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.
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
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)
Symbolic Regression (SR) is an Evolutionary Algorithm (EA) variant, which aims to generate mathematical equations for various tasks such as classification and regression. SR uses Genetic Algorithm (GA) to generate mathematical equations that best fit input data which have the least error. SR is notably useful in cases where features in a data set are known to have distinct mathematical relationships among each other and its output. This research aims to assess the efficacy of SR on biomedical data, such as electroencephalogram (EEG) signals, to classify human emotions. As the data is purely nu
Through the past 20 years, Computer sciences evolution has changed the world at all levels, economical, medical, social, etc. Nowadays, humans likely spent time on the Internet more than real world, and lead online social, economic and administrative activities. Therefore, the mapping between the virtual and real existence were obligatory, leading the community towards authentication and privacy needs. The Digital Identity was then born and involved into the Self-Sovereign Identity (SSI) to prove online users' and contents authenticity by preserving privacy and autonomy. This paper tracks the
Artificial Intelligence (AI) holds the potential to immensely benefit African societies, but its development and deployment has also raised some ethical issues that need to be considered. This paper explores multi-faceted ethical frameworks and practical considerations related to AI's implementation in Africa. It provides an overview of AI's prospective applications within the region and proposes an extensive ethical framework for evaluating AI deployment. It further discusses the associated risks and the necessity for efficacious AI regulation in the African context. This paper also underline