scholarly journals Novel indicators for evaluating topological threats to populations from pandemics applied to COVID-19

2020 ◽  
Author(s):  
Shun Adachi
Keyword(s):  
Objective Evaluation ◽  
Japanese Government ◽  
Infected People ◽  
Novel Approach ◽  
Accelerated Growth ◽  
Reliability And Robustness ◽  
Topological Number

ABSTRACTBACKGROUNDTo deal with pandemics, evaluating the temporal status of an outbreak is important. However, prevailing standards in this respect are mostly empirical and arbitrary. As an alternative, we focus on a novel approach which configures indicators that evaluate topological threats to populations due to the COVID-19 pandemic.METHODSWe extended the current PzDom model to calculate a threshold of the model for accelerated growth, an indicator of growth extent Re(v), covariance Re(s), a topological number E(l), and expected sums of possibly increasing numbers of infected people. We term this the exPzDom model.RESULTSThe indicators in the exPzDom model adhere well to the empirical dynamics of SARS-CoV-2 infected people and align appropriately with actual policies instituted by the Japanese government.CONCLUSIONSThe described indicators could be leveraged pursuant of objective evaluation based on mathematics. Further testing of the reliability and robustness of exPzDom model in other pandemic contexts is warranted.

scholarly journals Propagation Analysis of the Coronavirus Pandemic on the Light of the Percolation Theory

2021 ◽  
Author(s):  
Moez Guettari ◽  
Ahmed El Aferni
Keyword(s):  
Electrical Conductivity ◽  
Percolation Theory ◽  
Scaling Laws ◽  
High Accuracy ◽  
The Novel ◽  
Infected People ◽  
Boltzman Equation ◽  
Novel Approach ◽  
Propagation Analysis ◽  
Speed Of Propagation

Efforts to combat the Covid-19 pandemic have not been limited to the processes of vaccine production, but they first began to analyze the dynamics of the epidemic’s spread so that they could adopt barrier measures to bypass the spread. To do this, the works of modeling, predicting and analyzing the spread of the virus continue to increase day after day. In this context, the aim of this chapter is to analyze the propagation of the Coronavirus pandemic by using the percolation theory. In fact, an analogy was established between the electrical conductivity of reverse micelles under temperature variation and the spread of the Coronavirus pandemic. So, the percolation theory was used to describe the cumulate infected people versus time by using a modified Sigmoid Boltzman equation (MSBE) and several quantities are introduced such as: the pandemic percolation time, the maximum infected people, the time constant and the characteristic contamination frequency deduced from Arrhenius equation. Scaling laws and critical exponents are introduced to describe the spread nature near the percolation time. The speed of propagation is also proposed and expressed. The novel approach based on the percolation theory was used to study the Coronavirus (Covid-19) spread in five countries: France, Italy, Germany, China and Tunisia, during 6 months of the pandemic spread (the first wave). So, an explicit expression connecting the number of people infected versus time is proposed to analyze the pandemic percolation. The reported MSBE fit results for the studied countries showed high accuracy.

scholarly journals Physical development of children: historical experience and current challenges

2019 ◽  
Vol 4 (4) ◽  
pp. 89-96
Author(s):  
N. A. Skoblina ◽  
O. Yu. Milushkina ◽  
M. Yu. Gavryushin ◽  
Zh. V. Gudinova ◽  
O. V. Sazonova
Keyword(s):  
Comparative Analysis ◽  
Children And Adolescents ◽  
Objective Evaluation ◽  
Physical Development ◽  
Descriptive Statistics ◽  
Anthropometric Data ◽  
Historical Experience ◽  
Novel Approach ◽  
Golden Standard ◽  
Promising Solution

Aim. To develop the methodology to assess the standards of physical development of children and adolescents.Materials and Methods. We have analyzed the available literature and our previous results to identify current problems in evaluating physical development of children with the focus on regional standards.Results. Current methodology in the field clearly needs standardization. We propose that “Standards of physical development of children and adolescents” software enables the objective evaluation of physical development in relation to children and adolescents and therefore can be suggested as a golden standard. Comparative analysis of the anthropometric data using this program and standard descriptive statistics (SPSS 21) showed the similarity of the results.Conclusions. Contemporary problems in the study of physical development of children and adolescents include the lack of standardized methods, standards, and official documents. We suggest our novel approach as a promising solution.

scholarly journals Defect Prediction For Assembled Products: A Novel Model Based On The Structural Complexity Paradigm

