Miracle-dz/UniFAR-FTUs huggingface dataset:
Why Study Risk Perception

Studies of risk perception examine the opinions people express when they are asked, in various ways, to characterize and evaluate hazardous activities and technologies. This research aims to aid risk analysis and societal decision making by (i) improving methods for eliciting opinions about risk, (ii) providing a basis for understanding and anticipating public responses to hazards, and (iii) improving the communication of risk information among laypeople, technical experts, and policy makers.
Residential demand management and distribution grid impact assessment

Demand Response in the residential sector has the potential to help future energy systems to balance variable power generation with electric demand. Harnessing its flexibility is however a challenge. We study in this article a day-ahead planning optimization and a stochastic appliance scheduling procedure that could serve different objectives. The aim of the study is twofold. In a first step, we develop a bottom-up consumption model and a flexibility model in which users set preferences on the flexibility that each load is capable to deliver. The model both accounts for the active and reactive part of the power exchanged with the grid. In a second step, the impact of control decisions on the distribution grid is assessed. It is shown that voltage imbalance factor is likely to exhibit larger extreme values when demand response is used to fulfill external objective, especially in feeders where clients are single phase connected.
60 GHz beamforming using in-package bondwire antenna array

An antenna array using in-package bondwire to perform beamforming for 60 GHz applications is presented. 1 mil gold bondwire designed to resonate at 60 GHz was employed as an antenna array to provide smaller area and a cheaper way to manufacture it. The overall size of the bondwire antenna array on a CMOS chip is 1×3 mm2 and its radiation pattern shows fair agreement with simulation results.
Hybrid power for wireless sensors

Wireless sensors provide solutions to otherwise intractable problems in homeland defense and security, building automation, industrial process monitoring and control, structural health monitoring in bridges, aircraft, buildings and ships and a host of applications where the cost or feasibility of deploying wired sensors is impractical. The biggest challenge facing wireless sensors is power. While advances in power management and battery technology may enable 3 to 5 year battery life, in many applications even this is not sufficient. Energy harvesting techniques show potential to provide long lasting power, but suffer from low power density values, meaning that they must be oversized to deliver power for short duty cycle communications functions. In this paper we demonstrate a solution that draws on the benefits of energy harvesting for long life, and microbatteries and microsupercapacitors to provide back-up and pulse power capabilities without the need for refueling or recharging.
CONTINUOUS WAVEFORM ANALYSIS OF FORCE, VELOCITY, AND POWER ADAPTATIONS TO A PERIODIZED PLYOMETRIC TRAINING PROGRAM

This study assessed kinetic and temporal profile adaptations to the countermovement jump in response to a six week periodized plyometric training program. Twenty recreationally active women participated in the study (10 training, 10 control). Testing consisted of 3 maximal countermovement jumps on a force platform prior to and after six weeks of training. Key phases of the jumps were examined to assess differences in the profiles pre- and post-training using Analysis of Characterizing Phases. Periodized plyometric training significantly altered the profiles for force, velocity, and power (p < 0.05). A combination of greater eccentric velocity and power followed by increased concentric power enhanced the stretch shortening cycle and all three variables just before takeoff likely enhancing jump height.
Applicability and interpretability of logical analysis of data in condition based maintenance

his thesis studies the applicability and adaptability of a data mining artificial intelligence approach called Logical Analysis of Data (LAD) to diagnostic applications in Condition Based Maintenance (CBM). Most of the technologies used so far for decision support in CBM tend to automate the diagnostic process without offering any added knowledge that could be helpful to the maintenance operation and maintenance personnel. LAD possesses two key advantages over other decision making technologies used in CBM: (1) it is a non-statistical approach; as such no statistical assumptions are required for the input data, and (2) it generates interpretable patterns that could help solve maintenance problems. A study on the implementation of LAD in CBM is presented in this research whose objective are to study the applicability of LAD in different CBM situations requiring special considerations regarding the types of input data and maintenance decisions, adapt the LAD methodology to the particular requirements that arise from these applications, and improve the LAD methodology in line with the above two objectives in order to increase diagnosis accuracy and result interpretability. The novelty of the research presented in this thesis is (1) the application of LAD to CBM for the first time in applications that stand to benefit from the advantages that this technology provides; and (2) the innovative modifications to LAD methodology, particularly in the area of pattern generation, in order to improve its performance within the context of CBM. The research conducted in this thesis followed an evolutionary approach in order to achieve the objectives stated in the Introduction. The research applied LAD in three applications: (1) the detection of Rogue components within the spare part inventory of reparable components in a commercial airline company, (2) the detection and identification of faults in power transformers using DGA, and (3) the detection of faults in rotor bearings using vibration signals. This research concludes that LAD is a promising decision making approach that adds important benefits to the implementation of CBM in the industry.
Incorporating the e-HIM[R] Virtual Lab into the Health Information Administration Professional Practice Experience

