Miracle-dz/UniFAR-FTUs huggingface dataset:
Transport of fast electrons during LHCD in TS, JET, and ASDEX

A review of fast electron dynamic studies in the tokamaks TS, JET, and ASDEX during lower hybrid current drive is presented. In almost all experiments, the collisional slowing down is predominant, so a straightforward assessment of the fast electron radial transport is difficult, especially for large size tokamaks. From recent LH power modulation experiments performed on TS at low density, the fast electron diffusion coefficient, Dst, is found between 0.1-0.3m2s-1, close to the value determined on ASDEX in similar plasma conditions. An estimate of Dst is also obtained in TS and JET by modeling the plasma dynamics, using ray-tracing+Fokker-Planck codes. For JET, the fast electron transport is fully taken into account in the Fokker-Planck equation. Despite some quantitative discrepancies between Dst values determined from different methods, the diffusion rate of the fast electrons is weak enough for current profile control scenarii to be relevant on large tokamaks. A determination of the type of the turbulence - electrostatic or magnetic - that could drive the radial transport of fast electrons requires finer LH experiments.
An Efficient Power Control Technique for High-Frequency Resonant Inverter in Induction Heating System

An efficacious and reliable power control technique has been developed which can be used to regulate the output power of a high-frequency full bridge series resonant inverter (HF-FBSRI) in an induction heating (IH) system. In this paper, a modified buck-boost converter is presented to control the DC link/bus voltage which maintains the IH system under resonant mode and optimizes the performance of the IH system. Controlled DC link/bus voltage has been applied to this HF- FBSRI to control the average output power in the IH system. Using this aimed control technique, a wide range of output powers has been controlled and consistent performance of the IH system has been achieved. ZVS switching technique has been used to reduce the switching losses. Varying average power has been obtained at different duty cycles ranging from 0.2 to 0.8 with variable DC link voltage and it has been corroborated using PSIM environment for an IH system rated at 5500W.
Design and implementation of a new architecture of a real‐time reconfigurable digital modulator on FPGA

One of the prerequisites of electronic warfare (EW) is to have the means to provide secure point-to-point wireless data and voice communications with other ground stations. New technologies are giving rise to bigger information security threats. This situation illustrates the best the urgency of reducing the development time of EW systems. Previous works suggest that digital systems are the best candidates for this purpose and therefore form the backbone of modern EW. As a result, digital modulation techniques are widely used in modern wireless communication systems. This is largely due to their high resistance to noise and their high transmission capacity that can be achieved through data multiplexing. In this Letter, a new reconfigurable architecture of a phase shift keying (PSK) modulator is described and implemented on FPGA. The latter can be configured in real time to produce the following modulation schemes: QPSK, 8-PSK, and 16-PSK without having to regenerate the FPGA configuration bits. This action can be done by software via programming or manually using a DIP switch. The proposed design is implemented on the Xilinx xc7k325tfbg900 FPGA using the Genesis 2 development board. The experimental results are in agreement with the simulations.
A smart campus design: data-driven and evidence-based decision support solution design

The growth and the availability of the smart devices is becoming ubiquitous today and inter-networking of these devices make up what is commonly called the Internet of Things (IoT). IoT is being used to update, enhance, simplify and automate individual lives and communities. Most of the cities in general and universities in special are adopting IoT technologies in order to create a smart sustainable living and working environments. Based on the existing literature of smart campus domain, it can be observed that there is only a small number of models as such. This study attempts to bridge the following knowledge gaps of smart campus domain. This project falls into the concept of Smart Campus and aims to design a Smart Campus solution for Staffordshire University. The primarily goal is to design a solution architecture able to collect data from remote sensor networks and analyse them with the support of data analytics and machine learning techniques for sound business decision making. The project has two stages. The first stage is the business side of the project where a business requirement study has been done to extract the exact business requirements and once this complete the second stage was the technical implementation of one or many requirements and evaluation of the solution. The scope of this paper limits to the first stage of the project. A quantitative approach was chosen by considering the nature of this study. A self-administered online questionnaire was developed around several key challenges and directed especially to the staff members, in order to identify what are the expectations of university staff in relation to thematic topics. Subsequently, business requirements under each key challenge were ranked based on MoSCoW prioritisation method. Energy management, space utilisation and occupancy, cleanliness recognition, smarter car parking, internet enabled cafe, network and physical security and environment (temperature) control are the key business challenges identified. Moreover, intended system qualities and specific project benefits were also identified to scope the project well.
Choice of the regularization parameter for perfusion quantification with MRI

