The Moderating Role of Competition and Paradoxical Leadership on Perceptions of Fairness towards IoT Monitoring

Recent advances in monitoring systems used in the workspace are stirring a great deal of controversy. Several devices connected to the internet, coined as the Internet of Things (IoT), are now used to capture and analyze huge amounts of information on employee behavior to improve overall performance. Given the implications of the technology on privacy and predictive behavior, there is a dearth of studies that investigate employee perceptions to the unique challenges of “always on” monitoring and the power of analytics. To address this gap, the objective of the paper is answering the research question of how IoT-enabled monitoring influences employee perceptions of fairness. Based on the literature review, the pervasive and continuous nature of IoT-enabled monitoring suggests that, if not effectively managed, the technology will intensify employee perceptions of unfairness and lead to lack of commitment to the organization. We conducted semi-structured interviews with employees at two organizations in Qatar. The research in progress challenges current propositions on electronic monitoring and highlight the emerging role of competition, and paradoxical leadership in moderating the relationship between IoT-enabled monitoring and perceptions of fairness

Selective harmonic elimination in awide modulation range using modified Newton-raphson and pattern generation methods for a multilevel inverter

Considering the aim of having low switching losses, especially in medium-voltage and high-power converters, the pre-programmed pulse width modulation technique is very useful because the generated harmonic content can be known in advance and optimized. Among the different low switching frequency techniques, the Selective Harmonics Elimination (SHE) modulation method is most suitable because of its direct control over the harmonic spectrum. This paper proposes a method for obtaining multiple solutions for selectively eliminating specific harmonics in a wide range of modulation indices by using modified Newton-Raphson (NR) and pattern generation techniques. The different pattern generation and synthesis approach provide more degrees of freedom and a way to operate the converter in a wide range of modulation. The modified Newton-Raphson technique is not complex and ensures fast convergence on a solution. Moreover, multiple solutions are obtained by keeping a very small increase in the modulation index. In the previous methods, solutions were not obtainable at all modulation indices. In this paper, only exact solutions to the low-order harmonics elimination for Cascaded H-bridge inverter are reported for all modulation indices. Analytical and simulation results prove the robustness and correctness of the technique proposed in this paper. 2018 by the authors.Acknowledgments: This (publication, report, etc.) was made possible by NPRP grant # [X-033-2-007] from the Qatar National Research Fund (a member of Qatar Foundation).Scopu

A real-time early warning seismic event detection algorithm using smart geo-spatial bi-axial inclinometer nodes for Industry 4.0 applications

Earthquakes are one of the major natural calamities as well as a prime subject of interest for seismologists, state agencies, and ground motion instrumentation scientists. The real-time data analysis of multi-sensor instrumentation is a valuable knowledge repository for real-time early warning and trustworthy seismic events detection. In this work, an early warning in the first 1 micro-second and seismic wave detection in the first 1.7 milliseconds after event initialization is proposed using a seismic wave event detection algorithm (SWEDA). The SWEDA with nine low-computation-cost operations is being proposed for smart geospatial bi-axial inclinometer nodes (SGBINs) also utilized in structural health monitoring systems. SWEDA detects four types of seismic waves, i.e., primary (P) or compression, secondary (S) or shear, Love (L), and Rayleigh (R) waves using time and frequency domain parameters mapped on a 2D mapping interpretation scheme. The SWEDA proved automated heterogeneous surface adaptability, multi-clustered sensing, ubiquitous monitoring with dynamic Savitzky-Golay filtering and detection using nine optimized sequential and structured event characterization techniques. Furthermore, situation-conscious (context-aware) and automated computation of short-time average over long-time average (STA/LTA) triggering parameters by peak-detection and run-time scaling arrays with manual computation support were achieved. - 2019 by the authors.Funding: This publication was made possible by the NPRP grant # 8-1781-2-725 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

A real-time early warning seismic event detection algorithm using smart geo-spatial bi-axial inclinometer nodes for Industry 4.0 applications

Earthquakes are one of the major natural calamities as well as a prime subject of interest for seismologists, state agencies, and ground motion instrumentation scientists. The real-time data analysis of multi-sensor instrumentation is a valuable knowledge repository for real-time early warning and trustworthy seismic events detection. In this work, an early warning in the first 1 micro-second and seismic wave detection in the first 1.7 milliseconds after event initialization is proposed using a seismic wave event detection algorithm (SWEDA). The SWEDA with nine low-computation-cost operations is being proposed for smart geospatial bi-axial inclinometer nodes (SGBINs) also utilized in structural health monitoring systems. SWEDA detects four types of seismic waves, i.e., primary (P) or compression, secondary (S) or shear, Love (L), and Rayleigh (R) waves using time and frequency domain parameters mapped on a 2D mapping interpretation scheme. The SWEDA proved automated heterogeneous surface adaptability, multi-clustered sensing, ubiquitous monitoring with dynamic Savitzky-Golay filtering and detection using nine optimized sequential and structured event characterization techniques. Furthermore, situation-conscious (context-aware) and automated computation of short-time average over long-time average (STA/LTA) triggering parameters by peak-detection and run-time scaling arrays with manual computation support were achieved. - 2019 by the authors.Funding: This publication was made possible by the NPRP grant # 8-1781-2-725 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Multiple Output Contactless Inductive Power Transfer System For Electric Vehicle Battery Charging Station

The proposed fast-charging system is capable of simultaneously charging the three different duty electric vehicles (small, medium, heavy) at the same time. The size and weight of the proposed system are reduced by operating at a higher switching frequency. The load (battery) dependency and system efficiency are eliminated and improved, respectively, by adopting the series-series compensation network in the proposed system. The CC-CV charging algorithm is adopted to charge the battery and PI controller, and the additional controlling loop is developed to remove the overshoot of the current during the CC to CV transition

