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Web-based single session therapy training for mental health support providers: a mixed-methods evaluation study protocol
The growing mental health needs and constrained resources in low- and middle-income countries necessitate scalable solutions. Single Session Therapy (SST) is a global trend in brief and cost-effective options for mental health interventions. It involves a single planned session between mental health service provider and client. This study aims to present a protocol to develop and evaluate a culture specific web-based training program to equip mental health support providers with the skills and confidence to deliver SST. The study protocol uses a mixed-methods evaluation design through three phasesneed assessment where psychologists and social workers collaborate to identify training needs and co-create the program; development and expert validation of the web-based training program; and randomized control trial to evaluate the training, followed by in-depth discussions with participants. This study breaks new ground by empirically designing and evaluating a training program for SST. It uniquely co-designs and validates a culturally sensitive SST training program, leveraging the expertise of a renowned international panel. This protocol goes beyond a blueprint for replicating this study, it serves as a foundational guide for nations seeking to implement effective SST training for their mental health professionals, preventing duplication of efforts. The Author(s) 2024. -
Web User Access Log Analytics Using Neural Learning, Regression and Logit Boost Clustering Techniques for Accurate User Behavioural Pattern Identification
Web Usage Mining (WUM), is the process of mining user behaviour patterns from huge log fles. Weblogs provide substantial input to learning the identity of an online user. Analysis of these patterns extracted from the weblog datasets is currently being explored by various researchers. Due to the recent advent of automation, mining patterns from weblogs are automated. These automated mining processes focus on browsing habits and usage patterns. To make this process of gathering better, there are many ways to look at how users act and put them into relevant groups.Identifying, detecting, and classifying features that demarcate specifc traits that are related is an important task. Conventional research is designed to discover web usage mining strategies through clustering and classifcation methods. However, there is a need to focus on and improve the accuracy of the prediction systems that classify acquired features to fgure out the patterns of web users. Deep learning methods are used to mine weblog data to improve accuracy and precision. To improve user behaviour pattern mining, a two-level clustering process is introduced as Ensemble Fuzzy K-Means with Logit Boost Clustering (EFK-LBC) technique to extract the weblog. In this technique, a preprocessing step is included to remove redundant data and choose reliable log fles. The Fuzzy-K means clustering technique is used to identify behavioural patterns exhibited by recurrent users. Finally, the Logit Boost Clustering method is introduced to the data,that help in generating a strong cluster. Clustering of web users frequent behavioural patterns using the Logit Boost ensemble technique helps the proposed EFK-LBC method to improve newlinethe accuracy up to 88% and reduce the clustering time by 20% compared with existing approaches. Though the proposed EFK-LBC technique performs better for user identifcation, the different initialization of clusters provides various fnal clustering results. -
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Web Platforms for Fintech Products
Internet marketing and digital marketing are not synonymous in the minds of the majority of the population, yet this may not be true. Given the rise in popularity of digital marketing as a marketing tactic, it is critical to comprehend the distinctions between the two methods. Even while it should be evident that they might be connected, there is very little difference between them. Internet marketing is merely a subclass of digital marketing, as well as the extent of digital marketing encompasses much more than internet marketing. This paper discussed digital marketing technologies, as well as the advantages and disadvantages of employing digital marketing and digital finance tools in general. In order to remain competitive, businesses must overcome obstacles and seize possibilities presented by digital marketing technologies. Lastly, it's critical to prioritise digital marketing and make use of digital finance techniques in order to maintain a good performance without wasting time or money. 2022 IEEE. -
Web mining patterns discovery and analysis using custombuilt Apriori Algorithm
International Journal of Engineering Inventions Vol.2, Issue 5,pp.16-21 ISSN No. 2278-7461 -
Weather Forecasting Accuracy Enhancement Using Random Forests Algorithm
