Dr. R. R. Deshmukh, Professor, M.E., M.Sc. (CSE) Ph.D. FIETE, Presently working as Professor and Head and Program coordinator for Department of Science and Technology sponsored FIST in Department of Computer Science and Information Technology, Dr. B.A.M. University, Aurangabad, (MS), India. He is a Fellow member and working as Chairman, IETE Aurangabad Centre, He has been elected as sectional member of ICT section of Indian Science congress Association. He is life member of ISCA, CSI, ISTE, IEEE, IAEng, CSTA, IDES and a senior member of ACEEE. He was Vice-Chairman of IETE Aurangabad Centre for last 4 years and member of Management Council of Dr. B. A. M. University. He is Member of Academic Council and Senate member of Dr. B. A. M. University, Aurangabad. Edited Nine books and published more than 95 research papers in reputed Journals, National and International conferences. He is reviewer and editor of several journals at national
Stock market data analysis needs the help of artificial intelligence and data mining techniques. ... more Stock market data analysis needs the help of artificial intelligence and data mining techniques. The volatility of stock prices depends on gains or losses of certain companies. News articles are one of the most important factors which influence the stock market. This study basically shows the effect of emotion classification of financial news to the prediction of stock market prices. In order to find correlation between sentiment predicted from news and original stock price and to test efficient market hypothesis, we plot the sentiments of two companies (Infosys and Wipro) over a period of 10 years. For emotion classification, various classifiers such as Naive Bayes, Knn and SVM are evaluated. The comparison between positive sentiment curve and stock price trends reveals co-relation between them.
The paper presents novel technique for recognizing faces. The proposed method uses mutual informa... more The paper presents novel technique for recognizing faces. The proposed method uses mutual information for feature extraction techniques. Feed Forward Neural Network (FFNN) and Self Organizing Map Neural network (SOM) are used for classification. Performance analysis is done by computing False Acceptance Ratio (FAR) and False Rejection Ratio (FRR). Experimentation is done over FACE4 database and achieved better performance.
Speech has much capability as an interface between human and computer which comes under the Human... more Speech has much capability as an interface between human and computer which comes under the Human Computer interaction (HCI). The major challenge has been the nature of voice is ever varying speech signal. The paper presents the development of the speech recognition system using Swahili speech database which was collected in three sets: digits, isolated words and sentences from both native and non native speakers of Swahili language. Different feature extraction techniques deployed in the system are: Linear Prediction Coding (LPC) and Mel-Frequency Coefficients (MFCC). We have used the 12 coefficient features from MFCC and 20 coefficients features from LPC. All these features extracted techniques are applied and tested for the own developed Swahili speech database. Recognition and verification were done using confusion matrix and Support Vector Machine (SVM) as a classifier for the classification purpose. LDA was tested for the entire dataset for the dimension reduction. LDA gave a ...
In the process of iris recognition localization and segmentation are the primary preprocessing st... more In the process of iris recognition localization and segmentation are the primary preprocessing step that locate the iris and segments it from the remaining part of the image. The normalization and feature extraction are very important and crucial stages which prepare the iris image to extract the required unique features and create the templates that can be compared to find the uniqueness among the two irises. Normalization allows transformation of iris region into a fixed size dimensions that can be compared. In short normalization produces constant dimension size images of every localized input iris image which are ready to further processing and comparison of such images is possible due to their nature of constant dimension size. In general the normalization process prepares the segmented image for feature extraction process. This paper discusses the enhanced normalization process based on Daugman's rubber sheet model and feature extraction is based cumulative sum based chang...
Proceedings of the International Conference on Data Science, Machine Learning and Artificial Intelligence
In this research paper study of water quality & water level monitoring using remote sensing &... more In this research paper study of water quality & water level monitoring using remote sensing & GIS technique and require the satellite data for the study is reviewed. For human being we required fresh water so it is important to monitor The different water quality parameter i.e. physical, chemical, biological parameter are also reviewed in this paper. The optical property of water can be easily access. The different satellite sensor also reviewed in this paper. To calculate water level which satellite sensor is require and which technique is used.
