Papers by kavitha chaduvula
International journal of engineering and advanced technology, Oct 10, 2019
The primary objective of this paper is to embed secret information using Binary-Square Embedding ... more The primary objective of this paper is to embed secret information using Binary-Square Embedding (BSE) technique in binary image. Using BSE, we intend to use an associate rule for Reversible Data Concealing in Encipher Images (BSE-RDCEI). This approach use BSE to implant binary bits in subordinate bit-planes of the first picture into its superior bitplanes such that the subordinate bit-planes be able to be kept back for concealing undisclosed information in resulting progression. BSE-RDCEI utilize bit-stage scrambling method when undisclosed information implant to unfold implant undisclosed information to the complete noticeable encipher image so it will forestall undisclosed information as of failure. A safety key style method is projected to reinforce the safety stage of BSE-RDCEI. Procedures of BSE-RDCEI be totally revertible. The key information & unique picture will exist remade in various ways. Examinations and correlations demonstrate that BSE-RDCEI has relate implanting rate about doubly bigger than the dynamic calculations, creates the checked decoded pictures with prime quality, and is in a situation to oppose the animal power, differential, commotion and data misfortune assaults.
Alzheimer's disease classification using competitive swarm <scp>multi‐verse</scp> optimizer‐based deep <scp>neuro‐fuzzy</scp> network
Concurrency and Computation: Practice and Experience, Mar 25, 2023
SummaryClassification of Alzheimer's disease (AD) from neuroimaging, like magnetic resonance ... more SummaryClassification of Alzheimer's disease (AD) from neuroimaging, like magnetic resonance imaging (MRI) through deep learning classifier has been increasing in research in recent decades. However, it is required for enhancing the accuracy of the AD classification for effective treatment. In this work, an efficient model termed competitive swarm multi‐verse optimizer + deep neuro‐fuzzy network (CSMVO + DNFN) is designed to accurately classify stages of AD. Preprocessing is done with a median filter. Then, the resulting image is segmented to find the interested regions by channel‐wise feature pyramid network module (CFPNet‐M). Some features obtained from the segmented image are haralick, convolutional neural network, and texture features. The devised method is more efficient in classifying different stages of AD with MRI modality. Furthermore, the developed model attained higher performance using metrics like the accuracy of 89.9%, sensitivity of 89.6%, and specificity of 87.0% based on the k‐fold value.
International Journal of Modern Education and Computer Science, Oct 8, 2022
By and large, software testing can be well thought-out as a adept technique of achieving improved... more By and large, software testing can be well thought-out as a adept technique of achieving improved software quality as well as reliability. On the other hand, the eminence of the test cases had significant effect on the fault enlightening competence of testing activity. Prioritization of Test case (PTC) remnants one challenging issue, as prioritizing test cases remains not up in the direction of abrasion by means of respect to Faults Detected Average Percentage (FDAP) and time execution results. The PTC is predominantly anticipated to scheme assortment of test cases in accomplishing timely optimization by means of preferred properties. Earlier readings have been presented for place in order the accessible test cases in upsurge speed the fault uncovering rate in testing. In this phase, this learning schemes a Modern modified Harris Hawks Optimization centered PTC (M 2 H 2 O-PTC) method for testing. The anticipated M 2 H 2 O-PTC method aims to exhaust the possibilities the FDAP and curtail the complete execution time. Besides, the M 2 H 2 O algorithm is considered for boosting the examination and taking advantage abilities of the conservative H 2 O algorithm. For validating the enhanced efficiency of the M 2 H 2 O-PTC method, an extensive variety of simulations occur on contradictory standard programs and the outcomes are inspected underneath numerous characteristics. The investigational results emphasized enhanced proficiency of the M 2 H 2 O-PTC method in excess of the modern methodologies in standings of dissimilar measures.
Visual and buying sequence features-based product image recommendation using optimization based deep residual network
Gene Expression Patterns, Sep 1, 2022
Content-based video recommendation system (CBVRS): a novel approach to predict videos using multilayer feed forward neural network and Monte Carlo sampling method
Multimedia Tools and Applications, Aug 11, 2022
A Detailed Survey on Bit Plane Complexity Segmentation (BPCS) and RSA Algorithm for Secured Medical Data Transfer
2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), Sep 24, 2021
For computer users, data security is a major concern. In the medical field the data must be prese... more For computer users, data security is a major concern. In the medical field the data must be present in a hidden form rather than original. Each of us has essential medical data that we want to keep safe from others. Bit Plane Complexity Segmentation (BPCS) is described in this article as a method for hiding information within images in various planes. The algorithm can be used with the RSA public key encryption scheme to enhance security in data transmission. It is important to determine a threshold (approximate) value so that the stego and original images are the same, and so that the hiding capacity is greater with less computing cost. This process imposes a number of restrictions. This paper presents two modules encryption and decryption while transferring medical text in a hidden mode. Error rate is calculating with PSNR, BER and MER with three bit planes Red, Blue and Green.