2021 ◽  
Author(s):  
Elisa Verna ◽  
Gianfranco Genta ◽  
Maurizio Galetto ◽  
Fiorenzo Franceschini
Keyword(s):  
Objective Assessment ◽  
Structural Complexity ◽  
Objective Evaluation ◽  
Industrial Applications ◽  
Defect Prediction ◽  
The Novel ◽  
Subjective Knowledge ◽  
Design And Optimization ◽  
Novel Approach ◽  
Novel Model

Abstract Increased assembly complexity is one of the main challenges in manufacturing. Complexity can induce increased assembly cost and time, operational issues, costly defects and quality losses. Several approaches have been proposed in the literature to predict product defects by using assembly complexity as predictor. Despite defect prediction is of utmost importance from the early stages of product and related quality inspection design, most approaches are not directly applicable because they rely on the operators' prior subjective knowledge and are designed for specific industrial applications. To overcome this issue, the present research proposes a novel approach to predict product defects from a more objective evaluation of complexity. This is one of the first attempts to predict product defects and improve its quality with a purely objective assessment of the complexity of the assembled product, without the need for operators' evaluations and assembly experience. Defect rates in the model are predicted by using a recent conceptual paradigm of complexity that considers only structural properties of assembly parts and their architectural structure. The novel model is applied to a real assembly process in the electromechanical field and is compared with one of the most accredited in the literature, i.e. the Shibata-Su model. Empirical results show that, despite the super-linear relationship between defect rates and complexity in both models, the objective approach used in the novel model leads to more accurate and precise predictions of defectiveness rates, as it does not include the variability introduced by operators' subjective assessments. Adopting this novel model can effectively improve the estimate of product defects and support designers’ decisions for assembly quality-oriented design and optimization, especially in early design phases.

scholarly journals KL-MOB: automated COVID-19 recognition using a novel approach based on image enhancement and a modified MobileNet CNN

2021 ◽  
Vol 7 ◽  
pp. e694
Author(s):  
Mundher Mohammed Taresh ◽  
Ningbo Zhu ◽  
Talal Ahmed Ali Ali ◽  
Mohammed Alghaili ◽  
Asaad Shakir Hameed ◽  
...  
Keyword(s):  
Neural Network ◽  
Loss Function ◽  
X Ray ◽  
Infected People ◽  
Kl Divergence ◽  
Novel Approach ◽  
Starting Point ◽  
The World ◽  
Novel Coronavirus ◽  
Sensitivity Specificity

The emergence of the novel coronavirus pneumonia (COVID-19) pandemic at the end of 2019 led to worldwide chaos. However, the world breathed a sigh of relief when a few countries announced the development of a vaccine and gradually began to distribute it. Nevertheless, the emergence of another wave of this pandemic returned us to the starting point. At present, early detection of infected people is the paramount concern of both specialists and health researchers. This paper proposes a method to detect infected patients through chest x-ray images by using the large dataset available online for COVID-19 (COVIDx), which consists of 2128 X-ray images of COVID-19 cases, 8,066 normal cases, and 5,575 cases of pneumonia. A hybrid algorithm is applied to improve image quality before undertaking neural network training. This algorithm combines two different noise-reduction filters in the image, followed by a contrast enhancement algorithm. To detect COVID-19, we propose a novel convolution neural network (CNN) architecture called KL-MOB (COVID-19 detection network based on the MobileNet structure). The performance of KL-MOB is boosted by adding the Kullback–Leibler (KL) divergence loss function when trained from scratch. The KL divergence loss function is adopted for content-based image retrieval and fine-grained classification to improve the quality of image representation. The results are impressive: the overall benchmark accuracy, sensitivity, specificity, and precision are 98.7%, 98.32%, 98.82% and 98.37%, respectively. These promising results should help other researchers develop innovative methods to aid specialists. The tremendous potential of the method proposed herein can also be used to detect COVID-19 quickly and safely in patients throughout the world.

A Novel Approach for Image Enhancement via Nonsubsampled Contourlet Transform

2014 ◽  
Vol 23 (3) ◽  
pp. 345-355
Author(s):  
Yunlan Tan ◽  
Chao Li ◽  
Guangyao Li ◽  
Wenlang Luo ◽  
Weidong Tang
Keyword(s):  
Image Enhancement ◽  
Mapping Function ◽  
Objective Evaluation ◽  
Input Image ◽  
Contourlet Transform ◽  
Nonlinear Mapping ◽  
Nonsubsampled Contourlet Transform ◽  
Low Contrast ◽  
Novel Approach ◽  
Image Transform

