Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Protection Scheme Based on Hybrid Pick-Up and Optimal Hierarchy Selection of Relays in the Variable DGs-Distribution System

The increasing proliferation of distributed generators (DGs) demands a robust and comprehensive design of the communication-based adaptive protection scheme, which must be able to not only deal with the known changes in the DGs-distribution system but also handle the unknown changes due to variations in the operating mode, network configuration, and number, type, and size of DGs. On one side, with the increasing installations of DGs, the deployment of the communication system in protection is increasing to monitor the system status and select the relays’ settings accordingly. However, on the other side, if information flow does not happen due to the presence of pre-fault failure of the relay-agents and/or communication links, a protection scheme may fail to provide the suitable protection. This paper proposes a centralized adaptive protection scheme to deal with such failures and varying operating conditions. It provides optimal relays settings for varying operating conditions of the DGs-distribution system with the aim of providing fast, comprehensive, and self-adaptive protection. In order to achieve these objectives, two algorithms have been developed: the first algorithm determines optimal hybrid pick-up settings of the relays, and the second algorithm determines the adaptive hierarchies of the relays. With the inclusion of these two algorithms, the relay coordination problem has been formalized linearly. The performance of the proposed scheme has been tested and validated for various known and unknown events with different types of short circuit faults of different fault impedances on the 37-bus IEEE test distribution system in a MATLAB simulation and coding environment. The results show that the proposed method not only provides the optimal relay's coordination in varying situations but also effectively reduces the protection latency due to pre-fault failures of the relays and communication links, and low level of fault currents.
Parallel Computing and Optimization with COMSOL Multiphysics

—In this thesis the parallel capabilities of COMSOL Multiphysics are investigated. A description for how one can run COMSOL on a Linux cluster is presented. The speedup was found to be poor for medium-sized simulations with less than 10 million degrees of freedom. The speedup for parametric sweeps were found to be excellent. Particle swarm optimization (PSO) was implemented using LiveLink for Matlab
Engineering Identity across the Mechanical Engineering Major

The Mechanical Engineering Department at Seattle University was awarded a National Science Foundation RED (Revolutionizing Engineering and Computer Science Departments) grant in 2017 to study how student identities are affected when a department makes “revolutionizing” changes. These can result in graduates who not only are prepared technically and professionally with a practical, realistic understanding of what it is to be an engineer, but also who identify with and are committed to the engineering profession. The expectation is that immersion in this program will affect students’ identities as they move through the program. This paper focuses on implicit identity data collected via implicit association tests (IATs) during the first year of the five-year grant. It shows that although engineering students in the current program implicitly identify with engineering, both men and women consider engineering to be a male field. These data serve as a baseline for the ongoing identity research supported by the grant and point to the need for programmatic changes that help females and non-Whites develop stronger identities with engineering.
Impact of High Renewable Penetration on the Power System Operation Mode: A Data-Driven Approach

The high penetration of renewable energy will substantially change the power system operation. Traditionally, the annual operation of a power system can be represented by some typical operation modes and acts as the basis for the power-system-related analysis. The introduction of highly penetrated renewable energy will make the power system operation mode highly diversified and variable. These modes may not follow traditional empirical patterns. In this paper, we propose a data-driven method based on high-dimensional power system operation data (including power flow, unit generation, and load demand) to identify the pattern of the operation modes and analyze the impact of high renewable penetration. Specifically, the proposed data-driven method is composed of simulation, preprocessing, clustering, dimension reduction, and visualization with the aim to provide an intuitive understanding of the operation mode variety under high renewable penetration. In addition, several indices are introduced to quantify the space dispersion, time variation, and seasonal consistency of operation modes. A case study on actual Qinghai provincial power system in China validates the effectiveness of the proposed data-driven method and indicates that the dispersion and time variation of operation mode will significantly increase in the beginning and then saturate with the increase in renewable penetration level. The operation mode is also less correlated with seasons in renewable energy dominated power system.
The phonesthetics of blends: A lexicographic study of cognitive blends in the OED

Abstract This preliminary study of 285 morphological and cognitive blends (attestation dates 1200-2012) aims to investigate the role of phonesthemes in the structuring of the English lexicon. A study of OED word origins shows a disparity between older (1200-1900) and recent blends (1903-2012). Sound symbolism plays an overriding role in over 50% of older blends, leading to a study of initial phonesthemes (i.e. consonant clusters). Several case studies of diachronic semantic shift attested in the OED point to the existence of multidirectional motivation ties. This preliminary study supports the psycholinguistic theory that 1) there is a structured secondary sound symbolism in English, and that 2) it is still productive today and may play a role in the creation of neologisms as well as ensuring their survival (see Bergen, 2010: 52). A more in-depth usage-based analysis using sophisticated measurement tools is the next step in the study.
Freeze–Thaw Pre-Treatment of Cassava Tubers to Improve Efficiency of Mechanical Peeling