Lecture Notes on Data Engineering and Communications Technologies
Humans can express their feelings by speaking, dancing, writing, etc., but speech is considered t... more Humans can express their feelings by speaking, dancing, writing, etc., but speech is considered to be the easiest form of communication. There are various techniques on conversion of speech which are discussed in this paper. Since ancient times people communicate with each other by the use of some specific language. In India, various languages are spoken but Devnagri is a language, which plays an important role since ancient Indian society. In today’s world some modern languages have based on Devnagri like Marathi, Hindi, Sanskrit, and some South Indian languages also but the research in this field is very rare. The conversion of speech into text can be beneficial for the people who faces problem while communicating in society. The main objective of this paper is to summarize and compare various methods used in various stages of speech to text conversion.
International Journal of Advanced engineering, Management and Science, 2016
Data de-duplication is one of the essential data compression techniques for eliminating duplicate... more Data de-duplication is one of the essential data compression techniques for eliminating duplicate copies of repeating data, and it has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. To protect the privacy of sensitive data while supporting de-duplication, the salt encryption technique has been proposed to encrypt the data before its outsourcing. To protect the data security in a better way, this paper makes the first attempt to formally address the problem of authorized data de-duplication. Different from traditional de-duplication systems, the derivative privileges of users are further considered in duplicate check besides the data itself. We also present various new de-duplication constructions which supports the authorized duplicate check in hybrid cloud architecture. Security analysis demonstrates that the scheme which we used is secure in terms of the definitions specified in the proposed security model. We enhance our system in secu...
International Journal of Innovative Technology and Exploring Engineering
Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition. Atypical communica... more Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition. Atypical communication mostly occurs in tandem with ASD. We compared voice pitch of 16 Marathi children and adolescents with ASD of age of 7 to 18 with 27 Typically Developing (TD). Speech samples have been recorded and stored in .wav format with sampling frequency of 48000 Hz. For analysis we used PRAAT, a program for speech analysis, manipulation and synthesis. We divided the ASD and TD group into total 4 groups on basis of age and gender for comparison. We found that differences in voice pitch are present in these comparison groups, and male ASD group have more pitch variation than respective comparison groups. In future we look forward to include more ASD participants in study to increase the Marathi speech database for ASD.
This paper gives a comparison of two extracted features namely pitch and formants for emotion rec... more This paper gives a comparison of two extracted features namely pitch and formants for emotion recognition from speech. The research shows that various features namely prosodic and spectral have been used for emotion recognition from speech. The database used for recognition purpose was developed on Marathi language using 100 speakers. We have extracted features pitch and formants. Angry, stress, admiration, teasing and shocking have been recognized on the basis of features energy and formants. The classification technique used here is KNearest Neighbor (KNN). The result for formants was about 100% which is comparatively better than that of energy which was 80% of accuracy. Keywords-Database, Emotion recognition, Feature Extraction, Formants, KNN classification , Pitch, Speech signals.
Various operations performed by waiters like starting from taking orders till delivery of food/me... more Various operations performed by waiters like starting from taking orders till delivery of food/menu to the customer, also billing by cashier made manually. Due to manual process and paperwork may cause time delay, ignorance of customer, errors in billing leads to dissatisfaction of customers. As in today’s digital era, customers expect high quality, smart services from restaurant. So to improve quality of service and to achieve customer satisfaction, we proposed improvised E-Menu Recommendation System. This system can build e-reputation of restaurant and customer community in live. All orders and expenses are stored in database and give statistics for expenses and profit. The proposed recommender system uses wireless technology and menu recommender to build improvised E-Menu Recommendation System for customer-centric service. Professional feels and environment are provided to the customers/delegates with additional information about food/menu by using interactive graphics. Outcomes ...
This paper proposes a system of isolated digit recognition for Marathi language using HTK approac... more This paper proposes a system of isolated digit recognition for Marathi language using HTK approach. The database used contains 800 utterances of 40 individuals. Among them 20 are female and 20 are male. For training the acoustic features of the database powerful MFCC i.e. Mel frequency cepstral coefficients technique is used. We have used word level model to recognize the Marathi isolated digits. The result analysis of the system shows 99.75% recognition with 48.75% accuracy.
