Null Steering of Adaptive Beamforming Using Linear Constraint Minimum Variance Assisted by Particle Swarm Optimization, Dynamic Mutated Artificial Immune System, and Gravitational Search Algorithm

Linear constraint minimum variance (LCMV) is one of the adaptive beamforming techniques that is commonly applied to cancel interfering signals and steer or produce a strong beam to the desired signal through its computed weight vectors. However, weights computed by LCMV usually are not able to form the radiation beam towards the target user precisely and not good enough to reduce the interference by placing null at the interference sources. It is difficult to improve and optimize the LCMV beamforming technique through conventional empirical approach. To provide a solution to this problem, artificial intelligence (AI) technique is explored in order to enhance the LCMV beamforming ability. In this paper, particle swarm optimization (PSO), dynamic mutated artificial immune system (DM-AIS), and gravitational search algorithm (GSA) are incorporated into the existing LCMV technique in order to improve the weights of LCMV. The simulation result demonstrates that received signal to interference and noise ratio (SINR) of target user can be significantly improved by the integration of PSO, DM-AIS, and GSA in LCMV through the suppression of interference in undesired direction. Furthermore, the proposed GSA can be applied as a more effective technique in LCMV beamforming optimization as compared to the PSO technique. The algorithms were implemented using Matlab program

Mapping the Invisible: A Framework for Tracking COVID-19 Spread Among College Students with Google Location Data

The COVID-19 pandemic and the implementation of social distancing policies have rapidly changed people\u27s visiting patterns, as reflected in mobility data that tracks mobility traffic using location trackers on cell phones. However, the frequency and duration of concurrent occupancy at specific locations govern the transmission rather than the number of customers visiting. Therefore, understanding how people interact in different locations is crucial to target policies, inform contact tracing, and prevention strategies. This study proposes an efficient way to reduce the spread of the virus among on-campus university students by developing a self-developed Google History Location Extractor and Indicator software based on real-world human mobility data. The platform enables policymakers and researchers to explore the possibility of future developments in the epidemic\u27s spread and simulate the outcomes of human mobility and epidemic state under different epidemic control policies. It offers functions for determining potential contacts, assessing individual infection risks, and evaluating the effectiveness of on-campus policies. The proposed multi-functional platform facilitates the screening process by more accurately targeting potential virus carriers and aids in making informed decisions on epidemic control policies, ultimately contributing to preventing and managing future outbreaks

Design, fabrication, and physical properties analysis of laminated Low-E coated glass for retrofit window solutions

The ever-growing demand for improved energy efficiency in buildings has stimulated a stream of research focused on innovative retrofit energy solutions. Laminated low emissivity (Low-E) type coated glass components can be used in retrofitting window systems for enhancing energy savings provided by the insulating properties of glass laminates containing these heat-mirror-type coatings. In particular, custom-designed double-silver low-E coatings embedded into the laminate structure (directly facing the polymer interlayers during and after the lamination) are of interest due to being protected from environmental exposure, enabling easy component transportation, storage, and window retrofits. In this study, we provide some details on the design of several reflector-type solar control low-E coatings of high environmental stability and demonstrate the feasibility of their fabrication on 3 mm thick glass substrates, followed by the lamination. We describe the optical properties of laminated structural glass components of potential usefulness for retrofitting window applications in new and existing buildings. Several thin-film coatings of a low-E type are deposited by using the RF magnetron sputtering technique and then subjected to lamination by using transparent epoxy and PVB materials, to be protected by a clear glass cover layer. The optical performance characteristics of these coatings (measured before and after lamination) elucidate the effects these lamination materials and cover glass thickness have on the final optical properties (leading to a slight reduction in the optical transmission in the visible spectral range, by around 8–10 % while retaining low thermal emissivity across the infrared spectral range). The outcomes of this research, if industrialized could contribute significantly to the development of sustainable building components and practices, and to acheiving a reduction in building energy consumption by way of enabling window retrofit operations at potentially reduced costs

Salsa20 based lightweight security scheme for smart meter communication in smart grid