The effect of a freeze–thaw pre-treatment (FTP) on the peeling process of cassava tubers was investigated in this study. The length and weight of the cassava tubers varied from 200 to 280 mm and 500 to 900 g, respectively. A prototype abrasive cassava peeling machine was used. The operational parameters were the rotational speed of the brushes (550–1150 rpm), peeling time (1–5 min), thawing temperature (50–90 °C), and incubation time of the thawing treatment (0–120 s). Response surface methodology was applied to optimize FTP to improve the peeling process of cassava tubers. Peeled surface area and peel loss were measured as the responses. Results revealed that the peeled surface area and peel loss were significantly influenced by the rotational speed of the brushes, peeling time, and the incubation time of the thawing treatment (p < 0.05). Under optimal peeling conditions, with a rotational speed of 1000 rpm, a peeling time of 3.4 min, a thawing temperature of 59 °C, and an incubation time of 90 s, the peeled surface and the peel loss were approximately 99.5 and 19%, respectively. The results show that the use of FTP can improve cassava peeling by softening the peels and increasing the peeled surface area.
Perfectionists do not like to share knowledge? Investigating the relationship between perfectionism and knowledge sharing and testing the moderation effect of coaching

ABSTRACT The purpose of this study was to examine the relationship between perfectionism and knowledge sharing by using a structural equation modelling analysis, and the perception of coaching style was tested as a moderator. The results revealed that high personal standards and concern over mistakes, which are aspects of perfectionism, significantly relate to knowledge-sharing attitude and intention. Furthermore, managers’ coaching styles affect the relationship between perfectionism and knowledge sharing. For employees who fear making mistakes, a high level of managerial coaching can promote knowledge-sharing intention and attitude among employees. However, for perfectionistic employees who set high standards for self-performance, a high level of managerial coaching diminishes their knowledge-sharing intention. Researchers have suggested that different coaching styles are preferred according to employees’ personalities. The results of this study offer insights for implementing appropriate management interventions and provide directions for human resource managers, employees, and related professionals to promote knowledge sharing in organisations.
The Self-Degradation Mechanism of Polyvinyl Chloride-Modified Slag/Fly Ash Binder for Geothermal Wells

Polyvinyl chloride (PVC) releases hydrochloric acid (HCl) during its thermal degradation, and hydrochloric acid can react with hydration products of alkali-activated binders. According to this characteristic of PVC and the temperature change that occurs during the development of a geothermal well, the PVC was added into slag/fly ash binder to develop self-degradable materials. The thermal degradation properties of PVC, compressive strength, hydration products, and microstructure of binders at different stages were tested, in order to study the degradation mechanism of the material. It was found that 20% PVC reduced the compressive strength, decreasing the level of binder from 13.95% to 76.63%. The mechanism of PVC promoting the material degradation mainly includes the following: (1) the thermal degradation of PVC increases the number of multiple damage pores in the material, at a high temperature; (2) HCl generated by the PVC thermal degradation reacts with the binder gels, and breaks them into particles; and (3) HCl also reacts with other substances in the binder, including CaCO3 and NaOH in the pore solution.
Analytical Derivation of Seismic Fragility Curves for Historical Masonry Structures Based on Stochastic Analysis of Uncertain Material Parameters

ABSTRACT This work presents a probabilistic method to assess the seismic vulnerability of historical masonry structures, such as churches or cathedrals, including uncertainty analysis of the material parameters. The proposed approach considers the pushover analysis using the finite element method for the structural evaluation of the seismic behaviour of masonry structures. A stochastic analysis based on Monte Carlo simulation investigates the effect of the uncertainty of the structural members’ mechanical parameters on the evaluation of the seismic fragility. The method is applied to the seismic assessment of the bay structure of Santa Maria del Mar church in Barcelona, Spain. This case study is characterised by complex geometry and material heterogeneity, and shows to be sensitive enough to the uncertainty of the material properties to experience two possible collapse mechanisms in case of an earthquake. The study presents how to derive analytical seismic fragility curves by considering the uncertainties regarding the material properties and the different types of collapse mechanism.
Electric Vehicle Charging Management Using Auction Mechanism for Reducing PV Curtailment in Distribution Systems

