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Whispered Speech Emotion Recognition with Gender Detection using BiLSTM and DCNN
Emotions are human mental states at a particular instance in time concerning ones circumstances, mood, and relationships with others. Identifying emotions from the whispered speech is complicated as the conversation might be confidential. The representation of the speech relies on the magnitude of its information. Whispered speech is intelligible, a low-intensity signal, and varies from normal speech. Emotion identification is quite tricky from whispered speech. Both prosodic and spectral speech features help to identify emotions. The emotion identification in a whispered speech happens using prosodic speech features such as zero-crossing rate (ZCR), pitch, and spectral features that include spectral centroid, chroma STFT, Mel scale spectrogram, Mel-frequency cepstral coefficient (MFCC), Shifted Delta Cepstrum (SDC), and Spectral Flux. There are two parts to the proposed implementation. Bidirectional Long Short-Term Memory (BiLSTM) helps to identify the gender from the speech sample in the first step with SDC and pitch. The Deep Convolutional Neural Network (DCNN) model helps to identify the emotions in the second step. This implementation is evaluated using the wTIMIT data corpus and gives 98.54% accuracy. Emotions have a dynamic effect on genders, so this implementation performs better than traditional approaches. This approach helps to design online learning management systems, different applications for mobile devices, checking cyber-criminal activities, emotion detection for older people, automatic speaker identification and authentication, forensics, and surveillance. (2023), (Iranian Academic Center for Education). All Rights Reserved. -
WHETHER STUDENTS CONSIDER PLAGAIRISM AS AN ETHICAL ISSUE
New media play an important role in the spreading of plagiarism in the modern world. The facilities that are provided by new media like websites; blogs etc provide information to the knowledge seeker which may cause for plagiarism in many cases. Plagiarism is an issue faced by academic field and researcher due to the influence of new media. This paper is studying whether students consider plagiarism as ethical issue. Study is analyzing students attitude towards plagiarism especially students attitude toward online plagiarism. This is a study conducted using both qualitative and quantitative methods. The study is very much important in the contemporary time due the changing treads in the concept of academic due to the impact of new media and information flow. The paper evaluates the understanding of student regarding plagiarism. The study is also evaluating the factors that force students to do plagiarism in their works. The study uses the techniques like survey, in-depth interview and focus group discussion to reach conclusion. -
Whether shoppers of tier I city are aware about multi-brand outlets? /
Asian Journal Of Management, Vol.7, Issue 3, ISSN: 0976-495X (Print), 2321-5763 (Online). -
Whether CSR is internalized in corporate India? An empirical study
Purpose: The purpose of this research paper is to examine whether Corporate Social Responsibility is internalized in Corporate India?. Design/Methodology/Approach: The primary data were used to meet this papers main objective. The structured questionnaires were sent to 2100 managerial people in different sectors of corporate through email and finally 318 responses were received. These figures represent an acceptable response rate of 15 %. The collected were analysed and identified the findings with the help of appropriate statistical tools. Findings: The results demonstrate that there is significant difference among senior and top managers of the corporate India towards internalisation of CSR practices. Further, there is no difference between the managers personal profile and their perceptions CSR practices. The identified results are having managerial implications in the Corporate in India. Originality/Value: The authors main contributions are: Theoretical approach particularly stakeholder model of CSR has been discussed and made it link to the present days CSR practices of corporate India. Secondly the identified results are having managerial implications towards successful CSR strategy for the corporate India. 2019, Institute of Advanced Scientific Research, Inc.. All rights reserved. -
Where to Check Homework? The Emphasis on Supportive Feedback via Social Media by Teachers in CALL and Its Consequences on EFL Learners' Self-assessment, Academic Success, Academic Enjoyment
This study investigates the impact of Facebook-mediated supportive feedback on English as a Foreign Language (EFL) learners' self-assessment, academic enjoyment, and academic success in a Computer-Assisted Language Learning (CALL) context. Using a sequential exploratory methodology, this study holistically investigates the research objectives using qualitative and quantitative approaches. Two intact classrooms of lower-intermediate EFL students in an Iraqi language institute were selected; one class was designated as the experimental group receiving Facebook-mediated tasks and the other as the control group using conventional teaching strategies. Among the tools for data collecting were a teacher-made test, semi-structured interviews, and observation. Compared to the control group, the experimental groupwhich received extra Facebook-mediated tasks and conventional course materialsshowcased notably greater degrees of self-assessment, academic enjoyment, and academic success. Positive perceptions of Facebook-mediated interactions were found through the qualitative analyses of observations and interviews, thereby stressing learners' higher motivation, collaboration, and sense of community. The implications of the study are discussed. 2024, The Pacific Association for Computer Assisted Language Learning (PacCALL). All rights reserved. -
