International Journal of Innovative Research in Computer Science & Technology
High and rising fuel consumption has occurred in past times. resulted in enormous growth in renew... more High and rising fuel consumption has occurred in past times. resulted in enormous growth in renewable energy generation and consumption. As economies Photovoltaic (PV) solar is becoming more popular as the world's interest in cleaner energy grows. is becoming a more viable option. PV energy harvesting and managing has numerous advantages, but it also has certain disadvantages, such as low energy conversion efficiency due to optical and electrical losses. Because of the random component associated with its genesis, the partial shading problem, the first of these losses is typically the most hardest to deal with. As a result, shading countermeasures exist as an important component of power converting unit, so as to reduce negative influence over power efficiency extraction. Despite the fact that each of these processes has its own set of shortcomings, a large range of different techniques have been devised as well as evaluated in literature to far. We proposes a MATLAB simulation ...
International Journal of Innovative Research in Engineering & Management
For system frequency control, the current work proposes a multi-area power system integrating var... more For system frequency control, the current work proposes a multi-area power system integrating various renewable sources. An effective controller with intrinsic superior capabilities of restricting peak deviation, steady state errors, and oscillatory behavior of a dynamic system is an apparent alternative for autonomous generation control of interconnected power systems. The most difficult part of using a controller is figuring out how to get the most out of it. Because of its space complexity, the trial and error method of determining the benefit by indirect optimization with an acceptable performance index appears to be insufficient. As a result, it appears that using an effective algorithm technique to find the maximum gains for the controllers is the best option. The gains of the controllers are addressed in this work and thus are optimized using a meta-heuristic technique in this study.
International Journal for Research in Applied Science and Engineering Technology
Automated voice recognition is a branch of algorithms and cognitive computing that tries to produ... more Automated voice recognition is a branch of algorithms and cognitive computing that tries to produce robots which can interact with other folks through speaking. Speaking is a data imply suggesting includes both verbal and psycholinguistic information in addition to paralinguistic data. Emotion is a good example of paralinguistic information transmitted in part through speech. Verbal interaction gets simpler because of the development of technologies that can comprehend paralinguistic information such as mood. In this Cnns circuits' usefulness in language research emotion identification was investigated. Spectrograms with a wide range of frequencies of audio samples remained employed as only a source characteristic for the internet infrastructure The circuits had been educated. to identify speaking patterns provided by performers when expressing a certain mood. We used English-language speech resources to validate and develop our technologies The information used for retraining was expanded by two levels in each database. As a result of this, the dropout strategy was employed to. The genderagnostic, language-agnostic CNN models, as per our findings, achieved the highest degree of accuracy, beat Consequences of elections in the literary, and equalled or even surpassed human performance on benchmark databases. Future study should test the capability of deep learning methods in voice emotion identification using real-life speech data.
International Journal of Innovative Research in Engineering & Management
The use of a Fuzzy logic-based controller for automatic generation control (AGC) and load frequen... more The use of a Fuzzy logic-based controller for automatic generation control (AGC) and load frequency control (LFC) of two area power plants in an interconnected power system is proposed in this paper. In addition, a superconducting magnetic Energy Storage (SMES) unit is being considered in two areas. After a sudden load disturbance, the implementation of SMES combination arrests the initial fall in frequency deviation and tie-line power deviation. The simulation results show that the proposed SMES unit improves system performance significantly. The system's sensitivity analysis is carried out by altering the parameters and operating load conditions from their nominal values. Even when the system is subjected to wide variations in loading conditions and system parameters, the optimised gains of the proposed fuzzy logic- based controller and fuzzy controller along with SMES controllers do not need to be reset. Finally, different types of load patterns are used to test the effective...
2019 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC)
Contents are the significant document into images or videos. Different authors or scientist prese... more Contents are the significant document into images or videos. Different authors or scientist presents different strategies to separate the helpful contents from a picture or a moving picture but some it is very difficult to extract the contents because of picture quality. So we propose a substitute method to discover and compute the contents that is uncommonly planned for being associated with shading pictures with complex foundation. The emphasis is on an issue which is identified with contents extraction in video pictures. In this work, we present calculation for removing content in video, pictures using Prewett Edge Detection in terms of precision rate and recall rate. Distinctive types of shading pictures digitized from imparting TV are used to test the estimation and the unfathomable execution result was gotten. For execution examination of our proposed strategy, parameters, for example, precision rate and recall rates have been watched.
