In the fight against the coronavirus, social distancing has proven to be an effective measure to hamper the spread of the disease. The system presented is for analyzing social distancing by calculating the distance be...
In the fight against the coronavirus, social distancing has proven to be an effective measure to hamper the spread of the disease. The system presented is for analyzing social distancing by calculating the distance between people in order to slow down the spread of the virus. This system utilizes input from video frames to figure out the distance between individuals to alleviate the effect of this pandemic. This is done by evaluating a video feed obtained by a surveillance camera. The video is calibrated into bird's view and fed as an input to the YOLOv3 model which is an already trained object detection model. The YOLOv3 model is trained using the Common Object in Context (COCO). The proposed system was corroborated on a pre-filmed video. The results and outcomes obtained by the system show that evaluation of the distance between multiple individuals and determining if rules are violated or not. If the distance is less than the minimum threshold value, the individuals are represented by a red bounding box, if not then it is represented by a green bounding box. This system can be further developed to detect social distancing in real-time applications.
Cancer is one of the most difficult types of illnesses today, diagnosing the disease in the early stage is still tough for doctors. Genetic profiling plays a fundamental role in discovering environmental risk factors ...
Cancer is one of the most difficult types of illnesses today, diagnosing the disease in the early stage is still tough for doctors. Genetic profiling plays a fundamental role in discovering environmental risk factors for cancer. a special mixed layered strategy of option tree and cluster is applied to create a most cancers risk assessment scheme. The proposed gadget is an invaluable device that forecasts certain types of cancers and it's worth your serious considerations. This research uses statistical tools such as grouping, clustering and estimation to discover the aptitude of cancer patients. We have suggested this cancer prediction method in our paper based on the information-mining strategy. This computer reports the number of human breast cancers in the immediate future. This gadget is checked to be completed with previous clinical knowledge. The aim of this model is to protect the customers and to make it affordable to the person using it. and a predictive model will aid in physical injury prevention and diagnosis. This research helps detect a person's chances of developing cancer at an early stage of treatment.
Air pollution is one of the biggest challenges of our daily lives. It affects human well-being by hypersensitivity and other pulmonary infections, which can lead to death. The growth of industries and automobiles dona...
Air pollution is one of the biggest challenges of our daily lives. It affects human well-being by hypersensitivity and other pulmonary infections, which can lead to death. The growth of industries and automobiles donates more to air emissions. Natural air is important for all humans, and various developments have been used to constantly check air quality. This role offers a kind of continuous observation system for atmospheric emissions where the grouping of large poisonous gases into the air is detected using cost efficient sensors. This system shows the air quality reliably in a cloud by using an Internet of Things (IoT) scene, which is efficiently experienced from our PC or PDA. Nevertheless, the system includes an arrangement to store previously estimated details. This helps experts to study the air existence of the territory they are searching for a while for important purposes. Likewise, the frame identifies air quality and sends signals to the partners when the assessment of pollutants rises above a specified amount. In addition, it can be well implemented everywhere to check air quality in a smart smaller plan.
作者：
P. AnanthiS. Jabeen BegumV. Latha JothiS. KayalviliS. GokulrajM.E student
Computer Science and Engineering Velalar College of Engineering and Technology Erode Tamil Nadu India Professor
Computer Science and Engineering Velalar College of Engineering and Technology Erode Tamil Nadu India Associate Professor
Computer Science and Engineering Velalar College of Engineering and Technology Erode Tamil Nadu India
Predictive and analytic models for forecasting the vulnerability and recovery rate of patients who are affected by COVID 19 are made in this project for good analysis and better decision-making. In this project, linea...
Predictive and analytic models for forecasting the vulnerability and recovery rate of patients who are affected by COVID 19 are made in this project for good analysis and better decision-making. In this project, linear regression (LR) a Machine Learning model is used to forecast the number of patients will get the infection in near future. By simulating SIRD model, the infection spread and recovery rate of the disease in a geographic region can be predicted. The vulnerability of the disease is checked by observing the transmission of disease over a period. In addition to this many info graphic models and graphs are created for easy understanding of data to get more insights about the disease. However, these prediction models enable us to make quick response of pandemic and to bring a conclusion to the disease. INDEX TERMS: Covid 19, data science, machine learning, prediction, analysis, pandemic, recovery and infection.
