Kirti Wanjale - Academia.edu (original) (raw)

Papers by Kirti Wanjale

Journal of Information and Optimization Sciences, 2023

In computer music, instrument recognition is a critical part of sound modeling. Pitch, timbre, lo... more In computer music, instrument recognition is a critical part of sound modeling. Pitch, timbre, loudness, duration, and spatialization are all components of musical sounds. All of these components play a significant part in determining the quality of the tonal sound. It is possible to alter the first four parameters, but timbre always poses a challenge [6]. It was inevitable that timbre would take center stage. Musical instruments are distinguished from one other by their distinct sound quality, independent of their pitch or volume. To distinguish between monophonic and polyphonic music recordings, this method might be used. In Musical Information Retrieval, classification plays one of the critical role. Monophonic instrument classification can be found in literature with quiet a substantial combinations of features and classifiers. Polyphonic instrument classification witnessed less references in the literature and is still an area to be explored specifically when it comes to Indian Classical domain. The present paper exactly focusses on this experimentation. Several Indian instruments were used to produce training data sets for the proposed approach’s evaluation purposes. Among the instruments utilized are the flute, harmonium, and sitar. Statistical and spectral factors are used to classify Indian musical instruments along with the Artificial Intelligence-based methods. Hybrid features from multiple domains that extract essential musical properties are extracted. Accuracy is demonstrated through an Indian Musical Instrument SVM and GMM classification. With monophonic sounds, SVM and Polyphonic produce an average accuracy of 89% and 91%. GMM outperforms SVM in monophonic recordings by a factor of 96.33 and polyphonic recordings by a factor of 93.33, according to the results of the studies. The future scope of this recognition framework can be an Artificial Intelligence System with a system linked with the Industrial Internet of Things (IIOT) framework to develop a standalone system or application which can be used for real- time classification of instruments.

Lecture notes in networks and systems, 2023

Turkish Journal of Computer and Mathematics Education (TURCOMAT), Apr 5, 2021

Social media sites like Flickr permit clients to annotate pictures with free labels referred as “... more Social media sites like Flickr permit clients to annotate pictures with free labels referred as “tag”, which altogether contribute to the improvement of the web picture retrieval. Tag-based picture hunt is an important strategy to discover pictures contributed by social media users in such social sites. In this paper, we propose a social re-positioning framework for tag-based and feature based image retrieval with the thought of image significance and assorted qualities. In social media network, measuring the relevance of tags with respect to the visual, semantic and view contents is a critical task. We go for re-positioning image, concurring to their visual data, semantic data and social pieces of information. This framework gives the potential of tag relevance fusion for real-world deployment.

Parkinson’s disease is a central nervous system disorder in which dopamine generating cells prese... more Parkinson’s disease is a central nervous system disorder in which dopamine generating cells present in the substantia nigra (a part of our brain) gets damaged or perished. Due to a deficiency of dopamine, which acts as a neurotransmitter in our body, symptoms of Parkinson’s disease are caused. The change in vocal speech is one of the major symptoms shown and can be used to detect this disease. In this paper, there is an implementation and proprietary comparison of various machine learning models. The proposed model comparison shows that ANN is the comparatively better ML model to detect and predict Parkinson’s disease which has accuracy for total UPDRS is 83.56 % and for motor, UPDRS is 85.135 % which are the scales for measuring the severity elaborated further. We have utilized "Sklearn", "TensorFlow" and "Keras" python AI libraries to actualize all the ML models. It sums up that the accuracy generated by the proposed model is 84.45 % which is substantially higher than the research work done so far.

A novel approach to extract and retrieve furniture items from an image database and online websit... more A novel approach to extract and retrieve furniture items from an image database and online websites which includes multiple furniture items, and then find the similar items from the database. The image could be taken using phone cameras or downloaded from online websites or from shopping malls. A real time application is developed in android phone to find the similar images of furniture taken using the phone camera in which people are interested in. The additional processing can be divided into three steps: first, certain image segmentation techniques are need to be applied to split out each individual furniture item; then, an object recognition technique is applied to each segmented furniture item; finally a shape feature matching scheme is used to retrieve similar images to the segmented furniture items from the database.

