Dr. Chetana Prakash - Academia.edu (original) (raw)

Papers by Dr. Chetana Prakash

Recently, significant growth in using online-based learning stream (i.e., elearning systems) have... more Recently, significant growth in using online-based learning stream (i.e., elearning systems) have been seen due to pandemic such as COVID-19. Forecasting student performance has become a major task as an institution is focusing on improving the quality of education and students' performance. Data mining (DM) employing machine learning (ML) techniques have been employed in the e-learning platform for analyzing student session streams and predicting academic performance with good effects. A recent, study shows ML-based methodologies exhibit when data is imbalanced. In addressing ensemble learning by combining multiple ML algorithms for choosing the best model according to data. However, the existing ensemblebased model does not incorporate feature importance into the student performance prediction model. Thus, exhibits poor performance, especially for multi-label classification. In addressing this, this paper presents an improved ensemble learning mechanism by modifying the XGBoost algorithm, namely modified XGBoost (MXGB). The MXGB incorporates an effective cross-validation scheme that learns correlation among features more efficiently. The experiment outcome shows the proposed MXGBabased student performance prediction model achieves much better prediction accuracy contrary to the state-of-art ensemble-based student performance prediction model.

EAI/Springer Innovations in Communication and Computing, 2023

2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Feb 1, 2017

The Internet of Things is an emerging technology across the world, which helps to connect sensors... more The Internet of Things is an emerging technology across the world, which helps to connect sensors, vehicles, hospitals, industries and consumers through internet connectivity. This type of architecture leads to Smart Cities, Smart home, Smart agriculture and Smart World. Architecture of IoT is very complex because of the large number of devices, link layer technology and services that are involved in this system. However, security in IoT is the most important parameter. In this paper, we give an overview of the architecture of IoT with the help of Smart World. In the second phase of this paper, we discuss the security challenges in IoT followed by the security measures in IoT. Finally, these challenges, which are discussed in the paper, could be research direction for future work in security for IoT.

Asian Journal of Computer Science and Technology

Periodontal disease, characterized by alveolar bone loss, is a prevalent oral health condition th... more Periodontal disease, characterized by alveolar bone loss, is a prevalent oral health condition that requires early detection and management to prevent further progression. This paper proposes a novel approach for alveolar bone loss detection and localization in dental X-ray images using the YOLOv5 object detection algorithm. We annotated a dataset of dental radiographs with alveolar bone loss regions and fine-tuned the YOLOv5 model on this dataset. Our approach achieved high accuracy and robustness in detecting and localizing alveolar bone loss regions, with precision, recall, and F1 score exceeding 90%. The real-time processing capabilities of YOLOv5 make it suitable for clinical implementation, providing an efficient and accurate solution for periodontal disease management. The automated alveolar bone loss detection and localization using YOLOv5 can significantly assist dentists in the early diagnosis and treatment planning of periodontal diseases, leading to improved patient outc...

International Journal of Computer and Electrical Engineering, 2012

In this paper, we explore the use of Bessel features derived from speech utterances, to develop G... more In this paper, we explore the use of Bessel features derived from speech utterances, to develop Gaussian mixture speaker models for text independent Speaker Identification. The proposed approach to speaker identification is based on existing methods that employ Gaussian mixtures for the modeling of speakers. However, we have developed the speaker models from the Bessel features derived from the speech utterances, as an alternative to Mel-frequency cepstral coefficients for developing the speaker models. The proposed approach is tested on two databases of ten and twenty speakers respectively and their performance is evaluated. Finally, we have made some suggestions for future work involving the use of Bessel features for text independent speaker identification Index Terms-Gaussian mixture models, Bessel functions, text independent, speaker identification.

Contrast Media & Molecular Imaging

The image enhancement for the natural images is the vast field where the quality of the images de... more The image enhancement for the natural images is the vast field where the quality of the images degrades based on the capturing and processing methods employed by the capturing devices. Based on noise type and estimation of noise, filter need to be adopted for enhancing the quality of the image. In the same manner, the medical field also needs some filtering mechanism to reduce the noise and detection of the disease based on the clarity of the image captured; in accordance with it, the preprocessing steps play a vital role to reduce the burden on the radiologist to make the decision on presence of disease. Based on the estimated noise and its type, the filters are selected to delete the unwanted signals from the image. Hence, identifying noise types and denoising play an important role in image analysis. The proposed framework addresses the noise estimation and filtering process to obtain the enhanced images. This paper estimates and detects the noise types, namely Gaussian, motion a...

