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Melanoma Skin Cancer Detection using a CNN-Regularized Extreme Learning Machine (RELM) based Model
Recent years have brought a heightened awareness of skin cancer as a potentially fatal type of human disease. While all three forms of skin cancer - Melanoma, Basal, and Squamous are terrifying, Melanoma is the most erratic. Melanoma cancer is curable if caught at an early stage. Multiple current systems have demonstrated that computer vision can play a significant role in medical image diagnosis. This study suggests a new approach to picture categorization that can help convolutional neural networks train more quickly (CNN). CNN has seen widespread use in multiclass image classification datasets, but its poor learning performance for huge volumes of data has limited its usefulness. On the other hand, whereas Regularized Extreme Learning Machine (RELM) are capable of rapid learning and have strong generalizability to improve their recognized accuracy quickly. This study introduces a novel CNN-RELM, a novel classifier that integrates convolutional neural networks with regularized extreme learning machines. CNN-RELM begins by training a Convolutional Neural Network (CNN) through the gradient descent technique until the desired learning and target accuracy is achieved. This approach outperforms the CNN and RELM model with an accuracy of around 98.6%. 2023 IEEE. -
Memes as multimodal ensemble
Memes have now become a common medium of communication. There are multiple ways memes are considered in academia. Semiotics offers information on how the media and modes that memes consist of can be interpreted and how the characteristics of semiotic resources apply to memes. Drawing from a pool of memes collected during the Kerala assembly election in 2021, this research argues that certain memes need to be categorised as multimodal ensemble. Different modalities play different roles meaning construction, and they also collaborate with each other for a uniform purpose. By comparing existing memes defined in academia and multiple methodologies to analyse memes, the paper puts forth a framework to analyse memes. 2023 De Gruyter Mouton. All rights reserved. -
Memetic Spider Monkey Optimization for Spam Review Detection Problem
Spider monkey optimization (SMO) algorithm imitates the spider monkey's fission-fusion social behavior. It is evident through literature that the SMO is a competitive swarm-based algorithm that is used to solve difficult real-life problems. The SMO's search process is a little bit biased by the random component that drives it with high explorative searching steps. A hybridized SMO with a memetic search to improve the local search ability of SMO is proposed here. The newly developed strategy is titled Memetic SMO (MeSMO). Further, the proposed MeSMO-based clustering approach is applied to solve a big data problem, namely, the spam review detection problem. A customer usually makes decisions to purchase something or make an image of someone based on online reviews. Therefore, there is a good chance that the individuals or companies may write spam reviews to upgrade or degrade the stature or value of a trader/product/company. Therefore, an efficient spam detection algorithm, MeSMO, is proposed and tested over four complex spam datasets. The reported results of MeSMO are compared with the outcomes obtained from the six state-of-art strategies. A comparative analysis of the results proved that MeSMO is a good technique to solve the spam review detection problem and improved precision by 3.68%. 2023 Mary Ann Liebert, Inc., publishers. -
Memorialisation and Identity in Mah India: Revealing French Colonial Legacies
Mah nestled in the Mahdistrict of the Puducherry Union Territory in India, holds profound historical ties to French colonial India. Unlike the broader Indian subcontinent, which witnessed fervent anti-colonial movements against British rule leading to political decolonisation in 1947, Mahexperienced a belated political awakening, reluctantly integrating into the Indian Union in 1954. Despite the withdrawal of the French, the enduring legacy of French colonial ideology and culture continued to shape the ethos of Mah In contemporary times, a significant presence of French nationals in India, particularly in Pondicherry, Karaikal, and Mah has fostered the evolution of a unique linguistic identity known as Indian French. Within Mah landmarks such as St. Teresas Shrine, the Statue of Marianne in Tagore Park at Cherukallayi, remnants of St. George Fort, and sculptures inspired by M. Mukundans novel On the Banks of the Mayyazhi stand as tangible vestiges of the erstwhile French presence. Serving as repositories of bygone French culture, these sites emerge as dynamic arenas of memory production. Notably, Tagore Park in Mah adorned with fictional documentation through sculptures, assumes a pivotal role as a space that harmonizes memory and history, functioning as a reservoir for collective memory concerning French colonial rule. Mah deliberate urban planning reflects a nuanced approach, embodying the concept of a living testament to French colonialism rather than a conventional museum. This architectural strategy underscores the deliberate preservation and commemoration of Mah historical past. Through interviews with French nationals residing in Mah this research explores how these landmarks have become pivotal in the production of memories and the construction of identities for the French community in India and Mah Leveraging Maurice Halbwachs theoretical framework, the study unveils the intricate interplay between collective memory and present-day identity formation, shedding light on the transformation of personal memory into historical memory and its subsequent amalgamation into collective memory. With close to 50 French families residing in and around Mahstill, the study involves interviews with ten families, focusing on landmarks like St. Teresas Shrine, the Statue of Marianne, the ruins of St. George Fort, and sculptures based on one of M. Mukundans novels. So, through interviews of the French citizens of Mah this paper highlights how the cultural artefacts and popular landmarks of Mahbecome sites of memory of the French colonisation. 2024, The International Academic Forum (IAFOR). All rights reserved. -