Truncated singular value decomposition (TSVD) is an effective method for the deconvolution of dynamic contrast enhanced (DCE) MRI. Two robust methods for the selection of the truncation threshold on a pixel-by-pixel basis—generalized cross validation (GCV) and the L-curve criterion (LCC)—were optimized and compared to paradigms in the literature. GCV and LCC were found to perform optimally when applied with a smooth version of TSVD, known as standard form Tikhonov regularization (SFTR). The methods lead to improvements in the estimate of the residue function and of its maximum, and converge properly with SNR. The oscillations typically observed in the solution vanish entirely, and perfusion is more accurately estimated at small mean transit times. This results in improved image contrast and increased sensitivity to perfusion abnormalities, at the cost of 1–2 min in calculation time and hyperintense clusters in the image. Preliminary experience with clinical data suggests that the latter problem can be resolved using spatial continuity and/or hybrid thresholding methods. In the simulations GCV and LCC are equivalent in terms of performance, but GCV thresholding is faster.
Reconsidering downwind operation by analysis of the National Renewable Energy Laboratory’s Phase VI data

Data are presented comparing upwind versus downwind operation of the National Renewable Energy Laboratory’s Phase VI wind turbine. Power was not reduced as expected for downwind, which may be attributed to inboard three-dimensional effects. Average flap bending loads were reduced with downwind coning and compared well with prediction. Fatigue loads were increased with downwind; however, fatigue was mitigated with a tower shroud. The shroud needs to align with the freestream, demonstrated by an increase in fatigue loads from a 10° shroud misalignment. Pressure data were acquired in the tower wake at the rotor location with and without the shroud. The bare tower wake data compared well with previous work. The shroud wake data at 10° and 20° misalignment showed velocity reduction and turbulence exceeding the bare tower values. Downwind operation, with an aligning tower shroud, should be considered for future designs given the load benefits of downwind coning.
A novel segmented routing algorithm based on the markov decision process in mobile opportunistic networks

The purposes of research of routing algorithms in the mobile opportunistic networks are to improve the message delivery ratio, control overhead, and reduce the end‐to‐end delay. Now the performance of routing algorithms is very low because the opportunistic network structure is sparse and the network topology is variable. In this article, we use the Markov random process to propose a new segmented routing algorithm with a higher efficiency in opportunistic networks. In the stage of multicopy, we propose a forwarding strategy with the Markov decision process (MPD) to forward messages to multiple relay nodes quickly. In the stage of singe copy, we establish a precise delivery model to forward messages to the destination node with less relay nodes by combining the MPD with historical encountering information of nodes. The two‐stage segmented routing algorithm not only balances the relationship between the delivery ratio and the network overhead, but also saves network resources. Compared with other routing algorithms, our proposed segmented routing algorithm is superior to the existing routing algorithms in the message delivery ratio, message delay, and network overhead. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Non-Intrusive Load Monitoring Based on Novel Transient Signal in Household Appliances with Low Sampling Rate

Nowadays climate change problems have been more and more concerns and urgent in the real world. Especially, the energy power consumption monitoring is a considerate trend having positive effects in decreasing affecting climate change. Non-Intrusive Load Monitoring (NILM) is the best economic solution to solve the electrical consumption monitoring issue. NILM captures the electrical signals from the aggregate energy consumption, feature extraction from these signals and then learning and predicting the switch ON/OFF of appliances used these feature extracted. This paper proposed a NILM framework including data acquisition, data feature extraction, and classification model. The main contribution is to develop a new transient signal in a different aspect. The proposed transient signal is extracted from the active power signal in the low-frequency sampling rate. This transient signal is used to detect the event of household appliances. In household appliances event detection, we applied to Decision Tree and Long Short-Time Memory (LSTM) models. The average accuracies of these models achieved 92.64% and 96.85%, respectively. The computational and result experiments present the solution effectiveness for the accurate transient signal extraction in the electrical input signals.
Research on interactive steering control strategy between driver and AFS in different game equilibrium strategies and information patterns

