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.
Surge and swab pressures are additional pressure drop due to the pipe movement upward/downward during drilling activities including drill string reciprocation and tripping operations. It describes the changes in pressure in the annulus because of pipe movement, resulting in a variety of expensive drilling issues, such as well kick, formation breakdown, and lost circulation. The key objective of this study is to examine the factors that influencing the surge and swab pressures and determine the extent of their influence., In addition to optimizing the drilling parameters that determine the grea
Skin cancer is regarded as the world's deadliest disease. Patients with incorrect diagnoses and substandard treatment have a very low chance of survival. However, if the disease is discovered sooner, the patient has a greater chance of survival and can be cured. Consequently, diagnosing and treating a patient in the earliest phases is difficult and complex. A system capable of autonomously diagnosing and detecting skin cancer at an earlier stage is required to address these issues. This study employed several deep learning models, including VGG16, VGG19, Xception, ResNet50, InceptionResNetV2,
The healthcare industry is expanding quickly along with new technologies like IoT (Internet of Things). The fundamental idea behind integrating IoT into healthcare facilities is to build it accessible by physicians from a remote location, allowing for simple patient-doctor contact as well as remote disease detection in an emergency situation. But for the IoT health system to provide exceptional patient’s care, it is vital to ensure a high level of safety. The health histories of the patients contain critical data which must only be available to authorized people, as any data which exists on
The development of smart cities demands automation in various things, including traffic engineering management. Intelligent Transportation System, usually abbreviated as ITS, is one of the supporting components of a smart city. One of the automation that can be handled in ITS is the detection of road marking violations. Road marking violations (especially in Indonesia) often occur at road intersections. Therefore, in this research, the detection and counting of the number of road marking violators at road intersections will be carried out. We propose user-defined markings to detect road markin
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