, which is then used to rank the features. Further, we proposed an optimized deep belief network (ODBN) as a classification model to classify T2D and non-diabetes. To improve the performance of ODBN, an adaptive chimp optimization algorithm (AChOA) is introduced to optimize the weight parameters and achieved a performance accuracy of 96.57%. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
A Model for storage optimization of brain MRI images for tumor detection using image processing technique
Magnetic Resonance Imaging (MRI) is a major non-invasive method for Brain tumor detection. The anatomical assessment of brain newlinetumor can be carried out using brain MRI image analysis. MRI is widely used in brain tumor identification and classification. Images generated during the diagnosis purpose are unattended after the specified diagnosis. newlineBrain MRI images in Digital Imaging and Communications in Medicine (DICOM) format require large amount of storage space. newlineAccumulation of the MRI images put forward the requirement of more storage space. To store large number of images, existing storage models has to be handled wisely. Research associated with storage, process and newlinemanipulation of medical image data using modern technologies with a minimal human intervention is the need of the time. Image processing deals with the study and development of innovative technologies for newlineanalysis,representation and interpretation of the image data. In this research, the need of an efficient storage model that can help in storing the brain MRI images is studied with the help of image processing technique. To store the brain MRI images with a reduced storage space, a matrix-based method is proposed. In this model brain MRI images in newlineDICOM format are converted into matrix format. In the DICOM images, the image data and header information together hold the details of the patient and image data. These data are converted and stored in the matrix. newlineThe stored matrix is accessed as the input to the proposed model. The proposed model follows different image processing steps.The process starts with pre-processing of brain MRI images followed by clustering of newlinewhite matter (WM), gray matter (GM) and cerebrospinal fluid (CSF), segmentation of tumor and classification of tumor and finally it handles the storage of the MRI images. In the pre-processing step, filtering algorithms are applied on MRI to remove the noise and text artifacts. The newlinewhite matter, gray matter and CSF are separated using the K-means newlineclustering method. -
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. -
A model to measure receptivity among teachers and to facilitate smooth transition of anademic trainers or teachers /
Patent Number: 202241032185, Applicant: Trixy Elizabeth John.
The invention provides a model for facilitating receptivity to change in teachers. The model provide a four-correlated factor structure. The model includes individual, organisational, bridging, and educational factors. The factors in the present invention created based on respective sub-factors provides the foundation for the model. The different sub factors comprise self-efficacy and self-regulation for individual factors; school climate, school support, principal support, professional training, communication, and participation for organisational factors. -
A model to predict the influence of inconsistencies in Thermal Barrier Coating ( TBC) thicknesses in pistons of IC engines /
Materials Today Proceedings, Vol.5, Issue 5, Part 2, pp.12623-12631 -
A Model to Predict the Influence of Inconsistencies in Thermal Barrier Coating (TBC) Thicknesses in Pistons of IC Engines
LHR (Low heat Rejection) engines comprise of components that are modified with ceramic Thermal Barrier Coatings (TBC) to derive improvements in performance, fuel efficiency, combustion characteristics and life. In addition to engine parameters, the ability of TBCs (250 - 300?m thick) to function favorably depends on materials technology related factors such as surface-connected porosity, coating surface roughness, uniformity and consistency in coating thickness [1]. Right since the nineties, emphasis has been placed on the complexity of piston contours from a coating processing standpoint because the piston bowl geometry although appears simple, is actually quite complex. Robotic plasma gun manipulation programs have been developed to obtain uniform coating properties and thicknesses which are highly classified information. Thicker coatings offer better thermal insulation characteristics but in thickness deficient regions, TBCs may be as thin as ?30 microns. Applied via the 'line of sight' process, in the Atmospheric Plasma Spray System the coating thickness does not get developed adequately if the components comprise of contours with shadow regions. Thus the coating quality of a LHR engine heavily depends upon the shape of the engine components. This affects the barrier effects offered by the TBC and is reflected via generation of unwanted thermal gradients in the combustion chamber and on the external piston walls that adversely influence the engine performance. Extensive diesel engine cycle simulation and finite-element analysis of the coatings have been conducted to understand their effects on (a) diesel engine performance and (b) stress state in the coating and underlying metal substructure. Research work presented here involves the need and developmental efforts made via Computational Fluid Dynamics (CFD) to generate a model via ANSYS - Fluent simulation software that predicts the temperature gradient across TBCs of various ceramics and coating thicknesses. The geometric model was developed using the dimensions obtained using a CMM (Coordinate Measuring Machine) in Solidworks and the mesh was developed in Altair Hypermesh. The generated mesh consists of 221938 elements. Interfaces were created between the piston-bond coat-top coat surfaces. The Ansys-FLUENT CFD code solves the energy equation to find out the temperature drop in the piston for different combustion temperatures. Although most of the cavities presented are not rectangular, incompressible and steady laminar flow was assumed. The Semi-Implicit Method for Pressure-linked Equations (SIMPLE) was used to model the interaction between pressure and velocity. The energy variables were solved using the second order upwind scheme. In addition, the CFD program uses the Standard scheme to find the pressure values at the cell faces. Convergence was determined by checking the scaled residuals and ensuring that they were less than 10-6 for all variables. Two cases with combustion temperatures varying between 700 and 800 K were developed in Ansys FLUENT, wherein the thickness was deficient in the 'shadow' region. The model was validated via experimentation involving thermal shock cycle tests in prototype burner rig facility and measuring the temperature drop across the TBC as well. Non uniform coatings, leading to non-uniform drop in temperature across the thickness are most likely to affect the lubrication system of the engine and therefore the performance. Substantial efforts must be directed towards development of consistent and uniformly thick coatings for optimum performance of the LHR engine. 2017 Elsevier Ltd. All rights reserved. -
A modern approach of swarm intelligence analysis in big data: Methods, tools, and applications
Swarm intelligence is one of the most modern and less discovered artificial intelligence types. Until now it has been proven that the most comprehensive method to solve complex problems is using behaviours of swarms. Big data analysis plays a beneficial role in decision making, education domain, innovations, and healthcare in this digitally growing world. To synchronize and make decisions by analysing such a big amount of data may not be possible by the traditional methods. Traditional model-based methods may fail because of problem varieties such as volume, dynamic changes, noise, and so forth. Because of the above varieties, the traditional data processing approach will become inefficient. On the basis of the combination of swarm intelligence and data mining techniques, we can have better understanding of big data analytics, so utilizing swarm intelligence to analyse big data will give massive results. By utilizing existing information about this domain, more efficient algorithm can be designed to solve real-life problems. 2023, IGI Global. All rights reserved. -
A modified approach for extraction and association of triplets
In this paper we present an enhanced algorithm with modified approach to extricate various Triplets i.e. subject-predicate-object from Natural language sentences. The Treebank Structure and the Typed Dependencies obtained from Stanford Parser are used to elicit multiple triplets from English Sentences. Typed Dependencies represents grammatical connections among the words of any sentence and represents how triplets are associated. The intended interpretation behind the extraction of Triplets is that the subject is acting on the object in a way described by the predicate. In graphical form it can be considered that subject and object will be acting as nodes i.e. entities and predicate as edges i.e. relationship. The resulting triplets and relations can be useful for building and analysis of a social network graph and for generating communication pattern and Information retrieval. 2015 IEEE.