This article will highlight the experiences of two baccalaureate Health Information Administration (HIA) programs in the adoption of the American Health Information Management Association’s (AHIMA) e-HIM Virtual Laboratory (Virtual Lab) into the Professional Practice Experience (PPE). Information describing the implementation of the Virtual Lab, issues encountered, and subsequent feedback from students and faculty regarding this new technology is provided.
DIMENSIONS OF ORGANIZATIONAL CULTURE AS PREDICTOR WORK UNITS PERFORMANCE

Hospital are always faced with attemps to manage human resources. Human resources were critical success of organizatation. The culture in an organization could be seen from the resulted performance.The study aimed to identify the dimensions of organizational culture on work unit. Result of dimensions obtained by each units would be connected with their respective performances. Assessment of work unit performance was done by compairing the result of the work with the Minimum Service Standards in Hospital. The study was conductedusing cross sectional study design with a quantitative approach. By using a questionnaire as instrument, addressed towards 22 units of work. Dimensions of organizational culture that was dominant in 15 work units in H.M Mawardi Islamic Hospital was long term oriented. For the performance of work units, 63.5% had a good performance and the remaining 36,5% had poor performance. Test of relationship between the dimensions of organizational culture with the performance of work units was done using corelational contingency statistical test. The result of test of relationship was (R=0.186). The conclusion that can be drawn was, indicators of Minimum Service Standards in Hospital were still insufficient to assess the performance of each unit with follow guidelinesof Kepmenkes 129 in 2008.
An efficient compensator for the voltage related power quality problems in distribution systems

This paper presents a robust control algorithm for voltage disturbance extraction and mitigation. The proposed mitigating device is the dynamic voltage restorer (DVR). The proposed DVR can compensate the voltage unbalance and mitigate voltage harmonics in the time of normal operation in addition to its basic functions for mitigating different voltage sags. The suggested control algorithm employs the adaptive perceptron to effectively and adaptively track and extract the fundamental, most common voltage harmonics, and voltage unbalance which includes negative and zero sequence voltage drops. Digital simulation results are obtained using PSCAD/EMTDC to prove robustness of the proposed ideas, and to verify the effectiveness of the mitigating device.
The Fault Tolerable Control System Structure of SY-II Remote Operated Vehicle

In order to improve the Remote Operated Vehicle (ROV) into a reliable and maintainable one, this paper has presented a fault tolerance control system structure. Its surface platform includes fault diagnosis and tolerance modules. In fault diagnosis module, a second order sliding mode observer has been built on the basis of its dynamic model, so as to diagnose the thrusters’ conditions through the residue of command quantity. Coresponding with its thrusters’ position, a force allocation model has been established to realize fault tolerable control. Based on duality priciple, the energy-like function concerning ROV control is established. On the basis of the energy-like function, the recurrent strategy has been deduced for thrust allocation when some of thrusters are found failure. Simulations and experiments have been made to verify and analyse the control system structure. They have proved the SY-II control architecture is a reliable control system, it can detect the thruster fault precisely, realize fault tolerable control.
Influence of Different Series Dynamic Resistors on Low-voltage Ride-through of Brushless Doubly Fed Induction Generator

Abstract—The brushless doubly fed induction generator has been proposed for use in wind turbines as a more reliable alternative to the more commonly used doubly fed induction generator. To realize the commercial promises of the brushless doubly fed induction generator in this role, it must meet the existing grid connection codes, particularly with respect to low-voltage ride-through. In this article, the application of series dynamic resistors is proposed to enhance brushless doubly fed induction generator low-voltage ride-through capability, and the required analysis is provided. Three locations for series dynamic resistors are suggested in the brushless doubly fed induction generator circuit and are compared to each other from various points of view, e.g., their impact on current peaks and reactive power generation. Furthermore, modal analysis is performed to check the impact of series dynamic resistors on the damping of power winding and control winding dynamics. The validity of the analysis and the effectiveness of the proposed approach are confirmed via time-domain simulations.
Effect of antenna aperture, EUT and stirrer step size on measurements in mode-stirred reverberation chambers