International journal of computer applications, Nov 26, 2015

Interactive whiteboard involving human interaction have been an active field of research in past ... more Interactive whiteboard involving human interaction have been an active field of research in past years in human computer interaction (HCI). There is a need for adoption of natural interfaces between user and computing devices. This is trending in educational as well as corporate sector where various interactive application, tools and methodologies are used to make the presentation, summarization of difficult concepts easy and also to simulate collaborative work and enhance teaching practices. For Instance, it is a common practice to draw business processes on a traditional whiteboard, using conventional modeling notation such as UML, BPMN, during meetings between software programmers and business clients. Since it is a traditional whiteboard, software developer may need to redesign the process diagram on his computer by referring the whiteboard, this can be time consuming. Alternative way will be to use pen-based input device such as an electronic interactive whiteboard or graphics tablet. Use and working of interactive whiteboard have received researchers' attention as it has been found to be easy and highly effective interaction method. This paper presents a short review for interactive whiteboard technology and its operations proposed in the literature. Some examples of applications are also investigated.

International journal of computer applications, Feb 25, 2010

In the medical field, images, and especially digital images, are produced in ever increasing quan... more In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. Content based access to medical images for supporting clinical decision making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into Picture Archiving and Communication Systems (PACS) have been created. This article gives an overview of available literature in the field of content based access to medical image data and on the technologies used in the field. Section 1 gives an introduction into generic content based image retrieval and the technologies used. Section 2 describes the basic algorithm used in the implemented systems. Section 3 describes various methods of implementing CBIR. New research directions are being defied that can prove to This article also identifies explanations to some of the outlined problems in the field as it looks like many propositions for systems are made from the medical domain and research prototypes are developed in computer science departments using medical datasets. Still, there are very few systems that seem to be used in clinical practice. Content-Based Image Retrieval (CBIR) has been a topic of research interest for nearly a decade. Approaches to date use image features for describing content. A survey of the literature shows that progress has been limited to prototype systems that make gross assumptions and approximations.

Behavioural Neurology, Apr 11, 2022

The emergence of the latest technologies gives rise to the usage of noninvasive techniques for as... more The emergence of the latest technologies gives rise to the usage of noninvasive techniques for assisting health-care systems. Amongst the four major cardiovascular diseases, stroke is one of the most dangerous and life-threatening disease, but the life of a patient can be saved if the stroke is detected during early stage. The literature reveals that the patients always experience ministrokes which are also known as transient ischemic attacks (TIA) before experiencing the actual attack of the stroke. Most of the literature work is based on the MRI and CT scan images for classifying the cardiovascular diseases including a stroke which is an expensive approach for diagnosis of early strokes. In India where cases of strokes are rising, there is a need to explore noninvasive cheap methods for the diagnosis of early strokes. Hence, this problem has motivated us to conduct the study presented in this paper. A noninvasive approach for the early diagnosis of the strokes is proposed. The cascaded prediction algorithms are time-consuming in producing the results and cannot work on the raw data and without making use of the properties of EEG. Therefore, the objective of this paper is to devise mechanisms to forecast strokes on the basis of processed EEG data. This paper is proposing time series-based approaches such as LSTM, biLSTM, GRU, and FFNN that can handle time series-based predictions to make useful decisions. The experimental research outcome reveals that all the algorithms taken up for the research study perform well on the prediction problem of early stroke detection, but GRU performs the best with 95.6% accuracy, whereas biLSTM gives 91% accuracy and LSTM gives 87% accuracy and FFNN gives 83% accuracy. The experimental outcome is able to measure the brain waves to predict the signs of strokes. The findings can certainly assist the physicians to detect the stroke at early stages to save the lives of the patients.

International journal of scientific research in science, engineering and technology, Apr 15, 2020

Agrarian production is that trait on which our nation's economy immensely depends. This is th... more Agrarian production is that trait on which our nation's economy immensely depends. This is the motivation that recognition of leaves unhealthiness is the solution for saving the reduction of crops and productivity. It requisite enormous amount of work, mastery in the leaf diseases, and additionally need the extreme amount of time. Thus, image processing techniques are applied for the discovering and recognition of plant leaf unhealthiness. Recognition of plant leaf diseases along some automatic method is useful as it decrease a huge effort of observing in large farms, and at initial phase itself it identify the signs of diseases. Plant leaf disease detection and identification includes the stages like image acquisition, image pre-processing, image segmentation, feature extraction and classification. This paper discusses techniques for image pre-processing, image segmentation algorithm used for automatic recognition and research on various plant leaf disease classification algorithms that may be used for leaves disease classification.

