Design and Evaluation of Parallel Processing Techniques for 3D Liver Segmentation and Volume Rendering
Ensuring Software Quality in Engineering Environments
New 3D Face Matching Technique for an Automatic 3D Model Based Face Recognition System
Algorithmic Cost Modeling: Statistical Software Engineering Approach
Prevention of DDoS and SQL Injection Attack By Prepared Statement and IP Blocking
At present, one of the major issues for a person to meet their prerequisites is the cluttered traffic. Regardless of the identity, on the off chance that are out and about to face the deal, even if an individual pursues the traffic rules. So as to determine the issue, this paper concentrates on structuring an application to dole out the genuine class mark for every single individual tweet identified with the traffic words. On the off chance that any message contains traffic related data, it will be sent as an alarm to the end clients who are following the present client, or else a similar tweet will be simply posted on the client divider. In advanced times, informal organizations have turned into an intriguing space for each human being to share and convey their ongoing updates with one another. So as to actualize this application, it picks a good online life, which is Twitter.
A stock market model using statistical analysis is used to predict sales by an investment manager in such a way as to recognize the main aspects that affect the same business strategy planning. The basic understanding of the necessary data for evaluating a predictive model is achieved using statistical methods. This helps the management to define the marketing strategy while preparing a report that helps the analyst to analyze the results obtained by the marketing officer. This paper presents a theoretical and analytical framework implementation using a support vector machines for stock market forecasting. The model tries to predict whether a stock price will be higher or lower in the future or it is on a given day which helps to determine whether to invest or not. Technical and fundamental analysis or time series analysis used by most of the stockbrokers for forecasting the stocks. Machine learning algorithms implemented using Python programming language predicts the stock market. However, this paper proposes that a machine learning (ML) approach based on these aspects will use the available stock information and use the resulting information to make accurate predictions.
This paper proposes a smart appointment booking system that provides the patients or any user with an effortless way of booking a doctor's appointment online. This is a web-based application that overcomes the issue of managing and booking appointments according to the choice or demands of the user. The task can sometimes become very tedious for the doctor's front office in manually allotting appointments for the users as per their availability. Hence, this paper offers an effective solution where users can view various booking slots available and select the preferred date and time. The already booked space will be marked yellow and will not be available to anyone else for the specified time. This system also allows users to cancel their bookings at any time. The system provides an additional feature of calculating the monthly earnings of doctors. The doctor must just feed the system regularly with daily earnings, and the system automatically generates a report of the total amount earned at the end of the month. The application uses Asp.net as a front-end and the Sol database as the back-end.
Coronavirus disease (COVID) is an unprecedented crisis, causing a huge amount of unhappiness and security problems. Wearing a face mask in public places can effectively reduce the transmission of coronavirus, so people should wear facial covers or masks to protect themselves from this pandemic. Therefore, this makes a facial confirmation an inconvenient task since obvious parts of the face are hidden. An important focus of analysts during the advancing COVID pandemic is to come up with ideas to address this problem with quick and productive measures. This paper proposes a reliable method based on hidden area removal and deep learning-based highlights to solve the problem of hidden face recognition measures. To deal with these challenges, it separates two unique usages in particular, such as closed-eye face detection and hidden face detection. It basically determines if a person has a mask on their face or not. It can be effectively applied transparently where a mask is needed. In contrast, the covered face affirmation means recognizing the presence of a mask on the face based on the eye area and shelter areas, as well as checking the temperature to ensure safety measures. This paper provides a survey of different research accomplished with the methodology on face mask detection with temperature check.
In the present era, cybersecurity has become an integral part of information technology. The biggest problem right now is how to protect the information. Since cybercrime has become a reality, it is more important to consider the different ways in which, cybersecurity can protect the information. Governments and organizations have begun to take precautionary measures to prevent these cybercrimes. This paper, mainly focuses on cyber security in the latest technologies, practices and changing trends.
