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Topic Review
Communication Architectures
Communication architecture plays an important role in the intelligent control and autonomous collaboration of UAV (Unmanned Air Vehicle) swarms. And we know that UAV swarm communication architecture technology has already made great progress. When faced with different mission scenarios, there are different communication architectures to choose from. Centralized communication architecture is suitable for scenarios where the UAV swarm is small, and the task is relatively simple. Each individual UAV requires a long-range communication link with the infrastructure. The decentralized communication architecture expands communication coverage through a multi-hop network. The dedicated gateway UAV is responsible for U-T-I (UAV to Infrastructure) communication. The “single-group swarm Ad hoc network” architecture is appropriate for a swarm of the same type UAVs, while “multi-group swarm Ad hoc network” and “multi-layer swarm Ad hoc network” architectures can be deployed using different types of UAVs. In a “multi-group swarm Ad hoc network”, communication between two different groups can also suffer from delays. In addition, in terms of robustness, "multi-layer swarm Ad hoc network" architecture is a relatively reliable system because it overcomes SPOF (Single Point of Failure).
  • 1.5K
  • 12 Apr 2021
Topic Review
Artificial Neural Networks
Artificial Intelligence (AI) researches and builds intelligent software and machines, provides a particular solution to a particular defined complex problem. To carry out these tasks, it uses models and algorithms such as genetic algorithms, particle swarm optimization, artificial neural networks (ANNs), and hybrid models (two or more of the above). ANNs are flexible to accommodate non-linear and non-physical data; however, they require large multidimensional data set to reduce the risk of extrapolation. ANNs are widely used in different branches of science for their learning ability and adaptability to various settings.
  • 4.5K
  • 12 Apr 2021
Topic Review
Structure of Power QKD Network
Considering the complexity of the power grid environment and the diversity of power communication transmission losses, this paper proposes a quantum key distribution (QKD) network structure suitable for power business scenarios. Through the simulation of the power communication transmission environment, the performance indicators of quantum channels and data interaction channels in the power QKD system are tested and evaluated from six aspects, such as distance loss, galloping loss, splice loss, data traffic, encryption algorithm, and system stability. In the actual environment, this paper combines the production business to build a QKD network suitable for power scenarios, and conducts performance analysis. The experimental results show that the power QKD technology can meet the operation index requirements of power business, as well as provide a reference for the large-scale application of the technology.
  • 1.0K
  • 12 Apr 2021
Topic Review
Information Exactly Defined
This review focuses the exact and global definition of information (for unambiguous interpretation as mathematical object) and its digital application. New uniformly defined "domain vectors" (DVs), with structure "UL plus number sequence", are proposed. The "UL" is an efficient global pointer to the uniform online definition of the (after the UL) following number sequence. DVs are globally exactly defined, identified, interoperable, comparable, and (language independently) searchable by criteria which users can define online. The introduction of a compact DV data structure may substantially improve the digital representation of information.
  • 2.0K
  • 11 Apr 2021
Topic Review
Blood Flow Modeling
Blood flow modeling consists of using computational techniques to investigate the blood flow behavior in a rapid and accurate fashion. This has become an area of extensive research due to the prevalence of cardiovascular diseases, responsible for a critical number of deaths every year worldwide, most of which are associated with atherosclerosis, a disease that causes unusual hemodynamic conditions in arteries. In the present review,  the application of computational simulations by using different physiological conditions of blood flow, several rheological models, and boundary conditions, were discussed.
  • 1.8K
  • 10 Apr 2021
Topic Review
Deep Learning Based Speech Synthesis
Speech synthesis, also known as text-to-speech (TTS), has attracted increasingly more attention. Recent advances on speech synthesis are overwhelmingly contributed by deep learning or even end-to-end techniques which have been utilized to enhance a wide range of application scenarios such as intelligent speech interaction, chatbot or conversational artificial intelligence (AI). For speech synthesis, deep learning based techniques can leverage a large scale of <text, speech> pairs to learn effective feature representations to bridge the gap between text and speech, thus better characterizing the properties of events.
  • 4.2K
  • 08 Apr 2021
Topic Review
Deep Reinforcement Learning in Economics
The popularity of deep reinforcement learning (DRL) applications in economics has increased exponentially. DRL, through a wide range of capabilities from reinforcement learning (RL) to deep learning (DL), offers vast opportunities for handling sophisticated dynamic economics systems. DRL is characterized by scalability with the potential to be applied to high-dimensional problems in conjunction with noisy and nonlinear patterns of economic data. In this paper, we initially consider a brief review of DL, RL, and deep RL methods in diverse applications in economics, providing an in-depth insight into the state-of-the-art. Furthermore, the architecture of DRL applied to economic applications is investigated in order to highlight the complexity, robustness, accuracy, performance, computational tasks, risk constraints, and profitability. The survey results indicate that DRL can provide better performance and higher efficiency as compared to the traditional algorithms while facing real economic problems in the presence of risk parameters and the ever-increasing uncertainties. View Full-Text
  • 3.3K
  • 08 Apr 2021
Topic Review
Smoothed-Particle Hydrodynamics
Smoothed-particle hydrodynamics is a computational mesh-free Lagrangian method developed by Gingold, Monaghan, and Lucy in 1977, initially intended for use in astrophysics.
  • 1.1K
  • 08 Apr 2021
Topic Review
Complexity of Needs Model (DEA)
Data Envelopment Analysis (DEA) is a powerful non-parametric engineering tool for estimating technical efficiency and the production capacity of service units. The Complex-of-Needs Allocation Model proposed by Nepomuceno et al. (2020) is a two-step methodology for prioritizing hospital bed vacancy and reallocation during the COVID-19 pandemic. The framework determines the production capacity of hospitals through Data Envelopment Analysis and incorporates the Complexity of Needs in two categories for the reallocation of beds throughout the medical specialties. As a result, we have a set of inefficient health-care units presenting less complex bed slacks to be reduced, i.e. to be allocated for patients presenting more severe conditions.
  • 854
  • 08 Apr 2021
Topic Review
Gompertz Function with R
The Gompertz function is a sigmoid curve being a special case of a logistic curve. Although it was originally designed to describe mortality, it is now used in biology. For example, it is useful to describe many  phenomena such as the growth of a cancerous tumor confined to an organ without metastasis, the growth of the number of individuals in a population, e.g. prey in a Volterra-Lotka model, the germination of seeds, etc. It also models as the logistic function the growth of a colony of bacteria or in an epidemic the spread of the number of infected people. However, despite its many applications, in many cases the fitting of experimental data to the Gompertz function is not always straightforward. In this article we present a protocol that will be useful when performing the data regression to this curve using the statistical package R.
  • 21.2K
  • 07 Apr 2021
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