International Journal of Mathematical Sciences and Computing, Nov 8, 2016

In this paper, we propose an interaction based projection display system, which enables an infrar... more In this paper, we propose an interaction based projection display system, which enables an infrared pen touch interaction on flat surface (e.g. walls, whiteboard, tables), with a webcam (with an infrared filter removed) and a projector. The challenge of infrared pen touch detection is to sense the touching and movement information of an infrared pen on the surface just from the 2-dimensional image captured by the webcam. In our method, the content of a computer is projected on the surface and the user interacts with the surface using an infrared pen, the movement of an infrared pen is captured by the webcam. Here, the infrared LED light act as a tracking point which helps in controlling the content projected on surface. The proposed method is performed in three stages: 1) the infrared pen LED image is captured and tracked using webcam 2) the calibration of webcamprojector setup is done by principle of Homography 3) the tracked coordinates or location of Infrared pen LED is mapped to computer cursor. By this way, movement of infrared pen allows user to control computer content projected on the surface.

Journal of Discrete Mathematical Sciences and Cryptography

The exchange of medical information has been drastically altered by patient-centered developments... more The exchange of medical information has been drastically altered by patient-centered developments such as personal health records (PHR). By giving patients a place to handle their own PHR on a unified transactional platform, personal health record (PHR) services increase the efficiency with which medical information may be kept, accessed, and transferred. With the ultimate objective of providing patients with total surveillance under data, our findings is focused on creating a state-of-the-art infrastructure for the safe transfer of personal health data via cloud computing. Patients have the option of encrypting their PHR files, which provides an additional layer of security and allows them to set access control limits such as who has access to their files and to what degree. When data is encrypted in the cloud, only approved users may access it. Using cloud-based platforms to share health records raises concerns over confidentiality and privacy, which are addressed by the proposed ...

Lecture Notes in Networks and Systems

Proceedings of the 4th International Conference on Information Management & Machine Intelligence

International Journal on Recent and Innovation Trends in Computing and Communication, Mar 11, 2023

Artificial intelligence (AI) has the potential to transform the human resource (HR) industry by a... more Artificial intelligence (AI) has the potential to transform the human resource (HR) industry by automating routine tasks, improving decisionmaking, and enhancing employee engagement and retention. In this paper, we explore the use of machine learning and deep learning techniques to boost employee retention in the HR industry. We review the current state of the art in AI for HR, including the use of predictive analytics, natural language processing, and chatbots for talent management and employee development. We also discuss the challenges and ethical considerations of using AI in HR, including issues of bias and the need for transparent and explainable algorithms. Finally, we present case studies of successful AI-powered HR initiatives that have demonstrated improvements in employee retention and engagement. Our findings suggest that AI has the potential to significantly enhance employee retention in the HR industry, but its implementation requires careful planning and consideration of potential risks and ethical issues.

Wireless Communications and Mobile Computing

This is a topic that receives a lot of interest since many applications of computer vision focus ... more This is a topic that receives a lot of interest since many applications of computer vision focus on the detection of objects in visually appealing environments. Information about an object’s appearance and information regarding the object’s motion are both used as crucial signals in the process of identifying and recognising any given item. This information is used to characterise and recognise the item. The identification of objects based solely on their outward appearance has been the subject of a substantial amount of research. However, motion information in the recognition task has received only a marginal amount of attention, despite the fact that motion plays an essential role in the process of recognition. In order to analyze a moving picture in a way that is both fast and accurate, it is required to make use of motion information in conjunction with surface appearance in a strategy that has been designed. Dynamic texture is a kind of visual phenomenon that may be characteris...

BioMed Research International

Protein is the material foundation of living things, and it directly takes part in and runs the p... more Protein is the material foundation of living things, and it directly takes part in and runs the process of living things itself. Predicting protein complexes helps us understand the structure and function of complexes, and it is an important foundation for studying how cells work. Genome-wide protein interaction (PPI) data is growing as high-throughput experiments become more common. The aim of this research is that it provides a dual-tree complex wavelet transform which is used to find out about the structure of proteins. It also identifies the secondary structure of protein network. Many computer-based methods for predicting protein complexes have also been developed in the field. Identifying the secondary structure of a protein is very important when you are studying protein characteristics and properties. This is how the protein sequence is added to the distance matrix. The scope of this research is that it can confidently predict certain protein complexes rapidly, which compens...