Analysis and results are presented that quantify the effect of the nonzero size of the EUT, antenna aperture or stirrer step on the measured vs. the actual physical field inside and performance of a reverberation chamber. The effect of local averaging on the variance function, normalized spectral bandwidth, upward threshold crossing frequency and mean excursion length of the reverberation process is calculated, both for local spatial averaging and local stir averaging. Experimental results are shown that demonstrate the effect of aperture size on the measured coefficient of variation, spectral bandwidth and field anisotropy coefficients.
A comprehensive failure model for crashworthiness simulation of aluminium extrusions

Abstract A correct representation of the plastic deformation and failure of individual component parts is essential to obtaining accurate crashworthiness simulation results. The aim of this paper is to present a comprehensive approach for predicting failure in a component based on macroscopic strains and stresses. This approach requires the use of a number of different failure mechanism representations, such as necking (due to local instabilities), as well as ductile and shear fracture. All failure criteria have been developed in a way to include the influence of non-linear strain paths. The effectiveness of this approach in predicting failure is then discussed by comparing numerical results with test data by three point bending and axial compression tests of double chamber extrusion components. All studies presented in this paper were carried out on extrusions made from aluminium alloy EN AW-7108 T6.
Analysis of the influence of 3D coordination on the perception of horizontal curvature using driving simulator

The presented research used a driving simulator to study the effect of isolated vertical crest curves overlapped with horizontal curves on driver's perception and behavior. The curves were consistent with the existing design standards. The research was conducted in four phases: (1) Design a test road with road design software; (2) Convert the designed road to a scenario in the driving simulator; (3) Execute simulation experiments with 48 subjects; and (4) Analyze statistically the obtained simulation results. The participated in the experiments subjects were surveyed to assess their perception of the curve sharpness and the available sight distances. The survey results indicate that the driver's perception of curves depends on the algebraic difference of grades. On the other hand, the operating speeds on different curves were not statistically different from each other. In the matter of fact, the difference between the lowest and highest operating speeds on curves was only 10 km/h. Surprisingly, the operating speeds on a flat curve tended to be lower than on the curves superimposed on vertical crest curves. The likely causes of these results are discussed in the paper. Keywords - coordination, driving simulator, horizontal curvature perception, sight distance, driver behavior, three-dimensional analysis Language: en
Effects of different PTSD modeling methods on fear and depressive behavior in rats: a protocol for systematic review and network meta analysis

Background: Posttraumatic stress disorder (PTSD) is a debilitating mental disorder that occurs after exposure to traumatic events. This disorder can result in a interference to personal and family functioning, causing great threat to people's life and public health. Animal models remain the effective tools to the pathophysiological study of PTSD, There are many model paradigms of PTSD, and the purpose of this study is to evaluate the effect of different model paradigms of PTSD on depression-like and fear-like behavior using systematic review and network meta-analysis (NMA). Methods: The authors will retrieve a total of seven electronic databases by April 2020. After a series of screening, the two researchers will use Aggregate Data Drug Information System (ADDIS) and Stata software to analyze the data extracted from randomized controlled animal studies in PTSD rats . Ultimately, the evidence grade of the results will be evaluated.Discussion: The results of this study will provide references for evaluating the influence of different rats models of PTSD on depression-like and fear-like behavior, and provide decision-making references for clinical practice. Systematic review registration: PROSPERO CRD42020182389.
Energy harvesting-aware design for wireless nanonetworks

ENERGY HARVESTING-AWARE DESIGN FOR WIRELESS NANONETWORKS Shahram Mohrehkesh Old Dominion University, 2015 Director: Dr. Michele C. Weigle Nanotechnology advancement promises to enable a new era of computing and communication devices by shifting micro scale chip design to nano scale chip design. Nanonetworks are envisioned as artifacts of nanotechnology in the domain of networking and communication. These networks will consist of nodes of nanometer to micrometer in size, with a communication range up to 1 meter. These nodes could be used in various biomedical, industrial, and environmental monitoring applications, where a nanoscale level of sensing, monitoring, control and communication is required. The special characteristics of nanonetworks require the revisiting of network design. More specifically, nanoscale limitations, new paradigms of THz communication, and power supply via energy harvesting are the main issues that are not included in traditional network design methods. In this regard, this dissertation investigates and develops some solutions in the realization of nanonetworks. Particularly, the following major solutions are investigated. (I) The energy harvesting and energy consumption processes are modeled and evaluated simultaneously. This model includes the stochastic nature of energy arrival as well as the pulse-based communication model for energy consumption. The model identifies the effect of various parameters in this joint process. (II) Next, an optimization problem is developed to find the best combination of these parameters. Specifically, optimum values for packet size, code weight, and repetition are found in order to minimize the energy consumption while satisfying some application requirements (i.e., delay and reliability). (III) An optimum policy for energy consumption to achieve the maximum utilization of harvested energy is developed. The goal of this scheme is to take advantage of available harvested energy as much as possible while satisfying defined performance metrics. (IV) A communication scheme that tries to maximize the data throughput via a distributed and scalable coordination while avoiding the collision among neighbors is the last problem to be investigated. The goal is to design an energy harvesting-aware and distributed mechanism that could coordinate data transmission among neighbors. (V) Finally, all these solutions are combined together to create a data link layer model for nanonodes. We believe resolving these issues could be the first step towards an energy harvesting-aware network design for wireless nanosensor networks.
Identification of Finite Automata Using Recurrent Neural Networks

