Browse Items (1473 total)
Sort by:
-
Effect of Phonological and Phonetic Intervention on Proficiency in English Pronunciation and Oral Reading Among Bengaluru Teacher Trainees
The current research aimed to determine the effect of phonological and phonetic intervention in enhancing proficiency in English pronunciation and oral reading among teacher trainees. The study adopted a single-group pre and post-test intervention design. The researcher developed intervention modules on phonology and phonetics, and a segmental approach was adopted to teach individual sounds. The research design was executed in five stages: experts' opinions on the need for such a study, a preliminary study to find the need for the study, the development of intervention modules and validation of the modules, the pilot study to check the reliability of the tools, and the main study. The researcher applied Oscillo-graphic and observation methods to analyse and test the participants' pronunciation and oral reading progress during the experiment. Communicative Language Learning (CLL) and Audiolingual approaches were adopted to teach individual sounds to participants. The National Assessment of Educational Progress Scale for Reading and Pronunciation (NAEP 2012) was adopted to measure the scores. The other instruments, i.e., audio-to-test phonetic transcription software and Audacity recording software, were used in the experiment to record and analyse the audio clips. The experiment was conducted on n=104 teacher trainees of Bengaluru, India. The current study targeted teacher trainees/ B Ed college students of English method as a population. The population of teacher trainees was 1470 English methods from Bangalore north, south, and central. Further, the sample size for the main study was 104, and it was selected through a stratified random sampling technique. The assessment tools overall reliability (Cronbach Alpha value) (NAEP) on Pronunciation and Oral reading is 0.873. The data normality was tested with the Kolmogorov-Smirnov test. The data EFFECT OF PHONOLOGICAL AND PHONETIC INTERVENTION was normally distributed. Hence, the data was not normally distributed; the non- parametric tests were used to test the hypotheses. The hypotheses testing on phonological and phonetic awareness revealed the difference between pre- intervention and post-intervention scores in phonological and phonemic awareness and oral reading among teacher trainees, the sig. Value is less than 0.05 across all the attributes. The Wilcoxon signed rank test revealed the scores after the intervention, a post-test with a statistically significant value of 0.001. The post-test score, which was after the intervention, is significantly higher. The values across all the attributes related to oral reading and pronunciation with a statistically significant value of 0.001. The other hypotheses testing on gender, age, and qualification, the Mann-Whitney test, and Kruskal Wallis were used, and the results were not statistically significant. The statistical test was used to test the progressive improvement of teacher trainees during the intervention, and it was statistically significant with 0.001 across all the attributes. The data analysis revealed a positive impact of intervention at the post-test on teacher trainees. The study has navigated the need for language proficiency among teacher trainees, especially in English pronunciation and oral reading. The study substantiates the evidence that effective intervention and teachers' knowledge of pronunciation would enhance proficiency levels in pronunciation and oral reading among teacher trainees. The study also hopes that Policy Makers, Universities, B.Ed. Colleges and teacher educators will be beckoned to use technology-integrated intervention to teach phonology and phonetics. -
Persuasive techniques used by advertisers in television commercials /
The purpose of this research is to observe the persuasive techniques used by advertisers in television commercials focussing on eight different advertisements belonging to four different categories. The researcher concentrates on the different components utilized by promoters to summon passionate reaction on the viewers/consumers. The commercials chosen by the researcher depict essential connections that are esteemed and kept up in the society. -
Multi Parameterized Modified Local Binary Pattern for Lung Cancer Detection by Deep Learning Methods
The research work is focusing on developing a classification model for Lung Cancer detection by integrating the image features with Modified Local Binary Pattern (MLBP), Modified Principal Component Analysis (MPCA), newlinesymptoms and Risk factors using Deep Learning methods and converting the image features into three dimensional (3D) images. The aim of this research is to identify the malignant and normal tumours from the Computer newlineTomography (CT) images with improved accuracy. The 2D CT images of Lung Cancer patients have been preprocessed with Median and Gabor filtering methods and watershed segmentation. The CT images are also newlineprocessed with the Zero Component Analysis (ZCA) whitening and Modified Local Binary Pattern. The processed image is used in the research for classification. The Lung Cancer dataset in the research are collected from newlinevarious medical colleges. The dataset contain CT images with