Turkish Journal of Computer and Mathematics Education (TURCOMAT), Apr 5, 2021

Machine Learning Approach for Cloud Data Analytics in IoT, 2021

Journal of Information and Optimization Sciences, 2023

In computer music, instrument recognition is a critical part of sound modeling. Pitch, timbre, lo... more In computer music, instrument recognition is a critical part of sound modeling. Pitch, timbre, loudness, duration, and spatialization are all components of musical sounds. All of these components play a significant part in determining the quality of the tonal sound. It is possible to alter the first four parameters, but timbre always poses a challenge [6]. It was inevitable that timbre would take center stage. Musical instruments are distinguished from one other by their distinct sound quality, independent of their pitch or volume. To distinguish between monophonic and polyphonic music recordings, this method might be used. In Musical Information Retrieval, classification plays one of the critical role. Monophonic instrument classification can be found in literature with quiet a substantial combinations of features and classifiers. Polyphonic instrument classification witnessed less references in the literature and is still an area to be explored specifically when it comes to Indian Classical domain. The present paper exactly focusses on this experimentation. Several Indian instruments were used to produce training data sets for the proposed approach’s evaluation purposes. Among the instruments utilized are the flute, harmonium, and sitar. Statistical and spectral factors are used to classify Indian musical instruments along with the Artificial Intelligence-based methods. Hybrid features from multiple domains that extract essential musical properties are extracted. Accuracy is demonstrated through an Indian Musical Instrument SVM and GMM classification. With monophonic sounds, SVM and Polyphonic produce an average accuracy of 89% and 91%. GMM outperforms SVM in monophonic recordings by a factor of 96.33 and polyphonic recordings by a factor of 93.33, according to the results of the studies. The future scope of this recognition framework can be an Artificial Intelligence System with a system linked with the Industrial Internet of Things (IIOT) framework to develop a standalone system or application which can be used for real- time classification of instruments.

Lecture notes in networks and systems, 2023

Turkish Journal of Computer and Mathematics Education (TURCOMAT), Apr 5, 2021

Social media sites like Flickr permit clients to annotate pictures with free labels referred as “... more Social media sites like Flickr permit clients to annotate pictures with free labels referred as “tag”, which altogether contribute to the improvement of the web picture retrieval. Tag-based picture hunt is an important strategy to discover pictures contributed by social media users in such social sites. In this paper, we propose a social re-positioning framework for tag-based and feature based image retrieval with the thought of image significance and assorted qualities. In social media network, measuring the relevance of tags with respect to the visual, semantic and view contents is a critical task. We go for re-positioning image, concurring to their visual data, semantic data and social pieces of information. This framework gives the potential of tag relevance fusion for real-world deployment.

Parkinson’s disease is a central nervous system disorder in which dopamine generating cells prese... more Parkinson’s disease is a central nervous system disorder in which dopamine generating cells present in the substantia nigra (a part of our brain) gets damaged or perished. Due to a deficiency of dopamine, which acts as a neurotransmitter in our body, symptoms of Parkinson’s disease are caused. The change in vocal speech is one of the major symptoms shown and can be used to detect this disease. In this paper, there is an implementation and proprietary comparison of various machine learning models. The proposed model comparison shows that ANN is the comparatively better ML model to detect and predict Parkinson’s disease which has accuracy for total UPDRS is 83.56 % and for motor, UPDRS is 85.135 % which are the scales for measuring the severity elaborated further. We have utilized "Sklearn", "TensorFlow" and "Keras" python AI libraries to actualize all the ML models. It sums up that the accuracy generated by the proposed model is 84.45 % which is substantially higher than the research work done so far.

A novel approach to extract and retrieve furniture items from an image database and online websit... more A novel approach to extract and retrieve furniture items from an image database and online websites which includes multiple furniture items, and then find the similar items from the database. The image could be taken using phone cameras or downloaded from online websites or from shopping malls. A real time application is developed in android phone to find the similar images of furniture taken using the phone camera in which people are interested in. The additional processing can be divided into three steps: first, certain image segmentation techniques are need to be applied to split out each individual furniture item; then, an object recognition technique is applied to each segmented furniture item; finally a shape feature matching scheme is used to retrieve similar images to the segmented furniture items from the database.