India is moving towards the direction of digital economy. The initiative of National projects lik... more India is moving towards the direction of digital economy. The initiative of National projects like Digital India, Smart Cities and National Broadband Network has the direct impact on governance, transparency and accountability. As there is increase in the use of ICT for development and better governance, this rapid change towards a digital environment equally has brought forward the challenges of cyber security. According to national statistics, for last few years, out of all cybercrimes were reported across the country, Maharashtra state tops the list than any other states in India, so it becomes important to predict and analyze cybercrime trends for the future. This paper highlights the importance of data mining and machine learning and use the linear regression model to predict future cybercrime trends with reference to Maharashtra state. The real dataset of cybercrime is collected from the government website of Maharashtra state. Then the linear regression model is trained on th...
Palmprint is important member of biometric family, different types of algorithms and system have ... more Palmprint is important member of biometric family, different types of algorithms and system have been proposed and great success has been achieved in Palmprint research, most of the previous Palmprint recognition works use white light source of illumination, which does not highlights the more feature these problem is solved by spectral band of multispectral Palmprint. This paper present feature level image fusion of multispectral Palmprint images for that purpose Polytechnique Hongkong University database is used. Initially the images were subjected to some preprocessing operation like filtering. Wavelet theory is introduced to resolve the Palmprint features extraction problem, and for matching purpose distance matrix is calculated by using Euclidian distance. Wavelet- based image fusion method is used as fusion strategy in our schema we have done fusion of Approximation Coefficient of RGB, NIR images, got the fused image by applying the DWT technique, to reduce the high dimensional...
The earth crust is made up of variety of minerals. These minerals are having very significant app... more The earth crust is made up of variety of minerals. These minerals are having very significant applications in our day today life. The various studies, characterizing physical, chemical, electrical, structural properties, have been carried out on the Lonar crater for studying mineralogy, surface morphology and geology but has not been done by remote sensing technology. So, the proposed work focused on exploring the mineralogy at the Lonar crater by using high resolution hyperspectral imageries. The spectral reflectance of minerals was characterized by using FieldSpec4 spectroradiometer. The minerals at Lonar crater were explored by performing preprocessing and spectral analysis. The techniques used in the work are Spectral Angle Mapper and Spectral Feature Fitting. The results of the work marked the presence of pigeonite and augite at Lonar crater which indicates that this crater is the result of extrusive volcanic activity. Also, the presence of augite underneath basaltic igneous ro...
Second International Conference on Computer Networks and Communication Technologies
In recent years, mobile ad-hoc networks have rooted their pillars for emergency communication owi... more In recent years, mobile ad-hoc networks have rooted their pillars for emergency communication owing to reasonable cost, diversity, and easiness of mobile devices. The mobile ad-hoc networks is a self-coordinated, distributed and infrastructure-less network of mobiles nodes. These characteristics of MANET enhanced the applicability of MANET in the field of emergency communication such as military and police operations, flood control and fire disaster management, etc. In MANET, a broadcast storm causes network problems as there are redundant broadcasts and packet collisions. Classical broadcast methods have motivated on evading broadcast storms by preventing some rebroadcasts. The further problem is the link breakages induced by node instability and their power exhaustion. In this research, we propose an adaptive neighbor knowledge-based hybrid broadcasting method to address these network problems. This method refines the counter threshold based on neighbourhood, mobility and energy of the node and makes use of the refined thresholds to make the broadcasting decision. The proposed method perform best as compared to AMECBB and TCBB by decreasing delay, packet dropping, and routing overhead and energy consumption.
