Jntu Kakinada
Compuer Science and Engineering
— Agriculture is a significant part of a developing country like India, and agricultural intervention is essential in rural livelihood. As per the statistical measurement, 65% of the Indian economy is dependent on agriculture and... more
— Agriculture is a significant part of a developing
country like India, and agricultural intervention is essential in
rural livelihood. As per the statistical measurement, 65% of
the Indian economy is dependent on agriculture and farming.
On the other hand, various plant diseases hugely affect most
crops. In this concern, the farmer needs an effective plant leaf
disease analysis model to detect plant illness in t h e early
stages to moderate the criticality and prevent severe losses in
crop growth, quantity and production etc. In this regard, it is
possible to mention that the plant leaf disease identification
methods play a major role in protecting plants. Researchers
are working to analyze the plant diseases by using recognized
classifying techniques. Supportive, deep learning and Image
processing are the leading cutting-edge technologies used to
address these challenges. This work uses the Resnet 152 v2
model on a data set containing 7000 plant leaf pictures. The
model achieved 95% accuracy which is better than many
previous models discussed in the literature.
country like India, and agricultural intervention is essential in
rural livelihood. As per the statistical measurement, 65% of
the Indian economy is dependent on agriculture and farming.
On the other hand, various plant diseases hugely affect most
crops. In this concern, the farmer needs an effective plant leaf
disease analysis model to detect plant illness in t h e early
stages to moderate the criticality and prevent severe losses in
crop growth, quantity and production etc. In this regard, it is
possible to mention that the plant leaf disease identification
methods play a major role in protecting plants. Researchers
are working to analyze the plant diseases by using recognized
classifying techniques. Supportive, deep learning and Image
processing are the leading cutting-edge technologies used to
address these challenges. This work uses the Resnet 152 v2
model on a data set containing 7000 plant leaf pictures. The
model achieved 95% accuracy which is better than many
previous models discussed in the literature.
- by brahmaji godi
- •
In the present study Diabetics is one of the critical diseases which can fall at any group of age and gender. The major causes lead to diabetics is mostly inheritance, in a proper healthy lifestyle, Irregular food habits, stress, and no... more
In the present study Diabetics is one of the critical diseases which can fall at any group of age and gender. The major causes lead to diabetics is mostly inheritance, in a proper healthy lifestyle, Irregular food habits, stress, and no physical exercise. Prediction of Diabetics is a very important study since it is one of the leading causes of sudden kidney failures, heart attacks, and brain stroke etc. The diabetic patient treatment can be done through patient health history. The Doctor can find hidden information about the patient through healthcare applications and it will be used for effective decision-making for the patient"s health condition. The healthcare industry is also collecting a large amounts of patient health information from different data warehouses. Using these healthcare databases researchers used to extract information for predicting the diabetics of the patient. Researchers are focused on developing software with the help of machine learning methods that can help clinicians to make better decisions about a patient's health based on their prediction and diagnosis. The main purpose of this program is to diagnose a patient's diabetes using machine learning methods. A relative study of the various competences of machine learning approaches will be done through a graphical representation of the results. The goal and objective of this project is to predict the chances of diabetics then provide early treatment to patients, which will reduce the life-risk and cost of treatment. For this purpose a probability modeling and machine learning approach like Support Vector Machine algorithm Decision tree algorithm, Naive Bayes algorithm, Logistic regression algorithm are used to predict diabetics.
- by brahmaji godi
- •
Internet of Things (IoT) is an emerging technology that is drastically improving with many new enhancements in medical and health domains. IoT Health wearable devices are taking new challenges by upgrading with innovative technology and... more
Internet of Things (IoT) is an emerging technology that is drastically improving with many new enhancements in medical and health domains. IoT Health wearable devices are taking new challenges by upgrading with innovative technology and resources. Using health wearable devices, in/out patient's health status can be monitored periodically and regularly. This paper introduces an IoT application framework E-Healthcare Monitoring System (EHMS) integrated with Machine learning (ML) techniques to design an advanced automation system. Using this system it will connect, monitor and decisions making for proper diagnosis.
