Miracle-dz/UniFAR-FTUs huggingface dataset:
Piezoresistive Nanomechanical Humidity Sensors Using Internal Stress In-Plane of Si-Polymer Composite Membranes

This article presents the design and fabrication process of a highly miniaturized nanomechanical Si-polymer composite membrane-type internal-stress sensor (MIS) with piezoresistive elements for humidity detection. The 500-μm<sup>2</sup> area dimension sensor consists of a thin Si-polymer composite membrane supported by two piezoresistive Si beams. The composite membrane is fabricated as follows: First, 1-μm-wide width Si slits with 1 μm separation gaps are formed by using photolithography and deep reactive-ion etching, and then, the Si slits are filled with a functional polymer (methyl methacrylate based acrylate resin: OLESTER<sup>TM</sup>Q155). This composite device acts as an absorber of vapor molecules and, consequently, generates stress. The fabricated sensor in a humidity-controlled chamber shows a relative resistance change Δ<italic>R</italic>/<italic>R</italic><sub>device</sub> = 0.6% for 58% relative humidity (RH) change and a highly linear steady response of 5.2 mV/%RH up to 70% RH change with sensing resolution of 0.5% humidity. The measured polymer expansion ratio of ε<sub>p</sub> = 2.4 × 10<sup>−3</sup> is consistent with the theoretical estimation using the weight fraction of water adsorbed in the polymer.
Optimizing the Fast Fourier Transform Using Mixed Precision on Tensor Core Hardware

The Fast Fourier Transform is a fundamental tool in scientific and technical computation. The highly parallelizable nature of the algorithm makes it a suitable candidate for GPU acceleration. This paper focuses on exploiting the speedup due to using the half precision multiplication capability of the latest GPUs' tensor core hardware without significantly degrading the precision of the Fourier Transform result. We develop an algorithm that dynamically splits the input single precision dataset into two half precision sets at the lowest level, uses half precision multiplication, and recombines the result at a later step. This work paves the way for using tensor cores for high precision inputs.
60-GHz Low-Noise VGA and Interpolation-Based Gain Cell in a 40-nm CMOS Technology

This paper presents the design and measurement of an interpolation-based low noise and variable gain cell (IBA-cell) in the 60-GHz band, using a 40-nm CMOS technology. The interpolation-based gain cell is designed for an innovative analog beamforming front end, where the array pattern is not only controlled in the phase domain, but also wins the flexibility in the magnitude domain. The circuit specifications are first derived for the application at 60 GHz. Techniques to combine low noise figure (NF) with variable gain tuning are presented focusing on the NF and linearity (IIP3) on the example of a 60-GHz low noise amplifier and variable gain amplifier. Subsequently, the design and measurement of the whole gain cell (IBA-cell) integrated into a single chip are reported with the technique of a cross-coupled feedback loop to reduce the phase variations over the gain tuning states and enhance the variations of IIP3. The IBA-cell achieves 15.8-dB maximum gain and 6.5-dB NF at 57 GHz with the gain tuning range from −2 to 15.8 dB and IIP3 varying from −11.3 to −16 dBm over the gain control range. The IBA-cell consumes a dc power of maximum 54 mA from 1.1 V.
Mutual Coupling Reduction of Slot Antenna Array by Controlling Surface Wave Propagation

In this communication, we present a methodology to reduce mutual coupling in a planar slot antenna array by using electric metamaterial. The proposed methodology is based on resisting and steering the propagation of surface wave. Initially, an array of complementary split-ring resonator (CSRR) is designed between the two slots for suppressing the surface wave propagation. Afterward, to steer the surface wave propagation, complementary fishnet structures are designed on the two sides of the slot array. Finally, for a better level of isolation improvement, both CSRR and complementary fishnet structures are simultaneously used. The final design has achieved at least 14 dB improvements in isolation level throughout the wide operating bandwidth of around 2 GHz, even if the gap between the slots is only 3.4 mm. The efficiency and the realized gain of the proposed antenna have also been studied. Because of the use of both metamaterial structures as a complementary, the overall configuration becomes fully planar and easy to realize.
Current Ripple Reduction for Cascaded H-bridge Converter with Phase-Shifted Carrier PWM

