We present a simple, near-real-time Bayesian method to infer and forecast a multiwave outbreak, and demonstrate it on the COVID-19 pandemic. The approach uses timely epidemiological data that has been widely available for COVID-19. It provides short-term forecasts of the outbreak’s evolution, which can then be used for medical resource planning. The method postulates one- and multiwave infection models

The outbreak of COVID-19 in 2020 has led to a surge in interest in the mathematical modeling of infectious diseases. Such models are usually defined as compartmental models, in which the population under study is divided into compartments based on qualitative characteristics, with different assumptions about the nature and rate of transfer across compartments. Though most commonly formulated as ordinary

Stay cables are one of the key elements of cable-stayed bridges and are characterized by lightweight, low inherent damping, and high flexibility. They are continuously subjected to small-to large-amplitude vibrations due to various types of dynamic loads that may, in the long term, cause fatigue and fracture problems for the cable system, and may eventually compromise the safety of cable-stayed bridges

Clustering is one of the most vital image segmentation techniques. However, proper image clustering has always been a challenging task due to blurred and vague areas near to concerned object boundaries. Therefore, rough set based clustering techniques like Rough k-means (RKM) has been employed in image clustering domain because rough set concept can handle the overlapping clusters to a great extent

Multi-scale models enriched with the second gradient of the displacement field and based on the concept of representative volume element (RVE) are examined and discussed in detail in this paper. The development of new models relies on the Method of Multi-Scale Virtual Power from which equilibrium equations and homogenisation relations are derived employing variational arguments. Two classes of enhanced

The Internet of Things (IoT) is basically like a system for connecting computer devices, mechanical and digital machines, objects, or individuals provided with the unique system (UIDs) and without transfer to transmit data over an ability human-to-human or computer-to-human relation. Another thing on the internet is that the items in the IoT are like a connected manner with humans and computers to

A wireless network is used to connect various wired organizational structures and provide connectivity within the organization for employees to move freely by avoiding the hurdle of a physical network. Maintenance of WLAN security is crucial to an organization because WLANs are directly linked to the core organization’s network. In this paper, we reviewed the architectures and protocols of wireless

Technological advancements modernize the way we live with the changes made both globally and nationwide. These technological improvements also cause adverse effects in the form of security threats. To overcome this problem, many researchers integrated both big data and artificial intelligence (AI) techniques to enhance the security of internet-connected devices. Big data normally represents the massive

This paper deals with the mathematical modeling of atherosclerosis based on a novel hypothesis proposed by a surgeon, Prof. Dr. Axel Haverich (Circulation 135(3):205–207, 2017). Atherosclerosis is referred as the thickening of the artery walls. Currently, there are two schools of thoughts for explaining the root of such phenomenon: thickening due to substance deposition and thickening as a result of

This paper aims to review the recent progress in the research carried out by scientists worldwide regarding American Footballers' head injuries and head protective equipment, focusing on the role of computation methods, mainly finite element method application to American Football helmet design and testing as well as head injury biomechanics. The helmet technology has been constantly improved, and

For screening breast tumors, different imaging modalities like ultrasound, mammography, computed tomography (CT), magnetic resonance imaging (MRI) have been utilized. Mammography and CT use ionizing radiations and hence are not preferred for pregnant women. Even though MRI has high sensitivity for differentiating between breast tumor types, it is costlier and not available everywhere. Therefore, ultrasound

Machine learning (ML) holds significant potential for predicting soil properties in geotechnical design but at the same time poses challenges, including those of how to easily examine the performance of an algorithm and how to select an optimal algorithm. This study first comprehensively reviewed the application of ML algorithms in modelling soil properties for geotechnical design. The algorithms were

Metaheuristic algorithms are widely used in various fields of optimization engineering. These algorithms have become popular because of their ability to explore and exploit solutions in various problem areas. The Spotted Hyena Optimizer (SHO) algorithm is a metaheuristic algorithm inspired by the life of spotted hyenas, introduced by Dhiman and Kumar (2017) to solve continuous optimization problems

An overview of high-fidelity modeling of pathogen propagation, transmission and mitigation in the built environment is given. In order to derive the required physical and numerical models, the current understanding of pathogen, and in particular virus transmission and mitigation is summarized. The ordinary and partial differential equations that describe the flow, the particles and possibly the UV

Since end of 2019 the COVID-19 pandemic, caused by the SARS-CoV-2 virus, is threatening humanity. Despite the fact that various scientists across the globe try to shed a light on this new respiratory disease, it is not yet fully understood. Unlike many studies on the geographical spread of the pandemic, including the study of external transmission routes, this work focuses on droplet and aerosol transport