In today's world, weather forecasting is essential for decision-making in a variety of fields, including agriculture, transportation, and disaster preparedness. It's not simple to make weather predictions. Today, both in business and academia, data analytics is growing in importance as a tool for decision-making. The adoption of data-driven concepts is for our graduates, enhancing their marketability. Data Analytics us a study belonging to science that analyses gathered raw data, which makes conclusions about the particular information. Data analytics has been used by many sectors recently, such as hospitality, where this industry can collect data, find out where the problem is, and manage to fix the problem. Nominal, ordinal, interval, and ratio data levels are the four types of data measurement. Applications of data analytics can be found in many industries, including shipping and logistics, manufacturing, security, education, healthcare, and web development. Any business that wants to succeed in the modern digital economy should make analytics a core focus. To make such data meaningful, a transformation engine was used with types from several sources. Ironically, this has made analytics harder for businesses. As businesses employ more platforms and applications, the amount of data available has grown tremendously. This article focuses on different applications of data analytics in the modern world. Weather forecasting is a highly intricate and multifaceted process that draws upon data from various sources. It relies on a combination of scientific studies and sophisticated weather models to decipher the vast amount of information available. 2023 IEEE. -
Wearable Smart Technologies: Changing the Future of Healthcare
Wearable smart technologies are the innovative solutions for the issues of healthcare services. In this chapter, a review of the innovative wearable healthcare devices and applications has been done. Wearable devices are used for supervision and illness control. These innovative wearable technologies can straightforwardly affect the medical dynamic, can upgrade the quality of treatment for patients, and can reduce the expenses incurred in it. The large health record generated by the wearable devices provides an opportunity for data analysts to apply machine learning techniques for prediction on the data generated by sensors. Today's wearable smart technologies are capable of being integrated into eyeglasses, cloths, shoes, belts, watches, etc. Sensors can be inserted in these objects to be worn. The advanced forms of wearable technologies can be attached to the skin of the wearer. A smartphone is mainly utilized to collect data and communicate it to a server situated at a remote area for greater capacity and investigation. Maximum innovations related to wearable technologies are still in the prototyping phase. The study covers almost every aspect of wearable technologies, which could be helpful in the future for innovation and research in this area. 2024 selection and editorial matter, Ankur Beohar, Ribu Mathew, Abhishek Kumar Upadhyay, and Santosh Kumar Vishvakarma -individual chapters, the contributors. All rights reserved. -
Wearable Sensors for Pervasive and Personalized Health Care
Healthcare systems are designed to provide commendable services to cater health needs of individuals with minimum expenditure and limited use of human resources. Pervasive health care can be considered as a major development in the healthcare system which aims to treat patients with minimal human resources. This provides a solution to several existing healthcare problems which might change the future of the healthcare systems in a positive way. Pervasive health care is defined as a system which is available to anyone at any point of time and at any place without any location constraints. At a broader definition, it helps in monitoring the health-related issues at a home-based environment by medical stakeholders which is very beneficial in case of emergency situations. This chapter elaborates architecture of IoT, how wearable sensors can be used to help people to get personalized and pervasive healthcare systems, and it also gives a detailed working of different types of IoT-enabled wearable devices for pervasive health care. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Wearable Leaf-Shaped Slotted Antenna Including Human Phantom for WBAN Applications
A 5.8 GHz leaf-shaped slotted antenna for Wireless Body Area Network (WBAN) applications is presented in this piece of content. The leaf structure includes tri leaves, having a complete ground plane at the lowest floor and a central circle slot. The suggested antenna is 60 mm by 60 mm by 1.16 mm in total dimensions. The ISM (Industrial Science and Medical) band frequency of 5.8 GHz is covered by this antenna's radiation range of 5.5 to 6.4 GHz. The radiated pattern, efficiency, S11 magnitude and gain were the different attributes of the leaf-patterned slot antenna. The creation of a stylish leaf-shaped antenna that can be incorporated into clothing designs is the main goal of this project. This antenna may be used in difficult situations because of its flexible base and conductive fabric. The method considers the needs of wearable antennas, such as the impact of human interactions on this antenna, as well as the opposite. 2023 IEEE. -
Wear characterization of hnt filled glass-epoxy composites using taguchis design of experiments and study of wear morphology