International journal of computer applications, Nov 26, 2015

Interactive whiteboard involving human interaction have been an active field of research in past ... more Interactive whiteboard involving human interaction have been an active field of research in past years in human computer interaction (HCI). There is a need for adoption of natural interfaces between user and computing devices. This is trending in educational as well as corporate sector where various interactive application, tools and methodologies are used to make the presentation, summarization of difficult concepts easy and also to simulate collaborative work and enhance teaching practices. For Instance, it is a common practice to draw business processes on a traditional whiteboard, using conventional modeling notation such as UML, BPMN, during meetings between software programmers and business clients. Since it is a traditional whiteboard, software developer may need to redesign the process diagram on his computer by referring the whiteboard, this can be time consuming. Alternative way will be to use pen-based input device such as an electronic interactive whiteboard or graphics tablet. Use and working of interactive whiteboard have received researchers' attention as it has been found to be easy and highly effective interaction method. This paper presents a short review for interactive whiteboard technology and its operations proposed in the literature. Some examples of applications are also investigated.

International journal of computer applications, Feb 25, 2010

In the medical field, images, and especially digital images, are produced in ever increasing quan... more In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. Content based access to medical images for supporting clinical decision making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into Picture Archiving and Communication Systems (PACS) have been created. This article gives an overview of available literature in the field of content based access to medical image data and on the technologies used in the field. Section 1 gives an introduction into generic content based image retrieval and the technologies used. Section 2 describes the basic algorithm used in the implemented systems. Section 3 describes various methods of implementing CBIR. New research directions are being defied that can prove to This article also identifies explanations to some of the outlined problems in the field as it looks like many propositions for systems are made from the medical domain and research prototypes are developed in computer science departments using medical datasets. Still, there are very few systems that seem to be used in clinical practice. Content-Based Image Retrieval (CBIR) has been a topic of research interest for nearly a decade. Approaches to date use image features for describing content. A survey of the literature shows that progress has been limited to prototype systems that make gross assumptions and approximations.

Behavioural Neurology, Apr 11, 2022

The emergence of the latest technologies gives rise to the usage of noninvasive techniques for as... more The emergence of the latest technologies gives rise to the usage of noninvasive techniques for assisting health-care systems. Amongst the four major cardiovascular diseases, stroke is one of the most dangerous and life-threatening disease, but the life of a patient can be saved if the stroke is detected during early stage. The literature reveals that the patients always experience ministrokes which are also known as transient ischemic attacks (TIA) before experiencing the actual attack of the stroke. Most of the literature work is based on the MRI and CT scan images for classifying the cardiovascular diseases including a stroke which is an expensive approach for diagnosis of early strokes. In India where cases of strokes are rising, there is a need to explore noninvasive cheap methods for the diagnosis of early strokes. Hence, this problem has motivated us to conduct the study presented in this paper. A noninvasive approach for the early diagnosis of the strokes is proposed. The cascaded prediction algorithms are time-consuming in producing the results and cannot work on the raw data and without making use of the properties of EEG. Therefore, the objective of this paper is to devise mechanisms to forecast strokes on the basis of processed EEG data. This paper is proposing time series-based approaches such as LSTM, biLSTM, GRU, and FFNN that can handle time series-based predictions to make useful decisions. The experimental research outcome reveals that all the algorithms taken up for the research study perform well on the prediction problem of early stroke detection, but GRU performs the best with 95.6% accuracy, whereas biLSTM gives 91% accuracy and LSTM gives 87% accuracy and FFNN gives 83% accuracy. The experimental outcome is able to measure the brain waves to predict the signs of strokes. The findings can certainly assist the physicians to detect the stroke at early stages to save the lives of the patients.

International journal of scientific research in science, engineering and technology, Apr 15, 2020

Agrarian production is that trait on which our nation's economy immensely depends. This is th... more Agrarian production is that trait on which our nation's economy immensely depends. This is the motivation that recognition of leaves unhealthiness is the solution for saving the reduction of crops and productivity. It requisite enormous amount of work, mastery in the leaf diseases, and additionally need the extreme amount of time. Thus, image processing techniques are applied for the discovering and recognition of plant leaf unhealthiness. Recognition of plant leaf diseases along some automatic method is useful as it decrease a huge effort of observing in large farms, and at initial phase itself it identify the signs of diseases. Plant leaf disease detection and identification includes the stages like image acquisition, image pre-processing, image segmentation, feature extraction and classification. This paper discusses techniques for image pre-processing, image segmentation algorithm used for automatic recognition and research on various plant leaf disease classification algorithms that may be used for leaves disease classification.