Efficient Feature Extraction Algorithms to Develop an Arabic Speech Recognition System, 2020
This paper studies three feature extraction methods, Mel-Frequency Cepstral Coefficients (MFCC), ... more This paper studies three feature extraction methods, Mel-Frequency Cepstral Coefficients (MFCC), Power-Normalized Cepstral Coefficients (PNCC), and Modified Group Delay Function (ModGDF) for the development of an Automated Speech Recognition System (ASR) in Arabic. The Support Vector Machine (SVM) algorithm processed the obtained features. These feature extraction algorithms extract speech or voice characteristics and process the group delay functionality calculated straight from the voice signal. These algorithms were deployed to extract audio forms from Arabic speakers. PNCC provided the best recognition results in Arabic speech in comparison with the other methods. Simulation results showed that PNCC and ModGDF were more accurate than MFCC in Arabic speech recognition.
Stock market data analysis needs the help of artificial intelligence and data mining techniques. ... more Stock market data analysis needs the help of artificial intelligence and data mining techniques. The volatility of stock prices depends on gains or losses of certain companies. News articles are one of the most important factors which influence the stock market. This study basically shows the effect of emotion classification of financial news to the prediction of stock market prices. In order to find correlation between sentiment predicted from news and original stock price and to test efficient market hypothesis, we plot the sentiments of two companies (Infosys and Wipro) over a period of 10 years. For emotion classification, various classifiers such as Naive Bayes, Knn and SVM are evaluated. The comparison between positive sentiment curve and stock price trends reveals co-relation between them.
The paper presents novel technique for recognizing faces. The proposed method uses mutual informa... more The paper presents novel technique for recognizing faces. The proposed method uses mutual information for feature extraction techniques. Feed Forward Neural Network (FFNN) and Self Organizing Map Neural network (SOM) are used for classification. Performance analysis is done by computing False Acceptance Ratio (FAR) and False Rejection Ratio (FRR). Experimentation is done over FACE4 database and achieved better performance.
Speech has much capability as an interface between human and computer which comes under the Human... more Speech has much capability as an interface between human and computer which comes under the Human Computer interaction (HCI). The major challenge has been the nature of voice is ever varying speech signal. The paper presents the development of the speech recognition system using Swahili speech database which was collected in three sets: digits, isolated words and sentences from both native and non native speakers of Swahili language. Different feature extraction techniques deployed in the system are: Linear Prediction Coding (LPC) and Mel-Frequency Coefficients (MFCC). We have used the 12 coefficient features from MFCC and 20 coefficients features from LPC. All these features extracted techniques are applied and tested for the own developed Swahili speech database. Recognition and verification were done using confusion matrix and Support Vector Machine (SVM) as a classifier for the classification purpose. LDA was tested for the entire dataset for the dimension reduction. LDA gave a ...
In the process of iris recognition localization and segmentation are the primary preprocessing st... more In the process of iris recognition localization and segmentation are the primary preprocessing step that locate the iris and segments it from the remaining part of the image. The normalization and feature extraction are very important and crucial stages which prepare the iris image to extract the required unique features and create the templates that can be compared to find the uniqueness among the two irises. Normalization allows transformation of iris region into a fixed size dimensions that can be compared. In short normalization produces constant dimension size images of every localized input iris image which are ready to further processing and comparison of such images is possible due to their nature of constant dimension size. In general the normalization process prepares the segmented image for feature extraction process. This paper discusses the enhanced normalization process based on Daugman's rubber sheet model and feature extraction is based cumulative sum based chang...
Proceedings of the International Conference on Data Science, Machine Learning and Artificial Intelligence
In this research paper study of water quality & water level monitoring using remote sensing &... more In this research paper study of water quality & water level monitoring using remote sensing & GIS technique and require the satellite data for the study is reviewed. For human being we required fresh water so it is important to monitor The different water quality parameter i.e. physical, chemical, biological parameter are also reviewed in this paper. The optical property of water can be easily access. The different satellite sensor also reviewed in this paper. To calculate water level which satellite sensor is require and which technique is used.
Lecture Notes on Data Engineering and Communications Technologies
Humans can express their feelings by speaking, dancing, writing, etc., but speech is considered t... more Humans can express their feelings by speaking, dancing, writing, etc., but speech is considered to be the easiest form of communication. There are various techniques on conversion of speech which are discussed in this paper. Since ancient times people communicate with each other by the use of some specific language. In India, various languages are spoken but Devnagri is a language, which plays an important role since ancient Indian society. In today’s world some modern languages have based on Devnagri like Marathi, Hindi, Sanskrit, and some South Indian languages also but the research in this field is very rare. The conversion of speech into text can be beneficial for the people who faces problem while communicating in society. The main objective of this paper is to summarize and compare various methods used in various stages of speech to text conversion.