Memory response on generalized thermoelastic medium in context of dual phase lag thermoelasticity with non-local effect
Theory of non-local continuum is contemporary appraised and is found to be supplementary coherent to capture the impacts of each and every point of the material at its single point. The conviction of memory dependent derivative is also newly appraised and is observed to be more intuitionistic for predicting the realistic character of the real-world obstacles. Attractiveness of the belief of a memory dependent derivative lies in its unique properties such as its significant constituents a kernel function and time-delay are freely selected according to the requirement of a problem. The present study comprises a new meticulous thermoelastic heat conduction model for the homogeneous, isotropic, thermoelastic half space medium concerning memory effects and non-local effects. Governing equations are constructed on the basis of the newly appraised non-local generalized theory of thermoelasticity with two phase lags in the frame of a memory dependent derivative. Exact analytical solutions of the physical fields such as dimensionless temperature, displacement as well as thermal stress are evaluated by using a suitable technique of the Laplace transform. Quantitative results are determined in a time-domain for different values of time by taking the numerical inversion of the Laplace transform. Noteworthy role of the constituents of the memory dependent derivative such as kernel function as well as time-delay factor has been scrutinized on the crucial field variables of the medium through computational outcomes. Moreover, the impact of non-local parameter is examined on the variations of field quantities through the quantitative results. 2022 by IPPT PAN, Warszawa. -
Mental health counsellors perceptions on use of technology in counselling
The objectives of the study were: (a) to explore the self-reported knowledge of counsellors about technology in counselling. (b) to understand the flexibility, usage, and openness to integrating the technology services in their practice, and (c) to identify the problems associated with using technology as a process in counselling. Semi-structured interviews of eleven practising counsellors in Bangalore and Chennai, India, recruited through snowball sampling, were used for data collection. The deductive content analysis of the interview transcripts generated seven concepts, each comprising of several categories. The seven concepts were 'attitude', 'strengths', 'weakness', 'suitability', 'skills and training', 'therapeutic alliance', and 'theoretical approaches'. The analysis revealed that the counsellors preferred face-to-face counselling and were not using technology for their mainstream practice, but all were quite aware of the process, the benefits and costs of using different forms of technology. The study revealed that the counsellors were also aware about the target population and mental health issues for online counselling. This study has strong implications for building additional skills and enhancing training for counsellors to use technology in their counselling practice, along with the formulation of legal and ethical policies, certification and licensing, in order to protect both the clients and counsellors. 2019, Springer Science+Business Media, LLC, part of Springer Nature. -
Mental Health Data Analysis Using Cloud
In health care related research studies, there exists a need for retrieving patient's health record from multiple sites. So here comes the digitization of health records, which leads to a wide range of access to various users such as doctors, patients, psychiatrists and pharmacists. The sensitive nature of individual health care data pose a threat to security. Moreover, the increased access of health information by the users threatens the privacy and confidentiality of the stored data. Notwithstanding the existing privacy protection approaches used for mental health records, we suggest a privacy preserving data analysis methodology enabling protection of health records, once user access to records are granted. This paper mainly focuses on utilizing the data analysis approach in preserving privacy of personal health records to overcome the drawbacks of existing approaches. 2020 IEEE. -
Mental Health in the Times of Corona: A model for Positive Mental Health During the Global Pandemic
As the world comes to terms with the changes brought on by the appearance and spread of Covid-19, there is an increase in fear and anxiety levels. The World Health Organization has stressed on the need to focus on mental health, as the epidemic affects both young and old. One of the biggest challenges is that the situation has no precedent. This has led to the creation of uncertainty and doubt. The current study focusses on studying the positive mental health of the Indian population. For the study, the researchers have restricted the scope to include only Generation Y and Generation Z, as they form a majority of the working population and literature suggests that negative moods, stressors and apprehensions are far more prevalent among the younger sections of the society. The findings suggest that positive mental health is not dependent on gender or age. However, some of the dimensions do show significant variance. The researchers have also proposed a model of Positive Mental Health based on the dimensions of the Positive Mental Health Instrument. 2021, National Academy of Psychology (NAOP) India. -