Weather forecasting, as an important and indispensable procedure in people’s daily lives, evaluates the alteration happening in the current condition of the atmosphere. Big data analytics is the process of analyzing big data to extract the concealed patterns and applicable information that can yield better results. Nowadays, several parts of society are interested in big data, and the meteorological

Image processing is among the significant areas of growth in the current scenario. It consist of a set of techniques typically used to enhance the raw image obtained from different scenes. Segmentation of images is an essential step in image analysis and pre-processing. During the course of the work, standard multilevel thresholding methods are very effective due to their low computational cost, reliability

A multiscale approach for the detailed simulation of water droplets dispersed in a turbulent airflow is presented. The multiscale procedure combines a novel representative volume element (RVE) with the Pseudo Direct Numerical Simulation (P-DNS) method. The solution at the coarse-scale relies on a synthetic model, constructed using precomputed offline RVE simulations and an alternating digital tree

The past few decades have seen a significant spurt in developing lower-order, parsimonious models of large-scale dynamical systems used for design and control. These surrogate models effectively capture the most interesting dynamic features of the full-order models (FOMs) while preserving the input–output relation. Model order reduction (MOR) techniques have intensively been further developed to treat

Drug combination therapies are successfully used in the treatment of cancer disease. The synergistic drug combinations not only increase the drug efficacy, but also reduce the drug dosage. The exhaustive combination of synergistic drugs makes it more challenging. The deep learning techniques are used to handle this issue. In this paper, a comprehensive review on deep synergistic drug combination is

The field of software development has been rich alongside its heterogeneous nature. In the past few decades, paradigms and research work cultures have also undergone different changes. As every software is confined to an order, which ensure its steadiness and empowers it to be perceptible by our eyes, and builds up “similarities to” and “contrasts from” the alternative software(s). Adding new features

Food Adulteration is a deceptive act of misleading food buyers for economic gain. It has been a major concern due to its risk to public health, reduction of food quality or nutritional value. It is a food fraud that has incensed the food industry and has attracted the attention of the community since the last century. To ensure consumer protection against fraudulent activities, authentication of food

The advancement in electromagnetic metamaterials, which commenced three decades ago, experienced a rapid transformation into acoustic and elastic systems in the forms of phononic crystals and acoustic/elastic metamaterials. Since its early discovery, numerous wave phenomena alongside the possible engineering applications have been highlighted. The existing and emerging fields of metamaterials are far

CAPTCHA stands for Completely Automated Public Turing Test to Tell Computers and Human Apart. CAPTCHA is used for internet security. A few CAPTCHA schemes are available today like, text-based, audio-based, video/animation-based, puzzle based etc. In this paper, all these types are collaborating at single place to analyze. The main aim of this article is to present a literature to identify and recognize

The pandemic of 2019 has led to an enormous interest in all aspects of modeling and simulation of infectious diseases. One central issue is the redesign and deployment of ventilation systems to mitigate the transmission of infectious diseases, produced by respiratory emissions such as coughs. This work seeks to develop a combined Digital-Twin and Machine-Learning framework to optimize ventilation systems

In industries, precise measurement of different form errors is critical and challenging for stringent geometric and dimensional control in manufactured part. These form errors have significant influence on the functional performance of an industrial product that arises due the inherent invariability in measurement techniques and manufacturing devices. Several research have been conducted for evaluation

A correction to this paper has been published: https://doi.org/10.1007/s11831-021-09607-5

From the early days of pattern recognition, word spotting have been important test beds for studying how well machines can perform better decision making. In recent years, word spotting have made dramatic advances with state-of-the-art techniques reaching high level of performance in real life applications. This word spotting domain have driven research by providing suitable yet well-defined challenges

The construction industry is multidisciplinary in nature and various operations are executed at the same time. One of the major resources for executing construction operations is the human workforce. Management of this workforce with effective safety provisions is a prime factor for reducing accidents on construction sites. Nowadays, technologies such as Building Information Modeling (BIM) offer the

As an interdisciplinary between quantum computing and image processing, quantum image processing provides more possibilities for image processing due to the powerful parallel computing capabilities of quantum computers. In recent years, quantum image processing attracts more and more researcher’s attention. In order to allow researchers to better understand quantum image processing technology, we have

Currently, geometric over-constraints detection is of major interest in several different fields. In terms of product development process (PDP), many approaches exist to compare and detect geometric over-constraints, to decompose geometric systems, to solve geometric constraints systems. However, most approaches do not take into account the key characteristics of a geometric system, such as types of

Photoplethysmography (PPG) sensor-enabled wearable health monitoring devices can monitor realtime health status. PPG technology is a low-cost, noninvasive optical method used to measure a volumetric change in blood during a cardiac cycle. Continues analysis of change in light signal due to change in the blood helps medical professionals to extract valuable information regarding the cardiovascular system

Additive Manufacturing concentrates the attention, not only of the research and academic community, but of the industry as well. Selective Laser Melting (SLM) and Selective Laser Sintering (SLS) are among the broadest employed methods in AM, since they can treat almost all types of materials. Along with the extensive experimental research that is carried out regarding SLS and SLM, modeling and simulation

The extensive progression in the Internet of Vehicles (IoV) and the exponential upsurge in data consumption reflect the importance of big data in IoV. In general, big data has gained a significant attraction in academia and industry to provide valuable business intelligence and evidence-based decisions. This has been a key enabler for the advancement of the Internet of Vehicles (IoV) in which big data

In this world of big data, the development and exploitation of medical technology is vastly increasing and especially in big biomedical imaging modalities available across medicine. At the same instant, acquisition, processing, storing and transmission of such huge medical data requires efficient and robust data compression models. Over the last 2 decades, numerous compression mechanisms, techniques

Due to the great challenges of measuring forces directly, identifying dynamic loads based on accessible responses is a crucial problem in engineering, helping ensure integrity and reliability of mechanical structures. Dynamic load identification is a difficult inverse problem due to matrix ill-posedness, noise-sensitivity and computational scale, especially in uncertain structures. Unexpected inaccurate

Food has a direct impact on an individual's life and is a significant area for the research community. Computational techniques in food-related computing are performed to address various food-related issues in the field of agronomy, medicine, biology etc. In this paper, we present a comprehensive review of research exclusively on segmentation techniques used for food computing. This paper illustrates

Plant disease detection is a critical issue that needs to be focused on for productive agriculture and economy. Detecting plant disease using traditional methods is a tedious job as it requires a tremendous amount of work, time, and expertise. Automatic plant disease detection is an important research area that has recently gained a lot of attention among the academicians, researchers, and practitioners

While considered a relatively emergent area of research (Bloch and Sacks in Autom Constr 91:256–272, 2018), Semantic Enrichment (SE) and Semantic Web services are among the prominent topics and trends in BIM research (BIM handbook a guide to building information modeling for owners, designers, engineers, contractors, and facility managers, John Wiley & Sons Inc, New Jersey). SE computational approaches

The automotive industry is facing a crucial time. The transformation from internal combustion engines to new electrical technologies requires enormous investment, and hence the IC engines are likely to serve as a means of transportation for the coming decades. The search for sustainable green alternative fuel and operating parameter optimization is a current feasible solution and is a critical issue

With the rapid development of logistics industry, vehicle scheduling is the key to the optimization of transportation links. Vehicle transportation route planning is becoming more and more important to reduce logistics costs. In recent decades, the research on VRP and related derivative problems has become more and more extensive. Based on the basic VRP, this paper classifies VRP according to its characteristics

The design of complex mechanical components is a time-consuming process which involves many design variables with multiple interacted objectives and constraints. Traditionally, the design process of mechanical components is performed manually depending on the intuition and experience of the designer. In recent decades, automatic methods have been proposed to effectively search diverse and large parameter

In today Internet era, confidential information transmitted over an insecure channel. With the significant development in the area of quantum computing, there is a need for unconditional security in confidential information. Quantum key distribution protocols are proven secure if all devices are perfect (in terms of technologies and proper protocol operations). The major challenges in quantum communication

This work bridges two research fields i.e. metaheuristics and wind farm layout design. Comparative performance of twelve metaheuristics (MHs) on wind farm layout optimisation (WFLO) was conducted. Four WFLO problems are proposed for benchmarking the various metaheuristics while the design problem is an attempt to simultaneously minimise wind farm cost and maximise wind farm totally produced power.