This paper proposes a new method to reduce the output current ripple in Cascaded H-bridge converter with Phase-Shifted Carrier PWM. The proposed technique introduces a new technique, namely Carrier Phase Angle Offset (CPAO), which changes the phase shift of the carriers between the phase legs of the converter. The mathematical analysis of the proposed technique is presented. Simulation results is provided to verify the theoretical analysis. The results show the proposed technique significantly reduces both the peak-to-peak and RMS current ripple.
The 30 kVA Permanent Magnet Synchronous Generator Wind-Cube Design, Implementation, Control; and Performance Measurements and Analysis

This paper presents a detailed design, implementation, control; and performance measurements and analysis of a 30 kVA Wind-Cube device when equipped with a permanent magnet synchronous generator (PMSG). Wind-Cube is a suitable electrical energy generating device from wind, for remote areas as a power supply system (RAPS) where large wind turbines are not practical to use. Wind-Cube is nearly doubling the ambient wind speed by using wind tunnel effect. Doubling the wind speed increases electrical energy generation by a factor approximately eight times. Wind-Cube cut in wind speed is lower than two meters per second. Although the application of PMSG in RAPS provides opportunities to improve voltage and frequency, control with maximum power point tracking (MPPT) together will be available. This paper studies about the PMSG as a wind turbine outfitted with battery bank and dump load. The battery bank framework and dump load can help with keeping up the dynamic power adjust amid over and under generation conditions and in addition sudden load changes. Through reenactment examines, it has been shown that RAPS can manage the load side voltage and frequency inside as far as possible while extricating the most extreme power from wind, which is an inborn ability of variable speed generator. The implementation and control results will be investigated, demonstrated and discussed through the work of this paper.
Statistics-Based Approach for Blind Post-Compensation of Modulator’s Imperfections and Power Amplifier Nonlinearity

Power amplifier (PA) nonlinearity and in-phase and quadrature-phase (I/Q) imbalance are major concerns for wireless transmitters. In this paper, we present a new closed-form expression for the probability density function (PDF) of I and Q components in the presence of transmitter’s impairments and propose a blind post-compensation approach for the mitigation of these impairments. These impairments include static PA nonlinearity and frequency-independent I/Q imbalance. The accuracy of the analytical PDF is evaluated using Kullback–Leibler divergence and Hellinger square distance. Simulation results show a reasonable correspondence between the derived PDF and non-parametric kernel density estimation-based PDF. After a closed-form PDF is obtained, higher order statistics-based method is used to estimate PA nonlinearity in the presence of I/Q impairments. Finally, a maximum-likelihood estimation of I/Q imbalance parameters is obtained using the analytical PDF. Simulation results show a normalized mean-squared error (NMSE) of around −40 dB and an adjacent channel power ratio of around −53 dBc, along with an error vector magnitude (EVM) of around 1%, for a 3-MHz local thermal equilibrium signal. Using laboratory measurements, an NMSE of around −35 dB and an EVM of 1.5% are achieved.
A New Election Algorithm for DPos Consensus Mechanism in Blockchain

The block chain has achieved great success in bit coin, and its decentralization idea caught highly attention of financial institutions, capital markets and academia. Decentralization is the most fundamental feature of the block chain, but decentralization sacrifices efficiency, while mining leads to high bit coin transaction costs; in some industries, such as the commercial retail, high efficiency and low cost are required. The consensus algorithm is the core technology to achieve non-centralization. This article proposes a DPoS consensus mechanism election algorithm. This algorithm improves the ring-based coordinator election algorithm. First, the algorithm is used to elect the agents, and then the final winner, reach a new consensus, meet the requirements of the block chain performance in the commercial retail sector, reduce transaction costs, and construct a fair, freely competitive, non-monopoly, secure and non-centralized block chain platform.
Image Style Transfer with Multi-target Loss for loT Applications

