Miracle-dz/UniFAR-FTUs huggingface dataset:
A Genetic Structuralism Analysis of Materialism in Frances Hodgson Burnett’s A Little Princess

Although the Industrial Revolution in Britain’s Victorian era contributed significantly toward Britain’s development, it also led to the emergence of materialism issues in society. This research aims to identify how materialism was constructed and to reveal the worldview on materialism expressed in A Little Princess (2017). Goldmann’s Genetic Structuralism is operated in this qualitative research. The results indicate that the materialism issue brought some adverse impacts or social problems, such as the division of social classes, the social gap between the upper, middle, and working classes, and child labor in the Victorian age. Besides, the worldview of Burnett’s social group resisted materialism by delineating these social issues and a binary opposition between a materialistic character shown by Miss Minchin and a non-materialistic character presented by Sara. Through the binary opposition, Burnett wanted readers to be aware of the negative impacts of practicing materialistic traits such as possessiveness, envy, and non-generosity. Possessiveness is shown by Miss Minchin's desire and attitude to retain all of Sara’s luxury stuff. Envy appears in Miss Minchin's envy of Sara’s wealth and prosperity. Non-generosity as Miss Minchin hard to donate her possessions or do charity. As a human fact product, A Little Princess can be interpreted as a view to getting a better life for poor child workers at that time.
Mutual Coupling Reduction in Multiple-Input Multiple-Output Antenna Based on Metamaterial at Low THz Frequency Band

In this study, spiral resonator and complementary spiral resonator metamaterials have been applied to increase isolation in a dual-element MIMO antenna operated in the low terahertz frequency range 0.55 THz to 0.63 THz. Mutual coupling is reduced in the entire working bandwidth of the antenna, relatively wide bandwidth of 13.5%, and is at its maximum value, equal to 23 dB, at the antenna resonance frequency of 0.58 THz. In addition, the values of envelope correlation coefficient, diversity gain, back-lobe radiation and realized gain over frequency are enhanced with metamaterial loading. Effectiveness of the metamaterial loading on mutual coupling reduction is confirmed through investigating surface current on the antenna structure. Compared to other methods of mutual coupling reduction which mentioned in the text of this study, the proposed method has a relative advantage in terms of wide bandwidth, simplicity of design and increase high isolation in the terahertz frequency band. Applications of this structure include beyond 5G technologies, medical imaging, high-bandwidth and high capacity in short-range communications at low THz frequency band.
Research on Reflection Model for Portable Solar Absorption Ratio Measurement System

Based on the integrating sphere method, the algorithm of reflection model for portable measurement system is proposed to reduce the influence of non-ideal integrating reflection model on solar absorption ratio measurement. Integrating sphere reflection model is generated through analysis and experiment of incident light shaping, and the systematic error of non-ideal integrating reflection model is eliminated by correction factor of measurement system. The feasibility and reality of the model is validated by comparison between the result of portable measurement system and the result of the result measured by spectrophotometer, and the measurement accuracy of the portal solar absorption ratio measurement system.
A Physiological Signal Emotion Recognition Method Based on Domain Adaptation and Incremental Learning

Temporal concept shift (TCS) is an unavoidable problem in physiological signal-based emotion recognition tasks, i.e., the data distribution of physiological signals is constantly changing over time, which gradually degrades the model accuracy. To this end, we propose a method based on a combination of domain adaptation and incremental learning to reduce the impact of temporal concept drift. In this paper, domain adaptation is used to reduce the distribution differences and incremental learning is used to prevent the learned knowledge from being forgotten. Finally, we validate the effectiveness of our approach on two real datasets.
A Wavelet Characters based Adaptive Prediction Horizon for Multi-Step Predictive Torque Control on PMSM Drives

The realized control performance and development for the predictive control are limited by the short prediction horizon (PH). To solve this problem, a multi-step predictive torque control (MPTC) with an adaptive prediction horizon based on continuous wavelet transform (CWT) is proposed in this paper, and applied to a permanent magnet synchronous motor (PMSM) driving system as a torque controller. The prediction horizon is auto-tuned by the obtained clustering character of CWT, and the final value of the prediction horizon is calculated based on the current operating state. The stability of the long prediction horizon for the proposed method is analyzed and demonstrated on the discrete-time domain. The correctness is demonstrated by validations, as well as advantages on speed integrated time and absolute error (ITAE) and stator current total harmonic distortion (THD).
Edge-preserving image reconstruction for Young's modulus recovery from ultrasonic data

This study addresses the problem of reconstructing the Young's modulus from an uniaxial strain field estimated from ultrasonic data. We suggest to improve the classical Tikhonov-based approach by allowing for the preservation of edges. This produces better solutions, both qualitatively and quantitatively (up to 6 dB improvement in contrast-to-noise ratio).
Design and Evaluation of Controllers based on Microservices