- by brahmaji godi
- •
Internet of Things (IoT) is playing a dynamic role in day to day human lives. It is an integrated platform relates with physical sensor components, wireless device networks, cloud based databases and application monitoring systems.... more
Internet of Things (IoT) is playing a dynamic role in day to day human lives. It is an integrated platform relates with physical sensor components, wireless device networks, cloud based databases and application monitoring systems. Technology of IoT expanded in many research areas such Agricultural forming, Air pollution, Wastage management, E-health monitoring etc. In this scenario the proposed system which relates to logistical industrial operation so, the authors try to use the Internet of Things as a solution to the problem. At present moving explosive vehicles are not monitored specifically by any online automated system. The aspect of monitoring and controlling moving heavy explosive vehicles is tough, which are carrying huge amount of cargo such as pharmacy chemicals, oils, gases. It is very difficult to monitor the moving vehicles in industrial areas and other locations. The major problem is with the identification of certain issues such as local and global positioning, park...
- by brahmaji godi and +1
- •
According to the norms of the Indian government, Aadhaar provides singlesource identity verification across the country for the residents. Currently, Aadhaar services are inadequate in our country. Even now, more than 30% of our Indian... more
According to the norms of the Indian government, Aadhaar provides singlesource identity verification across the country for the residents. Currently, Aadhaar services are inadequate in our country. Even now, more than 30% of our Indian population's information is not available with the Aadhaar server. According to the 2019 population census, about 89 crores of people are residents in rural areas. In our country, due to more population and fewer resources, much of the rural people’s information is not completely informed up to the mark. Even the government is taking relevant steps to collect the right information from the rural people. In this concern, other hidden reasons are also affecting rural development such as lack of education, awareness, and nearby resources. In the existing scenario, no sufficiently advanced automation system is available for Aadhaar services in rural areas. In the view of the Aadhaar grievance service, to overcome these issues researchers have proposed...
- by brahmaji godi
- •
Nowadays preparing an effective model for face recognition is difficult task. Face is a critical and complex multidimensional visual model. However in this Article, we present a method for face recognition based on Hidden Markov Model... more
Nowadays preparing an effective model for face recognition is difficult task. Face is a critical and complex multidimensional visual model. However in this Article, we present a method for face recognition based on Hidden Markov Model (HMM) and it has been widely used in various fi elds such as in speech recognition, gesture recognition and so on. We proposed this approach basically current face recognition techniques are dependent on issues like background noise, lighting and position of key features (i.e. the eyes, lips etc.).Moreover the face patterns are divided into numerous small-scale states and they are recombined to obtain the recognition result. Our experimental results shows that the proposed method has been achieved 96.5% recognition accuracy for 400 patterns of 40 Subjects i.e. 40 classes of which each class contains 10 patterns each. Apart from these results we did some comparative analysis with PCA. Over observations stated that the performance of HMM based face-recognition method is better than the PCA for face recognition.
The main objective of this paper is to give high performance gain in order to achieve high throughput with less delay. In communication networks, buffers are used to accommodate short term packet bursts so as to less packet drops and to... more
The main objective of this paper is to give high performance gain in order to achieve high throughput with less delay. In communication networks, buffers are used to accommodate short term packet bursts so as to less packet drops and to maintain high efficiency. Sizing buffers in wireless networks has fundamental issues arise when compared with wired, which leads to packet service times at different stations in WLANs being strongly coupled. the major presentation associated with the use of fixed size buffers in 802.11 WLANs and present dynamic buffer sizing algorithms that achieve significant performance gains and how the utility of proposed algorithm gives simulation results.
- by DEVANA RAJESWARI
- •
Unlike competing online Infringement solutions, Infringement is copy-paste elimination software. Infringement is the illegal use of another person's words or ideas without permission. It's a dishonest thing to do. Copyscape is an... more
Unlike competing online Infringement solutions, Infringement is copy-paste elimination software. Infringement is the illegal use of another person's words or ideas without permission. It's a dishonest thing to do. Copyscape is an anti-piracy programme that ensures all of our customers' essays and term papers are 100% unique. Users and organisations alike can now use cloud computing to access their data and run their programmes from any device with an internet connection, eliminating the need for local installations of software. Cloud computing is a method of storing and accessing information and software on remote servers and networks.Professors should be concerned about infringement because it happens frequently. Students in many engineering and computer science degree programmes take online courses where they are graded on the code they create on their own or in small groups. Multiple indicators make it hard to spot infringing code. Therefore, it is necessary to create an Infringement checking system that will accept code submissions from teachers and quickly identify instances of plagiarism. In other words, it analyses the structure of each uploaded assignment and finds any similarities. A straightforward style is used to summarise the similarity analysis results, which show which tasks are most similar to one another. This method has the advantage of relieving teachers of the tedious task of checking for Infringements.
