A Model for In-Plane Capacity of Multi-Leaf Stone Masonry WallsRead the full article
Journal of Engineering publishes research in several areas of engineering, including chemical engineering, civil engineering, computer engineering, electrical engineering, industrial engineering and mechanical engineering.
Chief Editor, Professor Wang, is the Vice Deputy Dean of the School of Aerospace Engineering at Tsinghua University.
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Exponential Disruptive Technologies and the Required Skills of Industry 4.0
The 21st century has witnessed precipitous changes spanning from the way of life to the technologies that emerged. We have entered a nascent paradigm shift (industry 4.0) where science fictions have become science facts, and technology fusion is the main driver. Thus, ensuring that any advancement in technology reach and benefit all is the ideal opportunity for everyone. In this study, disruptive technologies of industry 4.0 were explored and quantified in terms of the number of their appearances in published literature. The study aimed at identifying industry 4.0 key technologies which have been ill-defined by previous researchers and to enumerate the required skills of industry 4.0. Comprehensive literature survey covering the field of engineering, production, and management was done in multidisciplinary databases: Google Scholar, Science Direct, Scopus, Sage, Taylor & Francis, and Emerald Insight. From the electronic survey, 35 disruptive technologies were quantified and 13 key technologies: Internet of Things, Big Data, 3D printing, Cloud computing, Autonomous robots, Virtual and Augmented reality, Cyber-physical system, Artificial intelligence, Smart sensors, Simulation, Nanotechnology, Drones, and Biotechnology were identified. Both technical and personal skills to be imparted into the human workforce for industry 4.0 were reported. The review identified the need to investigate the capability and the readiness of developing countries in adapting industry 4.0 in terms of the changes in the education systems and industrial manufacturing settings. This study proposes the need to address the integration of industry 4.0 concepts into the current education system.
Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs)
This paper presents the design and development of a fuzzy logic-based multisensor fire detection and a web-based notification system with trained convolutional neural networks for both proximity and wide-area fire detection. Until recently, most consumer-grade fire detection systems relied solely on smoke detectors. These offer limited protection due to the type of fire present and the detection technology at use. To solve this problem, we present a multisensor data fusion with convolutional neural network (CNN) fire detection and notification technology. Convolutional Neural Networks are mainstream methods of deep learning due to their ability to perform feature extraction and classification in the same architecture. The system is designed to enable early detection of fire in residential, commercial, and industrial environments by using multiple fire signatures such as flames, smoke, and heat. The incorporation of the convolutional neural networks enables broader coverage of the area of interest, using visuals from surveillance cameras. With access granted to the web-based system, the fire and rescue crew gets notified in real-time with location information. The efficiency of the fire detection and notification system employed by standard fire detectors and the multisensor remote-based notification approach adopted in this paper showed significant improvements with timely fire detection, alerting, and response time for firefighting. The final experimental and performance evaluation results showed that the accuracy rate of CNN was 94% and that of the fuzzy logic unit is 90%.
Conceptual Framework for the Strategic Management: A Literature Review—Descriptive
The objective of this work is to review the literature of the main concepts that lead to determining the strategic approach, creation of strategies, organizational structures, strategy formulation, and strategic evaluation as a guide for the organizational management, taking into account the effects produced by the different types of strategies on the performance of organizations. In this article, the systemic literature review method was used to synthesize the result of multiple investigations and scientific literature. The process of reading and analysis of the literature was carried out through digital search engines with keywords in areas related to the strategic management. This research reveals the lack of scientific literature containing important theoretical concepts that serve the strategists as a guide in the creation, formulation, and evaluation of strategies. This review contributes to the existing literature by examining the impact of the strategic management on the organizational performance.
Resistance of Recycled Aggregate Concrete (RAC) Subjected to Drying-Wetting Cycles to Attack of Magnesium and Sodium Sulfates
Recycled aggregates were widely used in the concrete industry as a replacement of natural aggregates in the last two decades. In this study, the resistance of concrete mixtures having various levels of recycled aggregate as a replacement of natural coarse aggregate to the attack of magnesium and sodium sulfates was investigated. Five mixtures made with 0%, 25%, 50%, 75%, and 100% recycled aggregate were partially immersed in magnesium and sodium sulfate solutions having concentrations of 2.5%, 4.5%, and 6.5% and subjected to drying-wetting cycles for a total of 10 weeks. Mass losses of concrete specimens owing to the attack of sulfate solutions and the effect of drying-wetting cycles were recorded weekly. Results show that the incorporation of recycled aggregate decreased the compressive strength of concrete at ages of 7 and 28 days. The decline in the compressive strength was more significant when the replacement percentage exceeds 50%. Mass losses of concrete specimens were found to be increased as the level of recycled aggregate increased. Mass losses of concrete specimens having 100% recycled aggregate were approximately as twice as those of concrete specimens having 0% recycled aggregate owing to 10 weeks of partial immersion in magnesium sulfate solutions of concentrations of 2.5%, 4.5%, and 6.5%. The attack of sodium sulfates was less aggressive than that of the magnesium sulfates. Results also show that the reduction in the compressive strength is directly proportional to the mass loss following a linear equation of R-squared value of 0.937.
Simulation Strategies for Mixed Traffic Conditions: A Review of Car-Following Models and Simulation Frameworks
The area of traffic flow modelling and analysis that bridges civil engineering, computer science, and mathematics has gained significant momentum in the urban areas due to increasing vehicular population causing traffic congestion and accidents. Notably, the existence of mixed traffic conditions has been proven to be a significant contributor to road accidents and congestion. The interaction of vehicles takes place in both lateral and longitudinal directions, giving rise to a two-dimensional (2D) traffic behaviour. This behaviour contradicts with the traditional car-following (CF) or one-dimensional (1D) lane-based traffic flow. Existing one-dimensional CF models did the inclusion of lane changing and overtaking behaviour of the mixed traffic stream with specific alterations. However, these parameters cannot describe the continuous lateral manoeuvre of mixed traffic flow. This review focuses on all the significant contributions made by 2D models in evaluating the lateral and longitudinal vehicle behaviour simultaneously. The accommodation of vehicle heterogeneity into the car-following models (homogeneous traffic models) is discussed in detail, along with their shortcomings and research gaps. Also, the review of commercially existing microscopic traffic simulation frameworks built to evaluate real-world traffic scenario are presented. This review identified various vehicle parameters adopted by existing CF models and whether the current 2D traffic models developed from CF models effectively captured the vehicle behaviour in mixed traffic conditions. Findings of this study are outlined at the end.
Cells Electrical Characterization: Dielectric Properties, Mixture, and Modeling Theories
Electrical detection of biotic materials and their properties is always crucial in Biomedical Engineering. It emphasizes elaborate analysis of a certain disease diagnosis using electrical means which includes the study of electrical properties followed by detection, identification, and quantification of biotic entities. Proper and early detection of cells, which can be normal or cancerous, holds never-ending demand. This review emphasizes the electrical characterization methods in modeling and classification of cell properties. Moreover, standard methods have been highlighted and discussed to yield performance analysis. This study suggests that techniques presented for single-cell analysis (SCA) are always precise and hold great scope compared to those for cell mixture. SCA plays a promising role in disease diagnosis and treatment planning, as it not only detects the cells but also helps in identification. Distinct electrical-based cell detection techniques are highlighted, along with the pros and cons of various SCA devices. The content, in terms of methodologies and available techniques, of this review paper is useful to attract researchers working in this area.