BENTHAM SCIENCE PUBLISHERS eBooks, Mar 21, 2023

Asian Journal of Computer Science and Technology

In dental diagnosis, rapid identification of dental complications from radiographs requires highl... more In dental diagnosis, rapid identification of dental complications from radiographs requires highly experienced medical professionals. Occasionally, depending exclusively on a expert's judgement could lead to changes in diagnosis, that could eventually lead to difficult treatment. Although fully automatic diagnostic tools aren’t still anticipated, image pattern recognition has grown into decision support, opening with discovery of teeth and its constituents on X-ray images. Dental discovery is a topic of study for more than previous two decades, depending primarily on threshold and region-based strategies. In this study, we proposed segmentation based Teeth X-Ray images using a couple of machine learning algorithms as well as deep learning algorithms i.e., Support Vector Classifier (SVC), Random Forest algorithm and Convolutional Neural network (CNN) which would help us in accurate identification and classification. This article also presents a comprehensive comparison between t...

The following decade will witness a surge in remote health-monitoring systems that are based on b... more The following decade will witness a surge in remote health-monitoring systems that are based on body-worn monitoring devices. These Medical Cyber Physical Systems (MCPS) will be capable of transmitting the acquired data to a private or public cloud for storage and processing. Machine learning algorithms running in the cloud and processing this data can provide decision support to healthcare professionals. There is no doubt that the security and privacy of the medical data is one of the most important concerns in designing an MCPS. The pervasiveness of smart phones and the advance of wireless body sensor networks (BSNs), mobile Healthcare (m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security and privacy preservation.

2020 International Conference on Inventive Computation Technologies (ICICT), 2020

Medical imaging has become a very important non-invasive diagnosis tool for various diseases. Dur... more Medical imaging has become a very important non-invasive diagnosis tool for various diseases. During image acquisition, they get acquainted with noise because of modality and/or because of body conditions such as patient’s position or body fat. Most common noise in ultrasound is speckle, CT and MRI are motion and electrical noises. And other additional noise can also be present such as salt and pepper, Gaussian, Poisson. These noises degrade image quality. The only expert radiologist can make an appropriate diagnosis. Hence it is very important to perform de-noising. Many techniques are present for de-noising which are basically dependent on noise type. Here an attempt is made to remove speckle noise using multilevel hybrid filters. Ultrasound images of the common carotid artery are degraded by speckle noise and then de-noised using the median, wiener, NLM, Homorphic, Bilateral and hybrid filter are applied. Performance of these algorithms is measured using PSNR, MSE, SSIM and ROC c...

International Journal for Research in Applied Science and Engineering Technology, 2021

In recent years, the number of surveillance cameras installed to monitor private and public space... more In recent years, the number of surveillance cameras installed to monitor private and public spaces has increased rapidly. The demand has raised for smarter video surveillance of public and private spaces using intelligent vision systems which can differentiate between 'suspicious' and 'unsuspicious' behaviours according to the human observer. Generally, the video streams are constantly recorded or monitored by operators. In these cases, an intelligent system can give more accurate performance than a human. We have proposed a method called motion influence map under machine learning for representing human activities. Optical-flow is computed for each pixel in a frame that are processed sequentially. The key feature of the proposed motion influence map is that it effectively reflects the motion characteristics such as movement speed, movement direction, and size of the objects or subjects and their interactions within a frame sequence. It further extracts frames of hig...

Indian Journal of Paediatric Dermatology, 2019

Background: Pigmentary disorders are believed to be the most common group of dermatoses in the pe... more Background: Pigmentary disorders are believed to be the most common group of dermatoses in the pediatric age group. Loss of pigment can have a profound psychological impact on parents of the affected child. There are few studies available in India about the evaluation of hypopigmented lesions in the pediatric age group. Objectives: The objective of this study was conducted to assess the knowledge and attitude and various practices of parents toward hypopigmented disorders. Materials and Methods: A total of 130 pediatric patients were evaluated for hypopigmented lesions. Parent of each child was given a preformed questionnaire for the assessment of knowledge and attitude and various practices of their skin condition. Results: The frequency of hypopigmentary disorders among children was 3.28/1000. The mean age was 8.41 years. Nearly 9.33% of patients had onset at birth. In the study of 130 parents, 82 had low, 32 had moderate, and 14 had high knowledge levels, and 84 had unfavorable, and 46 had favorable attitudes. The parents, who had incorrect practices, were 53% and 35.67% had correct practices. Conclusion: The most common hypopigmentary conditions are benign and self-limiting, which requires proper counseling of the parents. A good knowledge and attitude will not only liberate them from traditional beliefs and home remedies that have been used in most of the Indian households but will also make them understand the magnitude of the problem their child could face if they do not seek proper advice from a doctor at the right time.