In self-adaptive software systems, generic controllers can be configured parametrically according to system needs, even though their reuse is restricted because of the wide range of services that can be provided by each of the stages of a feedback control loop, like MAPE-K. Rainbow is a typical example of such a generic, monolithic controller. This paper advocates controllers that are structurally flexible, and which are composed from micro-controllers, each providing specific services (e.g., based on microservices). To provide evidence on the feasibility of our approach, we compare three different architectural configurations for the controller: monolithic, decentralised, and decentralised with a meta-controller. Results from our experiments indicate that even though the decentralised configuration with a meta-controller demanded more computational resources, it performed comparatively well when compared to the other configurations. We conclude that a multi-layered controller design, based on micro-controllers, provides the basis for defining structurally flexible controllers at operational-time, and may promote reuse at development-time.
Temporal Decomposition Transformer for Probabilistic Energy Forecasting

To ensure the balance of power supply and demand, probabilistic energy forecasting is significant to determine the power generation and dispatch strategies. In order to solve the probabilistic forecasting problem of energy time series, we develop a novel transformer-based decomposition framework, i.e., the temporal decomposition transformer (TDT) to estimate the probability distribution of future time series. TDT achieves accurate and reliable probabilistic forecasting by predicting the mean and standard deviation of time series successively through the decomposition framework. TDT uses the tranformer decoder to capture the temporal feature in the historical time series, and then two tranformer decoders predict the mean and standard deviation of the time series at each future time instant respectively, where the standard deviation is forecasted based on the forecasting of the mean. Finally, the time series probabilistic distribution is modeled by log-likelihood regression. By accomplishing extensive experiments on two real-world energy time series datasets, we conclude that TDT achieves better forecasting accuracy in both point forecasting and probability energy forecasting than compared methods.
Topological Radon Transforms and Their Applications

Here X and Y are real analytic manifolds, S is a subanalytic subset of X\times Y and f and g are restrictions of natural projections p_{1} and p_{2} to S respectively. In [24], [38], [45], several operations, such as direct and inverse images and so on, on constructible functions were introduced. See Section 2.1 for the precise definitions. Therefore, we can associate a constructible function $\varphi$ on X with a constructible function
Secrets Leaking Through Quicksand: Covert Channels in Approximate Computing

Approximate computing (AxC) has emerged as an attractive architectural paradigm especially for artificial-intelligence applications, yet its security implications are being neglected. We demonstrate a novel covert channel where the malicious sender modulates transmission by switching between regular and AxC realizations of the same computational task. The malicious receiver identifies the transmitted information by either reading out the workload statistics or by creating controlled congestion. We demonstrate the channel on both an Android simulator and an actual smartphone and systematically study measures to increase its robustness. The achievable transmission rates are comparable with earlier covert channels based on power consumption, but the malicious behavior of our channel is more stealthy and less detectable.
Cascaded Model Predictive Control for the Ferrite-Assisted Synchronous Reluctance Motor with Asymmetric Rotor Structure

The ferrite-assisted synchronous reluctance motor (FA-SynRM) with asymmetric rotor structure can highly improve motor performance by making its magnetic and reluctance torques reach their maximum values near or at the same current phase angles. Considering the asymmetric rotor structure and the flux shift, a new design of maximum torque per ampere (MTPA) control strategy and a cascaded model predictive control (MPC) method are needed. In this paper, the MTPA control strategy and cascaded MPC method are designed for the FA-SynRM with asymmetric rotor structure. The construction of current-loop model predictive controller is deduced in detail. A new design of MTPA control strategy is derived to make full use of both components of its torque. By simulations under different load and speed conditions, it is demonstrated that the proposed MTPA control strategy and cascaded MPC method for FA-SynRM has high accuracy and stability in complex conditions.
microSecEnD: A Dataset of Security-Enriched Dataflow Diagrams for Microservice Applications

Dataflow diagrams (DFDs) are useful resources in securing applications since they show a software system’s architecture and allow assessing architectural security and weaknesses. Enriching them with annotations about implemented security features further strengthens this ability. This is especially true for microservice applications, as their most pressing security concerns stem from their separation into multiple services. Researchers need data to work on these issues and enhance microservices’ architectural security. In this work, we present microSecEnD, a dataset of 17 manually created DFDs that are extensively annotated with information on implemented security features. We provide traceability for all model items. Further, a mapping to a list of 17 architectural security best-practices is provided. Finally, for each best-practice that an application violates, we present a model variant that does adhere to it.
An end-to-end Lithium Battery Defect Detection Method Based on Detection Transformer