ABSTRACT In the past decade, several publications have shown that it is advisable to design an advanced driver assistance system using a shared control structure. This paper is concerned with the modelling and verification of an interactive steering control strategy between a driver and an active front steering (AFS) controller to investigate the complex interactions between human driver and an AFS system. Using game theory as a general framework, a more comprehensive mathematical model system of interactive steering control potentially applicable to explore human drivers’ behaviours in shared control of intelligent vehicles is presented and discussed in this paper. The effects of different information patterns, namely the open-loop pattern and the closed-loop feedback pattern on modelling shared steering control between driver and AFS have been investigated. Simulation and hardware-in-loop implementation results prove the validity of steering interactive modelling in different game information patterns. Specifically, the results show that, in the Nash equilibrium strategy situation, the driver and the AFS controller may become more rational and reasonable in the process of completing the same dynamic task in the closed-loop feedback information patterns compared to the open-loop ones; and the differences between feedback Nash and feedback Stackelberg may depend on the step size of discretisation.
Scaling cosmology with variable dark-energy equation of state

Interactions between dark matter and dark energy which result in a power-law behavior (with respect to the cosmic scale factor) of the ratio between the energy densities of the dark components (thus generalizing the ΛCDM model) have been considered as an attempt to alleviate the cosmic coincidence problem phenomenologically. We generalize this approach by allowing for a variable equation of state for the dark energy within the CPL-parametrization. Based on analytic solutions for the Hubble rate and using the Constitution and Union2 SNIa sets, we present a statistical analysis and classify different interacting and non-interacting models according to the Akaike (AIC) and the Bayesian (BIC) information criteria. We do not find noticeable evidence for an alleviation of the coincidence problem with the mentioned type of interaction.
Galaxy redshift surveys with sparse sampling

Survey observations of the three-dimensional locations of galaxies are a powerful approach to measure the distribution of matter in the universe, which can be used to learn about the nature of dark energy, physics of inflation, neutrino masses, etc. A competitive survey, however, requires a large volume (e.g., Vsurvey ∼ 10Gpc3) to be covered, and thus tends to be expensive. A ``sparse sampling'' method offers a more affordable solution to this problem: within a survey footprint covering a given survey volume, Vsurvey, we observe only a fraction of the volume. The distribution of observed regions should be chosen such that their separation is smaller than the length scale corresponding to the wavenumber of interest. Then one can recover the power spectrum of galaxies with precision expected for a survey covering a volume of Vsurvey (rather than the volume of the sum of observed regions) with the number density of galaxies given by the total number of observed galaxies divided by Vsurvey (rather than the number density of galaxies within an observed region). We find that regularly-spaced sampling yields an unbiased power spectrum with no window function effect, and deviations from regularly-spaced sampling, which are unavoidable in realistic surveys, introduce calculable window function effects and increase the uncertainties of the recovered power spectrum. On the other hand, we show that the two-point correlation function (pair counting) is not affected by sparse sampling. While we discuss the sparse sampling method within the context of the forthcoming Hobby-Eberly Telescope Dark Energy Experiment, the method is general and can be applied to other galaxy surveys.
One-dimensional electron transport in semiconductor nanostructures

In this short article, a summary is presented of recent progress in understanding the behaviour of electrons in semiconductor nanostructures. The method of shaping the electron gas is by electrostatic confinement with split gates. Whereas a rigid one-dimensional system shows the canonical conductance quantization, the relaxation of confinement, towards two-dimensionality results in strong electron-electron repulsion, splitting the line of electrons into two separate rows. This situation is the precursor to the formation of a Wigner lattice and is an example of how the topology of the electron gas is determined by electron correlation.
An Approach for System Risk Assessment and Mitigation by Optimal Operation of Wind Farm and FACTS Devices in a Centralized Competitive Power Market

A high-speed degradation in the raw materials of the conventional energy sources forces the whole world toward the use of renewable energy as electrical sources. Renewable energy is not only used for fulfillment of the rapidly increased electricity demands, but also minimizes the system economic risks in competitive power markets. This paper proposes a simple and efficient approach for curtailing the system risk in the deregulated power systems. The optimal placement and operation of wind generators and flexible alternating current transmission system (FACTS) devices are determined, which ensure considerable profit and social welfare achievements by minimizing the system economical risk. Two new indices named marginal pricing index and marginal congestion index have also been proposed to identify the most critical buses and lines in terms of pricing and MVA flows, respectively. These indices help place the wind generators and FACTS devices optimally. The value-at-risk (VaR) and conditional-value-at-risk (CVaR) have also been incorporated as risk assessment tools in the considered systems. The relation between VaR and CVaR with social welfare and generation cost has also been highlighted in this work. The modified IEEE 14-bus and practical 39-Bus New England systems have been considered for validating the effectiveness of the proposed approach.
Axion cosmology with long-lived domain walls

