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Topic Review
Videos Data Augmentation for Deep Learning Models
In most Computer Vision applications, Deep Learning models achieve state-of-the-art performances. One drawback of Deep Learning is the large amount of data needed to train the models. Unfortunately, in many applications, data are difficult or expensive to collect. Data augmentation can alleviate the problem, generating new data from a smaller initial dataset. Geometric and color space image augmentation methods can increase accuracy of Deep Learning models but are often not enough. More advanced solutions are Domain Randomization methods or the use of simulation to artificially generate the missing data. Data augmentation algorithms are usually specifically designed for single images. Most recently, Deep Learning models have been applied to the analysis of video sequences.
  • 2.3K
  • 25 Mar 2022
Topic Review
Update on Cyber Health Psychology
In recent years, there has been more and more talk of cyber health psychology and the implication that new technologies can have in the diagnosis, treatment, and rehabilitation of psychopathological issues in the field of mental health, ranging from post-traumatic stress disorder (PTSD) to addiction to substances of abuse.
  • 616
  • 25 Mar 2022
Topic Review
Cybersecurity in the Maritime Sector
Global maritime sector is increasingly reliant on digitalisation, operational integration, and automation. Leading shipbuilders and operators seek to innovate by utilizing cutting-edge technologies and systems that go beyond traditional designs to create ships with advanced remote control, communication, and connectivity capabilities. Those capabilities are tested through various autonomous vessel projects.
  • 387
  • 25 Mar 2022
Topic Review
A Rule-Based Grapheme-to-Phoneme Conversion System
Natural language processing often requires grapheme-to-phoneme (G2P) conversion of an orthographic text. G2P converts strings of graphemes to corresponding sequences of phonetic transcription characters, directly from orthographic representations and it is crucial for many applications in various areas of speech and language processing.
  • 885
  • 25 Mar 2022
Topic Review
Wireless Technologies for Social Distancing in COVID-19 Pandemic
So-called “social distance” refers to measures that work to prevent disease spread through minimizing human physical contact frequency and intensity, including the closure of public spaces (e.g., schools and offices), avoiding large crowds, and maintaining a safe distance between individuals. Because it reduces the likelihood that an infected person would transmit the illness to a healthy individual, social distance reduces the disease’s progression and impact. During the early stages of a pandemic, social distancing techniques can play a crucial role in decreasing the infection rate and delaying the disease’s peak. Consequently, the load on healthcare systems is reduced, and death rates are reduced. The concept of social distancing may not be as easy as physical distancing, given the rising complexity of viruses and the fast expansion of social interaction and globalization. It encompasses numerous non-pharmaceutical activities or efforts designed to reduce the spread of infectious diseases, including monitoring, detection, and alerting people. Different technologies can assist in maintaining a safe distance (e.g., 1.5 m) between persons in the adopted scenarios. There are a number of wireless and similar technologies that can be used to monitor people and public locations in real-time.
  • 884
  • 25 Mar 2022
Topic Review
Athlos: A Framework for Developing Scalable MMOG Backends
The development of resource-intensive, distributed, real-time applications like Massively Multiplayer Online Game (MMOG) backends entails a variety of challenges, some of which have been extensively studied. Despite some advancements, the development and deployment of MMOG backends on commodity clouds and high-level computing layers continues to face several obstacles, including a non-standardized development methodology, lack of provisions for scalability, and the need for abstractions and tools to support the development process. In this paper, we describe a set of models, methods, and tools for developing scalable MMOG backends and hosting them on commodity cloud platforms. We present Athlos, a framework that allows game developers to leverage our methodology to rapidly prototype MMOG backends that can run on any type of cloud environment. We evaluate this framework by conducting simulations based on several case-study MMOGs to benchmark its performance and scalability, and compare the development effort needed, and quality of the code produced with other approaches. We find that MMOGs developed using this framework: (a) can support a very high number of simultaneous players under a given latency threshold, (b) elastically scale both in terms of runtime and state, and (c) significantly reduce the amount of effort required to develop them. Coupled with the advantages of high-level computing layers such as Platform, Backend, and Function-as-a-Service, we argue that our framework accelerates the development of high-performance, scalable MMOGs, that leverage the resources of commodity cloud platforms.
  • 513
  • 25 Mar 2022
Topic Review
Procedures in Mathematical Problems and Video Games
Video game use is widespread among all age groups, from young children to older adults. The wide variety of video game genres, which are adapted to all tastes and needs, is one of the factors that makes them so attractive. In many cases, video games function as an outlet for stress associated with everyday life by providing an escape from reality. The recreational aspect of video games is more important than the educational aspect. However, the students were not aware of using the problem-solving procedures they learned at school to solve different challenges in the video games. Furthermore, overcoming video game challenges stimulates positive emotions as opposed to the negative emotions generated when solving mathematical problems. 
  • 876
  • 24 Mar 2022
Topic Review
A New Container Throughput Forecasting Paradigm under COVID-19
COVID-19 has imposed tremendously complex impacts on the container throughput of ports, which poses big challenges for traditional forecasting methods. Combining this with change-point analysis and empirical mode decomposition (EMD), this uses the decomposition–ensemble methodology to build a throughput forecasting model. Firstly, EMD is used to decompose the sample data of port container throughput into multiple components. Secondly, fluctuation scale analysis is carried out to accurately capture the characteristics of the components. Subsequently, here tailor the forecasting model for every component based on the mode analysis. Finally, the forecasting results of all the components are combined into one aggregated output. 
  • 576
  • 24 Mar 2022
Topic Review
Bayesian Nonlinear Mixed Effects Models
Nonlinear mixed effects models have become a standard platform for analysis when data is in the form of continuous and repeated measurements of subjects from a population of interest, while temporal profiles of subjects commonly follow a nonlinear tendency. While frequentist analysis of nonlinear mixed effects models has a long history, Bayesian analysis of the models has received comparatively little attention until the late 1980s, primarily due to the time-consuming nature of Bayesian computation. Since the early 1990s, Bayesian approaches for the models began to emerge to leverage rapid developments in computing power, and have recently received significant attention due to (1) superiority to quantify the uncertainty of parameter estimation; (2) utility to incorporate prior knowledge into the models; and (3) flexibility to match exactly the increasing complexity of scientific research arising from diverse industrial and academic fields. 
  • 1.0K
  • 23 Mar 2022
Topic Review
Toward Blockchain Realization
Since FinTech was stimulated by the invention of blockchain, without the full realization of blockchain technologies in the following years, FinTech has not been fully realized. The lack of distributed synchronization might be the most difficult challenge such that the trust provided by blockchain is not good enough for public use. 
  • 625
  • 22 Mar 2022
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