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Wheat Yield Prediction using Temporal Fusion Transformers
In precision framing, Machine Learning models are an essential decision-making tool for crop yield prediction. They aid farmers with decisions like which crop to grow and when to grow certain crops during the sowing season. Many Machine Learning algorithms have been used to support agriculture yield prediction research, but it is observed that Deep Learning models outperform the benchmark Machine Learning algorithms with a significant difference in accuracy. However, though these Deep Learning models perform better, they are not preferred or widely used in place of Machine Learning models. This is because Deep Learning methods are black box methods and are not interpretable, i.e., they fail to explain the magnitude of the impact of the features on the output, and this is unsuitable for our use case.In this paper, we propose using Temporal Fusion Transformer (TFT), a novel approach published by Google researchers for wheat yield prediction viewed as a Time Series Forecasting problem statement. TFT is the state-of-the-art attention-based Deep Learning architecture, which combines high-performance forecasting with interpretable insights and feature importance. We have used TFT to perform wheat yield prediction and compare its performance with various Machine Learning and Deep Learning algorithms. 2023 IEEE. -
Whats the best time to give work? A study on relationship between employee moods and performance at different time intervals
Employees change their behavior many times in a day due to many factors. It is not uncommon to see any employee being agitated over petty issues at work place. This paper aims at identifying meaning, relationships between moods and performance. Employees decision-making abilities depend on mood and his mood depend on his personality, work environment variables such as protocols, procedures, work events, dynamics of formal and informal communication. We equate this daily swing to three-time frames named morning, afternoon and evening. Our attempt has been to try to establish a relationship between moods and emotions and employee performance which can increase the productivity level of the employee. This research intends to establish a more robust relationship and involves better evaluative and interpretive models to cope with the non-linearitys related to the complexity of the model and facilitate better decision-making with more accurate and intricate or comprehensive yet simple approach. Development of such relationship will help managers in dealing with the employees and take measures to increase productivity by adopting suggestions and conclusions from this study. IJSTR2019. -
What Numbers Never Revealed: Tracing Dalit Christian Modernity Through Malayalam Literature
Kerala has a long-standing history of Christianity as well as conversions. Conversions can be dated back to the fifteenth and sixteenth centuries, which saw a large number of slave caste conversions. For the slave castes of KeralaPulayas and ParayasChristianity offered a salvation from the circle of pollution. Scriptures provided the slave castes new vistas of knowledge which they encultured to form a counter discourse against the public sphere set up by the dominant castes. The public sphere of the Malayalee psyche was formed by the ideas of caste pollution, which restricted the slave castes from accessing the social space. A new Dalit perspective on the religious consciousness of the converted Christians will show the role of the Bible, Original Sin, and Repentance on their daily lives. Dalit Christian literature becomes the primary source where Christianity metamorphoses into an oppositional force in resisting oppression as well as in creating a social space with agency. 2022 Indian Institute of Management, Ahmedabad. -
What is Remembered in Pandemic: A Commentary on the Mediated Memories of Piety in COVID-19
The paper explores how the experiences of the present pandemic are shaped by the memories of popular religious piety during past pandemics and epidemics. Taking insights from the works of Astrid Erll and Reinhart Koselleck, the process remembering-imagining system within the context of the pandemic is discussed by tracing the reemergence of pandemic deities and narratives of piety in India. Using digitally documented and disseminated narratives on piety emerging during COVID-19, an attempt is made to understand how these narratives shape the experiences, responses, and collective memory of the pandemic. Through a discussion of the shift in the imagination of political leadership and the moral responsibilities of the community, an attempt is made to highlight the mode in which the narratives on piety shape the contours of a time that is otherwise unimaginable. The mediated memories of popular religious piety make it possible to remember similar crisis times and to imagine and reinstate the social order that is threatened by this sudden unimaginable crisis. The paper thus argues that within the context of India, popular religious piety, though often overlooked, becomes a significant part of making sense and shaping the experiences of the pandemic time. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
What is beautiful is good: An evalutation of effectiveness of attractiveness in celebrity endorsements
