Kongzhi yu Juece/Control and Decision (ISSN:1001-0920) is a monthly peer-reviewed scopus indexed journal originally founded in 1986. It is sponsored by the Ministry of Education, china and Northeastern University, china. Kongzhi yu Juece/Control and Decision (ISSN:1001-0920) has always adhered to the correct purpose of running the journal, and has been committed to gathering and disseminating excellent academic achievements, inspiring technological innovation, and promoting the development of disciplines in my country.Aiming at major national needs and international frontiers, this journal has published a large number of original and high-level research result. The journal was selected into the "China Science and Technology Journal Excellence Action Plan Project" in December 2019.In the future, it will strive to build an open innovation, collaborative integration.
In this paper, we present an impressive face recognition model, which represents a robust improvement over the original MobileNetv2. Our model introduces the Receptive Field Block (RFB) to prevent any loss of facial feature information, expands the perceptual field, and implementing multi-scale feature fusion to enhance the model's feature extraction capability. Moreover, we have incorporated Coordinate Attention (CA) into the RFB to enhance recognition accuracy within the lightweight network. The proposed model is named CA_RFB_MobileNetv2. Our experimental results from eight public datasets d
Power quality disturbances are a major concern during the operation of utility grid. Integration of the renewable energy sources to the grid has further deteriorated the power quality due to use of power electronic converters and drives. Proper detection and classification of the various power quality disturbances is needed to identify the origin and to execute adequate mitigation measures. Here, an Artificial Neural Network (ANN) based classifier is used to identify different power quality disturbances and its performance is evaluated. A data-set consisting of nine different disturbances wit
The disposal and management of refinery oil sludge pose significant environmental challenges and sustainable approaches for remediation. This article reviews the prospective strategy of co-remediating refinery, oil sludge with food waste digestate, using the optimization and predictive abilities of the Artificial Neural Network (ANN) models. By combining of refinery oil sludge and food waste digestate not only effectively resolves the problem of waste management but also presents positive prospects for the remediation of oil-contaminated soils. This review summarizes current research on the us
Speech synthesis is the field of computer science that focuses on designing computer systems that produce written text. It is possible for a computer to convert written text into voice by using a telephone or microphone. The process of generating synthesized speech is, by definition, a speech synthesis process. In this research, a novel Tamil Text -to-Speech based deep learning approach has been proposed. Initially, the features from the text are extracted using Principal Component Analysis (PCA) and the features from speech signals are extracted using Mel Frequency Cepstral Coefficient (MFCC)
Biogas is a highly efficient and beneficial energy source. Biogas is an energy source generated from the anaerobic the decomposition of organic materials by bacteria. The anaerobic digestion (AD) process generates biogas, which presents significant economic and environmental benefits. The economic advantages include the production of thermal energy, electrical power, and fuel, with the utilisation of digestate produced by the anaerobic digestion (AD) procedure as a form of fertiliser. The environmental advantages include the effective handling of organic waste, the recovery of nutrients, a dec