Lung Cancer and without Lung Cancer. The research is conducted by integrating the selected Image features, Risk factor and symptoms of Lung Cancer of the newlinesame patients. The Integration using feature selections is carried out with Modified Principal Component Analysis. The Modified Principal Component Analysis is used in the research to reduce the time complexity. The results are evaluated with Gini coefficient, Confusion Matrix parameters and ROC newlinecurve. Two Dimensional (2D) CT images are converted into a Three Dimensional (3D) image for the clarity and the visibility of Lung Cancer nodules. The conversion from 2D to 3D has been using combining two methods, the orthogonality and visualization of 4D rotation. This enabled to find the location of the Lung Cancer from different angle and with different viewpoints. The 3D image shows the location of the Lung Cancer by Four Dimensional (4D) visualization and 3D rotation, thus giving clarity to the newlineexisting 2D images. -
-
Construction of Prime Time Television News Discussions
Studies in the western context have shown consistent observations of Television News being one of their prime modes of news and current affairs in the past. In India, watching the news has been an age-old requirement, for many reasons. English news in a non-native English-speaking country like India has encouraged citizens to learn the language, engage in focused viewership and rely on Television news for stories, news, views, and the episodic reality. Ever since news reception was transitioned to the realm of social media and new media, Television prime time news strived to be in the limelight. To understand the existence of prime time news, the study focused on two objectives : to identify constituents of communicative techniques framed in prime time news discussions of Indian English Television News Channels and to establish the role of prime time News Discussions as creators of complex news narratives. With the help of Critical Discourse Analysis (CDA) as the umbrella theory, Multimodal Discourse Analysis (MDA), and Stuart Hall s Encoding and Decoding, the research progressed to understand the ways and means to analyse news. Each of the episodic news presentations from 5 December 2017 to 13 December 2017 pertaining to prime-time news debates of Republic TV and Times Now were used. were analysed using a qualitative method of textual analysis. The manifestation of all cues on the screen were deconstructed to comprehend their existence. Each episode was connotatively derived to understand conversations and use of graphics. There are multiple findings under each of the units. On understanding the manifestation and intermingling of various units of analysis with each other, it was unanimously concluded that polarization of opinions is the key to engage a concise news narrative of the day. Whilst important news is not the source, political debates, underestimation, and complex visualization enhance the brand name of the news channel. -
Use of social media applications in Indian governing policies /
New media is prevalent tool and a mass medium since it became associated with social networking. Apart from public relation companies and executives, Government agencies are also using new media like YouTube, Facebook and Twitter extensively. The study aims to depict of how social media and mobile applications are being used by governments to inform, engage and serve people. -
A psychoanalytical study of surrealist elements in films /
Psychoanalysis has over the years been a centre of attraction and intense research and study by critiques, psychologists, sociologists, etc. due to its unique outlook at the world, Freud’s psychoanalytical theories have found their way onto films, which use the creativity of visuals, sounds, effects etc to create the world Freud claims to be hidden behind the human consciousness. No film can escape psychoanalysis as it frames the underlying reasoning behind human behavior and thus this forms a most intriguing realm of study. -
Pain detection system in real time healthcare environment
The negative feeling of pain is often involuntarily expressed through facial expressions. Facial expression therefore is an important non-verbal cue to determine if a person is in pain. This property can be applied for diagnosis of pain especially among patients who are differently challenged and lack the ability of expressing their issue. In spite of the developments made so far, this field still lags behind in finding pain expressing faces in an uncontrolled environment through unprocessed real time images and videos. To bridge this gap, the study proposed a
hybrid or fusion model that could adequately detect a face expressing pain. The model was executed with inputs taken from pre-recorded or stored videos and live streamed videos. It involved the combination of Patch Based Model (PBM), Constrained Local Model (CLM), and Active Appearance Model (AAM) in concurrence with image algebra. -
Pain Detection System In Real Time Healthcare Environment
