Pulkit Jain¹, Paras Chawla¹, Mehedi Masud^2,*, Shubham Mahajan³, Amit Kant Pandit³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3337-3353, 2022, DOI:10.32604/cmc.2022.023053

Abstract Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications. In particular the need for automating the process of real-time food item identification, there is a huge surge of research so as to make smarter refrigerators. According to a survey by the Food and Agriculture Organization of the United Nations (FAO), it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and a large amount of food is wasted from homes and restaurants itself. Smart refrigerators have been very successful in… More >

Cuixiang Wang¹, Xing Shao^1,2,3,*, Yifan Meng⁴, Jun Gao¹

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 931-945, 2021, DOI:10.32604/cmc.2020.012267

Abstract In RFID (Radio Frequency IDentification) system, when multiple tags are in the operating range of one reader and send their information to the reader simultaneously, the signals of these tags are superimposed in the air, which results in a collision and leads to the degrading of tags identifying efficiency. To improve the multiple tags’ identifying efficiency due to collision, a physical layer network coding based binary search tree algorithm (PNBA) is proposed in this paper. PNBA pushes the conflicting signal information of multiple tags into a stack, which is discarded by the traditional anti-collision algorithm. In addition, physical layer network… More >