Design and Implementation of IoT based flood alert monitoring system using microcontroller 8051
Materials Today: Proceedings, Jul 1, 2021
Abstract In the Internet of Things (IoT) the physical objects network is described as “things” li... more Abstract In the Internet of Things (IoT) the physical objects network is described as “things” linked to sensors, software and other technologies to connect and share information through the Internet with other devices and systems. The floods lead to large losses of life and property in several countries. However, the absence of sufficient technology results in further death and property losses as a result of flooding in developed countries. This is because of a lack of flood alert systems. The objective of this paper is to monitor the flood situation and provide a text message warning in the event of a threat. The main aim of this paper is to detect rising river water levels at a safe distance away from the railways and to allow the respective authorities to take appropriate measures by means of SMS. A sensor is a system that senses and reacts to certain physical data. The 8051 microcontrollers were produced by Intel in 1981. The microcontroller is 8-bit. It has 40 DIP pins, 4 kb of ROM stores and 128 bytes of RAM and two timers and 16 bits. It is equipped with 2 timers. There are four parallel 8-bit ports that are programmable and adjustable as necessary. The hardware device that uses GSM mobile technology for the provision of an information link with a remote network is a GSM modem or a GSM module. A float switch is a level sensor type, a fluid control system that is used inside a tank. A condenser is a tool that stores electrical energy in an electric field. It's a passive electronic feature with two terminals. A LED is a semiconductor light source that transmits light through the flowing current. Liquid Crystal Display stands for LCD. It is a thin, flat display device used in a variety of electronics. A digital electronic level shifter is a system used in the transformation of signs from one logic or voltage domain to another, also known as logic level shifter or voltage level Translation. A diode is an electronic component with a two-terminal that mainly conducts current in one direction, with low resistance and high resistance in one direction. The aim of this paper is to detect early Flood and give early warnings to Needy people.
Zenodo (CERN European Organization for Nuclear Research), Jun 15, 2023
Objectives-The aim of the project is to design and development of IoT based security surveillance... more Objectives-The aim of the project is to design and development of IoT based security surveillance system using Arduino and ESP32 Cam. Paper focuses on sophisticated visual based security surveillance technologies. In the previous era, we have monitored and recorded situations using surveillance cameras, but manually. One of the most significant and difficult areas of computer vision is surveillance and real-time monitoring, which has many applications in daily life, including security monitoring. Given that the recorded footage may be used to identify persons and track their movements, the installation of surveillance cameras and a sign warning that the area is being watched can significantly dissuade thieves and criminals. Research design/methodology-The system is designed to detect motion using a passive infrared (PIR) sensor and trigger the ESP32 Cam.In addition, the system is equipped with a SIM module that allows the system to send SMS notifications to a designated recipient in case of a detected motion event.The system provides a simple and efficient solution for monitoring and protecting the environment. Overview of findings-Wi-Fi, a local area network that operates in a scattered or local environment, can make it more sophisticated. One of the most popular communication technologies in use today is the IoT area that allows low transmit power & low cost is the Wi-Fi network protocol. The ESP32, comes with Wi-Fi. High network traffic and computing load are reduced by ESP32. With the use of sensors linked to the security cameras, this system enables the user to receive notifications whenever an intrusion is detected.
International Journal of Integrated Engineering, Dec 31, 2022
The heart anomalies detection is a significant task in cardiac medical research. The CT, ULTRASOU... more The heart anomalies detection is a significant task in cardiac medical research. The CT, ULTRASOUND, CTA and MRI scans have been used to detect heart diseases but giving false experimental outcomes in longer time of conversion (ToC). Therefore, patients haven't getting better treatment from doctors. So that in this research work an ultrasound image scan-based heart disease prediction and classification is performed with deep learning technology. The LeNet 10 deep learning classifier has been trained Kaggle dataset using appropriate CNN layers. Proposed CNN LeNet-10 is a 165 layers technology consists of flattened layer, dense layer, convolution layer, max pooling layer and etc. Classification and feature extraction has been performed to loading with LeNet-10 architecture. The real time heart ultrasound test images are collecting from Manipal super specialty hospital Vijayawada, these test features are managed to test.CSV file. In pre-processing step, Ostu segmentation and histogram equalization is applied to make heart ultrasound images to be clear. In Segmentation, edge and region-based convolutional steps are applied such that deep features have been identified. LeNet-10 classification is used to find affected area as well as abnormality location. Finally proposed deep learning with confusion matrix can generating application measures. Implementation has been performed on python 3.9 and DL (Deep learning) packages like TensorFlow, keras, sklearn and etc. The measures like Accuracy 98.37%, sensitivity 97.81%, Recall 98.34% and F1 score 98.98% had been attained, proposed heart disease estimation application is more robust and compete with present technology.