Glass-epoxy composites are increasingly being used in several industrial applications, viz. automobile, marine, aerospace, electrical and electronics components, especially in tribological components, viz. bearings, impellers, cams, driving wheels, bolts, nuts, seals, bushes and gears, which are used extensively in machinery because their lower weight, exceptional strength, resistance to corrosion capabilities, and cost effectiveness. The work focuses on optimization of the process parameters of the dry sliding wear test, viz. the applied load, disc rotation speed, weight percentage (wt.%) of the Halloysite nanotube (HNT) filler, time as well as the track diameter to minimize the wear rate of the glass fabric reinforced epoxy composite against EN-32 steel. In this research, the specimens are fabricated in accordance with the ASTM G-99 standard and the experiment is carried out with various combinations of parameters using a pin-on-disc tribometer, while keeping the time and track diameter constant. To proceed further, trial runs are conducted using MINITAB 19 software to optimize the process parameters for minimum wear by developing Taguchis design of experiments (DOE) based on the L45 orthogonal array (OA), and subse-quent analysis of the signal-to-noise (S/N) ratio. The results of the optimization clearly indicate that the wt.% of HNT is the most significant parameter that has a significant effect on minimizing the applied load, speed and sliding wear rate. In over-view, the experiment results showed that the combined parameters influenced the wear. In addition, scanning electron microscopy (SEM) is performed to study the surface morphologies of the worn specimens and determine the wear mechanism in accordance with the test results. The wear mechanism clearly indicates that there is a larger amount of matrix debris, fiber breakage and fiber-matrix debonding in the neat composites as compared to the HNT filled glass-epoxy composites since a distinct pattern of micro coring and segregation of the filler along the peripheries of the glass fiber-epoxy interstitial sites, leading to strong bonding between the fibers and matrix are observed in the HNT filled composites. The strong bonding thus resists the wear to a certain extent, and the wear debris is relatively less in the HNT filled composites as compared to the neat composites. 2020, Polish Society of Composite Materials. All rights reserved. -
WEAR AND FRICTION BEHAVIOUR OF ALUMINIUM METAL MATRIX COMPOSITE REINFORCED WITH GRAPHITE NANOPARTICLES
In the current research work, AA7050 a marine aluminium alloy was reinforced with the nano-graphite particles, processed through the stir casting technique. The scanning electron microstructure reveals, that the nanoparticles were uniformly distributed over the matrix material and the hardness of the composites increased with a rise in the weight percentage of Gr particles owing to the Hall patch effect. The wear experiments were conducted by varying reinforcement, load, velocity, distance, and temperature, and the experimental runs were designed using the L25 orthogonal array, in which wear, coefficient of friction and worn surface hardness were recorded as a response. The wear resistance of the composites increases with a rise in the graphite content attributed to the formation of a mechanically mixed layer, the wear rate transfers from mild to severe, when there is shift in temperature from 100C to 150C. The worn surface hardness of the composites was higher than those of as-cast composites owing to the presence of Fe on the surface confirmed through the EDAX mapping. The composites were optimized using the modified PROMETHEE optimization technique and the results revealed that AA7050 reinforced with 8% Gr particles showed the best result and was recommended for the marine sector. 2024, Scibulcom Ltd.. All rights reserved. -
Wear and Friction Behaviour of Aluminium Metal Matrix Composite Reinforced with Graphite Nano Particles for Vehicle Structures
In the current research work, AA7050 a marine aluminium alloy was reinforced with the nano graphite particles processed through stir casting technique. The scanning electron microstructure reveals that the nano particles were uniformly distributed over the matrix material and the hardness of the composites increase with raise in weight percentage of Gr particles owing to the Hall-Petch effect. The wear experiments were conducted by varying reinforcement, load, velocity, distance and temperature. The experimental runs were designed using the L25 orthogonal array in which wear, coefficient of friction and worn surface hardness were recorded as response. The wear resistance of the composites increases with raise in the graphite content attributed to the formation of mechanical mixed layer, the wear rate transfer from mild to severe when there swift in temperature from 100C to 150C. The worn surface hardness of the composites was higher than the as cast composites owing to the presence of Fe on the surface confirmed through the EDAX mapping. The composites were optimized using the modified PROMETHEE optimization technique and results revealed that AA7050 reinforced with 8% Gr particles showed best result and recommended for the marine sector. 2024. Carbon Magics Ltd. -
Weakly nonlinear stability analysis of salt-finger convection in a longitudinally infinite cavity