The DETR model is often affected by noise information such as complex backgrounds in the application of defect detection tasks, resulting in detection of some targets is ignored. In this paper, AIA DETR model is proposed by adding AIA (attention in attention) module into transformer encoder part, which makes the model pay more attention to correct defect information. Rather than the noise information on the image, so as to improve the detection ability of lithium battery surface defects. Experiments show that AIA DETR model can well detect the defect target of lithium battery, effectively reduce the missed detection problem, and reach 81.9% AP in the lithium battery defect data set
FirmwareDroid: Towards Automated Static Analysis of Pre-Installed Android Apps

Supply chain attacks are an evolving threat to the IoT and mobile landscape. Recent malware findings have shown that even sizeable mobile phone vendors cannot defend their operating systems fully against pre-installed malware. Detecting and mitigating malware and software vulnerabilities on Android firmware is a challenging task requiring expertise in Android internals, such as customised firmware formats. Moreover, as users cannot choose what software is pre-installed on their devices, there is a fundamental lack of transparency and control. To make Android firmware analysis more accessible and regain some transparency, we present FirmwareDroid, a novel open-source security framework for Android firmware analysis that automates the extraction and analysis of pre-installed software.FirmwareDroid streamlines the process of software extraction from Android firmware for static security and privacy assessments. With FirmwareDroid, we lay the groundwork for researchers to automate the security assessment of Android firmware at scale, and we demonstrated the capabilities of FirmwareDroid by analysing 5,728 Android firmware samples from various vendors. We analysed 75,141 unique pre-installed Android applications to study how common advertising tracker libraries (a piece of software that collects user usage data) are used and which permissions pre-installed Android apps inherit. We conclude that 20.53% of all apps in our dataset include advertising trackers and that 88.14% of all used permissions are signature-based.
Snapshot Testing Dataset

Snapshot testing is a form of software testing that is focused on visual components by highlighting any code changes when compared to a previously stored state. This quick and simple method of testing is growing popular among the industry with companies such as Spotify and Robinhood. Despite its growing popularity, snapshot testing is barely explored in academia. In this paper, we use GitHub API to collect a dataset of 686 repositories tagged with Jest, a popular testing framework capable of snapshot testing. From those repositories, we found 4,604 snapshot files and 11,367 test files. The top-10 repositories represent 20% of all snapshot files in the dataset, even though it is only 3% of the size. We acknowledge that improvements can be made in the dataset but due to the lack of data on snapshot testing, we believe the current dataset is useful in helping researchers to study this topic.
Supergravity: An Anthology of Solutions

As we have seen, supergravity theories are just ordinary field theories providing the coupling to Einstein Gravity of a collection of lower spin fields in diverse dimensions, with a variety of self-couplings that are controlled by a web of special geometric structures springing from the scalar sector of the Lagrangian. Ultimately, responsible for the specific choice of these special geometries and for the geometric organization of the field-theory are the constraints imposed by supersymmetry, yet the general pattern that, through a historically process, has been unveiled in supergravity, might have a more general validity. There are probably, in the same pattern, further cases of interest that violate supersymmetry but which, without the lesson taught by it, might not have been dreamed of. For instance the class of D = 4 theories of the form (8.4.1) is larger than the set obtained as bosonic sectors of supergravity Lagrangians. In supergravity there are special choices for the scalar manifolds that, as recalled in (8.4.2), are symmetric coset manifolds in a large number of cases, yet the list of symmetric cosets is not exhausted by supergravity. As long as the numerator group G can be symplectically embedded in Sp(2nv,R) according to (8.3.50), the Gaillard-Zumino master formula (8.3.67) for the kinetic matrix NΛΣ(φ) holds true and all physical consequences encoded in the duality symmetries follow as well. Supergravity theories form also an interrelated web. The main connection between Lagrangians in diverse dimensions is provided by compactification and dimensional reduction. A D-dimensional gravitational theory containing p-forms that, as we know, are related to (p + 1)-branes, can admit vacuum-solutions of the form: M (0) D =M (0) d ×MD−d (9.1.1)
Blockchain-enabled Decentralized Anonymous Crowdsourcing Based on Anonymous Payments

Decentralizing crowdsourcing using blockchain removes the trusted mediator who may cause social biases in data aggregation and uncertainties in ensuring proper rewards to workers. Permissionless blockchain discloses all data on public ledgers, which compromises the privacy and anonymity of workers and induces free-riders. State-of-the-art anonymous crowdsourcing systems enable anonymity through identity registration of workers and a trusted setup for key generation. However, these systems fail to support anonymous payments to workers, which may compromise the identities of workers. In this paper, we incorporate anonymous payments in crowdsourcing and dispense with identity registration and trusted setup to support open anonymous participation from any worker. Our solution is based on the decentralized anonymous payment systems (e.g., Zerocoin), commitment schemes, and efficient non-interactive zero-knowledge proofs.
Physical-aware Interconnect Testing and Repairing of Chiplets