De-raining a Single Picture Using Multi-scale Recurrent Neural Networks
2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)
Alzheimer's disease classification using competitive swarm multi‐verse optimizer‐based deep neuro‐fuzzy network
Concurrency and Computation: Practice and Experience
A Real and Accurate Ultrasound Fetal Imaging Based Heart Disease Detection Using Deep Learning Technology
International Journal of Integrated Engineering
The heart anomalies detection is a significant task in cardiac medical research. The CT, ULTRASOU... more The heart anomalies detection is a significant task in cardiac medical research. The CT, ULTRASOUND, CTA and MRI scans have been used to detect heart diseases but giving false experimental outcomes in longer time of conversion (ToC). Therefore, patients haven’t getting better treatment from doctors. So that in this research work an ultrasound image scan-based heart disease prediction and classification is performed with deep learning technology. The LeNet 10 deep learning classifier has been trained Kaggle dataset using appropriate CNN layers. Proposed CNN LeNet -10 is a 165 layers technology consists of flattened layer, dense layer, convolution layer, max pooling layer and etc. Classification and feature extraction has been performed to loading with LeNet-10 architecture. The real time heart ultrasound test images are collecting from Manipal super specialty hospital Vijayawada, these test features are managed to test.CSV file. In pre-processing step, Ostu segmentation and histogram...
Content-based video recommendation system (CBVRS): a novel approach to predict videos using multilayer feed forward neural network and Monte Carlo sampling method
Multimedia Tools and Applications
International Journal on Smart Sensing and Intelligent Systems
This manuscript proposes a cloud data storage security, which has always been an important aspect... more This manuscript proposes a cloud data storage security, which has always been an important aspect of Quality of Service (QOS). Here, an effectual and flexible distributed scheme (DS) with Explicit Dynamic Data Support (EDDS) is proposed to ensure the accuracy of user data in the cloud. By using hemimorphic token with distributed verification of erasure-coded data, the proposed scheme achieves the integration of storage correctness insurance and data error localization. The proposed scheme supports secure and efficient dynamic operations on data blocks, such as data update, delete and append. The performance analysis shows that the proposed scheme is highly efficient.
An optimized generalized adversarial system for predicting specific substructures in brainstem
Multimedia Tools and Applications
Visual and buying sequence features-based product image recommendation using optimization based deep residual network
Gene Expression Patterns
A New hybrid classification algorithm for predicting customer churn
2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), 2021
Decision trees, support vector machine and gradient boosting are very popular algorithms for pred... more Decision trees, support vector machine and gradient boosting are very popular algorithms for predicting the customer churn with good comprehensibility and strong predictive performance. In spite ofall strengths, the decision trees be likely have some problems forholding linear-relations amongthe variables, support vector machine performs marginally better than logistic regression, and gradient boosting givesgreater results when compared with logistic regression, with less development effort. Hencenew hybrid-algorithm, aboosting leaf model (BLM), was proposed forclassifying the data in better way. The basic idea behind this BLM is diverse models was constructed among the segments of data instead of entire dataset thusleads to improved predictive performances how ever observance comprehensibility among those models which constructed on leaves. ThisBLM resides two stages they are one is segmentation and the other one is prediction stages. Inthe first stageby using decision tree segment...
A Detailed Survey on Bit Plane Complexity Segmentation (BPCS) and RSA Algorithm for Secured Medical Data Transfer
2021 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)
Now a day images or pictures play a prominent role in the world. Content-based image retrieval (C... more Now a day images or pictures play a prominent role in the world. Content-based image retrieval (CBIR) systems are used to retrieve similar images based on query image. This system is capable of identifying similarities between query image and the set of images placed in the database. Even though it is an important research area from the last two decades, still there is scope for new technologies and algorithms to manipulate large amount of image databases in different fields like medical, social media and space images. Image contents are colors, texture and shape play significant role for image retrieval. All most all image retrieval systems are based on efficient feature extraction methods which are well-organized. This paper mainly concentrates to extract exact or most relevant images from the image database, here we compare query image with database image using pixels present in intensity vector. To accomplish this, the images are converted into gray scale. To achieve this, we ar...
Feature Extraction assumes a significant function in the region of picture handling. Before getti... more Feature Extraction assumes a significant function in the region of picture handling. Before getting Features, different picture pre-processing strategies like binarization, thresholding, resizing, standardization and so forth are applied on the inspected picture. From that point onward, Feature extraction methods are applied to get Features that will be helpful in arranging and acknowledgment of pictures. Feature extraction strategies are useful in different picture handling applications for example character acknowledgment. As Features characterize the conduct of a picture, they show its place regarding capacity taken, proficiency in arrangement and clearly in time utilization moreover. Here in this paper, we will talk about different kinds of Features, include extraction procedures and clarifying in what situation, which Features extraction method, will be better. Thus, in this paper, we will mention Features and Feature extraction strategies if there should be an occurrence of ch...
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Papers by kavitha chaduvula