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Automated testbed and real-time port analysis for reconfigurable inputoutput boards
In the computational world, automation plays a vital role in every aspect. The idea of developing and testing Reconfigurable InputOutput (RIO) Boards automatically without manual interaction is a challenging task. Initially, testing was done manually which takes a lot of time and also requires human interaction. With the proposed idea one can reduce human interaction and testing time with smart automated design setup. This testing includes testing of various functionalities of the RIO boards. This can be done by testing the features of each port with its pin configuration. To be more precise, in this process an automated testbed is designed and algorithms are proposed to verify the features of each pin such as Digital Read, Digital Write, Analog Read and Analog Write of the RIO boards along with the motor pins. Thus, the proposed method makes the setup simple, without any complications by giving the instructions to perform the testing process for each board without human interaction. Results show that the proposed method can reduce time consumption 95%, human interaction by 95% and increase testing accuracy to 87%. 2020 Informa UK Limited, trading as Taylor & Francis Group. -
Automated Verification of Open/Closed Principle: A Code Analysis Approach
The SOLID principles are foundational to software engineering, focusing on the maintainability, scalability, and extensibility of software systems. The Open/Closed Principle (OCP), a pivotal element among these principles, underscores the need to design software modules that are open for extension yet closed for modification. This research explores automated verification techniques for OCP, addressing the validation of software modules through extensibility and adaptability assessments. The principal objectives involve the development of a code analysis approach and a methodology capable of automating the verification of adherence to OCP in developed codes, providing actionable insights to software developers. The system focuses on specific aspects of OCP, including inheritance, abstraction, and polymorphism, and aims to provide clear indications of where violations occur within a codebase. The implementation uses the Abstract Syntax Tree (AST) analysis to examine class definitions. The automated analysis of Python code using the defined rules offers a clear understanding of OCP adherence. Results are presented in Pandas DataFrames, indicating potential violations and providing developers with actionable insights to enhance code quality and maintainability. Overall, the automated code verification system aims to enhance code quality and adherence to fundamental design principles, paving the way for advancements in automated code analysis and software engineering practices. 2024 IEEE. -
Automatic blood group identification device /
Patent Number: 202141026963, Applicant: Ajit Danti.
Our invention Automatic Blood Group Identification Device is an event of a coffee price image process system that enables the determination of human blood sorts. to see the blood sorts, it had been used the plate check that accommodates the mixture antigens specifics of blood sorts determination and also the sample blood of the donor. -
Automatic Classification of Normal and Affected Vegetables Based on Back Propagation Neural Network and Machine Vision
This article presents a neural network and machine vision-based approach to classify the vegetables as normal or affected. The farmers will have great difficulty if there is a change from one disease control to another. The examination through an open eye to classify the diseases by name is more expensive. The texture and color features are used to identify and classify different vegetables into normal or affected using a neural network and machine vision. The mixture of both the features is proved to be more effective. The results of experiments show that the proposed methodology extensively supports the accuracy in automatic detection of affected and normal vegetables. The applications in packing and grading of vegetables are the outcome of this research article. 2019, Springer Nature Singapore Pte Ltd. -
Automatic detection of violence activity-A tool for women's safety /
Patent Number: 202041006858, Applicant: Debanjan Konar.
Human activity detection has gained popularity owing to wide range of applications from! game development to surveillance. Recent development of Deep Pose (Human pose detection using deep neural network) allows extrapolating the skeletal structures and joint sequences of the actors in a video sequence. This work aims to promote the violence-activities of human-being using Deep Pose on multi-person interaction in real-time. -
Automatic detection of violence activity-A tool for women's safety /
Patent Number: 202041006858, Applicant: Debanjan Konar.
Human activity detection has gained popularity owing to wide range of applications from game development to surveillance. Recent development of Deep Pose (Human pose detection using deep neural network. -
Automatic Diagnosis of Autism Spectrum Disorder Detection Using a Hybrid Feature Selection Model with Graph Convolution Network
A neurodevelopmental disorder is called an autism spectrum disorder (ASD) that influences a persons assertion, interaction, and learning abilities. The consequences and severity of symptoms of ASD will vary from person to person; the disorder is mainly diagnosed in children aged 15years and older, and its symptoms may include unusual behaviors, interests, and social challenges. If it is not resolved at this stage, it will become severe in the coming days. So, in this manuscript, we propose a way to automatically tell if someone has ASD that works well by using a combination of feature selection and deep learning. Four phases comprise the proposed model: preprocessing, feature extraction, feature selection, and prediction. At first, the collected images are given to the preprocessing stage to remove the noise. Then, for each image, three types of features are extracted: the shape feature, texture feature, and histogram feature. Then, optimal features are selected to minimize computational complexity and time consumption using a new technique based on a combination of adaptive bacterial foraging optimization (ABFO), support vector machines-recursive feature elimination (SVM-RFE), minimum redundancy and maximum relevance (mRMR). Then, the graph convolutional network (GCN) classifier uses the selected features to identify an image as normal or autistic. According to the research observations, our models accuracy is enhanced to 97.512%. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. -
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Automatic fertilizer dispenser robot /
Patent Number: 354319-001, Applicant: Ravikumar R. -
Automatic fertilizer dispenser robot /
Patent Number: 354319-001, Applicant: Ravikumar R. -
Automatic fertilizer dispenser robot /
Patent Number: 354319-001, Applicant: Ravikumar R. -
Automatic fertilizer dispenser robot /
Patent Number: 354319-001, Applicant: Ravikumar R. -
Automatic Generation Control of Multi-area Multi-source Deregulated Power System Using Moth Flame Optimization Algorithm