This paper demonstrates that the recurrent neural networks can be used successfully for the identification of finite automata (FAs). A new type of recurrent neural network (RNN) is proposed and the offline training algorithm, regulated Levenberg -Marquadt (LM) algorithm, for the network is developed. Simulation result shows that the identification and the extraction of FAs are practically achievable.
A conceptual framework for requirement specification and evaluation of active safety functions

Active safety functions intended to prevent vehicle crashes are becoming increasingly prominent in traffic safety. Successful evaluation of their effects needs to be based on a conceptual framework, i.e. agreed-upon concepts and principles for defining evaluation scenarios, performance metrics and pass/fail criteria. The aim of this paper is to suggest some initial ideas toward such a conceptual framework for active safety function evaluation, based on a central concept termed ‘situational control’. Situational control represents the degree of control jointly exerted by a driver and a vehicle over the development of specific traffic situations. The proposed framework is intended to be applicable to the whole evaluation process, from ‘translation’ of accident data into evaluation scenarios and definition of evaluation hypotheses, to selection of performance metrics and criteria. It is also meant to be generic, i.e. applicable to driving simulator and test track experiments as well as field operational tests.
Principal Component Analysis-Based Image Fusion Routine with Application to Automotive Stamping Split Detection

This study discusses the development and implementation of noncontact split detection method, for automotive stamping press lines. The system features a novel fusion routine that combines thermal and visible images in real-time, assisted with principle component analysis (PCA) subroutine. The thermal detector scans the temperature maps of the highly reflective steel sheets in the die cavity to locate abnormal temperature readings that might be indicative of high local wrinkling pressure, while the visible vision system offsets the blurring effect caused by heat diffusion across the surface and provide a spatial reference. The employed PCA uses a new singular value decomposition (SVD) that is more efficient than standard SVD computations, enabling the PCA to be applied in real-time acquisitions (∼30 Hz). The PCA affects the images by reducing the nonvalue data content (reduce redundancy, noise) while highlighting important features. The fusion is done using a pixel-level algorithm using different variations, where each is assessed for performance. The proposed detection system has been tested on an automotive pressline to assess the formability of complex-shaped panels and have shown high detection success rate. Different splits with variant shape, size, and severity have been detected under actual operating conditions.
A Phenomenological Model for the Hysteresis Behavior of Metal Sheets Subjected to Unloading/Reloading Cycles

The springback phenomenon is defined as elastic recovery of the stresses produced during the forming of a material. An accurate prediction of the springback puts high demands on the material modeling during the forming simulation, as well as during the unloading simulation. In classic plasticity theory, the unloading of a material after plastic deformation is assumed to be linearly elastic with the stiffness equal to Young's modulus. However, several experimental investigations have revealed that this is an incorrect assumption. The unloading and reloading stress-strain curves are in fact not even linear, but slightly curved, and the secant modulus of this nonlinear curve deviates from the initial Young's modulus. More precisely, the secant modulus is degraded with increased plastic straining of the material. The main purpose of the present work has been to formulate a constitutive model that can accurately predict the unloading of a material. The new model is based on the classic elastic-plastic framework, and works together with any yield criterion and hardening evolution law. To determine the parameters of the new model, two different tests have been performed: unloading/reloading tests of uniaxially stretched specimens, and vibrometric tests of prestrained sheet strips. The performance of the model has been evaluated in simulations of the springback of simple U-bends and a drawbead example. Four different steel grades have been studied in the present investigation.
Maximum modulation index of direct torque control with circular flux trajectory

This study considers the maximum modulation index of a direct torque control (DTC)-based converter. The maximum modulation index and maximum output voltage of the circular flux trajectory DTC method are analytically derived, and the result is validated by measurements. It is found out that the maximum modulation index of a DTC converter with a circular flux trajectory is slightly lower than the limit of the overmodulation range 1. The analysis is based on a new method of modelling the DTC output voltage with continuous analytical functions.