As the interconnect density of chiplets increases rapidly, some physics related defects appeared, such as coupling defects, etc. These defects are hard to detect with ordinary pseudo-random sequence patterns, some special test patterns are needed. Besides, the chip warpage caused by the thinning of 3D chips manufacturing and the uneven stress around TSVs or micro bumps will bring clustered faults of interconnections. For these defects, the repair rate of conventional interconnect redundancy method will be decreased. This paper proposes a physical-aware interconnect testing and repairing method of chiplets, using specific test patterns and clustered faults redundancy circuits to improve the interconnect test coverage and repair rate of chiplets. We also propose automatic repair circuits and the repair data synchronization scheme between multiple dies, so that the calculating and programming of repair data do not need to rely on the ATE programming, and the synchronization of the repair data between multiple dies can be done by hardware circuits automatically, which ensure the interconnection correctly after repairing.
Novel Nonlinear Time Domain Optimal Control Formulation of Wind Turbine Power System with GPOPS2 Software Simulations

Formulating a wind turbine power system (WTPS) as an optimal control problem is very natural and with great appeal – given the optimized objectives WTPSs always aim at achieving, such as but not limited to maximizing power generation and reducing fluctuations in the generated power; these objectives are better to be achieved especially when the WTPS is experiencing sudden changes or even faults. However, the literature does not provide much contributions in this domain given the nonlinearity of the problem and the lack of highly accurate time domain models. In this paper, we provide a novel nonlinear optimal control formulation for WTPSs taking advantage of very recent developments in accurate nonlinear time-domain modeling of WTPSs. This novel formulation enable, for the first time in the literature of WTPSs, the use of powerful optimal control solvers which traditionally work with systems of differential equations. We use in this paper the software optimal control solver GPOPS2, which is compatible with available software such as MATLAB®; this powerful solver has been proven promising in other fields such as unmanned aerial systems and robotics. we provide some simulation cases which show that optimal control solutions outperform PID controllers traditionally used by industry. We follow that with discussion on this novel approach and intended future directions.
Gloss-Aware Color Correction for 3D Printing

Color and gloss are fundamental aspects of surface appearance. State-of-the-art fabrication techniques can manipulate both properties of the printed 3D objects. However, in the context of appearance reproduction, perceptual aspects of color and gloss are usually handled separately, even though previous perceptual studies suggest their interaction. Our work is motivated by previous studies demonstrating a perceived color shift due to a change in the object’s gloss, i.e., two samples with the same color but different surface gloss appear as they have different colors. In this paper, we conduct new experiments which support this observation and provide insights into the magnitude and direction of the perceived color change. We use the observations as guidance to design a new method that estimates and corrects the color shift enabling the fabrication of objects with the same perceived color but different surface gloss. We formulate the problem as an optimization procedure solved using differentiable rendering. We evaluate the effectiveness of our method in perceptual experiments with 3D objects fabricated using a multi-material 3D printer and demonstrate potential applications.
Sap flow and sugar transport in plants

Green plants are Earth’s primary solar energy collectors. They harvest the energy of the Sun by converting light energy into chemical energy stored in the bonds of sugar molecules. A multitude of carefully orchestrated transport processes are needed to move water and minerals from the soil to sites of photosynthesis and to distribute energy-rich sugars throughout the plant body to support metabolism and growth. The long-distance transport happens in the plants’ vascular system, where water and solutes are moved along the entire length of the plant. In this review, the current understanding of the mechanism and the quantitative description of these flows are discussed, connecting theory and experiments as far as possible. The article begins with an overview of low-Reynolds-number transport processes, followed by an introduction to the anatomy and physiology of vascular transport in the phloem and xylem.Next, sugar transport in the phloem is exploredwith attention given to experimental results as well as the fluid mechanics of osmotically driven flows. Then water transport in the xylem is discussedwith a focus on embolism dynamics, conduit optimization, and couplings betweenwater and sugar transport. Finally, remarks are given on some of the open questions of this research field.
Voltage control of DC microgrid based on fuzzy neural network and improved particle swarm optimization algorithm

DC microgrid, characterized by high conversion efficiency, occupies a large part of the distribution network. However, due to the complexity and randomness of renewable energy and load, the voltage control of DC microgrid is inaccurate, which is an important indicator to measure the stable operation of the system. Considering the randomness, this paper studies the voltage control of DC microgrid including photovoltaic, wind power, energy storage and DC load systems. In this paper, the mathematical model of DC micro grid under multi energy coupling is established. Furthermore, fuzzy neural PID control with improved particle swarm optimization is proposed. Finally, the controller in this paper is proved to be effective through simulation experiments.