2771-1463ISSN (Online)
2771-1471ISSN (Print)
The purpose of the present article is to highlight the outcomes of Indian premier league cricket match utilizing a managed taking in come nearer from a team-based point of view. The methodology consists of prescriptive and descriptive models. Descriptive model focuses mainly on two aspects they are, it describes data and statistics of the previous information. i.e., batting, balling or allrounder and It predicts past matches of IPL. Predictive model predicts ranking and winning percentage of the team. The two models show the measurements of winning level of the group Winner that the user has selected. This paper predicts the result through which technique match has highest result. The dataset consists of two groups that is the toss outcome, venue date, which tells about of the counterpart for all matches. Since the nature impact can't be expected in the game, 109 matches which were either finished by downpour or draw/tie, have been taken out from the dataset. The dataset is partitioned into two sections to be specific the test information and the train information.The readiness dataset contains the 70% of the information from our dataset and the test dataset contains 30% of the information from our dataset. There were all out of 3500 coordinates in getting ready dataset and 1500 matches. This paper has been researched earlier by different scholars like Pathak and Wadwa, Munir etl ,and many other scholars. This viewpoint discusses the application of INDIAN PREMIER LEAGUE Matches held in different states. Gives the score of batsman and bowler with the help of machine learning techniques. Focuses on predicted analysis which is predicted by applying with various AI strategies to the real outcome actual result and gives the percentage of predicted result.
Read MoreDoi: https://doi.org/10.54216/JCHCI.010101
Vol. 1 Issue. 1 PP. 01-07, (2021)
The number of mobile Medicare applications has grown exponentially over the past few years, and it is expected to continue to grow soon. The use of health apps promises to be a good way to improve patient care and make work easier for professional. However, some cases of malfunction or misdiagnosis and treatment recommendations have been reported. Regulation is essential to protect users and support product development. So, to suppress the malfunctions we present a pharmacopeia Medicare app in which the customer can see the original profile and the specification of any stimulant with its useful information. This inculcates a clean process which procures a less chance of misapplication of the drugs. These mobile medical app companies have improved access to clinical references and point of care tools. However, it is difficult to identify mobile medical apps that are suitable for the practice of pharmacy. This app is entirely based on our experience in accrediting websites with health-related content and journal.
Read MoreDoi: https://doi.org/10.54216/JCHCI.010102
Vol. 1 Issue. 1 PP. 8-17, (2021)
In the modern world, people need immediate remedies for their health problems. Without considering the future effects of the heavy dose medicines, people intake those medicines to get immediate relief. As a result, they forget the natural and side effects free home remedies. And there is no awareness among the current generation youngsters and kids. To overcome this problem, we are developing a mobile application in dart language using flutter framework [2]. It uses KMP Algorithm [4] to recommends the medicine based on their allergic conditions matching. By this our system recommends the natural homemade medicines for their temporary health issues. This will increase the acceptance of these homemade medicines among the people.
Read MoreDoi: https://doi.org/10.54216/JCHCI.010103
Vol. 1 Issue. 1 PP. 18-27, (2021)
In many industries, the picture of the day now plays an important role in extracting information about the item. Many traditional image retrieval techniques have been used. It answers the user's question interactively by asking whether the image is relevant. In this digital age, graphics have become an important part of information processing. The image plays an important role in extracting information about the object in a variety of areas, including weather systems, tourism, medicine, and geology, in the processing of image registrations. There are several methods for retrieving images. It determines a person's inquiry interactively by asking users whether the image is relevant (similar). The efficient image database business has improved the process's functioning in the content-based image recovery system (CBIR). Content-based image recovery (CBIR) research has grown in importance. As individuals, we have studied and investigated various features in this manner or in combinations. We discovered that image Registration Processing (IRP) is a critical area in the industries. Several research papers on color feature and texture feature extraction were reviewed, and it was determined that point cloud data structure is best for image registration using the Iterative Closest Point (ICP) algorithm.
Read MoreDoi: https://doi.org/10.54216/JCHCI.010104
Vol. 1 Issue. 1 PP. 28-36, (2021)
Agriculture is the primary occupation in our country for ages. But now due to migration of people from rural to urban there is hindrance in agriculture. So, to overcome this problem we go for smart agriculture techniques using IoT. This paper includes various features like GPS based remote controlled monitoring, moisture & temperature sensing, intruders scaring, security, leaf wetness and proper irrigation facilities. It makes use of wireless sensor networks for noting the soil properties and environmental factors continuously. Various sensor nodes are deployed at different locations in the farm. Controlling these parameters are through any remote device or internet services and the operations are performed by interfacing sensors, Wi-Fi, camera with microcontroller. This concept is created as a product and given to the farmer’s welfare. AI Solution for Farmers perform soil analysis, climate analysis, and productivity analysis using linear regression. It helps farmers to understand about the crop to be sown as well as the factors affecting their productivity with the help of different types of graphs and tables. Farmers need not to do anything on the application as it is highly interactive as by using speech API.
Read MoreDoi: https://doi.org/10.54216/JCHCI.010105
Vol. 1 Issue. 1 PP. 37-45, (2021)