The traditional power gird is altering dramatically to a smart power grid with the escalating development of information and communication technology (ICT). Among thousands of electronic devices connected to the grid through communication network, smart meter (SM) is the core networking device. The consolidation of ICT to the electronic devices centered on SM open loophole for the adversaries to launch cyber-attack. Therefore, for protecting the network from the adversaries it is required to design lightweight security mechanism for SM, as conventional cryptography schemes poses extensive computational cost, processing delay and overhead which is not suitable to be used in SM. In this paper, we have proposed a security mechanism consolidating elliptic curve cryptography (ECC) and Salsa20 stream cipher algorithm to ensure security of the network as well as addressing the problem of energy efficiency and lightweight security solution. We have numerically analyzed the performance of our proposed scheme in case of energy efficiency and processing time which reveals that the suggested mechanism is suitable to be used in SM as it consumes less power and requires less processing time to encrypt or decrypt

Support Vector Machines Study on English Isolated-Word-Error Classification and Regression

Abstract: A better understanding on word classification and regression could lead to a better detection and correction technique. We used different features or attributes to represent a machine-printed English word and support vector machines is used to evaluate those features into two class types of word: correct and wrong word. Our proposed support vectors model classified the words by using fewer words during the training process because those training words are to be considered as personalized words. Those wrong words could be replaced by correct words predicted by the regression process. Our results are very encouraging when compared with neural networks, Hamming distance or minimum edit distance technique; with further improvement in sight

Towards Wearable Augmented Reality in Healthcare: A Comparative Survey and Analysis of Head-Mounted Displays

Head-mounted displays (HMDs) have the potential to greatly impact the surgical field by maintaining sterile conditions in healthcare environments. Google Glass (GG) and Microsoft HoloLens (MH) are examples of optical HMDs. In this comparative survey related to wearable augmented reality (AR) technology in the medical field, we examine the current developments in wearable AR technology, as well as the medical aspects, with a specific emphasis on smart glasses and HoloLens. The authors searched recent articles (between 2017 and 2022) in the PubMed, Web of Science, Scopus, and ScienceDirect databases and a total of 37 relevant studies were considered for this analysis. The selected studies were divided into two main groups; 15 of the studies (around 41%) focused on smart glasses (e.g., Google Glass) and 22 (59%) focused on Microsoft HoloLens. Google Glass was used in various surgical specialities and preoperative settings, namely dermatology visits and nursing skill training. Moreover, Microsoft HoloLens was used in telepresence applications and holographic navigation of shoulder and gait impairment rehabilitation, among others. However, some limitations were associated with their use, such as low battery life, limited memory size, and possible ocular pain. Promising results were obtained by different studies regarding the feasibility, usability, and acceptability of using both Google Glass and Microsoft HoloLens in patient-centric settings as well as medical education and training. Further work and development of rigorous research designs are required to evaluate the efficacy and cost-effectiveness of wearable AR devices in the future

Path optimization using genetic algorithm in laser scanning system

Laser marking is superior in quality and flexibility to conventional marking techniques such as ink stamping marking. The beam deflected scanning has been commonly applied in the industries. In this paper, the genetic algorithm (GA) has been proposed to optimize the scanning sequence, thus shortening the required laser scanning path. The GA would base on the real-number representation, namely Real-Coded Genetic Algorithm (RCGA). It employs the Dynamic Variable Length Two Point Crossover (DVL-2PC). The simulation results indicating that the proposed algorithm has good convergent speed and manage to solve the sequencing problem efficiently

An Innovative Approach for Environmental Monitoring by Solar Powered Kite

This study investigates the design of a solar powered kite equipped with sensors for any environmental data monitoring, such as, temperature, pressure and so on towards the elevated environment. The developed prototype transforms a traditional kite with a unique design approach that involves the upward height measurement, energy harvesting by solar cells as well as data transmission via wireless network. However, the results from initial monitoring shows only the vertical mapping of ambient temperature as the test case. The developed system can successfully sense and display the temperature data from various height within a certain range as found in the initial investigation. Therefore, upon monitoring various environmental parameters at any cases or during emergency situations using the solar-kite as the simple tool, decision can be made to take appropriate measures against any detrimental changes of the environment by other means