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Calendar of 13 Months
Has anyone of us missed an event because he was confused between days and dates? Do we really remember the date of any day if we do not have a calendar? Is the current Gregorian Calendar efficient enough for use, and does it really facilitate our life or make it more complicated? Have you ever thought about a much simpler way to calculate days and dates in a year? All these questions are answered in this article, in which the author proposes an original calendar that might facilitate our lives if we can apply it.
28 Oct 2020
Salient Object Detection
Detection and localization of regions of images that attract immediate human visual attention is currently an intensive area of research in computer vision. The capability of automatic identification and segmentation of such salient image regions has immediate consequences for applications in the field of computer vision, computer graphics, and multimedia. A large number of salient object detection (SOD) methods have been devised to effectively mimic the capability of the human visual system to detect the salient regions in images. These methods can be broadly categorized into two categories based on their feature engineering mechanism: conventional or deep learning-based. In this survey, most of the influential advances in image-based SOD from both conventional as well as deep learning-based categories have been reviewed in detail. Relevant saliency modeling trends with key issues, core techniques, and the scope for future research work have been discussed in the context of difficulties often faced in salient object detection. Results are presented for various challenging cases for some large-scale public datasets. Different metrics considered for assessment of the performance of state-of-the-art salient object detection models are also covered. Some future directions for SOD are presented towards end.
19 Nov 2020
Digital Twin: Origin to Future
Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.
25 Jun 2021
Intraretinal Fluid Pattern Characterization
The accumulation of fluids in the retinal layers is one of the main causes of blindness in developed countries. The main strategy for its study and diagnosis is through the use of Optical Coherence Tomography (OCT) images. This allows experts to observe the layers of the retina in a cross-sectional view. Commonly, for the analysis of these accumulations by means of computer diagnostic support systems, precise segmentation strategies are employed.
22 Apr 2021
Requirements Engineering in OTF-Computing
The idea of On-The-Fly (OTF) Computing is to compose and provide software services ad hoc, based on requirement descriptions in natural language. Since non-technical users write their software requirements themselves and in unrestricted natural language, deficits occur such as inaccuracy and incompleteness. These deficits are usually tackled by natural language processing methods, which have to face specific challenges in OTF Computing because maximum automation is the goal there. In the following, we present current automatic approaches for solving inaccuracies and incompleteness in natural language requirement descriptions.
30 Oct 2020
Bluetooth Low Energy Mesh Networks
Bluetooth Low Energy (BLE) is an increasingly prevalent Wireless Ad-Hoc Network (WAHN) technology for battery-powered Internet of Things (IoT) devices . The BLE standard was introduced by the Bluetooth Special Interest Group (SIG) in Bluetooth version 4.0, and subsequently enhanced in versions 4.2 and 5. Initially, BLE 4.x adopted the legacy Bluetooth Personal Area Network (PAN) model for multi-hop communications and the interconnection of networks. BLE 5 intends to address these inadequacies via the implementation of pure mesh topology to provide enhanced network coverage, inter-network connectivity, and improved security .
28 Oct 2020
Fog and Edge Computing
The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate and connect with each other. Conventional computing infrastructures are struggling to satisfy dramatic growth in demand from a deluge of connected heterogeneous end points located at the edge of networks while, at the same time, meeting quality of service levels. The complexity of computing at the edge makes it increasingly difficult for infrastructure providers to plan for and provision resources to meet this demand. While simulation frameworks are used extensively in the modelling of cloud computing environments in order to test and validate technical solutions, they are at a nascent stage of development and adoption for fog and edge computing. This paper provides an overview of challenges posed by fog and edge computing in relation to simulation.
23 Dec 2020
The paper is devoted to an overview of multi-agent principles, methods, and technologies intended to adaptive real-time data clustering. The proposed methods provide new principles of self-organization of records and clusters, represented by software agents, making it possible to increase the adaptability of different clustering processes significantly. The paper also presents a comparative review of the methods and results recently developed in this area and their industrial applications. An ability of self-organization of items and clusters suggests a new perspective to form groups in a bottom-up online fashion together with continuous adaption previously obtained decisions. Multi-agent technology allows implementing this methodology in a parallel and asynchronous multi-thread manner, providing highly flexible, scalable, and reliable solutions. Industrial applications of the intended for solving too complex engineering problems are discussed together with several practical examples of data clustering in manufacturing applications, such as the pre-analysis of customer datasets in the sales process, pattern discovery, and ongoing forecasting and consolidation of orders and resources in logistics, clustering semantic networks in insurance document processing. Future research is outlined in the areas such as capturing the semantics of problem domains and guided self-organization on the virtual market.
08 Feb 2021
A discrete quantum momentum operator
We introduce finite-differences derivatives intended to be exact when applied to the real exponential function. We want to recover the known results of continuous calculus with our finite differences derivatives but in a discrete form. The purpose of this work is to have a discrete momentum operator suitable for use as an operator in discrete quantum mechanics theory.
24 Aug 2021
Multiple Attribute-based Decision-making Models
Sustainability of agricultural practices depends on economic, environmental, and social conditions. The Rajasthan state of India has arid climatic conditions where kharif crops are commonly grown. In this work, the four major criteria are considered such as the farm area, crop yield per unit area, the cost prices, and the market sales price. Merged analytic hierarchy process (AHP) and entropy techniques have been employed to give reasonable weight coefficients for the objective and subjective weights to each criterion. Multiple attribute-based decision-making models (MADM) have been developed using three proven techniques, namely the Exprom2, the technique for order of preference by similarity to ideal solution (TOPSIS), and the VlseKriterijumska Optimizacija I KompromisnoResenje (VIKOR). The crop Pennisetum glaucum emerged as the most productive kharif crop in the arid climatic conditions of Rajasthan, India under the given criteria. The sensitivity analysis of the three methods identifies the most significant criteria and validates that Pennisetum glaucum is the first ranked crop despite the interchange of the weights. The methodology used in this study may be applied across the globe to select appropriate crops for maximizing the profit, optimizing the natural resources, and promoting sustainable agricultural practices. This study may be used to enhance the agricultural gross domestic product (GDP) to make the agriculturalists self-sufficient and to help the state policymakers in making elective regional policies.
05 Nov 2020
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