The negative feeling of pain is often involuntarily expressed through facial expressions. Facial expression therefore is an important non-verbal cue to determine if a person is in pain. This property can be applied for diagnosis of pain especially among patients who are differently newlinechallenged and lack the ability of expressing their issue. In spite of the developments made so far, this field still lags behind in finding pain expressing faces in an uncontrolled environment through unprocessed newlinereal time images and videos. To bridge this gap, the study proposed a hybrid or fusion model that could adequately detect a face expressing pain. The model was executed with inputs taken from pre-recorded or stored newlinevideos and live streamed videos. It involved the combination of Patch Based Model (PBM), Constrained Local Model (CLM), and Active newlineAppearance Model (AAM) in concurrence with image algebra. This allowed the efficient pain identification from raw home-made stored newlinevideos and live stream even through a bad recording device and under poor illumination. The hybrid model was implemented in a frame-by-frame manner for feature extraction and pain detection. The feature extraction part was done in pixel-based and point-based representation. For point-based representation, a concept called image algebra was used. For classification, three approaches viz. histogram technique, Feed newlineForward Neural Network (FFNN), and Multilayer Back Propagation Neural Network (MLBPNN) were implemented and analyzed. The videos newlineof different subjects showed facial expressions of pain::face, not::pain face and neutral::face. A home-made dataset was produced for storing the videos which was later used as the input and the selected features were stored. This dataset served as the training set for the proposed model. Though the data was not highly sensitive it was sufficient to confer adequate information for detecting pain expression. -
-
-
Outcome Evaluation of Child Sponsorship Programme of A Non-Governmental Organization
Child sponsorship programme is a vital tool for the integral development of the children at risk. Family based child sponsorship programme is one of the best services for the marginalized children which ensure their education while also respecting the rights of the children. The current study attempts to evaluate the outcome of child sponsorship programme of a non-Governmental organization newlinethrough a mixed method. Quasi-experimental post-test only design is the methodology used to conduct the study. The study evaluated the programme with regard to Self-esteem, Achievement motivation and family functioning of the sponsored children. The data was collected from 80 individuals for the quantitative study; using 3 standardized scales. Thematic analysis of qualitative data collected by interviewing 5 pairs of beneficiaries of the child sponsorship programme. The data was analysed using SPSS and R. The findings that there is a significant difference in terms of self-esteem and achievement motivation between the two groups of children. With regard to family newlinefunctioning conflict is much lesser among sponsored children (M=20.75) while compared to non-sponsored children (M=43.80). In terms of parenting and intimacy, the sponsored children are having higher score. Also, it was found out that self-esteem significantly mediated the impact of family functioning on achievement motivation of the individual(plt0.05). It is noticed that the effect of family functioning on achievement motivation was 0.504 and the direct effect was found to be 0.333. Selfesteem was found to strengthen the impact of family functioning on achievement motivation.Academic excellence improves the employability of respondents. Employment of newlinethose who received sponsorship can provide financial stability to the family. Therefore, this evaluation study confirmed the phenomenal effect of child sponsorship newlinein realizing inclusivity goals, as well as facilitate the personal, familial, economic, and social growth of sponsored children. -
Information and communication technology integration in education by harare secondary school teachers in relation to school technology culture and their educational leader competencies
Information and Communication Technology (ICT) integration in education refers newlineto using technology in teaching and learning processes. The use of Information and Communication Technology (ICT) in the classroom would solve a lot of the problems related to Zimbabwean secondary school education. It motivates students to learn by providing a variety of learning activities such as watching videos, viewing pictures and models and online quizzes. This interests students who are digital natives and is more applicable to their everyday experiences. newlineStudent participation increases when ICT is used in the classroom as students are newlineconversant with the use of technology. ICT integration in education also allows students to learn in circumstances where there are shortages of teachers. The culture which exists in a school and the competencies of the educational leaders cannot be ignored when planning for and assessing the outcome of ICT integration programs. This study focused on Information and Communication newlineTechnology Integration in Education by Harare Secondary School Teachers, in relation to School Technology Culture and their Educational Leader Competencies . A survey was carried out in government and private secondary schools in Harare, Zimbabwe during the period from October 2012 to mid-2013. The population was all the secondary school teachers in Harare district of Zimbabwe. According to the data obtained from the Ministry of Education in October 2012, the target population of secondary school teachers in Harare was 4 244. The sample size was calculated based on an equation cited from Camorin and Calmorin (2007:230). This newlinegave a sample of 248 teachers from Harare secondary schools. 140 were females and 108 males. Four research instruments were used for data collection: a proforma on demographics, the ICT Integration questionnaire (ICTIQ), the School Technology Culture (STC) Scale and the Educational Leader Competency (ELC) scale. -