International Journal of Advanced engineering, Management and Science, 2016
Data de-duplication is one of the essential data compression techniques for eliminating duplicate... more Data de-duplication is one of the essential data compression techniques for eliminating duplicate copies of repeating data, and it has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. To protect the privacy of sensitive data while supporting de-duplication, the salt encryption technique has been proposed to encrypt the data before its outsourcing. To protect the data security in a better way, this paper makes the first attempt to formally address the problem of authorized data de-duplication. Different from traditional de-duplication systems, the derivative privileges of users are further considered in duplicate check besides the data itself. We also present various new de-duplication constructions which supports the authorized duplicate check in hybrid cloud architecture. Security analysis demonstrates that the scheme which we used is secure in terms of the definitions specified in the proposed security model. We enhance our system in secu...
International Journal of Innovative Technology and Exploring Engineering
Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition. Atypical communica... more Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition. Atypical communication mostly occurs in tandem with ASD. We compared voice pitch of 16 Marathi children and adolescents with ASD of age of 7 to 18 with 27 Typically Developing (TD). Speech samples have been recorded and stored in .wav format with sampling frequency of 48000 Hz. For analysis we used PRAAT, a program for speech analysis, manipulation and synthesis. We divided the ASD and TD group into total 4 groups on basis of age and gender for comparison. We found that differences in voice pitch are present in these comparison groups, and male ASD group have more pitch variation than respective comparison groups. In future we look forward to include more ASD participants in study to increase the Marathi speech database for ASD.
This paper gives a comparison of two extracted features namely pitch and formants for emotion rec... more This paper gives a comparison of two extracted features namely pitch and formants for emotion recognition from speech. The research shows that various features namely prosodic and spectral have been used for emotion recognition from speech. The database used for recognition purpose was developed on Marathi language using 100 speakers. We have extracted features pitch and formants. Angry, stress, admiration, teasing and shocking have been recognized on the basis of features energy and formants. The classification technique used here is KNearest Neighbor (KNN). The result for formants was about 100% which is comparatively better than that of energy which was 80% of accuracy. Keywords-Database, Emotion recognition, Feature Extraction, Formants, KNN classification , Pitch, Speech signals.
Various operations performed by waiters like starting from taking orders till delivery of food/me... more Various operations performed by waiters like starting from taking orders till delivery of food/menu to the customer, also billing by cashier made manually. Due to manual process and paperwork may cause time delay, ignorance of customer, errors in billing leads to dissatisfaction of customers. As in today’s digital era, customers expect high quality, smart services from restaurant. So to improve quality of service and to achieve customer satisfaction, we proposed improvised E-Menu Recommendation System. This system can build e-reputation of restaurant and customer community in live. All orders and expenses are stored in database and give statistics for expenses and profit. The proposed recommender system uses wireless technology and menu recommender to build improvised E-Menu Recommendation System for customer-centric service. Professional feels and environment are provided to the customers/delegates with additional information about food/menu by using interactive graphics. Outcomes ...
This paper proposes a system of isolated digit recognition for Marathi language using HTK approac... more This paper proposes a system of isolated digit recognition for Marathi language using HTK approach. The database used contains 800 utterances of 40 individuals. Among them 20 are female and 20 are male. For training the acoustic features of the database powerful MFCC i.e. Mel frequency cepstral coefficients technique is used. We have used word level model to recognize the Marathi isolated digits. The result analysis of the system shows 99.75% recognition with 48.75% accuracy.