International Journal of Multimedia and Ubiquitous Engineering, 2017
This paper works on the detection of the breast cancer at early stage, by utilizing the mammogram... more This paper works on the detection of the breast cancer at early stage, by utilizing the mammogram images. This work pre-processes the given image by using histogram equalization to enhance the contrast of the image. Then the grey level co-occurrence matrix is used to extract the features from the image. The extracted features are reduced to the significant subset of features by using the sequential backward selection. Then, the image is classified as malignant or benign on the basis of significant subset of features by using the ANN classifier. Moreover, ANN classifier is optimized by selecting the optimized error value as stopping criteria. The result comparison and analysis on DDSM and MIAS datasets using parameters sensitivity, specificity, accuracy signifies effectiveness of the work.
Clustering, also known as unsupervised learning, is one of the most significant topics of machine... more Clustering, also known as unsupervised learning, is one of the most significant topics of machine learning because it divides data into groups based on similarity with the aim of extracting or summarizing new information. It is one of the most often used machine learning techniques. The most significant problem encountered in this subject is the sheer volume of electronic text documents accessible, which is increasing at an exponential rate, necessitating the development of efficient ways for dealing with these papers. Furthermore, it is not practicable to consolidate all of the papers from numerous locations into a single area for processing. In this study, the primary goal is to enhance the performance of the distributed document clustering approach for clustering big, high-dimensional distributed document datasets. For distributed storage and analysis, one of the most prominent open-source implementations of the big data analytic-based MapReduce model, such as the Hadoop framewor...
International journal of innovative research in engineering and management, Feb 27, 2022
A wind diesel hybrid system is an autonomous electricity generating system using wind turbines wi... more A wind diesel hybrid system is an autonomous electricity generating system using wind turbines with diesel generators to obtain a maximum contribution by the intermittent wind resource to the total power produced, while providing continuous high quality electric power. The main goal is to control load frequency and reduce fuel consumption enabling reduced system operating costs and environmental impacts. Frequency control in a power system is done to maintain an adequate balance between the consumed and generated active powers, so that the frequency remains within acceptable limits around the nominal frequency. Load-frequency control (LFC) is of importance in electric power system design and operation. The objective of the LFC in an interconnected power system is to maintain the frequency of each area within limits and to keep tie-line power flows within some pre-specified tolerances by adjusting the MW outputs of the generators so as to accommodate fluctuating load demands.
The paper presents a Feed-forward back-propagation Artificial Neural Network (ANN) model for dete... more The paper presents a Feed-forward back-propagation Artificial Neural Network (ANN) model for detection of breast cancer using Image Registration Techniques. Gray Level Co-occurrence Matrix (GLCM) features extracted from the known mammogram images are used to train the ANN based detection system. The ANN based detection system will be investigated for different number of neurons and layers on the basis of Mean Square Error (MSE) and optimum number of neurons and layers will be chosen.
Breast cancer is one of the leading cancers among women in developed countries including India. E... more Breast cancer is one of the leading cancers among women in developed countries including India. Early diagnosis of the cancer allows treatment which could lead to high survival rate or avoids further clinical evaluation or breast biopsy reducing the unnecessary expenditure. This paper aims to build Artificial Neural Network (ANN) model for detection of breast cancer based on Image Registration techniques. Gray Level Co-occurrence Matrix (GLCM) features are extracted and are used to train the ANN. The performance is analysed on the basis of Mean Square Error (MSE) for different number of neurons of ANN.
Breast cancer is one of the leading cancers among women in developed countries including India. E... more Breast cancer is one of the leading cancers among women in developed countries including India. Early diagnosis of the cancer allows treatment which could lead to high survival rate or avoids further clinical evaluation or breast biopsy reducing the unnecessary expenditure. This paper aims to build Artificial Neural Network (ANN) model for detection of breast cancer based on Image Registration techniques. Gray Level Co-occurrence Matrix (GLCM) features are extracted and are used to train the ANN. The performance is analysed on the basis of Mean Square Error (MSE) for different number of neurons of ANN.
