Development of a Novel Noise Reduction Algorithm for Smart Checkout RFID System in Retail Stores

This paper presents a smart checkout system designed to mitigate the issues of noise and errors present in the existing barcode and RFID-based systems used at retail stores’checkout counters.This is achieved by integrating a novel AI algorithm,called Improved Laser Simulator Logic(ILSL)into the RFID system.The enhanced RFID system was able to improve the accuracy of item identification,reduce noise interference,and streamline the overall checkout process.The potential of the systemfor noise detection and elimination was initially investigated through a simulation study usingMATLAB and ILSL algorithm.Subsequently,it was deployed in a small-scale environment to validate its real-world performance.Results show that RFID with the proposed new algorithm ILSL and AI basket is capable of accurately detecting the related itemswhile eliminating noise originating fromunrelated objects,achieving an accuracy rate of 88%.

Adaptive Active Control of Low Frequency Noise in a Duct

Aim To study a method realizing noise control for a physical model of progressive wave in a duct. Methods A mathematical model was constructed and a transfer function of the adaptive system for noise control was also worked out; moreover, the effects of some algorithms such as RLS,LMS and LSL on noise control were analyzed and compared. Results Without the feedback of sound, the mean noise reduce value(MNRV) of 27 5 dB for broadband noise from 0 to 500?Hz in frequency were achieved. When acoustic feedback took place and an air stream loudspeaker was used, the MNRV was only about 4 9?dB. But if the loudspeaker had a plain frequency feature, MNRV was improved by 10 2?dB. Conclusion The technique is applied to ruducing the noise from engines' exhausted gas pipes. It is, in principle, used for noise cancelling in a closed three dimensional space.

Interactive Genetic Algorithms with Fitness Adjustment

Noises widely exist in interactive genetic algorithms. However, there is no effective method to solve this problem up to now. There are two kinds of noises, one is the noise existing in visual systems and the other is resulted from user’s preference mechanisms. Characteristics of the two noises are presented aiming at the application of interac- tive genetic algorithms in dealing with images. The evolutionary phases of interactive genetic algorithms are determined according to differences in the same individual’s fitness among different generations. Models for noises in different phases are established and the corresponding strategies for reducing noises are given. The algorithm proposed in this paper has been applied to fashion design, which is a typical example of image processing. The results show that the strategies can reduce noises in interactive genetic algorithms and improve the algorithm’s performance effectively. However, a further study is needed to solve the problem of determining the evolution phase by using suitable objective methods so as to find out an effective method to decrease noises.

An interferometric phase shift fiber Bragg grating sensing system with greatly reduced background phase noise

We presented an interferometric phase shift fiber Bragg grating （FBG） sensor, which inherited the advantages of FBG sensors, and, at the same time, the greatly reduced full-width-at-half-maximum bandwidth brought longer coherent length, higher sensitivity, and lower phase noise. Experiments show that at least a 7 dB reduction of phase noise can be achieved compared to FBG sensors interrogated by interferometer with the same optical path difference.