2014 3rd International Conference on Eco-friendly Computing and Communication Systems, 2014

Billions of internet users are using social web sites, to stay connected with their friends, and ... more Billions of internet users are using social web sites, to stay connected with their friends, and to discover new friends to share photos, videos, social book marks and blogs which are considered as Big Data in social networks. With the increasing exposure to cyber attacks, it is necessary to develop trust and privacy among the user to secure photos and videos, profiles etc. In this paper, importance of trust and privacy of Big Data and existing methods to achieve trust and privacy is discussed considering Social networks.

The Independent Component Analysis with Reference (ICA - R) also called as constrained ICA (cICA)... more The Independent Component Analysis with Reference (ICA - R) also called as constrained ICA (cICA) extracts only the desired source signals from the mixture of source signals by incorporating some prior information into the separation process. To overcome the problem of designing the reference signal when there is no prior information about the desired signal in the cICA, an improved

Future Generation Computer Systems, 2013

Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas o... more Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein, sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fuelled by the recent adaptation of a variety of enabling device technologies such as RFID tags and readers, near field communication (NFC) devices and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A cloud implementation using Aneka, which is based on interaction of private and public clouds is presented. We conclude our IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.

Electronics Letters, 1994

A method for speaker identification based on the analysis of four sets of speech parameters is pr... more A method for speaker identification based on the analysis of four sets of speech parameters is proposed. The recognition is carried out by means of two classifiers: the first is based on self-organising Kohonen maps, a new prototype distribution map and a new similarity measure, and the second on AR-vector models. The final decision is realised by a voting principle using the classifiers' decisions.

speech.iiit.ac.in

In this paper, we explore Bessel features to determine the number of speakers from multispeaker s... more In this paper, we explore Bessel features to determine the number of speakers from multispeaker speech signals collected simultaneously from a pair of spatially separated microphones. The arrival of the speech signals from speaker to microphones gives the time delays of given speaker. The time delays can be estimated by performing the crosscorrelation to the band limited multispeaker signals collected at the two microphones. Signals are band limited using a finite number of Bessel coefficients. The computer simulation results demonstrate the proposed method is efficient compared to existing methods.

Systems, Signals and …, 2011

Voice onset time is an important temporal feature which is often overlooked in speech perception,... more Voice onset time is an important temporal feature which is often overlooked in speech perception, speech recognition as well as accent detection. The VOT in unvoiced stops varies with a number of factors, among which the most established one is the place of articulation. In this paper we propose an approach for the automatic detection of VOT. The proposed method uses Bessel expansion to emphasize the vowel and consonant regions of stop consonant vowel units (SCV) such as /ka/, /Ta/, /ta/ and /pa/. AM-FM signal has been emphasized after appropriate consideration of the range of Bessel coefficients, separately for the vowel and consonant regions of SCV units. The reconstructed signal from the Bessel expansion is a narrow-band AM-FM signal, therefore the amplitude envelope (AE) function for the emphasized signal can be estimated using discrete energy separation algorithm (DESA). For the detection of VOT, both the AE of vowel and consonat emphasized signal has been analyzed. Detection of VOT is analyzed for the continuous speech corpus consisting of recording television broadcast news bulletins.

Informal media, such as Twitter, are more relevant today than ever before. Twitter is still a val... more Informal media, such as Twitter, are more relevant today than ever before. Twitter is still a valuable tool for friends to communicate, but it has evolved into a public bulletin board where ordinary people, companies, and even big personalities like politicians and sports routinely publish their thoughts and participate in conversations. Since, Twitter is so extensively utilized throughout the world, the ability to do reliable opinion mining and gauge public opinion and perception on a variety of issues is more vital than ever. Emojis are frequently used to communicate feelings or sentiments that are difficult to express succinctly in language. For emoji-based opinion mining, a deep learning framework is presented to model the influence of emojis on text sentiment polarity. The emojis and words in microblog posts are combined to create emoji representations that include contextual information.