This paper is a two-dimensional linear and weakly nonlinear stability analyses of the three-dimensional problem of Chang et al. ["Three-dimensional stability analysis for a salt-finger convecting layer,"J. Fluid Mech. 841, 636-653 (2018)] concerning salt-finger convection, which is seen when there is sideways heating and salting along the vertical walls along with a linear variation of temperature and concentration on the horizontal walls. A two-dimensional linear stability analysis is first carried out in the problem with the knowledge that the result could be different from those of a three-dimensional study. A two-dimensional weakly nonlinear stability analysis, that is, then performed points to the possibility of the occurrence of sub-critical motions. Stability curves are drawn to depict various instability regions. With the help of a detailed stability analysis, the stationary mode is shown to be the preferred one compared to oscillatory. Local nonlinear stability analysis of the system is done in a neighborhood of the critical Rayleigh number to predict a sub-critical instability region. The existence of a stable solution at the onset of a weakly nonlinear convective regime is indicated, allowing one to perform a bifurcation study in the problem. Heat and mass transports are discussed by analyzing the Nusselt number, Nu, and Sherwood number, Sh, respectively. A simple relationship is obtained between the Nusselt number and the Sherwood number exclusively in terms of the Lewis number, Le. 2022 Author(s). -
Weakly Non-linear Stability Analysis of Triple-Diffusive Convection in a Bi-viscous Bingham Fluid Layer with Cross-Diffusion Effects
The paper investigates the impact of cross-diffusion on triple-diffusive convection in a bi-viscous Bingham fluid layer. Non-linear stability analysis is performed, and the expression of the critical-Rayleigh-number is obtained, resulting in an analytical solution of the Ginzburg-Landau model (GLM). The coefficients in the GLM involve the scaled Rayleigh-number, the solutal Rayleigh-numbers, the solutal diffusivity rates, the bi-viscous Bingham fluid parameter, and the cross-diffusion parameters. The solutal Rayleigh-numbers, the solutal diffusivity rates, and the bi-viscous Bingham fluid parameter alone determine the critical-Rayleigh-number, which provides the condition for the stationary onset. The neutral curves for the stationary mode are examined. It is found that the solutal diffusivities and bi-viscous Bingham fluid parameter advance the onset of convection, whereas the solutal Rayleigh-numbers delay it. The Nusselt number, Nu, and the Sherwood numbers, Sh1 and Sh2, determine the heat- and mass-transfer rates obtained for the convection system. We see that Nu, Sh1 and Sh2 increase with an increase in the values of the bi-viscous Bingham fluid parameter. Also, we observe that increase in the Prandtl number effect increases them, and the same is true of the solutal Rayleigh-numbers, whereas the opposite impact on Nu, Sh1 and Sh2 is seen for solutal diffusivities, Soret and cross-diffusion parameters. In general, we observe that mass-transfer is more than the heat-transfer (Sh1>Sh2>Nu) depending on the value of diffusivities. The Author(s), under exclusive licence to Springer Nature India Private Limited 2024. -
We wear multiple hats: Exploratory study of role of special education teachers of public schools in India
The role of special education teachers (SETs) is multifaceted. A gap was recognised in the literature in the lack of studies on the roles and responsibilities of SETs in India and the field realities of carrying out the role. The aim was to explore to what extent the special education teachers fulfil their roles and responsibilities. The following is an exploratory study, using open-ended questions that interviewed 12 SETs from five public schools in Delhi, India. The policy documents shared that the SETs were responsible for direct instruction to special needs students, parentteacher collaboration and documentation, including IEPs for students with special needs. But in practice, there were not any clear-cut boundaries, the SETs played multiple rolesSubject teacher, taking substitution periods, para teachers, these were keeping the SETs away from their core responsibilities. The results of the study demonstrated an undervaluation of the work of SETs and lack of support from the principal and regular teachers. The results concluded with recommendations for policy proposal with regards to defining the role of all stakeholders in an inclusive education school and improvements for the teacher education program. 2024 National Association for Special Educational Needs. -
We are Treated as Outsiders in Our Own City: Lived Experiences of Intersectional Stigma Against Sex Workers in Kolkata, India
Introduction: Sex workers in India experience intersectional stigma related to their gender identity, sexuality, and profession. The objective of the present study is to analyze the lived experiences of intersectional stigma against sex workers in Kolkata. Methods: We interviewed 30 cisgender female sex workers in March 2023 in Kolkata, India. Interviews were digitally audio recorded, translated from Bengali into English, and transcribed and coded using thematic analysis. Results: We identified five main themes regarding intersectional stigma: (1) internalized stigma regarding the shame associated with being a female sex worker, (2) perceived stigma of sex work as a dirty profession, associated with lower caste status, (3) enacted stigma against sex workers who are mothers, (4) enacted stigma against the children of sex workers, and (5) reduction of stigma through unionization/labor organizing. Conclusions: Intersectional stigma against sex workersis impacted by negative attitudes regarding gender, caste status, single motherhood, and occupation. We identified internalized stigma as a source of shame for sex workers. Sex workers also were perceived to beengaged in afilthy profession, associated with lower caste status. Those sex workers who were mothers experienced discrimination, as did their children. Respondents reported how collectivization has helped to address these experiences of stigma anddiscrimination. Policy Implications: Addressing the intersectional stigma against sex workers in Kolkata necessitates a shift in social attitudes.Findings underscore the urgent need for stigma reduction interventions and socialpolicies, including (1) labor protections for sex workers, (2) individual/community-level interventions for sex workers, and (3) media campaigns to address stigma reduction. By understanding the lived experiences of sex workers, we may develop better interventions to reduce stigma in the lives of sex workers in Kolkata and throughout India. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Wavelet packet transform based fusion of misaligned images