India is moving towards the direction of digital economy. The initiative of National projects lik... more India is moving towards the direction of digital economy. The initiative of National projects like Digital India, Smart Cities and National Broadband Network has the direct impact on governance, transparency and accountability. As there is increase in the use of ICT for development and better governance, this rapid change towards a digital environment equally has brought forward the challenges of cyber security. According to national statistics, for last few years, out of all cybercrimes were reported across the country, Maharashtra state tops the list than any other states in India, so it becomes important to predict and analyze cybercrime trends for the future. This paper highlights the importance of data mining and machine learning and use the linear regression model to predict future cybercrime trends with reference to Maharashtra state. The real dataset of cybercrime is collected from the government website of Maharashtra state. Then the linear regression model is trained on th...
Palmprint is important member of biometric family, different types of algorithms and system have ... more Palmprint is important member of biometric family, different types of algorithms and system have been proposed and great success has been achieved in Palmprint research, most of the previous Palmprint recognition works use white light source of illumination, which does not highlights the more feature these problem is solved by spectral band of multispectral Palmprint. This paper present feature level image fusion of multispectral Palmprint images for that purpose Polytechnique Hongkong University database is used. Initially the images were subjected to some preprocessing operation like filtering. Wavelet theory is introduced to resolve the Palmprint features extraction problem, and for matching purpose distance matrix is calculated by using Euclidian distance. Wavelet- based image fusion method is used as fusion strategy in our schema we have done fusion of Approximation Coefficient of RGB, NIR images, got the fused image by applying the DWT technique, to reduce the high dimensional...
The earth crust is made up of variety of minerals. These minerals are having very significant app... more The earth crust is made up of variety of minerals. These minerals are having very significant applications in our day today life. The various studies, characterizing physical, chemical, electrical, structural properties, have been carried out on the Lonar crater for studying mineralogy, surface morphology and geology but has not been done by remote sensing technology. So, the proposed work focused on exploring the mineralogy at the Lonar crater by using high resolution hyperspectral imageries. The spectral reflectance of minerals was characterized by using FieldSpec4 spectroradiometer. The minerals at Lonar crater were explored by performing preprocessing and spectral analysis. The techniques used in the work are Spectral Angle Mapper and Spectral Feature Fitting. The results of the work marked the presence of pigeonite and augite at Lonar crater which indicates that this crater is the result of extrusive volcanic activity. Also, the presence of augite underneath basaltic igneous ro...
Second International Conference on Computer Networks and Communication Technologies
In recent years, mobile ad-hoc networks have rooted their pillars for emergency communication owi... more In recent years, mobile ad-hoc networks have rooted their pillars for emergency communication owing to reasonable cost, diversity, and easiness of mobile devices. The mobile ad-hoc networks is a self-coordinated, distributed and infrastructure-less network of mobiles nodes. These characteristics of MANET enhanced the applicability of MANET in the field of emergency communication such as military and police operations, flood control and fire disaster management, etc. In MANET, a broadcast storm causes network problems as there are redundant broadcasts and packet collisions. Classical broadcast methods have motivated on evading broadcast storms by preventing some rebroadcasts. The further problem is the link breakages induced by node instability and their power exhaustion. In this research, we propose an adaptive neighbor knowledge-based hybrid broadcasting method to address these network problems. This method refines the counter threshold based on neighbourhood, mobility and energy of the node and makes use of the refined thresholds to make the broadcasting decision. The proposed method perform best as compared to AMECBB and TCBB by decreasing delay, packet dropping, and routing overhead and energy consumption.
Efficient Feature Extraction Algorithms to Develop an Arabic Speech Recognition System, 2020
This paper studies three feature extraction methods, Mel-Frequency Cepstral Coefficients (MFCC), ... more This paper studies three feature extraction methods, Mel-Frequency Cepstral Coefficients (MFCC), Power-Normalized Cepstral Coefficients (PNCC), and Modified Group Delay Function (ModGDF) for the development of an Automated Speech Recognition System (ASR) in Arabic. The Support Vector Machine (SVM) algorithm processed the obtained features. These feature extraction algorithms extract speech or voice characteristics and process the group delay functionality calculated straight from the voice signal. These algorithms were deployed to extract audio forms from Arabic speakers. PNCC provided the best recognition results in Arabic speech in comparison with the other methods. Simulation results showed that PNCC and ModGDF were more accurate than MFCC in Arabic speech recognition.
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