-3dc97f3d182b6b0ed3d-6a25 20220908005222265 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 09 30 2022 11 10 School of Computer Science and Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India. Varada Venkata Sai Dileep* Navuduru Rishitha School of Computer Science and Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India. Rakesh Gummadi School of Computer Science and Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India. Prof. Natarajan. P School of Computer Science and Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India. DNA Sequencing plays a vital role in the modern research. It allows a large number of multiple areas to progress, as well as genetics, meta-genetics, and phylogenetics. DNA Sequencing involves extracting and reading the strands of DNA. This research paper aims at comparing DNA Sequencing using “Machine Learning algorithms (Decision Trees, Random Forest, and Naive Bayes) and Deep Learning algorithms (Transform Learning and CNN)”. The aim of our proposed system is to implement a better prediction model for DNA research and get the most accurate results out of it. The “machine learning and deep learning models” which are being considered are the most used and reputed. A prediction accuracy of the higher range in deep learning is also being used which is also the better performer in different medical domains. The proposed models include “Decision Tree, Random Forest, Naive Bayes, CNN, and Transform Learning”. The Naive Bayes method gave greater accuracy of 98.00 percent in machine learning and the transform learning algorithm produced better accuracy of 94.57 percent in deep learning, respectively. 09 30 2022 20 27 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.J9273.09111022 https://www.ijitee.org/portfolio-item/J927309111022/ Department of Commerce, PSGR Krishnammal College for Women, Peelamedu, Coimbatore. (Tamil Nadu), India. Dr. D. Vijayalakshmi Mrs. S. Manasha* Department of Commerce, PSGR Krishnammal College for Women, Coimbatore. (Tamil Nadu), India. Speculation in commodity market is an important indicator that affects the prices of the commodities. Speculation is known as the purchase of a good for resale, or for temporary sale of a good with the purpose of repurchasing it later by hoping that earning profit from an interceding price change. Normally, excessive speculation in commodity market pushes up the prices and speculation create more fluctuations in prices. In this background, the studies focus on trend of speculation in gold future returns and also assess the short – run relationship between Gold futures returns and Speculative ratio. The data have been obtained from the MCX website. The statistical and econometric tools, such as, descriptive statistics, OLS Regression Model and Granger causality tests have been applied to analyze the data. The result of the study reveals that, time trend affects the speculation and there is no short run relationship between Gold futures returns and Gold Speculative ratio. Hence, it is proved that speculation is independent of futures price. 09 30 2022 28 30 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.J9274.09111022 https://www.ijitee.org/portfolio-item/J927409111022/