This paper proposes an image fusion method based on wavelet packet transform (WPT) for images with misaligned region of interest, which finds wide application in target recognition and feature extraction. The region of interest of the images are first aligned and then fused in the transform domain. The various no-reference parameters such as standard deviation (SD), spatial frequency (SF) are measured for the fused image. The result obtained from this method is compared with the other methods such as image fusion using discrete wavelet transform (DWT), stationary wavelet transform and guided filtering. It is evident from the simulation results that the two parameters are high for the fused image using wavelet packet transform. 2016 IEEE. -
Waveform Analysis and Feature Extraction from Speech Data of Dysarthric Persons
Speech recognition systems provide a natural way of interacting with computers and serve as an alternative to the more popular but less intuitive peripherals (input / output devices). Tools employing the techniques of Automatic Speech Recognition (ASR) can be extended to serve people with speech disabilities so that they can overcome the difficulties faced in their interaction with general public. An attempt is made here to achieve this goal by mapping the distorted speech signals of people with severe levels of dysarthria to that of a normal speech and/or less severe dysarthric speech. The analysis is carried out by comparing the speech waveforms of the people with and without communication disorders and then extracting the features from the audio files. The differences in time, duration, frequency and PSD are used to facilitate the mapping of unintelligible speech data to intelligible ones. When reasonable accuracy levels are achieved in this mapping, the normal voice can be used as the substitute / surrogate of the original distorted voice. 2019 IEEE. -
Wave Height Forecasting over Ocean of Things Based on Machine Learning Techniques: An Application for Ocean Renewable Energy Generation
With the evolution and integration of information and communication technologies, the marine environment is being converted into a smart ocean of things. The only way to monitor the marine environment is to access marine information through satellites, radar, etc. Recently, many researchers have focused their interest on generating power from renewable energy. Among all the available renewable resources, ocean waves are attracting the interest of researchers for power generation. Therefore, this article focuses on designing a data-driven forecasting model for marine renewable energy generation applications. This article applies a novel Gini-impurity-index-based bidirectional long short-term memory model for selecting the best ocean/marine environmental factors to forecast wave height and ultimately predict power generation using the numerical model. This article presents short- and long-term forecasting results. In the experiment, four stations each are taken for both short- and long-term forecasting. The average root-mean-square error was approximately 0.17 for long-term forecasting and approximately 0.05 for short-term forecasting. 1976-2012 IEEE. -
Water Purification Using Subnanostructured Photocatalysts
Visible light is an abundant resource, and photocatalysts absorb this light and use it to energize chemical reactions. Of the many types of reactions that are catalyzed by photocatalysts, wastewater purification is an important area. Photocatalysis is an economical, eco-friendly, and sustainable method of purifying water, a precious resource for which need is increasing while availability is shrinking. Of the several types of photocatalytic materials available, atomically dispersed metals and metal oxides appear to be the most promising. In conventional materials, the efficiency of utilization of active photocatalytic material is rather poor because only a small fraction of those present on the surface can serve as active materials. As the particle size decreases, this efficiency increases. In this respect, subnanometric catalysts such as single-site heterogeneous catalysts, atomically dispersed catalysts, and single-atom catalysts have distinct advantages when compared with their bulk and nanometric counterparts. The challenges in preparing stable single-atom catalysts have largely been overcome, and several methods are now available for their preparation. Many atomically dispersed photocatalytic materials have been synthesized, and many new insights have been gained, unlocking the tremendous potential in purifying wastewater by utilizing solar radiation. The aspects of higher activity, improved selectivity, economical use of materials, and a better understanding of the structure-activity relationship offered by subnanometric photocatalysts have been explored in this chapter. 2020 American Chemical Society.