International Journal of Innovative Research in Computer Science & Technology
High and rising fuel consumption has occurred in past times. resulted in enormous growth in renew... more High and rising fuel consumption has occurred in past times. resulted in enormous growth in renewable energy generation and consumption. As economies Photovoltaic (PV) solar is becoming more popular as the world's interest in cleaner energy grows. is becoming a more viable option. PV energy harvesting and managing has numerous advantages, but it also has certain disadvantages, such as low energy conversion efficiency due to optical and electrical losses. Because of the random component associated with its genesis, the partial shading problem, the first of these losses is typically the most hardest to deal with. As a result, shading countermeasures exist as an important component of power converting unit, so as to reduce negative influence over power efficiency extraction. Despite the fact that each of these processes has its own set of shortcomings, a large range of different techniques have been devised as well as evaluated in literature to far. We proposes a MATLAB simulation ...
International Journal of Innovative Research in Engineering & Management
For system frequency control, the current work proposes a multi-area power system integrating var... more For system frequency control, the current work proposes a multi-area power system integrating various renewable sources. An effective controller with intrinsic superior capabilities of restricting peak deviation, steady state errors, and oscillatory behavior of a dynamic system is an apparent alternative for autonomous generation control of interconnected power systems. The most difficult part of using a controller is figuring out how to get the most out of it. Because of its space complexity, the trial and error method of determining the benefit by indirect optimization with an acceptable performance index appears to be insufficient. As a result, it appears that using an effective algorithm technique to find the maximum gains for the controllers is the best option. The gains of the controllers are addressed in this work and thus are optimized using a meta-heuristic technique in this study.
International Journal for Research in Applied Science and Engineering Technology
Automated voice recognition is a branch of algorithms and cognitive computing that tries to produ... more Automated voice recognition is a branch of algorithms and cognitive computing that tries to produce robots which can interact with other folks through speaking. Speaking is a data imply suggesting includes both verbal and psycholinguistic information in addition to paralinguistic data. Emotion is a good example of paralinguistic information transmitted in part through speech. Verbal interaction gets simpler because of the development of technologies that can comprehend paralinguistic information such as mood. In this Cnns circuits' usefulness in language research emotion identification was investigated. Spectrograms with a wide range of frequencies of audio samples remained employed as only a source characteristic for the internet infrastructure The circuits had been educated. to identify speaking patterns provided by performers when expressing a certain mood. We used English-language speech resources to validate and develop our technologies The information used for retraining was expanded by two levels in each database. As a result of this, the dropout strategy was employed to. The genderagnostic, language-agnostic CNN models, as per our findings, achieved the highest degree of accuracy, beat Consequences of elections in the literary, and equalled or even surpassed human performance on benchmark databases. Future study should test the capability of deep learning methods in voice emotion identification using real-life speech data.
International Journal of Innovative Research in Engineering & Management
The use of a Fuzzy logic-based controller for automatic generation control (AGC) and load frequen... more The use of a Fuzzy logic-based controller for automatic generation control (AGC) and load frequency control (LFC) of two area power plants in an interconnected power system is proposed in this paper. In addition, a superconducting magnetic Energy Storage (SMES) unit is being considered in two areas. After a sudden load disturbance, the implementation of SMES combination arrests the initial fall in frequency deviation and tie-line power deviation. The simulation results show that the proposed SMES unit improves system performance significantly. The system's sensitivity analysis is carried out by altering the parameters and operating load conditions from their nominal values. Even when the system is subjected to wide variations in loading conditions and system parameters, the optimised gains of the proposed fuzzy logic- based controller and fuzzy controller along with SMES controllers do not need to be reset. Finally, different types of load patterns are used to test the effective...
2019 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC)
Contents are the significant document into images or videos. Different authors or scientist prese... more Contents are the significant document into images or videos. Different authors or scientist presents different strategies to separate the helpful contents from a picture or a moving picture but some it is very difficult to extract the contents because of picture quality. So we propose a substitute method to discover and compute the contents that is uncommonly planned for being associated with shading pictures with complex foundation. The emphasis is on an issue which is identified with contents extraction in video pictures. In this work, we present calculation for removing content in video, pictures using Prewett Edge Detection in terms of precision rate and recall rate. Distinctive types of shading pictures digitized from imparting TV are used to test the estimation and the unfathomable execution result was gotten. For execution examination of our proposed strategy, parameters, for example, precision rate and recall rates have been watched.