Transferring the style of an image is a fundamental problem in computer vision. Which extracts the features of a context image and a style image, then fixes them to produce a new image with features of the both two input images. In this paper, we introduce an artificial system to separate and recombine the content and style of arbitrary images, providing a neural algorithm for the creation of artistic images. We use a pre-trained deep convolutional neural network VGG19 to extract the feature map of the input style image and context image. Then we define a loss function that captures the difference between the output image and the two input images. We use the gradient descent algorithm to update the output image to minimize the loss function. Experiment results show the feasibility of the method.
RCS Reduction of a Microstrip Patch based on Broadband PRRS

A broadband polarization rotation reflective surface (PRRS) is designed and applied to wideband radar cross section (RCS) reduction in this paper. The PRRS can convert linearly polarized incident wave to reflective wave with orthogonal polarization, and a high polarization conversion ratio (PCR) can be achieved across a broad band. When the PRRS is arranged with in a chessboard configuration and placed around a microstrip patch, the monostatic RCS of the microstrip patch can be reduced 8dB from 6.9GHz to 14.9GHz. The RCS reduction performance and principle are also analysed.
Design and Analysis of Double E-shaped Array Antennas for an Outdoor RFID System

In this paper, two double E-shaped triple band array antennas operating at centimetre band are proposed for a radio-frequency identification (RFID) system. One of the proposed antennas provides resonance at frequencies of 7.23 GHz, 10 GHz and 11.748 GHz, while the other has resonance at 7.23 GHz, 9.1 GHz and 10.5 GHz. Both the antennas are moderately small sized with dimensions of 86.584 mm by 35.117 mm. At the highest resonance frequency, the first antenna has bandwidth 362 MHz and gain 8.13 dB, while the other has bandwidth 295 MHz and gain of 7.97 dB. These antennas are placed in an RFID system using orthogonal frequency division multiplexing (OFDM) modulation with non-orthogonal multiple access (NOMA). The bit error rate performance of RFID systems using the proposed array antennas is simulated for outdoor multipath fading channels. Results indicate the suitability of the array antennas in a NOMA-OFDM RFID scenario.
Resurrection of DC: An exposition for Future Power System

Historical background of AC and DC are presented and the changing scenario with the development of power electronics are pointed out. Advantages of DC systems in generation, transmission-distribution and consumption are discussed in the context of the existing AC system. A DC power system schematic is proposed and the main challenges with possible solutions in this regard are discussed.
Diet modulates colonic T cell responses by regulating the expression of a Bacteroides thetaiotaomicron antigen

Diet alters symbiont-specific immune responses via regulation of the expression of an outer membrane vesicle antigen. Dietary modulation of T cell immunity Commensal intestinal bacteria respond to dietary changes by modifying gene expression, leading to shifts in the levels of bacterial antigens encountered by the intestinal immune system. Wegorzewska et al. developed a mouse model system to investigate whether CD4+ T cell recognition of protein antigens of the gut symbiont Bacteroides thetaiotaomicron is subject to dietary modulation. TCR transgenic T cells for an outer membrane vesicle protein differentiated into both regulatory and effector T cells, with colitis emerging after selective regulatory T cell depletion. Dietary glucose was observed to strongly repress the T cell–detected antigen. These findings suggest that dietary modifications that reduce expression of immunodominant antigens targeted by T cells could help ameliorate some forms of human inflammatory bowel disease. T cell responses to symbionts in the intestine drive tolerance or inflammation depending on the genetic background of the host. These symbionts in the gut sense the available nutrients and adapt their metabolic programs to use these nutrients efficiently. Here, we ask whether diet can alter the expression of a bacterial antigen to modulate adaptive immune responses. We generated a CD4+ T cell hybridoma, BθOM, specific for Bacteroides thetaiotaomicron (B. theta). Adoptively transferred transgenic T cells expressing the BθOM TCR proliferated in the colon, colon-draining lymph node, and spleen in B. theta–colonized healthy mice and differentiated into regulatory T cells (Tregs) and effector T cells (Teffs). Depletion of B. theta–specific Tregs resulted in colitis, showing that a single protein expressed by B. theta can drive differentiation of Tregs that self-regulate Teffs to prevent disease. We found that BθOM T cells recognized a peptide derived from a single B. theta protein, BT4295, whose expression is regulated by nutrients, with glucose being a strong catabolite repressor. Mice fed a high-glucose diet had a greatly reduced activation of BθOM T cells in the colon. These studies establish that the immune response to specific bacterial antigens can be modified by changes in the diet by altering antigen expression in the microbe.
Inhibition of T cell activation and function by the adaptor protein CIN85