AbstractAn improved image enhancement approach via nonsubsampled contourlet transform (NSCT) is proposed in this article. We constructed a geometric image transform by combining nonsubsampled directional filter banks and a nonlinear mapping function. Here, the NSCT of the input image is first decomposed for L-levels and its noise standard deviation is estimated. It is followed by calculating the noise variance and threshold calculation, and computing the magnitude of the corresponding coefficients in all directional subbands. Then, the nonlinear mapping function is used to modify the NSCT coefficients for each directional subband, which keeps the coefficients of strong edges, amplifies the coefficients of weak edges, and zeros the noise coefficients. Finally, the enhanced image is reconstructed from the modified NSCT coefficients. Three experiments are carried out respectively on images from subjective vision quality and objective evaluation measures. The first experiment is the algorithm performed on images. The subsequent experiments are the information entropy and spatial frequency. The experimental results demonstrate that the proposed method can gain better performance in enhancing the low-contrast parts of an image while keeping its clear edges.

scholarly journals Modelling COVID-19 using the Fundamentals of Fluid Dynamics

2020 ◽  
Author(s):  
Harris Sajjad Rabbani ◽  
Kofi Osei-Bonsu ◽  
Peter Kwame Osei-Bonsu ◽  
Thomas Daniel Seers
Keyword(s):  
Mathematical Modeling ◽  
Fluid Dynamics ◽  
Mathematical Model ◽  
Global Health ◽  
Global Economy ◽  
Control Measures ◽  
Critical Importance ◽  
Social Disruption ◽  
Infected People ◽  
Novel Approach

As of 21st May 2020, there have been 4.89M confirmed cases worldwide and over 323,000 deaths of people who have tested positive for SARS-CoV-2. The outbreak of COVID-19, has not only caused widespread morbidity and mortality, but has also led to a catastrophic breakdown in the global economy and unprecedented social disruption. To lessen the global health consequences of COVID-19, sweeping COVID-19 lockdown and quarantine measures have been imposed within many nations. These measures have significantly impacted the world’s economy and in many cases has led to the loss of livelihood. Mathematical modeling of pandemics is of critical importance to understand the unfolding of transmission events and to formulate control measures. In this research letter, we have introduced a novel approach to forecasting epidemics like COVID-19. The proposed mathematical model stems from the fundamental principles of fluid dynamics, and can be utilized to make projections of the number of infected people. This unique mathematical model can be beneficial for predicting and designing potential strategies to mitigate the spread and impact of pandemics.

scholarly journals Increasing Intrinsic Motivation of Programming Students: Towards Fix and Play Educational Games

10.28945/4027 ◽  
2018 ◽  
Vol 15 ◽  
pp. 069-077 ◽  
Author(s):  
Selvarajah Mohanarajah
Keyword(s):  
Intrinsic Motivation ◽  
Educational Games ◽  
Objective Evaluation ◽  
Educational Game ◽  
Future Research ◽  
Scale Evaluation ◽  
Novel Approach ◽  
Initial Stage ◽  
Programming Students ◽  
Conditional Structures

Aim/Purpose: The objective of this research is to investigate the effectiveness of educational games on learning computer programming. In particular, we are examining whether allowing students to manipulate the underlying code of the educational games will increase their intrinsic motivation. Background: Young students are fond of playing digital games. Moreover, they are also interested in creating game applications. We try to make use of both of these facts. Methodology: A prototype was created to teach the fundamentals of conditional structures. A number of errors were intentionally included in the game at different stages. Whenever an error is encountered, students have to stop the game and fix the bug before proceeding. A pilot study was conducted to evaluate this approach. Contribution: This research investigates a novel approach to teach programming using educational games. This study is at the initial stage. Findings: Allowing the programming students to manipulate the underlying code of the educational game they play will increase their intrinsic motivation. Recommendations for Practitioners: Creating educational games to teach programming, and systematically allowing the players to manipulate the gaming logic, will be beneficial to the students. Recommendation for Researchers: This research can be extended to investigate how various artificial intelligence techniques can be used to model the gamers, for example, skill level. Impact on Society: The future generations of students should be able to use digital technologies proficiently. In addition, they should also be able to understand and modify the underlying code in the digital things (like Internet of Things).This research attempts to alleviate the disenchantment associated with learning coding. Future Research: A full scale evaluation – including objective evaluation using game scores – will be conducted. One-way MANOVA will be used to analyze the efficacy of the proposed intervention on the students’ performance, and their intrinsic motivation and flow experience.

scholarly journals The Adaptive Damping Technique: Improving the Simulation Accuracy of Hydraulic Transients