International Journal of Multimedia and Ubiquitous Engineering, 2017
This paper works on the detection of the breast cancer at early stage, by utilizing the mammogram... more This paper works on the detection of the breast cancer at early stage, by utilizing the mammogram images. This work pre-processes the given image by using histogram equalization to enhance the contrast of the image. Then the grey level co-occurrence matrix is used to extract the features from the image. The extracted features are reduced to the significant subset of features by using the sequential backward selection. Then, the image is classified as malignant or benign on the basis of significant subset of features by using the ANN classifier. Moreover, ANN classifier is optimized by selecting the optimized error value as stopping criteria. The result comparison and analysis on DDSM and MIAS datasets using parameters sensitivity, specificity, accuracy signifies effectiveness of the work.
Clustering, also known as unsupervised learning, is one of the most significant topics of machine... more Clustering, also known as unsupervised learning, is one of the most significant topics of machine learning because it divides data into groups based on similarity with the aim of extracting or summarizing new information. It is one of the most often used machine learning techniques. The most significant problem encountered in this subject is the sheer volume of electronic text documents accessible, which is increasing at an exponential rate, necessitating the development of efficient ways for dealing with these papers. Furthermore, it is not practicable to consolidate all of the papers from numerous locations into a single area for processing. In this study, the primary goal is to enhance the performance of the distributed document clustering approach for clustering big, high-dimensional distributed document datasets. For distributed storage and analysis, one of the most prominent open-source implementations of the big data analytic-based MapReduce model, such as the Hadoop framewor...
International journal of innovative research in engineering and management, Feb 27, 2022
A wind diesel hybrid system is an autonomous electricity generating system using wind turbines wi... more A wind diesel hybrid system is an autonomous electricity generating system using wind turbines with diesel generators to obtain a maximum contribution by the intermittent wind resource to the total power produced, while providing continuous high quality electric power. The main goal is to control load frequency and reduce fuel consumption enabling reduced system operating costs and environmental impacts. Frequency control in a power system is done to maintain an adequate balance between the consumed and generated active powers, so that the frequency remains within acceptable limits around the nominal frequency. Load-frequency control (LFC) is of importance in electric power system design and operation. The objective of the LFC in an interconnected power system is to maintain the frequency of each area within limits and to keep tie-line power flows within some pre-specified tolerances by adjusting the MW outputs of the generators so as to accommodate fluctuating load demands.
The paper presents a Feed-forward back-propagation Artificial Neural Network (ANN) model for dete... more The paper presents a Feed-forward back-propagation Artificial Neural Network (ANN) model for detection of breast cancer using Image Registration Techniques. Gray Level Co-occurrence Matrix (GLCM) features extracted from the known mammogram images are used to train the ANN based detection system. The ANN based detection system will be investigated for different number of neurons and layers on the basis of Mean Square Error (MSE) and optimum number of neurons and layers will be chosen.
Breast cancer is one of the leading cancers among women in developed countries including India. E... more Breast cancer is one of the leading cancers among women in developed countries including India. Early diagnosis of the cancer allows treatment which could lead to high survival rate or avoids further clinical evaluation or breast biopsy reducing the unnecessary expenditure. This paper aims to build Artificial Neural Network (ANN) model for detection of breast cancer based on Image Registration techniques. Gray Level Co-occurrence Matrix (GLCM) features are extracted and are used to train the ANN. The performance is analysed on the basis of Mean Square Error (MSE) for different number of neurons of ANN.
Breast cancer is one of the leading cancers among women in developed countries including India. E... more Breast cancer is one of the leading cancers among women in developed countries including India. Early diagnosis of the cancer allows treatment which could lead to high survival rate or avoids further clinical evaluation or breast biopsy reducing the unnecessary expenditure. This paper aims to build Artificial Neural Network (ANN) model for detection of breast cancer based on Image Registration techniques. Gray Level Co-occurrence Matrix (GLCM) features are extracted and are used to train the ANN. The performance is analysed on the basis of Mean Square Error (MSE) for different number of neurons of ANN.
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