The studies in the field of marketing have shown that characteristics of the source will influence persuasiveness of an advertisement. Attractiveness is one such celebrity characteristic that is widely studied by researchers in the field of marketing. However, still, literature failed to explain how attractiveness of celebrity endorsers influenced purchase intentions. This study tried to fill this gap by modelling the influence of celebrity attractiveness on purchase intention. It also evaluated the effect of respondents' gender on the model. The data collection for the study were carried out during March - June 2017. The study found that the effect of celebrity attractiveness on purchase intention was mediated by celebrity brand fit, attitude towards the advertisement, and attitude towards the brand. The study also evaluated the moderating effect of respondents' gender using chi- square analysis, which found no significant model difference among male and female respondents. These findings indicated that celebrity attractiveness created purchase intention in a mediated manner among the respondents, irrespective of their gender. 2018, Associated Management Consultants Private Limited. -
What fuels the employees in startups?: Data on hybrid/colocated/virtual working environment towards efficiency
Purpose: This article examines the concepts of workplace satisfaction and productivity using data. The data will be used to investigate the variables contributing to employee satisfaction to achieve optimum efficiency through various startup working environments. Design/ Methodology/ Approach: Descriptive causal investigation. A structured instrument scale questionnaire via the internet to 256 employees working for highly organized organizations in Bangalore, India, using Qualtrics. The researcher adopted a simple random sampling method. Findings: The respondents in the data believed that the pre-covid workplace was advantageous. The hybrid model's prevalence of autonomy and flexibility increases work productivity. When employees are given more responsibility, their job satisfaction and productivity increase. Research Limitations/ Implications: Collecting data in a startup was extremely difficult due to the difficulty of obtaining permission, and through the analysis, it was determined that businesses have a responsibility to provide supplemental benefits to remote employees, which may increase the level of job satisfaction and enjoyment experienced by these individuals. 2023 The Author(s) -
What drives the wheels of evolution in NGC 1512?: A UVIT study
Context. Environmental and secular processes play a pivotal role in the evolution of galaxies. These can be external processes such as interactions or internal processes linked to the action of bar, bulge, and spiral structures. Ongoing star formation in spiral galaxies can be affected by these processes. By studying the star formation progression in the galaxy, we can gain insights into the role of different processes that regulate the overall evolution of a galaxy. Aims. The ongoing interaction between the barred-spiral galaxy NGC 1512 and its satellite NGC 1510 offers an opportunity to inves- tigate how galactic interactions and the presence of a galactic bar influence the evolution of NGC 1512. We aim to understand the recent star formation activity in the galaxy pair and thus gain insight into the evolution of NGC 1512. Methods. The UltraViolet Imaging Telescope (UVIT) on board AstroSat enables us to characterise the star-forming regions in the galaxy with a superior spatial resolution of ?85 pc in the galaxy rest frame. We identified and characterised 175 star-forming regions in the UVIT far-ultraviolet (FUV) image of NGC 1512 and correlated with the neutral hydrogen (Hi) distribution. Extinction correc- tion was applied to the estimated photometric magnitude. We traced the star-forming spiral arms of the galaxy and studied the star formation properties across the galaxy in detail. Results. We detect localised regions of star-formation enhancement and distortions in the galactic disc. We find this to be consistent with the distribution of Hi in the galaxy. This is evidence of past and ongoing interactions affecting the star formation properties of the galaxy. We studied the properties of the inner ring. We find that the regions of the inner ring show maximum star-formation-rate density (log(SFRDmean[M yr?1 kpc?2]) ? ?1.7) near the major axis of the bar, hinting at a possible crowding effect in these regions. The region of the bar in the galaxy is also depleted of UV emission. This absence suggests that the galactic bar may have played an active role in the redistribution of gas and quenching of star formation inside the identified bar region. We therefore suggest that both secular and environmental factors might be influencing the evolution of NGC 1512. The Authors 2023. -
Whale Optimization Based Approach toCompress andFasten CNN forCrop Disease andSpecies Identification
In recent years deep learning and machine learning have been widely researched for image based recognition. This research proposes a simplified CNN with 3 layers for classification from 39 classes of crops and their diseases. It also evaluates the performance of pre-trained models such as VGG16 and ResNet50 using transfer learning. Similarly traditional Machine Learning algorithms have been trained and tested on the same dataset. The best accuracy using proposed CNN was 87.67% whereas VGG16 gave best accuracy of 91.51% among Convolution Neural Network models. Similarly Random Forest machine learning method gave best accuracy of 93.02% among Machine Learning models. Since the pre-trained models are having huge size hence in order to deploy these solutions on tiny edge devices compression is done using Whale Optimization. The maximum compesssion was obtained with VGG16 of 88.19% without loss in any performance. It also helped betterment of inference time of 44.13% for proposed CNN, 56.76% for VGG16 and 63.23% for ResNet50. 2023, Springer Nature Switzerland AG. -
Were the recent air pollution and landfill fires in Brahmapuram at odds with Kerala's vision of sustainable development?