2021 ◽  
Vol 6 (6) ◽  
pp. 1553-1564
Author(s):  
Jishnu Chandran R. ◽  
A. Salih
Keyword(s):  
Mathematical Model ◽  
Damping Coefficient ◽  
Variable Pressure ◽  
Coefficient Function ◽  
Transient Pressure ◽  
Local Pressure ◽  
Simulation Accuracy ◽  
Novel Approach ◽  
Proposed Model ◽  
Reliability And Robustness

Hydraulic surges are transient events frequently observed in various industrial and laboratory flow situations. Understanding surge physics and its accurate numerical prediction is crucial to the safety of flow systems. The maximum accuracy achievable for transient surge simulations is limited by the inefficiencies in the mathematical models used. In this work, we propose a mathematical model that incorporates an adaptive damping technique for the accurate prediction of hydraulic surges. This model also takes the compressibility effects in the liquid during the surge process into account. The novel approach of using the local pressure fluctuation data from the flow to adjust the unsteady friction for controlling the dissipation is introduced in this paper. The adaptive-dissipation is actualized through a unique 'variable pressure wave damping coefficient' function definition. Numerical simulation of three different valve-induced surge experiments demonstrates the reliability and robustness of the mathematical model. Numerical results from the proposed model show an excellent match with the experimental data by closely reproducing both the frequency and the amplitude of transient pressure oscillations. A comparative study explains the improvement in the simulation accuracy achieved by replacing the constant damping coefficient with the proposed variable coefficient. The superiority of the new model with the adaptive damping capability over the similar models in literature and those used in commercial software packages is also well established through this study.

scholarly journals The specificity of Japanese PCR assays for SARS-CoV-2 exceeds 99.7%

2020 ◽  
Author(s):  
Akihiro Tsukadaira
Keyword(s):  
Statistical Analysis ◽  
Prior Probability ◽  
Prediction Interval ◽  
Japanese Government ◽  
Infected People ◽  
Randomized Sampling ◽  
Pcr Assays ◽  
Japanese Residents

The Japanese government arranged a total of three charter flights to evacuate Japanese residents out of Wuhan Jan 29, 30, and 31, 2020. The project to rescue Japanese residents can be recognized as a randomized sampling study for the COVID-19 epidemic in Wuhan at that time. Jan 23, Jonathan MR et al stated in the medRxiv, in 14 days time (Feb 4, 2020), the number of infected people in Wuhan is estimated to be greater than 190 thousand (prediction interval, 132,751 to 273,649). In our study, the estimation of the COVID-19 cases in Wuhan around Jan 29, 30 and 31, 2020 exceeds the lower prediction 132,751 in the prior probability: 0.0134. Our statistical analysis is consistent with Jonathan MR et al, if the specificity of SARS-CoV-2 PCR assays in Japan exceeds 99.7%.

scholarly journals Automatic Detection of Spatiotemporal Urban Expansion Patterns by Fusing OSM and Landsat Data in Kathmandu

2019 ◽  
Vol 11 (19) ◽  
pp. 2296 ◽  
Author(s):  
Nishanta Khanal ◽  
Kabir Uddin ◽  
Mir Matin ◽  
Karis Tenneson
Keyword(s):  
Urban Growth ◽  
Land Use Planning ◽  
Vegetation Index ◽  
Urban Expansion ◽  
Google Earth ◽  
Growth Patterns ◽  
Rapid Expansion ◽  
Novel Approach ◽  
Accelerated Growth ◽  
The City

During the last few decades, a large number of people have migrated to Kathmandu city from all parts of Nepal, resulting in rapid expansion of the city. The unplanned and accelerated growth is causing many environmental and population management issues. To manage urban growth efficiently, the city authorities need a means to be able to monitor urban expansion regularly. In this study, we introduced a novel approach to automatically detect urban expansion by leveraging state-of-the-art cloud computing technologies using the Google Earth Engine (GEE) platform. We proposed a new index named Normalized Difference and Distance Built-up Index (NDDBI) for identifying built-up areas by combining the LandSat-derived vegetation index with distances from the nearest roads and buildings analysed from OpenStreetMap (OSM). We also focused on logical consistencies of land-cover change to remove unreasonable transitions supported by the repeat photography. Our analysis of the historical urban growth patterns between 2000 and 2018 shows that the settlement areas were increased from 63.68 sq km in 2000 to 148.53 sq km in 2018. The overall accuracy of mapping the newly-built areas of urban expansion was 94.33%. We have demonstrated that the methodology and data generated in the study can be replicated to easily map built-up areas and support quicker and more efficient land management and land-use planning in rapidly growing cities worldwide.

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