When it comes to classroom management, the attendance check is a critical component. Time-consuming, particularly when it comes to open meetings, is checking attendance by calling names or by handing around a sign-in ...
When it comes to classroom management, the attendance check is a critical component. Time-consuming, particularly when it comes to open meetings, is checking attendance by calling names or by handing around a sign-in sheet to make it easier to commit fraud. An implementation of a real-time attendance check is described in this article in great detail facial recognition system and its outcomes. The system must be able to identify a student's face in order for it to work first snap a photograph of the pupil and save it in a database as a reference for future use. During the event, there were students may be identified by using the webcam, which captures photos of their faces auto-detects faces and selects students with names that are most likely to match, and lastly, depending on the facial recognition findings, an excel file will be updated to reflect attendance. To identify faces in webcam footage, the system uses a pre-trained Haar Cascade model. As a result, a 128-bit FaceNet has been generated by training it to minimise the triplet loss. The dimensions of the facial picture. When two facial pictures have similar encodings If the two facial pictures are from the same student or different. Use of the system as part of a class, and the outcomes have been extremely positive. There has been a poll done to find out more about There are both advantages and disadvantages to using a college attendance system.
With advances in the mobile communications, many service-related tasks can be made quickly and easily. Mobile banking is one such service that has eliminated the need for a consumer to go to a branch to carry out many...
With advances in the mobile communications, many service-related tasks can be made quickly and easily. Mobile banking is one such service that has eliminated the need for a consumer to go to a branch to carry out many common transactions. In a country like India, where the last mile reach through brick-and-mortar banking facilities, mobile phones can complement the reach. This paper describes how mobile cloud architecture can be employed for banking and services to customers to enhance their banking experience as well as ensuring information security. This paper focuses on cloud-based risk architecture for banking solutions to address various issues related to mobile banking such as processing speed and storage capacity. Improved random forecast algorithm is used for the evaluation of the system. This proposed system achieves 99% of the system.
Balancing equations for excitation system is very basic and fundamental concept and in some cases it becomes more difficult so that a mathematical treatment is needed in order to make it easy for AC and DC Regulators ...
Balancing equations for excitation system is very basic and fundamental concept and in some cases it becomes more difficult so that a mathematical treatment is needed in order to make it easy for AC and DC Regulators Excitation Systems (ES). This research paper mainly focuses on an excellent application of The power generating units and higher power motors are majority included by wound field synchronous machines because of it has flexible field excitation, flux intrinsic weakening capacity and high efficiency. It can be also used in low to medium power range for high end solutions in a wide range. This paper is analyzing a study of modern methods and technologies of excitation system for AC and DC regulators.
We have solved the problem of substantiating the choice of the sampling interval of the temporal series of the technological process parameter measurements for automation systems, if there are errors, which takes into...
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In this paper we present a minimal solution for the rotational alignment of IMU-camera systems based on a homography formulation. The image correspondences between two views are related by homography when the motion o...
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Abstractive text summarization is the task of generating meaningful summary from a given document (short or long). This is a very challenging task for longer documents, since they suffer from repetitions (redundancy) ...
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Abstractive text summarization is the task of generating meaningful summary from a given document (short or long). This is a very challenging task for longer documents, since they suffer from repetitions (redundancy) when the given document is long and the generated summary should contain multi-sentences. In this paper we present an approach for applying generative adversarial networks in abstractive text summarization tasks with a novel time-decay attention mechanism. The data generator is modeled as a stochastic policy in reinforcement learning. The generator's goal is to generate summaries which are difficult to be discriminated from real summaries. The discriminator aims to estimate the probability that a summary came from the training data rather than the generator to guide the training of the generative model. This framework corresponds to a minimax two-player game. Qualitatively and quantitatively experimental results (human evaluations and ROUGE scores) show that our model can generate more relevant, less repetitive, grammatically correct, preferable by humans and is promising in solving the abstractive text summarization task.
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