Recently, significant growth in using online-based learning stream (i.e., elearning systems) have... more Recently, significant growth in using online-based learning stream (i.e., elearning systems) have been seen due to pandemic such as COVID-19. Forecasting student performance has become a major task as an institution is focusing on improving the quality of education and students' performance. Data mining (DM) employing machine learning (ML) techniques have been employed in the e-learning platform for analyzing student session streams and predicting academic performance with good effects. A recent, study shows ML-based methodologies exhibit when data is imbalanced. In addressing ensemble learning by combining multiple ML algorithms for choosing the best model according to data. However, the existing ensemblebased model does not incorporate feature importance into the student performance prediction model. Thus, exhibits poor performance, especially for multi-label classification. In addressing this, this paper presents an improved ensemble learning mechanism by modifying the XGBoost algorithm, namely modified XGBoost (MXGB). The MXGB incorporates an effective cross-validation scheme that learns correlation among features more efficiently. The experiment outcome shows the proposed MXGBabased student performance prediction model achieves much better prediction accuracy contrary to the state-of-art ensemble-based student performance prediction model.

EAI/Springer Innovations in Communication and Computing, 2023

2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Feb 1, 2017

The Internet of Things is an emerging technology across the world, which helps to connect sensors... more The Internet of Things is an emerging technology across the world, which helps to connect sensors, vehicles, hospitals, industries and consumers through internet connectivity. This type of architecture leads to Smart Cities, Smart home, Smart agriculture and Smart World. Architecture of IoT is very complex because of the large number of devices, link layer technology and services that are involved in this system. However, security in IoT is the most important parameter. In this paper, we give an overview of the architecture of IoT with the help of Smart World. In the second phase of this paper, we discuss the security challenges in IoT followed by the security measures in IoT. Finally, these challenges, which are discussed in the paper, could be research direction for future work in security for IoT.

Asian Journal of Computer Science and Technology

Periodontal disease, characterized by alveolar bone loss, is a prevalent oral health condition th... more Periodontal disease, characterized by alveolar bone loss, is a prevalent oral health condition that requires early detection and management to prevent further progression. This paper proposes a novel approach for alveolar bone loss detection and localization in dental X-ray images using the YOLOv5 object detection algorithm. We annotated a dataset of dental radiographs with alveolar bone loss regions and fine-tuned the YOLOv5 model on this dataset. Our approach achieved high accuracy and robustness in detecting and localizing alveolar bone loss regions, with precision, recall, and F1 score exceeding 90%. The real-time processing capabilities of YOLOv5 make it suitable for clinical implementation, providing an efficient and accurate solution for periodontal disease management. The automated alveolar bone loss detection and localization using YOLOv5 can significantly assist dentists in the early diagnosis and treatment planning of periodontal diseases, leading to improved patient outc...

International Journal of Computer and Electrical Engineering, 2012

In this paper, we explore the use of Bessel features derived from speech utterances, to develop G... more In this paper, we explore the use of Bessel features derived from speech utterances, to develop Gaussian mixture speaker models for text independent Speaker Identification. The proposed approach to speaker identification is based on existing methods that employ Gaussian mixtures for the modeling of speakers. However, we have developed the speaker models from the Bessel features derived from the speech utterances, as an alternative to Mel-frequency cepstral coefficients for developing the speaker models. The proposed approach is tested on two databases of ten and twenty speakers respectively and their performance is evaluated. Finally, we have made some suggestions for future work involving the use of Bessel features for text independent speaker identification Index Terms-Gaussian mixture models, Bessel functions, text independent, speaker identification.

Contrast Media & Molecular Imaging

The image enhancement for the natural images is the vast field where the quality of the images de... more The image enhancement for the natural images is the vast field where the quality of the images degrades based on the capturing and processing methods employed by the capturing devices. Based on noise type and estimation of noise, filter need to be adopted for enhancing the quality of the image. In the same manner, the medical field also needs some filtering mechanism to reduce the noise and detection of the disease based on the clarity of the image captured; in accordance with it, the preprocessing steps play a vital role to reduce the burden on the radiologist to make the decision on presence of disease. Based on the estimated noise and its type, the filters are selected to delete the unwanted signals from the image. Hence, identifying noise types and denoising play an important role in image analysis. The proposed framework addresses the noise estimation and filtering process to obtain the enhanced images. This paper estimates and detects the noise types, namely Gaussian, motion a...