Mental health professionals insights on developing and implementing a Mental Health Awareness and Destigmatisation program (MHAD) for adolescents
This study examined mental health professionals insights on developing and implementing a Mental Health Awareness and Destigmatisation (MHAD) program for adolescents aged 1418 years in Bangalore. Qualitative Interviews with 17 professionals revealed three main themes: 1. Awareness and Destigmatisation Programs: A Boon 2. Key Ingredients: Program Content and Delivery Style 3. Shaping Program Success: Key Drivers and Challenges. Professionals recommend interactive programs that promote open discussions and educate them on symptom recognition, online behavior, and healthy relationships. They identified key enablers and challenges, emphasizing the programs ability to empower adolescents, parents, and educators to create a supportive, stigma-free environment. 2024 Taylor & Francis Group, LLC. -
Mental health professionals view on the need for early intervention for offspring of individual with schizophrenia in India
Schizophrenia is a debilitating mental illness not only for the individual but also for the family, especially the children. There is a definitive likelihood of the vulnerability being transmitted to the child. As a result of the parents illness there may also be disruptions in the family dynamics and in home environment. However, many children have been found to show resiliency. The aim of this particular study was to explore the need for intervention in children who's either parent were being treated for schizophrenia. Using qualitative Interpretative Phenomenological Approach (IPA) mental health professionals from all over India were interviewed with the help of validated interview guide. To understand their lived in experience of these professionals the audio recorded interviews were transcribed and analysed for exploring the themes using thematic analysis. Significant themes found indicated that early interventions were crucial for the wellbeing of the child, specifically in the Indian scenario. 2018 Oriental Scientific Publishing Company. -
Mental Health Stigma: Strategies for Destigmatization in Healthcare Settings
Mental illness is one of the most common disabilities in the world. The term "mental illness stigma"describes harmful practices and misconceptions that lead to a detrimental effect on the mental health, motivation, and self-worth of those who suffer from mental illnesses. Health care services are important for treating and reducing the negative stigma of mental health, as they are areas where patients seek relief and support. The study aims to investigate the causes and how to reduce them. Explores ways to disrupt the health care environment, specifically the RESHAPE program, which focuses on the concept of "critical". This review paper looks at 8-10 papers on mental health and stigma and how stigma will be reduced. The results show that a large number of doctors and students are stigmatized, negatively affecting the lives of people affected by mental illness. RESHAPE, KAP, and IBH therapies are also effective ways to minimize mental health stigma. This intervention aims to educate public health workers, promote social cohesion, and integrate treatment into primary health care, improving treatment into primary health care, improving treatment quality and patient outcomes. The study draws attention to the importance of stigma reduction efforts in the long term in health education and practice emphasis. 2024 IEEE. -
Mental health through forgiveness: Exploring the roots and benefits
Forgiveness is conceptualized as the process of making peace with life. The three sources of forgiveness, another person, oneself, and a situation or circumstance are capable of freeing a person from a negative association to the source that has transgressed against a person. Research studies show the mental health benefits associated with forgiveness. The present study explores the experiences of adults who practice forgiveness, specifically, the indicators of forgiveness, the childhood antecedents, and the benefits of forgiving behavior. The study uses a qualitative research approach following a phenomenological framework. A total of 12 adults, ranging from 25 to 40 years of age, who received a high score on Heartland Forgiveness Scale were included in the study. Using semi-structured in-depth interviews, their personal experiences were explored. The data were analyzed using thematic analysis. The themes emerged show that the childhood antecedents of forgiveness are parental influences and early childhood experiences. The indicators of forgiving behavior include positive emotional state, empathy and perspective taking, and religiosity. The themes identified are enhanced sense of well-being, improved self-acceptance, and competence to deal with challenges. Forgiveness enhanced physical and psychological well-being. The findings of the study have several implications for religious leaders, teachers, parents, mental health professionals, and trainers. 2016 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Mental health treatment: Exploring the potential of augmented reality and virtual reality
By producing immersive, individualized, and captivating therapeutic experiences, augmented reality (AR) and virtual reality (VR) may significantly transform mental health treatment. These technologies provide efficacious resolutions for exposure therapy, augmenting conventional methodologies, mitigating social disapproval, and fortifying the therapeutic alliance. Virtual and augmented reality increase the accessibility and convenience of therapy by enabling highly individualized interventions. Training for mental health professionals, rigorous research, compliance with data privacy regulations, and adherence to ethical standards are essential for responsible use. Augmented reality (AR) and virtual reality (VR) can expand the accessibility of mental health services as costs decrease, thereby ultimately enhancing the welfare of those in search of assistance and recovery. Incorporating augmented reality and virtual reality into clinical practice may make mental health treatment more engaging, effective, and individualized. 2024, IGI Global. All rights reserved. -