Quantum Computing is an emerging technology that can perform high intensive computing tasks which are needed in different areas such as data search from high volume data repository, prime factorization, number theory, cybersecurity, polynomial evaluation, interpolation, Machine learning, Artificial Intelligence and many more applications. Any computational problem that can be solved by classical computer

Diabetes, one of the top 10 causes of death worldwide, is associated with the interaction between lifestyle, psychosocial, medical conditions, demographic, and genetic risk factors. Predicting type 2 diabetes is important for providing prognosis or diagnosis support to allied health professionals, and aiding in the development of an efficient and effective prevention plan. Several works proposed machine-learning

The objective of this study is to present a state-of-the-art review on applications and trends of meta-heuristics for remanufacturing problems. This literature review mainly encompass the most popular and frequently employed meta-heuristics like genetic algorithm, artificial bee colony, particle swarm optimization, ant colony optimization, simulated annealing, tabu search, variable neighborhood search

Bio-particulate matter includes grains, cereal crops, and biomass that are considered discrete materials with irregular size and shape. Although the flow of these particles can behave like a continuum fluid at times, their discontinuous behavior cannot be simulated with traditional continuum-based modeling. The Discrete Element Method (DEM), coupled with Computational Fluid Dynamics (CFD), is considered

In the past, knowledge in the fields of Architecture, Engineering and Construction (AEC) industries mainly come from experiences and are documented in hard copies or specific electronic databases. In order to make use of this knowledge, a lot of studies have focused on retrieving and storing this knowledge in a systematic and accessible way. The Building Information Modeling (BIM) technology proves

This review article revisits and outlines the perfectly matched layer (PML) method and its various formulations developed over the past 25 years for the numerical modeling and simulation of wave propagation in unbounded media. Based on the concept of complex coordinate stretching, an efficient mixed displacement-strain unsplit-field PML formulation for second-order (displacement-based) linear elastodynamic

This paper simply presents a state of the art survey among the machine learning based approaches for the Glioma classification. As Glioma classification is a very challenging task in the field of medical science and this task is well addressed and taken by the fraternity of machine learning experts, who are working day and night to devise automated approaches that can automate this whole process of

The dawn of the new era in precise diagnostic devices and personalized cancer treatment is intertwined with computational models capable of integrating biochemical factors and biophysical processes to simulate and predict cancer progression. In the last decade, thanks to the increase in the computational power, the development of more sophisticated and realistic models has gained attention in cancer

Several new technologies such as the smart cities, the Internet of Things (IoT), and 5G Internet need services offered by cloud computing for processing and storing more information. Hence, the heterogeneity of the new companies that used the above-mentioned technologies will add many vulnerabilities and security concerns for the cloud paradigm. Presently, cloud computing involves every component such

Data mining, data analytics and data processing are three inter-related processes that are carried out on large volume of datasets. Data can be of any form such as text, numeric, ontology, alpha-numeric, images, video, and other multi-dimensional datasets. People dataset is one of the famous datasets from the above datasets. Crowdsourcing is used to solve the large size of data with people. The crowdsourcing

In the course of driving, due to the influence of environment, signal acquisition device and the degree of unevenness of road surface, the collected signals fluctuate within certain error range and have randomness. To predict the fatigue life of mechanical structures more accurately, the processing method of random load signals for uncertainty is proposed. The collected load signals are converted into

The survey paper summarizes the recent applications and developments in the domain of Generative Adversarial Networks (GANs) i.e. a back propagation based neural network architecture for generative modeling. GANs is one of the most highlighted research avenue due to its synthetic data generation capabilities and benefits of representations comprehended irrespective of the application. While several

Cloud Computing has many facets to it which makes it diverse. Investigation of a cyber-crime that involves the cloud as a subject, object, or as an environment, is cloud forensics. Challenges in cloud forensics exist at every phase of digital forensics. To provide a holistic solution to overcome these challenges we must first understand the cloud forensics landscape (the Cloud). The elements which

Agriculture is one of the most crucial field contributing to the development of any nation. It not only affects the economy of nation but also has impact on the world food grain statistics. For agriculturist obtaining sustainable production of crop is always a challenge. Achieving optimum crop yield has always been a challenge for the farmer due to ever changing environmental conditions. The major

The objective of this article is to summarise the work that we have been doing as a group in the context of stabilised finite element formulations for viscoelastic fluid flows. Viscoelastic fluids are complex non-Newtonian fluids, characterised by having an irreducible constitutive equation that needs to be solved coupled with the momentum and continuity equations. The finite element approximation

The coordinated or selective power system can be considered as a sequence procedure among two protective devices installed in series and having certain features. The coordination of protective devices in protection system is a very substantial procedure to guarantee a strength and reliable power system. Directional overcurrent relays coordination is considered as an optimization problem. Due to the