This study aims at shedding light on the linguistic significance of collocation networks in the academic writing context. Following Firth’s principle “You shall know a word by the company it keeps.” The study intends to examine three selected nodes (i.e. research, study, and paper) shared collocations in an academic context. This is achieved by using the corpus linguistic tool; GraphColl in #LancsBox software version 5 which was announced in June 2020 in analyzing selected nodes. The study focuses on academic writing of two corpora which were designed and collected especially to serve the purpose of the study. The corpora consist of a collection of abstracts extracted from two different academic journals that publish for writ

Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can.Therefore,we utilized two objective

Underwater Wireless Sensor Networks (UWSNs) play a vital role in ocean monitoring and exploration. However, harsh underwater conditions and frequent topology changes caused by node and sink mobility pose significant challenges for reliable routing. Conventional routing protocols that depend on global route reconstruction and static paths generate excessive control overhead and degrade performance in large-scale underwater environments. In this paper, we propose an energy-efficient virtual cell-based mobile-sink adaptive routing (VC-MAR) protocol for UWSNs. The sensing field is logically partitioned into a three-dimensional grid of virtual cells, where a cell-gateway is elected in each cell to construct a low-overhead routing backbon

The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant m

In this work, a simple and new method is proposed to simultaneously improve the physical layer security and the transmission performance of the optical orthogonal frequency division multiplexing system, by combining orthogonal frequency division multiplexing technique with chaotic theory principles. In the system, a 2-D chaotic map is employed. The introduced system replaces complex operations such as matrix multiplication with simple operations such as multiplexing and inverting. The system performance in terms of bit error rate (BER) and peak to average ratio (PAPR) is enhanced. The system is simulated using Optisystem15 with a MATLAB2016 and for different constellations. The simulation results showed that the  BE

Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo