Authors:Owen R. Thornton Pages: 1 - 11 Abstract: Since the inaugural Comrades Marathon in 1921, ultramarathons have witnessed remarkable growth, with a recent surge in both participation and spectator interest. As performance improvement becomes a priority for researchers and ultramarathon runners, understanding pacing strategies, which greatly impact performance, is essential. Pacing strategies for ultramarathon runners can differ substantially based on factors such as age, distance, performance level, and the competition environment. These strategies can help overcome speed drops, especially when running on mountainous or flat terrain, and aid in implementing precooling strategies for improved running. However, no study has fully explored the distinct pacing techniques required for ultramarathons on hilly terrain compared to level roads or tracks. This review aims to provide researchers, coaches, and ultramarathon competitors with a better understanding of pacing processes and strategies across various terrains. It synthesizes effective pacing strategies from existing literature on mountain and track ultramarathons, highlighting similarities, differences, and potential gaps in knowledge. By doing so, this review aims to help ultramarathon participants more effectively comprehend and apply pacing tactics across a range of terrains. PubDate: 2023-03-21 DOI: 10.9734/ajarr/2023/v17i4474 Issue No:Vol. 17, No. 4 (2023)
Authors:Subhani Shaik, V. Kakulapati , Ramakanth Reddy Malladi Pages: 12 - 19 Abstract: This paper mainly deals with the prediction of location based on customer requirements. It also describes the location of the house, stores nearby by the house, duration of the house, transaction of data by the house and the latitude and longitude of the house, nearby station, and areas nearby house by using its contents to summarize the data. Take these contents on the x-axis and count on the x-axis then predict the data by using some algorithms in data science. Now, find the accuracy of data by training and testing, and then locate the particular location by using maps. Maps are the ones that can easily locate any region. By this, the customer can easily get access and can get the house with any legal requirements. The real-estate person can be gone through illegal things. In South India, propose to develop a model that can anticipate housing prices. It is an application of data science that makes use of algorithms. Prices of homes go up and down every day, and they aren't always proportional to the properties' actual values. Predicting the pricing of homes using only actual criteria is the primary emphasis of this effort. In this study, plan to conduct an analysis based on each of the fundamental criteria, and customer requirement are considered in the process of determining the prices. PubDate: 2023-03-22 DOI: 10.9734/ajarr/2023/v17i4475 Issue No:Vol. 17, No. 4 (2023)
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