Geographical area network-structural health monitoring utility computing model

In view of intensified disasters and fatalities caused by natural phenomena and geographical expansion, there is a pressing need for a more effective environment logging for a better management and urban planning. This paper proposes a novel utility computing model (UCM) for structural health monitoring (SHM) that would enable dynamic planning of monitoring systems in an efficient and cost-effective manner in form of a SHM geo-informatics system. The proposed UCM consists of networked SHM systems that send geometrical SHM variables to SHM-UCM gateways. Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. The inputs of the prediction algorithm are geometrical variables, environmental variables, and payloads. The proposed SHM-UCM is unique in terms of its capability to manage heterogeneous SHM resources. This has been tested in a case study on Qatar University (QU) in Doha Qatar, where it looked at where SHM nodes are distributed along with occupancy density in each building. This information was taken from QU routers and zone calculation models and were then compared to ideal SHM system data. Results show the effectiveness of the proposed model in logging and dynamically planning SHM.This publication was made possible by NPRP grant # 8-1781-2-725 from the Qatar National Research Fund (a member of Qatar Foundation). The publication of this article was funded by the Qatar National Library

Performance Analysis of a Three-to-Five Phase Dual Matrix Converter Based on Space Vector Pulse Width Modulation

In this paper, space vector pulse width modulation (SVPWM)-based algorithms for a five-phase open-end load fed from dual matrix converter (DMC) have been proposed. In the presented modulation methods, the reference output voltage vector is synthesized from two three-to-five phase matrix converters at both the ends of the load. Depending on the power-sharing of the two MCs, two proposed modulation methods are defined as equal reference sharing (ERS) and unequal reference sharing (URS). The performance of ERS and URS for the three-to-five phase DMC drive is compared. Performance comparison is based on the total harmonic distortion in the output voltages and the percentage of the voltage transferred from the source to the load, for the full linear modulation index (MI) range. Common mode voltage and zero sequence current in the load are also discussed. The efficiency of the ERS and URS is compared. It has been observed that the proposed ERS scheme offers better performance compared with URS for most of the MI values. The suggested modulation techniques are implemented in MATLAB/Simulink. The hardware setup is developed and control algorithm is implemented using dSPACE working in conjunction with the FPGA interface board for practical validation

Symmetric and Asymmetric Multilevel Inverter Topologies With Reduced Device Count

In this work, two new topologies of single-phase hybrid multilevel inverters for symmetrical and asymmetrical configurations are presented for use in drives and control of electrical machines and the connection of renewable energy sources. The proposed topology uses 2 dc sources, 12 switches, 1 flying capacitor, and 3 diodes to generate boosted 13-levels and 17-levels for symmetric and asymmetric configuration, respectively. Self-voltage balancing of its capacitor voltage regardless of load type, load dynamics, or modulation index is a key advantage of the suggested design. The higher performance of proposed topologies in terms of the total number of switches, TSV, THD, switch stress, and dc sources are demonstrated by comparing those with recently published topologies. In addition, a widely employed nearest level control modulation approach is used to provide output voltage levels with low THD. Finally, experiments were undertaken to validate the performance of the suggested topology. 2013 IEEE.This work was supported in part by Qatar University Research Grant from Qatar University, Doha, Qatar, under Grant QUCP-CENG-2020-2 and Grant QUCP-CENG-2022-571; and in part by the Qatar National Library, Doha.Scopu

Reinforcement learning-based decision support system for COVID-19

Globally, informed decision on the most effective set of restrictions for the containment of COVID-19 has been the subject of intense debates. There is a significant need for a structured dynamic framework to model and evaluate different intervention scenarios and how they perform under different national characteristics and constraints. This work proposes a novel optimal decision support framework capable of incorporating different interventions to minimize the impact of widely spread respiratory infectious pandemics, including the recent COVID-19, by taking into account the pandemic's characteristics, the healthcare system parameters, and the socio-economic aspects of the community. The theoretical framework underpinning this work involves the use of a reinforcement learning-based agent to derive constrained optimal policies for tuning a closed-loop control model of the disease transmission dynamics

Design and Sensitivity Analysis of Dynamic Wireless Chargers for Efficient Energy Transfer

Tunable Self-Oscillating Switching (TSOS) methods are a robust solution for tuning of Inductive Power Transfer (IPT) systems. However, they require deep analysis to be an appropriate choice for Dynamic Wireless Charging (DWC) systems. In this paper, the optimal operation point of TSOS in the maximum power transfer, efficiency, and Zero Voltage Switching (ZVS) realization perspectives are determined based on sensitivity analysis for DWC of Electric Vehicles (EVs). In the sensitivity analysis, all the possible states of the coupling factor and state of charge (SOC) are considered as system variables. Moreover, a new phasor modeling for constant voltage (battery) loads is proposed. The performance of this model is quite different from the conventional static model for the loads. Moreover, to limit the current of the charger under light couplings, a simple hysteresis controller is employed. A setpoint is proposed based on the sensitivity analysis method to transfer maximum energy in misaligned conditions. The proposed setpoint increases transferred energy and energy efficiency while limits the current of the charger. To analyze this method, simulation is done in the Simulink/MATLAB, and to verify the results, a laboratory prototype is implemented.This publication was made possible by Qatar University Collaborative Research grant # [QUCG-CENG-19/20-5] from the Qatar University. The statements made herein are solely the responsibility of the authors. The APC is funded by the Qatar National Library, Doha, Qatar.Scopu