AutomatikaPub Date : 2024-01-02DOI: 10.1080/00051144.2023.2296788
C. Maniveena, R. Kalaiselvi
{"title":"A security and privacy preserving approach based on social IoT and classification using DenseNet convolutional neural network","authors":"C. Maniveena, R. Kalaiselvi","doi":"10.1080/00051144.2023.2296788","DOIUrl":"https://doi.org/10.1080/00051144.2023.2296788","url":null,"abstract":"This method is able to synthesize fine-detailed images by the use of a global attention that gives more attention to the words in the textual descriptions. Also we have the deep attention multimodal similarity model (DAMSM) that calculates the matching loss in the generator. Though this work produced images of high quality, there was some loss while training the system and it takes enough time for training. Although there has been little study on applying character-level Dense Net algorithms for text classification tasks; the Dense Net structures we suggested in this paper have shown outstanding performance in image classification tasks. Extensive testing has revealed that they perform better when it comes to their ability to withstand interruption and that they can influence exerted many organizations implementing information usage and language information on the specifications of user privacy protection, framework implies, and regulatory requirements.","PeriodicalId":503352,"journal":{"name":"Automatika","volume":"137 7","pages":"333 - 342"},"PeriodicalIF":0.0,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139453284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AutomatikaPub Date : 2024-01-01DOI: 10.1080/00051144.2023.2296792
C. Kalamani, S. Lekashri, A. N. Duraivel, T. Selvin, Retna Raj
{"title":"An efficient reconfigurable FIR filter design with coefficient optimization using a modified bacterial foraging optimization algorithm","authors":"C. Kalamani, S. Lekashri, A. N. Duraivel, T. Selvin, Retna Raj","doi":"10.1080/00051144.2023.2296792","DOIUrl":"https://doi.org/10.1080/00051144.2023.2296792","url":null,"abstract":"ABSTRACT The digital filters play a significant role in the field of digital signal processing (DSP). The finite impulse response (FIR) filter is an attractive choice because of the ease of design and good stability. The digital filters have a wide variety of applications such as signal processing, control systems, telecommunication, etc. They are better than the analogue filters due to their performance. In recent times, software radios have achieved attention owing to requirements for integrated and reconfigurable communication systems. Hence, reconfigurations have emerged as a significant problem in the designs of FIRs. To match the frequencies of DSP applications, higher-order FIRs are required. If length of filters rises, addition and multiplication operations also increase. This paper proposes an efficient hardware design of RFIR that employs modified bacterial foraging optimizations (MBFOs) and common sub-expression eliminations (CSEs) in its executions. MBFOs output restricted counts of filter coefficients with sums of signed-power-of-two (SPT) terms while maintaining the quality of filtered responses. On obtaining coefficients, eliminations are executed by CSEs where hardware complexities are determined in terms of adders. Model sim software validated RFIRs using the Verilog code. The proposed design of RFIRs was compared with existing designs in terms of power usages, frequencies and areas.","PeriodicalId":503352,"journal":{"name":"Automatika","volume":"35 39","pages":"290 - 303"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139455662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}