- by Sai Srinivas Vellela and +3
- •
- Computer Science
This work makes two significant contributions to the current status of viticulture technology studies. We start with a detailed look at the history and current state of computer vision, image processing, and machine learning applications... more
This work makes two significant contributions to the current status of viticulture technology studies. We start with a detailed look at the history and current state of computer vision, image processing, and machine learning applications in the wine industry. We provide a concise overview of recent advances in vision systems and methodologies by analysing case studies from a wide range of fields, including as crop yield estimation, vineyard management and monitoring, disease detection, quality evaluation, and grape phonology. Here, we zero in on the ways in which modern vineyard management and vinification procedures can benefit from the application of computer vision and machine learning. In the paper's second section, we introduce the brandnew Grape CS-ML Database, which contains photos of grape varietals at various stages of development alongside the relevant ground truth data (e.g. pH, Brix, etc.) collected from chemical analysis. The creation of useful solutions for use in smart vineyards is a primary goal of this database, and it is hoped that it will inspire academics in computer vision and machine learning to work on this problem. We showcase the database's potential for a color-based berry recognition application by comparing white and red cultivars across a number of machine learning methods and colour spaces, and providing a set of reference data for evaluation. The study finishes by pointing out some of the issues that will need to be resolved in the future in order to fully utilise this technology in the viticulture industry.
- by Sai Srinivas Vellela and +3
- •
- Machine Learning
Nowadays, digitalization in the healthcare organizations places great emphasis on technological advances in clinical healthcare providers. Traditional methods for measuring and evaluating outcomes for patients in forecasting and... more
Nowadays, digitalization in the healthcare organizations places great emphasis on technological advances in clinical healthcare providers. Traditional methods for measuring and evaluating outcomes for patients in forecasting and diagnosing chronic diseases are being substituted by techniques that capture the most significant insights from medical information by combining predictive modeling with a highly valuable application of machine learning. Heart disease is nowadays among the worst disorders in the world. Because the death rate from heart disease remained largely significant, more intensive efforts in preventive are required, such as enhancing the accuracy of a heart disease prediction system. Additionally, an early diagnosis supports in the appropriate diagnosis of the condition as well as the management of its symptoms. By creating forecasting analytics, Machine Learning (ML) techniques can be used to anticipate chronic diseases including kidneys and cardiac disorders. Hence, this analysis presents coronary heart disease prediction and classification utilizing Hybrid Machine Learning methods. In this approach the combination of Decision Tree (DT) and Ada Boosting algorithms is used as a hybrid ML algorithm to predict the CHD. This method's performance is determined by the performance metrics such as accuracy, True Positive Rate (TPR), and S pecificity.
- by Sai Srinivas Vellela and +3
- •
- Computer Science
In order to share the initial data and the secret keys that will be used to encrypt the data, a secure protocol is presented in this research for spontaneous wireless ad hoc networks that leverages a hybrid symmetric/asymmetric scheme and... more
In order to share the initial data and the secret keys that will be used to encrypt the data, a secure protocol is presented in this research for spontaneous wireless ad hoc networks that leverages a hybrid symmetric/asymmetric scheme and the trust between users. Users' confidence in one another is established through their initial physical interaction. Our proposed solution is an end-to-end self-configuring secure protocol that can set up the network and provide secure services independently of any preexisting physical or virtual infrastructure. In a protected setting, users are able to pool resources and provide one other with access to innovative services. All necessary features for functioning independently are built within the protocol. We have created and refined it in low-powered devices. Communication, protocol messages, and network management, as well as the various processes involved in the formation of a network, are all broken down and described. Our solution is already in place, and is being used to evaluate the protocol's functionality and efficiency. Finally, we offer a security analysis of the system and compare the protocol to other protocols used in spontaneous ad hoc networks to emphasise its unique qualities.