BENTHAM SCIENCE PUBLISHERS eBooks, Mar 21, 2023

Asian Journal of Computer Science and Technology

In dental diagnosis, rapid identification of dental complications from radiographs requires highl... more In dental diagnosis, rapid identification of dental complications from radiographs requires highly experienced medical professionals. Occasionally, depending exclusively on a expert's judgement could lead to changes in diagnosis, that could eventually lead to difficult treatment. Although fully automatic diagnostic tools aren’t still anticipated, image pattern recognition has grown into decision support, opening with discovery of teeth and its constituents on X-ray images. Dental discovery is a topic of study for more than previous two decades, depending primarily on threshold and region-based strategies. In this study, we proposed segmentation based Teeth X-Ray images using a couple of machine learning algorithms as well as deep learning algorithms i.e., Support Vector Classifier (SVC), Random Forest algorithm and Convolutional Neural network (CNN) which would help us in accurate identification and classification. This article also presents a comprehensive comparison between t...

The following decade will witness a surge in remote health-monitoring systems that are based on b... more The following decade will witness a surge in remote health-monitoring systems that are based on body-worn monitoring devices. These Medical Cyber Physical Systems (MCPS) will be capable of transmitting the acquired data to a private or public cloud for storage and processing. Machine learning algorithms running in the cloud and processing this data can provide decision support to healthcare professionals. There is no doubt that the security and privacy of the medical data is one of the most important concerns in designing an MCPS. The pervasiveness of smart phones and the advance of wireless body sensor networks (BSNs), mobile Healthcare (m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security and privacy preservation.

2020 International Conference on Inventive Computation Technologies (ICICT), 2020

Medical imaging has become a very important non-invasive diagnosis tool for various diseases. Dur... more Medical imaging has become a very important non-invasive diagnosis tool for various diseases. During image acquisition, they get acquainted with noise because of modality and/or because of body conditions such as patient’s position or body fat. Most common noise in ultrasound is speckle, CT and MRI are motion and electrical noises. And other additional noise can also be present such as salt and pepper, Gaussian, Poisson. These noises degrade image quality. The only expert radiologist can make an appropriate diagnosis. Hence it is very important to perform de-noising. Many techniques are present for de-noising which are basically dependent on noise type. Here an attempt is made to remove speckle noise using multilevel hybrid filters. Ultrasound images of the common carotid artery are degraded by speckle noise and then de-noised using the median, wiener, NLM, Homorphic, Bilateral and hybrid filter are applied. Performance of these algorithms is measured using PSNR, MSE, SSIM and ROC c...

International Journal for Research in Applied Science and Engineering Technology, 2021

In recent years, the number of surveillance cameras installed to monitor private and public space... more In recent years, the number of surveillance cameras installed to monitor private and public spaces has increased rapidly. The demand has raised for smarter video surveillance of public and private spaces using intelligent vision systems which can differentiate between 'suspicious' and 'unsuspicious' behaviours according to the human observer. Generally, the video streams are constantly recorded or monitored by operators. In these cases, an intelligent system can give more accurate performance than a human. We have proposed a method called motion influence map under machine learning for representing human activities. Optical-flow is computed for each pixel in a frame that are processed sequentially. The key feature of the proposed motion influence map is that it effectively reflects the motion characteristics such as movement speed, movement direction, and size of the objects or subjects and their interactions within a frame sequence. It further extracts frames of hig...

Indian Journal of Paediatric Dermatology, 2019

Background: Pigmentary disorders are believed to be the most common group of dermatoses in the pe... more Background: Pigmentary disorders are believed to be the most common group of dermatoses in the pediatric age group. Loss of pigment can have a profound psychological impact on parents of the affected child. There are few studies available in India about the evaluation of hypopigmented lesions in the pediatric age group. Objectives: The objective of this study was conducted to assess the knowledge and attitude and various practices of parents toward hypopigmented disorders. Materials and Methods: A total of 130 pediatric patients were evaluated for hypopigmented lesions. Parent of each child was given a preformed questionnaire for the assessment of knowledge and attitude and various practices of their skin condition. Results: The frequency of hypopigmentary disorders among children was 3.28/1000. The mean age was 8.41 years. Nearly 9.33% of patients had onset at birth. In the study of 130 parents, 82 had low, 32 had moderate, and 14 had high knowledge levels, and 84 had unfavorable, and 46 had favorable attitudes. The parents, who had incorrect practices, were 53% and 35.67% had correct practices. Conclusion: The most common hypopigmentary conditions are benign and self-limiting, which requires proper counseling of the parents. A good knowledge and attitude will not only liberate them from traditional beliefs and home remedies that have been used in most of the Indian households but will also make them understand the magnitude of the problem their child could face if they do not seek proper advice from a doctor at the right time.