In this paper, a novel nature motivated optimization technique known as moth flame optimization (MFO) technique is proposed for a multi-area interrelated power system with a deregulated state with multi-sources of generation. A three-area interrelated system with multi-sources in which the first area consists of the thermal and solar thermal unit; the second area consists of hydro and thermal units. The third area consists of gas and thermal units with AC/DC link. System performances with various power system transactions under deregulation are studied. The dynamic system executions are compared with diverse techniques like particle swarm optimization (PSO) and differential evolution (DE) technique under poolco transaction with/without AC/DC link. It is found that the MFO tuned proportional-integral-derivative (PID) controller superior to other methods considered. Further, the system is also studied with the addition of physical constraints. The present analysis reveals that the proposed technique appears to be a potential optimization algorithm for AGC study under a deregulation environment. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Automatic Measurement and Differentiation of Traffic Volume Count
Traffic volume in India is growing drastically over the past few decades. This leads to an increased need of constructing more highways and underpasses. In order to have the definite knowledge of traffic volume, and to design the width and thickness of the pavements, periodical conduction of traffic census is necessary. At present, the evaluation of traffic volume is conducted manually. This system is tiresome and lacks accuracy. The data obtained from the traffic census decides the sanction of new highways, underpasses, or flyovers which involves huge investments. Hence, the accuracy of this data is very critical. In this paper, we propose an automatic tool that helps to measure the traffic volume and differentiate the vehicles using video processing tools in MATLAB. The proposed algorithm consists of the following steps: i Foreground Detection ii Blob Detection iii Blob Analysis iv Vehicle differentiation Counting. 2018 IEEE. -
Automatic Resume Parsing using Greywolf Algorithm Integrated with Strategically Constructed Semantic Skill Ontologies
The quest for finding the right candidate for their post has made the recruiters employ several methods since the beginning of corporate job recruitment. Apart from the skills and the quality of interview, a thing that matters the most and forms the basis of selection is the candidate's resume. Recruiters and companies have a tough time dealing with the several thousands resumes of the candidates which apply, as manually scanning them and finding the right selection can be tough most of the time. In this paper, Natural Language Processing(NLP) methods have been integrated with ontologies to improve the pace and quality of the recruitment process by proposing an automatic resume parser model. The resume of a candidate, along with his LinkedIn and GitHub profiles are weighted and using the Greywolf algorithm, the global maxima of the most deserving and qualified candidate are found and are recommended with a high accuracy of 96.13%. 2020 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0) -
Automatic Skin Lesion SegmentationA Novel Approach of Lesion Filling through Pixel Path
Abstract: Lesion segmentation is a vital step in a melanoma recognition system. Many algorithms were developed for the efficient skin lesion segmentation. Most of them fails to realize a perfect segmentation. This paper proposes a novel, fully automatic system, for the lesion segmentation in dermatograms. The proposed approach executes in two steps. Selection of root seed is the first step. All the lesion pixels in the dermatogram are identified during the second step. Traversal through a predefined lesion pixel path ensures the reachability of all lesion pixels irrespective of the possible lesion discontinuity. The proposed algorithm is tested with two publically available dataset, PH2 and images of ISBI2016 challenge. Out of the six evaluation parameters, the proposed method shows the best values for specificity, accuracy, Hammuode distance and XOR. This confirms the merit of the proposal with respect to existing popular methods. 2020, Pleiades Publishing, Ltd. -
Automatic smart attendance management system based on face recognition using deep learning /
Patent Number: 202141025155, Applicant: J Omana.
In this digital era, face recognition system plays a vital role in almost every sector. Face recognition is one of the mostly used biometrics. It can used for security, authentication, identification, and has got many more advantages. Furthermore, face recognition system can also be used for attendance marking in schools, colleges, offices, etc. The conventional method of calling name of each student is time consuming and there is always a chance of proxy attendance. -
Automatic vehicle license plate recognizer for kannada script using tensorflow based canvolutional neural network model /
Patent Number: 201941054190, Applicant: Dr. Arish P.
Automatic Vehicle License Plate Recognizer (AVLPR) is used to read license number of a vehicle by itself without direct human control. It is used to track citizens, movements and misidentiflcation of vehicles. Traditional ALVPR is mounted on police cars or on object like road signs and bridges. The challenging tasks in recognizing the license plate numbers in Kannada script are high contrast foreground or background colour, shape of the license plate, location of the plate in the bottom and middle of the vehicle. -
Automatic vehicle license plate recognizer for kannada script using tensorflow based canvolutional neural network model /
Patent Number: 201941054190, Applicant: Dr. Arish P.
Automatic Vehicle License Plate Recognizer (AVLPR) is used to read license number of a vehicle by itself without direct human control. It is used to track citizens, movements and misidentiflcation of vehicles. Traditional ALVPR is mounted on police cars or on object like road signs and bridges. The challenging tasks in recognizing the license plate numbers in Kannada script are high contrast foreground or background colour, shape of the license plate, location of the plate in the bottom and middle of the vehicle. -
Automatic Weld Features Identification and Weld Quality Improvement in Laser Sensor Integrated Robotic Arc Welding
In this study, an integration of point laser sensor in robotic arc welding has been performed for achieving robotic positional accuracy automatically in every welding cycle. With the help of defined focal length of laser sensor, weld seam positions as well as weld gap have been found automatically for any newly positioned work-piece. If there is any change in robot positioning compared to the master job, the shift in every axis is sent as signal to the robot controller so that robot end effector will adjust the shift amount automatically. The welding process parameters are set at optimal values. Taguchi approach so that maximum values of weld quality in terms of depth of penetration, yield strength and ultimate strength can be achieved in every welding cycle. Overall, with the proposed approach, a smart and productive way of operating industrial welding robot has been proposed which can be implemented in any medium to large scale industries for obtaining welding joints with minimum defects. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.