This paper proposes an electric vehicle (EV) charging management scheme for effective utilization of photovoltaic (PV) power based on an auction mechanism. The proposed scheme coordinates an amount of self-consumption of PV output by shifting the charging period of customers’ EVs, and it reduces PV curtailment caused by voltage rise in low-voltage distribution systems (LVDSs). The auction mechanism is introduced in order to assure both the equity of benefit in each customer and the autonomy that enables customers to voluntarily participate in the EV charging management scheme. The authors perform numerical simulations based on a Japanese distribution system model and evaluate the effectiveness of the proposed scheme. The results show that our proposed scheme reduces the residential operation cost and the PV curtailment in LVDSs without an enhanced communication network even taking into consideration the effects of forecasting errors of electricity demand and PV output, and unexpected disconnection condition of several EVs.
Therapeutic gloves for arthritis: development of a design framework

ABSTRACT Therapeutic gloves are an intervention widely recommended and prescribed by rheumatologists and occupational therapists for the management and treatment of hand arthritis. Different models of therapeutic gloves are commercially available, with varying design, construction and materials. However, a systematic classification for therapeutic gloves and their effectiveness has not been well established. In addition, little research has addressed the issue of material choice on glove performance. These knowledge gaps prompted the development of a framework for the design and engineering of functional and comfortable therapeutic gloves. Knowledge from multiple domains was integrated into a single framework and relationships between components were identified and characterised. The framework demonstrates that the design and engineering of therapeutic gloves requires fusion of functional design with comfort design to meet users’ demand for wearing comfort, relief of arthritic symptoms and improvement of hand function.
Modeling the Luminance Degradation of OLEDs Using Design of Experiments

Modeling the lifespan of an organic light-emitting diode (OLED) is a complex task as it depends on different potentially interacting factors. As the literature on this subject is still scant, new parametric models for calculating the lifespan of the OLED are proposed in this article. The design of experiment (DoE) methodology is used for cost and accuracy reasons. Different lifespan models based on thermal and electrical experimental aging tests are proposed. As stress factors, current density, temperature, and their interactions, which are rarely taken into account in aging studies, are simultaneously involved. The analysis of the model parameters highlights the prevalence of temperature compared to current density on the luminance performance of OLEDs. Nonlinear models appear as the most accurate.
Secrecy Performance Analysis of Cooperative MISO NOMA Networks Over Nakagami-m Fading

In this paper, we consider the physical layer security of a downlink cooperative multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) network over Nakagami-m fading. The network consists of a multi-antenna source, multiple decode-and-forward (DF) relays, and two users with different priority, in the presence of a passive eavesdropper. Specifically, we investigate the secure transmission from the source to the users via the help of the relays, in which the signals of the users might or might not be successfully decoded at the relays. Thus, we aim to design secure communication protocols for the considered system, where transmit antenna selection (TAS), maximal ratio transmission (MRT), and relay selection are employed based on the source-to-relays channel conditions. To characterize the secrecy performance, analytical and asymptotic expressions for the secrecy outage probability (SOP) of the overall system are derived. Our analytical results validated by Monte-Carlo simulations show that the secrecy performance of cooperative NOMA networks can be improved by increasing the number of antennas at the source and the number of relays. Comparing TAS and MRT, we conclude that TAS has lower complexity but can achieve the secrecy performane comparable with MRT. Finally, the results also indicate that our proposed protocol bring more general and practical insights with similar secrecy performance compared with the conventional solution.
KaRMMa 2.0 -- Kappa Reconstruction for Mass Mapping

We present KaRMMa 2.0 , an updated version of the mass map reconstruction code introduced in Fiedorowicz et al. (2022). KaRMMa is a full-sky Bayesian algorithm for reconstructing weak lensing mass maps from shear data. It forward-models the convergence ﬁeld as a realization of a lognormal ﬁeld. The corresponding shear map is calculated using the standard Kaiser– Squires transformation, and compared to observations at the ﬁeld level. The posterior distribution of maps given the shear data is sampled using Hamiltonian Monte Carlo chains. Our work improves on the original algorithm by making it numerically eﬃcient, enabling full-sky reconstructions at ≈ 7 arcmin resolution with modest computational resources. These gains are made with no loss in accuracy or precision relative to KaRMMa 1.0 . We compare the KaRMMa 2.0 posteriors against simulations across a variety of summary statistics (one-point function, two-point functions, and peak/void counts) to demonstrate our updated algorithm provides an accurate reconstruction of the convergence ﬁeld at mildly non-linear scales. Unsurprisingly, the lognormal model fails as we approach non-linear scales ( ℓ (cid:38) 200), which in turn biases the map posteriors. These biases are at the 2% level in the recovered power spectrum, and at the 5% to 15% level for other statistics, depending on the resolution.
Condition Monitoring of Electrolytic Capacitors in Boost Converters by Magnetic Sensors