2014 3rd International Conference on Eco-friendly Computing and Communication Systems, 2014

Billions of internet users are using social web sites, to stay connected with their friends, and ... more Billions of internet users are using social web sites, to stay connected with their friends, and to discover new friends to share photos, videos, social book marks and blogs which are considered as Big Data in social networks. With the increasing exposure to cyber attacks, it is necessary to develop trust and privacy among the user to secure photos and videos, profiles etc. In this paper, importance of trust and privacy of Big Data and existing methods to achieve trust and privacy is discussed considering Social networks.

The Independent Component Analysis with Reference (ICA - R) also called as constrained ICA (cICA)... more The Independent Component Analysis with Reference (ICA - R) also called as constrained ICA (cICA) extracts only the desired source signals from the mixture of source signals by incorporating some prior information into the separation process. To overcome the problem of designing the reference signal when there is no prior information about the desired signal in the cICA, an improved

Future Generation Computer Systems, 2013

Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas o... more Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein, sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fuelled by the recent adaptation of a variety of enabling device technologies such as RFID tags and readers, near field communication (NFC) devices and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A cloud implementation using Aneka, which is based on interaction of private and public clouds is presented. We conclude our IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.

Electronics Letters, 1994

A method for speaker identification based on the analysis of four sets of speech parameters is pr... more A method for speaker identification based on the analysis of four sets of speech parameters is proposed. The recognition is carried out by means of two classifiers: the first is based on self-organising Kohonen maps, a new prototype distribution map and a new similarity measure, and the second on AR-vector models. The final decision is realised by a voting principle using the classifiers' decisions.

speech.iiit.ac.in

In this paper, we explore Bessel features to determine the number of speakers from multispeaker s... more In this paper, we explore Bessel features to determine the number of speakers from multispeaker speech signals collected simultaneously from a pair of spatially separated microphones. The arrival of the speech signals from speaker to microphones gives the time delays of given speaker. The time delays can be estimated by performing the crosscorrelation to the band limited multispeaker signals collected at the two microphones. Signals are band limited using a finite number of Bessel coefficients. The computer simulation results demonstrate the proposed method is efficient compared to existing methods.

Systems, Signals and …, 2011

Voice onset time is an important temporal feature which is often overlooked in speech perception,... more Voice onset time is an important temporal feature which is often overlooked in speech perception, speech recognition as well as accent detection. The VOT in unvoiced stops varies with a number of factors, among which the most established one is the place of articulation. In this paper we propose an approach for the automatic detection of VOT. The proposed method uses Bessel expansion to emphasize the vowel and consonant regions of stop consonant vowel units (SCV) such as /ka/, /Ta/, /ta/ and /pa/. AM-FM signal has been emphasized after appropriate consideration of the range of Bessel coefficients, separately for the vowel and consonant regions of SCV units. The reconstructed signal from the Bessel expansion is a narrow-band AM-FM signal, therefore the amplitude envelope (AE) function for the emphasized signal can be estimated using discrete energy separation algorithm (DESA). For the detection of VOT, both the AE of vowel and consonat emphasized signal has been analyzed. Detection of VOT is analyzed for the continuous speech corpus consisting of recording television broadcast news bulletins.

Informal media, such as Twitter, are more relevant today than ever before. Twitter is still a val... more Informal media, such as Twitter, are more relevant today than ever before. Twitter is still a valuable tool for friends to communicate, but it has evolved into a public bulletin board where ordinary people, companies, and even big personalities like politicians and sports routinely publish their thoughts and participate in conversations. Since, Twitter is so extensively utilized throughout the world, the ability to do reliable opinion mining and gauge public opinion and perception on a variety of issues is more vital than ever. Emojis are frequently used to communicate feelings or sentiments that are difficult to express succinctly in language. For emoji-based opinion mining, a deep learning framework is presented to model the influence of emojis on text sentiment polarity. The emojis and words in microblog posts are combined to create emoji representations that include contextual information.