Titlebook: Intelligent Technologies: Concepts, Applications, and Future Directions, Volume 2; Satya Ranjan Dash,Himansu Das,Esau Villatoro Tello Book

predict

Soumya Ranjan Das,Prakash Kumar Ray,Debani Prasad Mishraal Entrepreneurship Monitor (GEM) of 20 countries between 2008 and 2018, as well as the World Bank’s Digital Adoption Index (WB DAI). Based on EO, a predictive model of entrepreneurial performance was constructed using machine learning and the XGBoost algorithm. According to the findings of this stu

fender

Debjani Panda,Satya Ranjan Dash studies are processed to develop a classification scheme of the influence of AI on business models. Furthermore, the interaction of the different innovation possibilities of AI is compared and with that the importance for the innovative power of companies. Additionally, strategy types are developed

表示問

Mir Wajahat Hussain,Diptendu Sinha Roynce, and long investment/equipment use cycles, SDG-3 has been one of the slowest to adopt innovative solutions by far. We discuss specific areas, such as blended reality or quantum computing, for emerging and future digital health applications. In this chapter, we provide: the “memoreBox” of social

同時發(fā)生

Handedness

,Designing of?Fault-Tolerant Models for?Wireless Sensor Network-Assisted Smart City Applications,k. Furthermore, a few specific smart city applications have been used as a case study for handling fault occurrences in real time. For this, four distinct faults—hardware fault, routing fault, communication fault, and framework fault—are taken into consideration. Four specific smart city application

完成

Test Scenarios Generation and Optimization of Object-Oriented Models Using Meta-Heuristic Algorithm utilized to occupy most resources, like cost, effort, and time. Usually, behavior illustration and Unified Modeling Language (UML) structural diagrams are used by researchers for test case generation at the early phase of evolution. This mechanism efficiently ensures the durability of the system wi

外來

phytochemicals

Ankylo-

Detection of Brain Abnormalities from Spontaneous Electroencephalography Using Spiking Neural Netwoy seizures dataset has experimented with traditional machine learning approaches and the deep learning approach. The schizophrenia dataset has experimented with a probability spiking neural network approach. Finally, the depression dataset is analysed with the fuzzy-based NeuCube spiking neural netw

Adenocarcinoma