- by Khader Basha Sk and +3
- •
- Computer Engineering
Power and other computing resources can be stored and processed in cloud computing environments. Depending on the features of the clients' devices, video streams, whether they are live or on-demand, often need to be transcoded or... more
Power and other computing resources can be stored and processed in cloud computing environments. Depending on the features of the clients' devices, video streams, whether they are live or on-demand, often need to be transcoded or converted (such as supported formats, bandwidth, and spatial resolution, for example). Currently, streaming service providers maintain multiple transcoded versions of the same video to serve various client devices because transcoding is a computationally expensive and time-consuming process. To eliminate jitters in accepted streams while transcoding, a task scheduling mechanism is included. To ensure that the consumer receives continuous video content delivery, this technique involves cutting a tiny number of video frames from a video segment. In this evaluation, admission control and scheduling based on QoS-aware video streams is the new task scheduling method for video recording that is suggested. With the help of this framework, streaming platform services have made efficient use of cloud resources while following to the Quality of Service (QoS) standards for video transmissions. The technologies are advancing a scheduling technique that is QoS-aware to effectively map video streams to cloud resources in order to deliver high QoS. The performance of this analysis is calculated on different aspects such as Accuracy, Qos and Recall. In this approach the QoS-aware video streaming based admission control and scheduling for video transcoding in cloud computing will give the best outcomes.
Cloud computing technology provides new opportunities for start-up,outsourcing individuals and corporations in health care outsourcing data and processing. The use of modern information technology can significantly improve the healthcare... more
Cloud computing technology provides new opportunities for start-up,outsourcing individuals and corporations in health care outsourcing data and processing. The use of modern information technology can significantly improve the healthcare system. As ubiquitous computing for novel healthcare systems, services, and applications became more closely linked to Cloud systems, the applications needed environments that were scalable, dependable, and secure, and containerized environments provided the right solutions.As the usage of,eHealth solutions advances new computer paradigms, such as cloud computing, have the potential to boost efficiency in storing medical health information while also lowering costs.In developing and underdeveloped nations, traditional analysis-based healthcare systems are still in use. Even though very few organisations use computer-based applications, doctors, and the government were unable to create a widespread network. A heterogeneous network can be built using the new technology of cloud computing to enhance the system. In this process,a cloud-based application with an integrated strategy and patients has been created to upgrade an antiquated healthcare system. Using this method, enormous numbers of Electronic Medical Records (EMR) will be saved every day.Furthermore, this way of developing an eHealth system ensures patient data privacy in the cloud.The platform presented here can be improve of a variety of cloud computing infrastructures that provide standardised, adaptive, and customised services for eHealth systems. The performance of this analysis is calculated on different aspects such as Accuracy, Precision, and S pecificity. Though the outcomes for various methods are different,an integrated approach to improve eHealthcare S ystem using dynamic Cloud Computing Platform will be the best results in this analysis.
Searching keywords in databases is complex task than search in files. Information Retrieval (IR) process search keywords from text files and it is very important that queering keyword to the relational databases. Generally to retrieve... more
Searching keywords in databases is complex task than search in files. Information Retrieval (IR) process search keywords from text files and it is very important that queering keyword to the relational databases. Generally to retrieve data from relational database Structure Query Language(SQL) can be used to find relevant records from the database. There is natural demand for relation database to support effective and efficient IR Style Keyword queries. This paper describes problem of supporting effective and efficient top-k keyword search in relational databases also describe the frame word which takes keywords and K as inputs and generates top-k relevant records .The results of implemented system with Skyline Sweeping(S.S) Algorithm shows that it is one effective and efficient style of keyword search
In recent years, Steganography and Steganalysis are two important areas of research that involve a number of applications. These two areas of research are important especially when reliable and secure information exchange is required.... more
In recent years, Steganography and Steganalysis are two important areas of research that involve a number of applications. These two areas of research are important especially when reliable and secure information exchange is required. Steganography is an art of embedding information in a cover image without causing statistically significant variations to the cover image. Steganalysis is the technology that attempts to defeat Steganography by detecting the hidden information and extracting. In this paper we propose an image Steganography that can verify the reliability of the information being transmitted to the receiver. The method can verify whether the attacker has tried to edit, delete or forge the secret information in the stegoimage. The technique embeds the hidden information in the spatial domain of the cover image and uses two special AC coefficients of the Discrete Wavelet Transform domain to verify the veracity (integrity) of the secret information from the stego image. The analysis shows that the BER and PSNR are improved in the case of DWT than DCT.
