Annu Chauhan, Dishika Chopra, Lirisha Tayal, Utsav Singal, K. Gupta, Monica Gupta
{"title":"Design of an Efficient Memristor-based Dynamic Exclusive-OR gate.","authors":"Annu Chauhan, Dishika Chopra, Lirisha Tayal, Utsav Singal, K. Gupta, Monica Gupta","doi":"10.47893/ijcct.2022.1428","DOIUrl":"https://doi.org/10.47893/ijcct.2022.1428","url":null,"abstract":"In this paper, an efficient memristor-based dynamic logic design for an Exclusive-OR gate is proposed. The proposed realization reduces the number of cascaded stages and component count thereby providing an overall performance improvement. The performance of the proposed design is compared with the most recent existing design through LTspice software simulations at 32 nm technology node in terms of total power consumption, average propagation delay, and number of components used in the implementation. The outcomes depict that the proposed design consumes 57 % reduced power and provides faster operation with 5.09 % improvement in propagation delay in comparison to its existing counterpart. Further, the robustness of the proposed design is verified by performing technology and capacitance variation. The results show the impeccable performance of proposed design across different load capacitance and technology nodes.","PeriodicalId":220394,"journal":{"name":"International Journal of Computer and Communication Technology","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123641258","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}
{"title":"Predicting Faultiness of Program Modules Using Mamdani Model by Fuzzy Profile Development of Software Metrics","authors":"M. Ali, Ahmed A. Abusnaina","doi":"10.47893/ijcct.2022.1422","DOIUrl":"https://doi.org/10.47893/ijcct.2022.1422","url":null,"abstract":"This research seminar proposed and implemented a new approach toward reliability and quality measurement of software systems by building a fault prediction model and faultiness degree estimation before starting the testing phase. The main goals of this model were to support decision making with regard to testing phase which leads to reduce the testing efforts, and to optimally assign the needed resources for testing activities. This research used KC2 dataset originated from National Aeronautics and Space Administration (NASA) project to evaluate the predictive accuracy of the proposed model. Software metrics in this dataset are of fuzzy nature, consequently, this work used MATLAB system to build a Mamdani fuzzy inference model. Then, this research applied and validated a published methodology for fuzzy profile development from data as an important requirement to build the model. Moreover, the proposed model utilized the capabilities of k-mean clustering algorithm as a machine learning technique to extract the fuzzy inference rules that were also required to build the model. Finally, this paper used suitable approaches to validate and evaluate the model. Accordingly, the results show that the proposed model provides significant capabilities in fault prediction and estimation.","PeriodicalId":220394,"journal":{"name":"International Journal of Computer and Communication Technology","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122565884","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}
Jie Wang, Zhenjin Li, Yidan Chen, Zhi-qiang Zhou, Shun Li
{"title":"Recognition and Selection of Governance Modes of Private Listed\u0000Enterprises Based on BP Neural Network.","authors":"Jie Wang, Zhenjin Li, Yidan Chen, Zhi-qiang Zhou, Shun Li","doi":"10.47893/ijcct.2022.1423","DOIUrl":"https://doi.org/10.47893/ijcct.2022.1423","url":null,"abstract":"Exploring the governance modes of private listed enterprises, this paper divides private listed enterprises into categories of small, medium and large. The governance modes of private listed enterprises can be divided into 9 categories according to two different management intensities of equity capital governance and manpower capital governance. The 9 categories of governance modes of private listed enterprises are identified by using the BP neural network mode. This paper analyses the evolution of private listed companies’ governance modes at different scales and analyses various governance modes. Therefore, small, medium and large private listed companies choose the “strong equity and weak manpower”, “moderate equity and moderate manpower” and “weak equity and moderate manpower” governance modes, respectively. This paper comparatively analyses the governance efficiency of governance modes at different scales. The results show that “moderate equity and moderate manpower” is the most effective management mode for all three scales.","PeriodicalId":220394,"journal":{"name":"International Journal of Computer and Communication Technology","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132333227","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}