-
Integrating Traditional Healing Practices with Cognitive Therapy: Attitude, Preparedness and Perceived Effectiveness among Clients and Therapists
Mental health and well- being has become a serious concern in the Indian health setting. The mental health care has been rapidly increasing. The various approaches involved in mental health has been explored widely in the Indian mental health setting. This research study aims to explore the integrated approach which involves traditional healing practices and cognitive therapy. The aim of this research study is to understand the three main variables attitude, preparedness and perceived effectiveness in clients and therapists while integrating traditional healing practices with cognitive therapy. The traditional healing practices explored in this study are yoga, meditation and mindfulness. The attitude of the clients and therapists towards the integrated approach has been studied. The preparedness of the clients as well as the preparedness of the therapists toward the integrated approach is also the next set of objectives in the research study. The next two objectives have been to study the perceived effectiveness of this approach in clients and therapists. The research study is a qualitative study. The data for the research study has been collected using semi- structured interviews. The data has been analyzed using thematic content analysis. The sample for the study includes 5 therapists and 10 clients who have been involved in this therapeutic approach. The results of the study show that there are two types of attitude clients who have interviewed hold towards the integrated approach. The two types of attitude include positive attitude and apprehensive attitude. The attitude of the therapists towards the approach has been positive and the factors which have led to the positive attitude has been cultural factors, familial background and previous exposure. The apprehensive attitude in clients have been due to the forced participation and past negative experience. The positive attitude of the therapists has been due to prior training and prior positive results. The preparedness and perceived effectiveness observed in therapists and clients have also been studied at length in the research study. The preparedness observed in clients has been due to previous exposure and knowledge and in therapists it has been due to extensive practice and the perceived effectiveness seen in clients. The perceived effectiveness observed in clients have been at three levels. They are physiological well- being, psychological well- being and improved relationships in the family. The perceived effectiveness in therapists have been seen as increased emotional and physical well- being as well as increased competence in the profession. -
-
Classification of Alzheimer's Disease Stages Using Machine Learning Techniques
Alzheimer s disease (AD) is a type of mental disorder which deteriorates the normal functioning of human brain by reducing the memory capacity of an individual. Age is the most common factor for AD and this disease cannot be reversed or stopped. Doctors can only treat the symptoms of AD which include personality changes and brain structural changes. Analyzing neuro-degenerative disorders, neuroimaging plays an important role in diagnosing subjects with AD and other stages of AD. The proposed research identified this gap and using MRI and PET newlineimages for recognizing AD in its early occurrences by the professionals. This helps in tailoring an appropriate treatment procedure for treating AD. As per literature survey, many researchers have worked with convolutional methods like inbuilt skull stripping with two or more conversions and classified with different CNN architectures. The proposed research experimented advanced skull stripping method and classified using deep learning architectures. This research emphasizes the implementation of ResNet50 architecture with T1 weighted MRI and Amyloid PET images for detecting the abnormalities in the brain patterns based on the image attributes. For the proposed experiment, a total of 5000 T1 weighted MRI data and 3000 newlineAmyloid PET data were used. The collected images were pre-processed with noise removal newlinetechniques and skull stripping method. The ResNet50 is used to classify AD from the data newlineobtained from the ADNI dataset. Pre-processed images /data were fed to the tuned for three class classification on ADNI image data at 200 Epochs shows the accuracy of 97.3% for T1 weighted MRI data and 98% for Amyloid PET data. The experimental results of the proposed model prove that it classifies the images according to various stages with better accuracy than the other existing models by achieving excellent results. -
-
-