The aluminum electrolytic capacitors (AEC) are important in filtering and energy storage applications since they are of high energy density and low cost. However, the AECs suffer from low reliability and limited lifetime due to the electrolyte vaporization. The degradation of AECs challenges the reliability and efficiency of the power electronic systems. Therefore, it is essential to monitor the condition of AECs for system reliability and efficiency. In this paper, a real-time condition monitoring technique for input and output AECs based on the estimation of equivalent series resistance (ESR) was developed for the boost converter. The ESRs were estimated by using the capacitor and inductor current obtained through the magnetic-field sensing by magnetic sensors. The influences of the load, duty cycle, inductance, ESR, and capacitance on the ESR estimation were investigated to develop the proposed methodology. The proposed methodology can largely improve the accuracy of the estimated ESR of output AEC in the boost converter. The higher accuracy enables predictive maintenance of AECs and contributes to the reliability and efficiency of power electronic systems. The simulation and experimental results from −25 °C to 100 °C verified that the proposed methodology could be used to estimate the ESR of input and output AECs accurately. The experimental results showed that the compact tunnel magnetoresistance (TMR) sensors were capable of measuring the capacitor and inductor current for the estimation of ESR. This technique is cost-effective and non-invasive since it can be implemented with TMR magnetic sensors and does not require the Hall-effect current transducers with magnetic concentrators of larger volume, higher cost, and limited bandwidth or invasive shunt resistors.
Cockle Shell-Derived Calcium Carbonate (Aragonite) Nanoparticles: A Dynamite to Nanomedicine

Cockle shell is an external covering of small, salt water edible clams (Anadara granosa) that dwells in coastal area. This abundant biomaterial is hard, cheap and readily available with high content of calcium carbonate in aragonite polymorphic form. At present, cockle shell-derived calcium carbonate nanoparticles (CSCaCO3NPs) with dual applications has remarkably drawn significant attention of researchers in nanotechnology as a nanocarrier for delivery of different categories of drugs and as bone scaffold due to its beneficial potentials such as biocompatibility, osteoconductivity, pH sensitivity, slow biodegradation, hydrophilic nature and a wide safety margin. In addition, CSCaCO3NP possesses structural porosity, a large surface area and functional group endings for electrostatic ion bonds with high loading capacity. Thus, it maintains great potential in the drug delivery system and a large number of biomedical utilisations. The pioneering researchers adopted a non-hazardous top-down method for the synthesis of CSCaCO3NP with subsequent improvements that led to the better spherical diameter size obtained recently which is suitable for drug delivery. The method is therefore a simple, low cost and environmentally friendly, which involves little procedural steps without stringent temperature management and expensive hazardous chemicals or any carbonation methods. This paper presents a review on a few different types of nanoparticles with emphasis on the versatile most recent advancements and achievements on the synthesis and developments of CSCaCO3NP aragonite with its applications as a nanocarrier for drug delivery in nanomedicine.
A Search Space Reduction Method for Transmission Expansion Planning Using an Iterative Refinement of the DC Load Flow Model

This paper provides a new methodology to compute a reduced but efficient set of candidate lines in a transmission expansion planning (TEP) context. Considering this reduced set of candidate lines should lead to similar investment decisions as if all the possible ac and dc candidate lines that could be installed in the network were considered. A first “hybrid” relaxed TEP problem is solved. Based on this initial solution, a new relaxed TEP problem is iteratively solved in which the dc load flow (DCLF) model is enforced to a certain extent in the partially expanded ac corridors. Once a convergence threshold has been reached, an upper bound of the number of candidate ac and dc lines to install in each corridor can be defined. This process results in a compact search space. Our algorithm has been implemented in General Algebraic Modeling Software (GAMS) and has been tested on a case study based on the European power system. The method produces very promising results and in the considered case study, leads to a very efficient investment.
Asynchronous Localization of Underwater Target Using Consensus-Based Unscented Kalman Filtering

Most applications of underwater acoustic sensor networks (UASNs) rely on accurate location information of targets. However, the asynchronous clock, stratification effect, and strong-noise characteristics of underwater environment make target localization more challenging as compared with terrestrial sensor networks. This paper focuses on an asynchronous localization issue for underwater targets, subjected to the isogradient sound speed and noise measurements. A network architecture including surface buoys, sensors, and the target is first designed, where the clocks on sensors and the target are not required to be synchronized. To eliminate the effect of asynchronous clocks, we establish the relationship between the propagation delay and the position. Particularly, the ray tracing approach is adopted to model the stratification effect. Then, a localization optimization problem is formulated to minimize the sum of all measurement errors. To solve the localization optimization problem, a consensus-based unscented Kalman filtering (UKF) localization algorithm is proposed, where the convergence conditions and Cramér–Rao lower bounds are also given. Finally, simulation results reveal that the proposed localization approach can reduce the localization time by comparing with the exhaustive search method. Meanwhile, the consensus-based UKF localization algorithm can improve localization accuracy as compared with other works.