The future of software engineering: Visions of 2025 and beyond

In the current technological scenario of the industry and businesses, there has been increasing need of software within systems and also an increasing demand being put onto software-intensive systems. This in effect will lead to a significant evolution of software engineering processes over the next twenty years. This is due to the fact of emerging technological advancements like Industry 4.0 and Internet of Things in the IT field, among other new developments. This paper addresses and tries to analyses the key research challenges being faced by the software engineering field and articulates information that is derived from the key research specializations within software engineering. The paper analyses the past and current trends in software engineering. The future of software engineering is also looked with respect to Industry 4.0 which including emerging technological platforms like Internet of Things. The societal impact aspect of future trends in software engineering is also addressed in this paper

Automatic detection of tuberculosis using VGG19 with seagull-algorithm.

Due to various reasons, the incidence rate of communicable diseases in humans is steadily rising, and timely detection and handling will reduce the disease distribution speed. Tuberculosis (TB) is a severe communicable illness caused by the bacterium Mycobacterium-Tuberculosis (M. tuberculosis), which predominantly affects the lungs and causes severe respiratory problems. Due to its significance, several clinical level detections of TB are suggested, including lung diagnosis with chest X-ray images. The proposed work aims to develop an automatic TB detection system to assist the pulmonologist in confirming the severity of the disease, decision-making, and treatment execution. The proposed system employs a pre-trained VGG19 with the following phases: (i) image pre-processing, (ii) mining of deep features, (iii) enhancing the X-ray images with chosen procedures and mining of the handcrafted features, (iv) feature optimization using Seagull-Algorithm and serial concatenation, and (v) binary classification and validation. The classification is executed with 10-fold cross-validation in this work, and the proposed work is investigated using MATLAB® software. The proposed research work was executed using the concatenated deep and handcrafted features, which provided a classification accuracy of 98.6190% with the SVM-Medium Gaussian (SVM-MG) classifier

Cyber physical systems: A smart city perspective

Cyber-physical system (CPS) is a terminology used to describe multiple systems of existing infrastructure and manufacturing system that combines computing technologies (cyber space) into the physical space to integrate human interaction. This paper does a literature review of the work related to CPS in terms of its importance in today’s world. Further, this paper also looks at the importance of CPS and its relationship with internet of things (IoT). CPS is a very broad area and is used in variety of fields and some of these major fields are evaluated. Additionally, the implementation of CPS and IoT is major enabler for smart cities and various examples of such implementation in the context of Dubai and UAE are researched. Finally, security issues related to CPS in general are also reviewed

Autonomous vehicles: A study of implementation and security

Autonomous vehicles have been invented to increase the safety of transportation users. These vehicles can sense their environment and make decisions without any external aid to produce an optimal route to reach a destination. Even though the idea sounds futuristic and if implemented successfully, many current issues related to transportation will be solved, care needs to be taken before implementing the solution. This paper will look at the pros and cons of implementation of autonomous vehicles. The vehicles depend highly on the sensors present on the vehicles and any tampering or manipulation of the data generated and transmitted by these can have disastrous consequences, as human lives are at stake here. Various attacks against the different type of sensors on-board an autonomous vehicle are covered

Hybrid Reality-Based Education Expansion System for Non-Traditional Learning

Many educators utilize conventional coaching methods to coach and study behaviors in a classroom with face-to-face, verbal contact. But, the coaching with learning atmosphere has developed further than the classroom. The incorporation of technology at the coaching with learning procedure is the novel tendency at teaching, by a favorable result. Technologies present surroundings for learning behaviors to happen anytime also everywhere to advantages instructors with students universal. One of the skills to have been demonstrating feasibilities of the appliance at learning surroundings is Hybrid Reality (HR), which includes together Virtual Reality (VR) with Augmented Reality (AR). This work attempts to construct ahead the recent condition of hybrid reality also its appliance at learning. The initial section depicts the fundamental formation of hybrid reality also its various divisions. The subsequent sections provide the superior construction of a few innovative appliances that are implemented for the hybrid reality. Lastly, the paper shows the benefits of those applications over the traditional teaching methods and the essential user reactions. The outcomes have highly in assistance of taking mobile applications based on Hybrid Reality into a contemporary teaching scheme

An energy-efficient cluster head selection in wireless sensor network using grey wolf optimization algorithm

Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms

Gender and Tahrir Square: contesting the state and imagining a new nation

This article argues that the concepts of ‘State’ and ‘Nation’ should be treated as separate from one another, hence, more than one image of the nation is possible at one given time. During the early days of the January 2011 Egyptian revolution, a contestation emerged between Mubarak’s state and the protesters in Tahrir Square over the image and notion of the Egyptian nation. Both the state and the protesters attempted to exclude one another from their respective discourse of the Egyptian nation. While reflecting back on a number of women’s voices who joined the early days of the Tahrir Square protests and using qualitative fieldwork interviews with Cairo-based feminist and political activists, this article points to the complexity of a newly forged image of Egyptian nationhood. In Tahrir Square, this image appeared to be largely framed within gendered criteria where notions of manhood and hyper visible gender equality were intrinsically linked to the broader objective of removing Mubarak and his regime. This raises the question of whether new gender paradigms of equality can continue to exist beyond Tahrir Square’s imagination of a ‘new’ nation