Mental Workload Estimation Using EEG
Mental workload contributes considerably to the outcome or the performance of any task. The concern of human workload increases during a human-machine collaboration task or in a multitasking environment. This paper presents a comparative study of machine learning algorithms used to estimate workload using Electroencephalography (EEG) data. An open-access EEG dataset acquired during a 'simultaneous capacity (SIMKAP) experiment' and 'no task' is used to create and validate models for binary classification of workload as present and absent respectively. The paper presents an implementation of various classification models that use EEG data to predict the workload. In this paper, implementation for KNN classifier (57.3%), Random Forest classifier (57.19%), MLP network classifier (58.2%), CNN+ LSTM network classifier (58.68%), and LSTM network classifier (61.08%) has been reported. The paper can be further extended to study operator workload in real-time using a brain-computer interface paradigm for any kind of task in a real-world application. The workload classification can be further used in human-machine tasks to decide task allocation between the system to achieve optimal performance in a complex critical system. 2020 IEEE. -
Mentha spicata assisted AgCuO nanocomposite enables anti-diabetic and vitamin-C sensing activities
Diabetes mellitus (DM), a multifactorial chronic health condition, affects a sizable portion of the global population, and more people are expected to contract it in the future, according to the World Health Organisation (WHO). Diabetes mellitus can be treated with conventional drugs, but most of the medications have a variety of side effects. The use of nanocomposites (NCs) to treat diabetes has been prioritized in this scenario. In this study, AgCuO NCs were synthesized using a green method using Mentha spicata leaf extract and their physicochemical properties were investigated with a variety of analytical techniques. According to an extensive in vivo and in vitro analysis of the biological activities of as-synthesized AgCuO NCs, AgCuO NCs possess effective antibacterial, anti-diabetic, and anti-hyperlipidemic characteristics. When AgCuO NCs are administered to STZ-induced animals in a concentration-based manner, the blood levels of inflammatory and liver marker enzymes are reduced and antioxidant enzyme levels are increased. Besides, AgCuO NCs exhibit excellent sensing activity with a limit of detection of 86 nM against Vitamin-C. This study reveals that AgCuO NCs derived from Mentha spicata may, therefore, prove to be a very successful anti-diabetic and biosensor candidate in the future. 2024 Elsevier B.V. -
Mentors perceived interest, motivation, and volunteering intention at DREAMS after school intervention programme
DREAMS stands for Desire, Readiness, Empowerment, Action, and Mastery for Success. Dreams afterschool intervention programme (ASIP) is to empower children who are weak in psychosocial skills to realize their full potential and to plan for a successful life with the help of college student mentors and senior community mentors. The present study explored the college student mentors interest and motivation to serve at DREAMS and the volunteering intention to stay or discontinue as mentors. The study bases its investigation purely on the mentors revelation of their experiences of DREAMS ASIP. Study followed phenomenological inquiry method and conducted semi-structured interview with 10 college-student mentors, which included 6 active mentors and 4 dropouts. A face-to-face interview conducted by the researchers recorded all the unique points diligently and conducted the data analysis using thematic analysis. Study found 3 main themes and 12 subordinate themes out of thematic analysis. The master themes are mentors interest, mentors motivation, and mentors volunteering experiences. The results section of the article presents the details of themes and sub-themes along with few excerpts of interviewees. Implications of the study might help other ASPs to understand the nature of their volunteers interest and motivation. Future researchers may study factors affecting the mentors strengths and weaknesses within the organisation. 2023 RESTORATIVE JUSTICE FOR ALL. -
Mergers and acquisitions in India Information Technology Industry and its impact on shareholders wealth
International Journal of Research in Commerce, IT & Management Vol. 2, Issue 4, pp. 118-121 ISSN No. 2231-5756 -
Mesoporous iron aluminophosphate: An efficient catalyst for one pot synthesis of amides by ester-amide exchange reaction
A series of metal aluminophosphates (MAlP: M = V, Fe, Co, Ni & Cu) were prepared by co-precipitation method. All the materials were characterized by various physico-chemical techniques. The materials were found to be mesoporous and moderately acidic. The catalytic activity of the materials was investigated in the synthesis of benzamides in a single pot reaction under solvent free refluxing conditions from methyl benzoate and different amines. Iron aluminophosphate was found to be the most effective catalyst for the synthesis of benzamides with 100% selectivity. The isolated yield of benzamide varied from 46% to 100% depending on the nature of amine. A possible reaction mechanism has been proposed which correlates the surface acidity and catalytic activity of the catalyst. The catalyst could be recycled for about three times without any appreciable loss in activity, thus making the method ecofriendly and economical.