Air pollution is a global issue, as is commercial, and industrial waste disposal. Industrialized cities have poor air quality. Emissions from fossil fuel, solid household resources and industry, uncontrolled construction, and human and natural activity pollution are the main sources. The purpose of the study is to investigate answers to the question: Were the recent air pollution and landfill fire in Brahmapuram at odds with Kerala's vision of sustainable development? The study consists of a content analysis of prominent newspaper reports on the Prisma model of sorting articles on Brahmapuram issues to investigate the issue and assess the acceptance of sustainable development in Kochi. The reports cover the period from March 3, 2023, to April 3, 2023. The content analysis revealed that the contractor's failure to meet their obligations was the immediate cause. However, the ineffectiveness of the State's solid waste management policies, from a general failure of waste segregation at source, posed a threat to sustainable development. The researcher classified the causes of the Kochi waste fire under the following reasons, namely, environmental, economic, social, and political. The researcher concluded that the recent landfill fire and air pollution at Brahmapuram were contrary to Keralas vision of sustainable development. 2024 by the authors. -
Well-being of North Eastern Migrant Workers in Bangalore
This paper explores the quality of life and subjective well-being of north-east migrant workers engaged in various formal and informal jobs in Bangalore. The composite well-being index reveals moderate well-being for the majority of workers. The disaggregated analysis, however, shows poor material conditions of life. Using the Day Reconstruction Method, we also find positive emotions associated with activities such as socialising but negative emotions for work and commuting. With respect to interacting partners, the negative emotions were highest while dealing with clients and customers. We also found positive correlations between life satisfaction and quality of life indicators, most strongly, with job quality. Lower quality of jobs, reported by women in comparison to men, suggests that organisations should aim to create more equal and enabling work spaces for all genders. 2020 Institute for Human Development. -
WELL-BEING AND PROSPERITY: Multidirectional Disciplinary Interactions with Religion
Despite significant advancements in science and technology, religion continues to influence human lives. The twentieth-century perspectives from social sciences, influenced by the secular hypothesis, mainly highlight the negative influence of religion on human progress and practically ignore its influential and positive impact on various fields of knowledge/disciplines. In this paper, we have examined literature from politics, economics, and psychology to understand religions impact on these disciplines and vice versa. We find that religions contribution to human society in the 20th and 21st centuries has been mostly positive, especially in education, healthcare, social justice, economic growth, ethics, and initiatives for eradicating inequality and injustice. For instance, religion provides effective coping measures and strategies when humans face uncertainties and catastrophes and facilitate comfort, confidence, and emotional wellness. Further, we realised that (i) the contemporary research literature in social sciences generally highlights the interaction between religion and various fields of knowledge in a unidirectional way i.e., religion influencing disciplines and not how disciplines influence religion, and (ii) that it fails to reveal a more complex multidirectional and circular relationship between religion and social sciences. This paper proposes ways to bring together social scientists and religious scholars to facilitate the much-needed discussion on the multidirectional relationship between religion and social sciences, thereby paving the way toward the well-being of individuals and social transformation. 2022 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore),. -
Well-being and Career Decision-making Difficulties Among Masters Students: A Simultaneous Multi-Equation Modeling
There is a stellar upsurge in the number of persons pursuing a masters level of education as well as the institutions offering it in the current generation. Nevertheless, an explicit theoretical and empirical implication of how the tutelages, at this level, shape the well-being of learnerssuch that it could help individuals overcome career decision-making difficulties remains to be elucidated. The present study addressed two major objectives. Firstly, we investigated the well-being of masters degree students along with career decision-making difficulties in India. Secondly, apart from exploring the possible influence of nationality of the respondents on career decision difficulty, the study expanded the literature on career decision-making difficulties to under-researched populations in developing countries. Through a cross-sectional research design, we recruited a sample of 136 masters degree respondents. The result reveals that while the composite well-being resources significantly influenced Career Decision Difficulties, the nationality of respondents appeared not as a germane factor in this context. Following the evaluation of the direct effect of individual well-being resources; Self-acceptance and Personal growth proved to have a statistically significant effect on career decision-making difficulties. Also, among the constituents of career decision-making difficulties studied, lack of readiness appears to be the major concern among the respondents. The findings expand the literature on cognitive, vocational, and organization science vis-a-vis career decision-making difficulties and provide useful insights for educational institutions and practitioners. 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
Weighted Mask Recurrent-Convolutional Neural Network based Plant Disease Detection using Leaf Images
Large losses in output, money, and quality/quantity of agricultural goods are incurred due to plant diseases. Seventy percent of India's GDP is tied to the agricultural sector, thus protecting plants from diseases is crucial. For this reason, it is important to keep an eye on plants from the moment they sprout. The usual approach for this omission is naked eye inspection, which is more time-consuming, costly, and requires significant skill. Thus, automating the method for detecting diseases is necessary to speed up this process. It is imperative that image processing methods be used in the creation of the illness detection system. Disease detection involves a number of processes, including Weighted Mask R-CNN, GLCM feature extraction, Multi-thresholding image pre-processing, and K means image segmentation classification. The weighted Mask R-CNN outperforms the standard RNN, the Mask R-CNN, and the CNN in terms of accuracy and recall in analytical trials by a significant margin. 2023 IEEE. -
