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RISS 인기검색어
- 검색키워드
- 저자 : Zeeshan Sadaf (검색결과 2 건)
- 무료
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Performance Analysis of Path Planning Algorithms for Fruit Harvesting Robot
Zeeshan Sadaf,Aized Tauseef 한국농업기계학회 2023 바이오시스템공학 Vol.48 No.2
Purpose Path planning is an essential part in designing of an agricultural robot. The path planning algorithms for fruit harvesting robots vary in performance, based on diff erent environments, obstacles, and constraints. This research aims to analyze and evaluate the most commonly used path planning algorithms by fruit harvesting robots in the past 10 years to assess the robot’s performance. The primary objective behind the comparative analysis of path planning algorithms is to ascertain which algorithm demonstrates better performance in terms of reaching the target fruit in the shortest time, requiring the least amount of computing resources, and being able to navigate around obstacles eff ectively. Hence, the study determines which path planning algorithm is the most effi cient for the application of fruit harvesting robot. Method In this study, four common path planning algorithms were evaluated namely A-star, Probabilistic Road Map, Rapidly exploring Random Tree, and improved Rapidly exploring Random Tree. Three cases were examined for performance. The fi rst case deals with performance based on varying orientations of fruit within the workspace. The second case investigates the performance in the presence of obstacles in the path, and the third case caters to performance due to varying distances of robot and the fruit. Matlab software was used for creating simulation environment for testing. Run time, path length, standard deviation, and total task time were obtained for each case and statistical analysis was done. Results It was found that improved Rapidly exploring Random Tree performed better in terms of path length and gave an optimal path as compared to the other algorithms due to its rewiring feature by an average of 21%. Run time of Rapidly exploring Random Tree was better than the other three algorithms. Conclusion Four most commonly used path planning algorithm were analyzed for performance for fruit harvesting robot for three diff erent cases. Despite the variations in performance across diff erent scenarios, the results confi rmed that the improved Rapidly exploring Random Tree algorithm outperformed all other algorithms under the given constraints.
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Mutational Analysis of Prohibitin - A Highly Conserved Gene in Indian Female Breast Cancer Cases
Najm, Mohammad Zeeshan,Akhtar, Md. Salman,Ahmad, Istaq,Sadaf, Sadaf,Mallick, Mohd Nasar,Kausar, Mohd Adnan,Chattopadhyay, Shilpi,Ahad, Amjid,Zaidi, Shuaib,Husain, Syed Akhtar,Siddiqui, Waseem Ahmad Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.10
Prohibitin (PHB) is a chaperone protein which is highly conserved evolutionarily. It shows significant homology with the Drosophila cc gene which is considered important for development and differentiation of Drosophila melanogaster. Investigations have revealed an involvement of PHB in cellular proliferation and development, apoptosis, signal transduction, mitochondrial function and regulation of the estrogen and androgen receptors. Therefore, we conducted the present study to analyze mutations in the highly conserved region in Indian female breast cancer patients. Conventional PCR-SSCP and Automated DNA sequencing were performed with a total of 105 breast cancer samples along with adjacent normal tissue. Of the total, 14.2% (15/105) demonstrated a mutation status of prohibitin observed in our study population. We identified a novel missense mutation (Thr>Ser), a novel deletion of T nucleotide in an intron adjacent to intron-exon boundary and a previously determined missense mutation (Val>Ala). A statistically significant correlation was obtained which suggested that prohibitin may be associated with tumor development and/or progression of at least some proportion of breast cancers.
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