When conducting searches in biomedical databases like PubMed, users are often presented with a high number of results, only a small fraction of which are actually relevant. Some solutions to the problem of too much information include... more
When conducting searches in biomedical databases like PubMed, users are often presented with a high number of results, only a small fraction of which are actually relevant. Some solutions to the problem of too much information include ranking and categorising, both of which can be combined. In this study, we concentrate on developing a system for classifying search results in biological databases. Annotating references in the biomedical literature with MeSH terms is a logical technique to categorise them. MeSH is the PubMed Subject Headings, a comprehensive concept hierarchy. In this study, we introduce the BioNav system, an innovative search interface that hierarchically organises search results according to medical subject headings. The search results are initially shown in a tree-like structure. BioNav only shows a fraction of the idea nodes at each node expansion stage to keep the estimated user navigation cost low. Whereas, prior efforts enlarge the hierarchy in a static, specified fashion, with no consideration for navigation cost modelling. We prove that choosing which concepts to reveal at each node expansion is an NP-complete issue, and we suggest both a heuristic and an optimal solution that is practical for trees of a manageable size. We demonstrate empirically that the user navigation cost is reduced by using BioNav compared to the best state-of-the-art classification methods. Exploration and finding of data through interactive means, The Look For, Interface design, User interaction methods.
- by Sai Srinivas Vellela and +3
- •
- Computer Science
Cloud computing technology provides new opportunities for start-up,outsourcing individuals and corporations in health care outsourcing data and processing. The use of modern information technology can significantly improve the healthcare... more
Cloud computing technology provides new opportunities for start-up,outsourcing individuals and corporations in health care outsourcing data and processing. The use of modern information technology can significantly improve the healthcare system. As ubiquitous computing for novel healthcare systems, services, and applications became more closely linked to Cloud systems, the applications needed environments that were scalable, dependable, and secure, and containerized environments provided the right solutions.As the usage of,eHealth solutions advances new computer paradigms, such as cloud computing, have the potential to boost efficiency in storing medical health information while also lowering costs.In developing and underdeveloped nations, traditional analysis-based healthcare systems are still in use. Even though very few organisations use computer-based applications, doctors, and the government were unable to create a widespread network. A heterogeneous network can be built using the new technology of cloud computing to enhance the system. In this process,a cloud-based application with an integrated strategy and patients has been created to upgrade an antiquated healthcare system. Using this method, enormous numbers of Electronic Medical Records (EMR) will be saved every day.Furthermore, this way of developing an eHealth system ensures patient data privacy in the cloud.The platform presented here can be improve of a variety of cloud computing infrastructures that provide standardised, adaptive, and customised services for eHealth systems. The performance of this analysis is calculated on different aspects such as Accuracy, Precision, and S pecificity. Though the outcomes for various methods are different,an integrated approach to improve eHealthcare S ystem using dynamic Cloud Computing Platform will be the best results in this analysis.
Publishing or sharing the social network data for social science research and business analysis lack of privacy. Existing technique k-anonymity is used to prevent identification of microdata. Even though an attacker may gaining sensitive... more
Publishing or sharing the social network data for social science research and business analysis lack of privacy. Existing technique k-anonymity is used to prevent identification of microdata. Even though an attacker may gaining sensitive data if a group of nodes largely share the same sensitive labels. We propose an algorithm, universal-match based Indirect Noise Node which makes use of noise nodes to preserve utilities of the original graph. Finally that technique prevents an attacker from reidentifying a user and finding the fact that a certain user has a specific sensitive value.