We investigate the cosmological constraints on axion models where the domain wall number is greater than one. In these models, multiple domain walls attached to strings are formed, and they survive for a long time. Their annihilation occurs due to the effects of explicit symmetry breaking term which might be raised by Planck-scale physics. We perform three-dimensional lattice simulations and compute the spectra of axions and gravitational waves produced by long-lived domain walls. Using the numerical results, we estimated relic density of axions and gravitational waves. We find that the existence of long-lived domain walls leads to the overproduction of cold dark matter axions, while the density of gravitational waves is too small to observe at the present time. Combining the results with other observational constraints, we find that the whole parameter region of models are excluded unless an unacceptable fine-tuning exists.
The degenerate gravitino scenario

In this work, we explore the ``degenerate gravitino'' scenario where the mass difference between the gravitino and the lightest MSSM particle is much smaller than the gravitino mass itself. In this case, the energy released in the decay of the next to lightest sypersymmetric particle (NLSP) is reduced. Consequently the cosmological and astrophysical constraints on the gravitino abundance, and hence on the reheating temperature, become softer than in the usual case. On the other hand, such small mass splittings generically imply a much longer lifetime for the NLSP. We find that, in the constrained MSSM (CMSSM), for neutralino LSP or NLSP, reheating temperatures compatible with thermal leptogenesis are reached for small splittings of order 10−2 GeV. While for stau NLSP, temperatures of TRH ≃ 4 × 109GeV can be obtained even for splittings of order of tens of GeVs. This ``degenerate gravitino'' scenario offers a possible way out to the gravitino problem for thermal leptogenesis in supersymmetric theories.
Application of Particle Swarm Optimization to a Scheduling Strategy for Microgrids Coupled with Natural Gas Networks

This article focuses on the minimization of operational cost and optimal power dispatch associated with microgrids coupled with natural gas networks using particle swarm optimization (PSO). Introducing a natural gas turbine in a microgrid to overcome the drawbacks of renewable energy resources is a recent trend. This results in increased load and congestion in the gas network. To avoid congestion and balance the load, it is necessary to coordinate with the electric grid to plan optimal dispatch of both interactive networks. A modification is done in applying PSO to solve this coupled network problem. To study the proposed approach, a 7-node natural gas system coupled with the IEEE bus 33 test system is used. The proposed strategy provides the optimal power dispatch. Moreover, it indicates that power sharing between the main grid and microgrid is reduced in such a way that it may help the main grid to shave the load curve peaks.
Supply chain optimisation with both production and transportation integration: multiple vehicles for a single perishable product

This paper deals with an extension of the integrated production and transportation scheduling problem (PTSP) by considering multiple vehicles (PTSPm) for optimisation of supply chains. The problem reflects a real concern for industry since production and transportation subproblems are commonly addressed independently or sequentially, which leads to sub-optimal solutions. The problem includes specific capacity constraints, the short lifespan of products and the special case of the single vehicle that has already been studied in the literature. A greedy randomised adaptive search procedure (GRASP) with an evolutionary local search (ELS) is proposed to solve the instances with a single vehicle as a special case. The method has been proven to be more effective than those published and provides shorter computational times with new best solutions for the single vehicle case. A new set of instances with multiple vehicles is introduced to favour equitable future research. Our study extends previous research using an indirect resolution approach and provides an algorithm to solve a wide range of one-machine scheduling problems with the proper coordination of single or multiple vehicles.
Design and characterization for travelling wave electrodes of high‐speed Mach‐Zehnder electro‐optic modulator on an n‐doped InP substrate

Designing a traveling wave electrode (TWE), which feeds a high‐speed electrical signal to modulate an optical signal, is a key issue of high‐speed Mach‐Zehnder electro‐optic modulator (MZM) development fields. In this article, we have presented TWE design and characterization results for an MZM on an n‐type InP substrate operating frequency range from DC to 25 GHz. A coplanar waveguide with ground structure has been adapted to the TWE to overcome lossy characteristics of the n‐type InP substrate and increase noise immunity. The designed results are analyzed as comparing with equivalent circuits extracted by the data, which is measured by a vector network analyzer. Consequently, we hope our results can be helpful in the fields of design and fabrication of high‐speed opto‐electric components.