International Journal of Mathematical Sciences and Computing, Nov 8, 2016

In this paper, we propose an interaction based projection display system, which enables an infrar... more In this paper, we propose an interaction based projection display system, which enables an infrared pen touch interaction on flat surface (e.g. walls, whiteboard, tables), with a webcam (with an infrared filter removed) and a projector. The challenge of infrared pen touch detection is to sense the touching and movement information of an infrared pen on the surface just from the 2-dimensional image captured by the webcam. In our method, the content of a computer is projected on the surface and the user interacts with the surface using an infrared pen, the movement of an infrared pen is captured by the webcam. Here, the infrared LED light act as a tracking point which helps in controlling the content projected on surface. The proposed method is performed in three stages: 1) the infrared pen LED image is captured and tracked using webcam 2) the calibration of webcamprojector setup is done by principle of Homography 3) the tracked coordinates or location of Infrared pen LED is mapped to computer cursor. By this way, movement of infrared pen allows user to control computer content projected on the surface.

Journal of Discrete Mathematical Sciences and Cryptography

The exchange of medical information has been drastically altered by patient-centered developments... more The exchange of medical information has been drastically altered by patient-centered developments such as personal health records (PHR). By giving patients a place to handle their own PHR on a unified transactional platform, personal health record (PHR) services increase the efficiency with which medical information may be kept, accessed, and transferred. With the ultimate objective of providing patients with total surveillance under data, our findings is focused on creating a state-of-the-art infrastructure for the safe transfer of personal health data via cloud computing. Patients have the option of encrypting their PHR files, which provides an additional layer of security and allows them to set access control limits such as who has access to their files and to what degree. When data is encrypted in the cloud, only approved users may access it. Using cloud-based platforms to share health records raises concerns over confidentiality and privacy, which are addressed by the proposed ...

Lecture Notes in Networks and Systems

Proceedings of the 4th International Conference on Information Management & Machine Intelligence

International Journal on Recent and Innovation Trends in Computing and Communication, Mar 11, 2023

Artificial intelligence (AI) has the potential to transform the human resource (HR) industry by a... more Artificial intelligence (AI) has the potential to transform the human resource (HR) industry by automating routine tasks, improving decisionmaking, and enhancing employee engagement and retention. In this paper, we explore the use of machine learning and deep learning techniques to boost employee retention in the HR industry. We review the current state of the art in AI for HR, including the use of predictive analytics, natural language processing, and chatbots for talent management and employee development. We also discuss the challenges and ethical considerations of using AI in HR, including issues of bias and the need for transparent and explainable algorithms. Finally, we present case studies of successful AI-powered HR initiatives that have demonstrated improvements in employee retention and engagement. Our findings suggest that AI has the potential to significantly enhance employee retention in the HR industry, but its implementation requires careful planning and consideration of potential risks and ethical issues.

Wireless Communications and Mobile Computing

This is a topic that receives a lot of interest since many applications of computer vision focus ... more This is a topic that receives a lot of interest since many applications of computer vision focus on the detection of objects in visually appealing environments. Information about an object’s appearance and information regarding the object’s motion are both used as crucial signals in the process of identifying and recognising any given item. This information is used to characterise and recognise the item. The identification of objects based solely on their outward appearance has been the subject of a substantial amount of research. However, motion information in the recognition task has received only a marginal amount of attention, despite the fact that motion plays an essential role in the process of recognition. In order to analyze a moving picture in a way that is both fast and accurate, it is required to make use of motion information in conjunction with surface appearance in a strategy that has been designed. Dynamic texture is a kind of visual phenomenon that may be characteris...

BioMed Research International

Protein is the material foundation of living things, and it directly takes part in and runs the p... more Protein is the material foundation of living things, and it directly takes part in and runs the process of living things itself. Predicting protein complexes helps us understand the structure and function of complexes, and it is an important foundation for studying how cells work. Genome-wide protein interaction (PPI) data is growing as high-throughput experiments become more common. The aim of this research is that it provides a dual-tree complex wavelet transform which is used to find out about the structure of proteins. It also identifies the secondary structure of protein network. Many computer-based methods for predicting protein complexes have also been developed in the field. Identifying the secondary structure of a protein is very important when you are studying protein characteristics and properties. This is how the protein sequence is added to the distance matrix. The scope of this research is that it can confidently predict certain protein complexes rapidly, which compens...

Turkish Journal of Computer and Mathematics Education (TURCOMAT), Apr 5, 2021

Machine Learning Approach for Cloud Data Analytics in IoT, 2021