Mr Muralidhar Pantula
@pondiuni.edu.in
Department of Computer Science
Pondicherry University
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
A. Mahalakshmi, Muralidhar Pantula, and Bethala Shirisha
AIP Publishing
Thandu Nagaraju, T. N. Chitti, and Muralidhar Pantula
AIP Publishing
Muralidhar Pantula, A. Mahalakshmi, and Thandu Nagaraju
AIP Publishing
Muralidhar Pantula
Inderscience Publishers
Anusha Penugonda and Muralidhar Pantula
Springer Nature Singapore
Muralidhar Pantula and K S Kuppusamy
Oxford University Press (OUP)
Abstract Evaluating readability of web documents has gained attention due to several factors such as improving the effectiveness of writing and to reach a wider spectrum of audience. Current practices in this direction follow several statistical measures in evaluating readability of the document. In this paper, we have proposed a machine learning-based model to compute readability of web pages. The minimum educational standards required (grade level) to understand the contents of a web page are also computed. The proposed model classifies the web pages into highly readable, readable or less readable using specified feature set. To classify a web page with the aforementioned categories, we have incorporated the features such as sentence count, word count, syllable count, type-token ratio and lexical ambiguity. To increase the usability of the proposed model, we have developed an accessible browser extension to perform the assessments of every web page loaded into the browser.
Taushif Anwar, V. Uma, Md. Imran Hussain, and Muralidhar Pantula
Springer Science and Business Media LLC
Muralidhar Pantula and K S Kuppusamy
Oxford University Press (OUP)
AbstractThe power of the WWW (World Wide Web) lies in the adoption of multiple types of media, which makes effective communication of content. Videos have emerged into a quick and efficient information delivery channel for users. To make a video accessible to persons with disabilities, several approaches have been proposed, which include various accessibility features such as closed captions and video descriptions. Captioning agencies use English as a primary language for creating captions, which cause problems for persons with low literacy skills. Ambiguity in the video affects the persons with low literacy skills and senior citizens and it leads them to consume more time in identifying/capturing the intended meaning. As the closed captions run along with the video frame, the comprehension is an issue. For predicting the readability assessment of closed captions for persons with low literacy skills, we developed a statistical formula based on the lexical and semantical ambiguity of the context. As a case study, caption files of top 50 English movies (as per IMDB top rated movies chart) were chosen and their readability scores were calculated. In addition, a machine learning model was developed using the ambiguity feature set in assessing the readability score of the closed captions. The result shows, our model is predicting the readability score with an accuracy of 92.6%.
Aedunuri Sambaraju, Muralidhar Pantula, and K. S. Kuppusamy
Springer International Publishing
Today’s Digital World is evolving rapidly and the smartphone usage has became mandatory. People use smartphones to get services like email, education, business, social communication, etc. For each service category, there are plenty of applications (Apps) available in the market. Along with Apps usage, it is obvious that a user need knowledge on securing devices and private data. We analyzed Naive Android Smartphone Users (ASUs) on different Security Areas where awareness is in need to secure the device as well as the data. The responses indicates that majority of the participants have a fear of Malicious Attacks on their private data, business information and financial transactions.
Muralidhar Pantula and K. S. Kuppusamy
Springer Science and Business Media LLC
Inclusion of online videos on a website attracts a large number of audience because of its ease of perception. Even though rendering videos on the web is advantageous, persons with disabilities face difficulties in accessing the content. Web Content Accessibility Guidelines (WCAG) has recommended closed captions for persons with hearing problems and Audio descriptions for the persons with visual problems, to remove the barriers in making the video content accessible. In this paper, we have incorporated a technique called Narrating the scene before the act. With this, persons with visual impairments will get a proper understanding of the context of the scene and they will be in a better position to easily grasp the content. We have designed a tool, entitled AuDIVA (Audio Description Inserter for Video Accessibility) which will insert the audio descriptions before the scene in the video at specified intervals. A survey conducted shows that the technique eases tasks for web developers to provide audio descriptions in the video.
Muralidhar Pantula and K. S. Kuppusamy
Springer Singapore
Identification of complex words is an interesting research problem with various application scenarios such as text simplification. There are various approaches to identify complex words either by incorporating the complete sentence in which the word appears or by focusing only on the word. This paper falls under the later category, which employs intra-word features in classifying a word either as simple or complex. A model termed CORDIF (COmplex woRD identification with Intra-word Features). The proposed methodology incorporates 19 intra-word features. These features are harnessed to train a machine learning model. A dataset termed as CWIdataset is built with the proposed set of intra-word features. With the proposed feature-set, an accuracy level of 84.75% was achieved. Later using this model, we have tested for identifying the complex words for nonnative persons. As a result, we concluded that for identifying complex words, personalized systems are needed.
Muralidhar Pantula and K. S. Kuppusamy
Association for Computing Machinery (ACM)
With the ongoing prolific expansion of the size of the World Wide Web, the quantity of video content is also expanding. With this massive increase in size, users encounter a serious problem when trying to decide which videos to spend their time on. Moreover, as a result of our modern-day faster lifestyles, users wish to consume the contents of the video as quickly as possible. This article proposes a model, entitled Fast Captions , that enables users to consume the video more quickly with the help of closed captions. The proposed model incorporates a temporal summarization of the captions that helps in understanding the contents of the video more quickly. A prototype implementation of the proposed Fast Captioning model is developed with the Facilitas media player, which allows the user to select the playing speed and renders the video with summarized captions. The results of the experiments conducted with the implementation confirms the acceptance of the proposed Fast Captions model with an acceptance rate of 92%.
Muralidhar Pantula and K. S. Kuppusamy
Springer Singapore
Video content has become one of the most noticeable online trends of recent times. It is no secret that videos have become a staple of everyone’s life. WCAG 2.0 suggested that closed captioning is needed to provide accessible audio content for the audience who are Deaf and Hard of Hearing due to their disability in pursuing the auditory information. Caption files are plain text files with time codes information for each frame. Readability of caption is one major challenge, due to variation in speaking rate and reading rate. The time duration of caption frame affects the flow of text perceived by the reader. This paper proposes a novel model for caption readability based on time dimension. The proposed algorithm calculates the readability of each frame corresponds to the time duration. As a result, we analyzed the caption frames with respect to time, word count, and syllables and identified that the time gap enhances the caption readability.
B. Ramesh, S. A. Bhavani, and P. Muralidhar
Springer India
This paper considers the problem of cryptanalysis of cipher streams. There are some tasks that improve the existing attacks and attempt to make eminent the partitions of ciphertext resulted by the encryption of plain text in which parts of the text are arbitrary and non-arbitrary. This paper delivers a tutorial of symmetric cryptography using LFSR with DNA prospective. The essential information speculative and computational properties of classic and contemporary cryptographic systems are exhibited, followed by scrutinization of the application of cryptography to the security of VoIP regularity in network organizations using LFSR scenario with the help of DNA using Bio-informatics. The implementation program is developed by java2.