The adaptor CIN85 inhibits T cell activation through its association with the phosphatase Sts-2 after TCR stimulation. Thou shalt not CIN The ubiquitously expressed adaptor protein CIN85 has distinct roles in different cell types. This adaptor inhibits the activation of the receptor tyrosine kinases EGFR and PDGFR but promotes B cell receptor signaling. To determine its function in T cells, Kong et al. compared the activation of mouse T cells lacking CIN85 or the highly related adaptor CD2AP. Only loss of CIN85 augmented T cell growth and IL-2 production. CIN85 associated with the inhibitory phosphatase Sts-2 and promoted its recruitment to T cell receptor microclusters after activation. These data define a previously unknown inhibitory interaction, which could be targeted to augment T cell function in cancer and immunity. T cell activation is initiated by signaling molecules downstream of the T cell receptor (TCR) that are organized by adaptor proteins. CIN85 (Cbl-interacting protein of 85 kDa) is one such adaptor protein. Here, we showed that CIN85 limited T cell responses to TCR stimulation. Compared to activated wild-type (WT) T cells, those that lacked CIN85 produced more IL-2 and exhibited greater proliferation. After stimulation of WT T cells with their cognate antigen, CIN85 was recruited to the TCR signaling complex. Early TCR signaling events, such as phosphorylation of ζ-chain–associated protein kinase 70 (Zap70), Src homology 2 (SH2) domain–containing leukocyte protein of 76 kDa (SLP76), and extracellular signal–regulated kinase (Erk), were enhanced in CIN85-deficient T cells. The inhibitory function of CIN85 required the SH3 and PR regions of the adaptor, which associated with the phosphatase suppressor of TCR signaling–2 (Sts-2) after TCR stimulation. Together, our data suggest that CIN85 is recruited to the TCR signaling complex and mediates inhibition of T cell activation through its association with Sts-2.
Big Data Algorithms Adapted to Vehicular Networks for Driver's Behavior Modeling. (Algorithmes de Big Data adaptés aux réseaux véhiculaires pour modélisation decomportement de conducteur)

Les technologies Big Data gagnent de plus en plus d’attentions de communautes de recherches variees, surtout depuis que les donnees deviennent si volumineuses, qu’elles posent de reels problemes, et que leurs traitements ne sont maintenant possibles que grâce aux grandes capacites de calculs des equipements actuels. De plus, les reseaux vehiculaires, aussi appeles VANET pour Vehicular Ad-hoc Networks, se developpent considerablement et ils constituent une part de plus en plus importante du marche du vehicule. La topologie de ces reseaux en constante evolution est accompagnee par des donnees massives venant d’un volume croissant de vehicules connectes. Dans cette these, nous discutons dans notre premiere contribution des problemes engendres par la croissance rapide des VANET, et nous etudions l’adaptation des technologies liees aux Big Data pour les VANET. Ainsi, pour chaque etape cle du Big Data, nous posons le probleme des VANET. Notre seconde contribution est l’extraction des caracteristiques liees aux VANET afin d’obtenir des donnees provenant de ceux-ci. Pour ce faire, nous discutons de comment etablir des scenarios de tests, et comment emuler un environnement afin, dans un premier temps, de tester une implementation dans un environnement controle, avant de pouvoir effectuer des tests dans un environnement reel, afin d’obtenir de vraies donnees provenant des VANET. Pour notre troisieme contribution, nous proposons une approche originale de la modelisation du comportement de conducteur. Cette approche est basee sur un algorithme permettant d’extraire des representants d’une population, appeles exemplaires, en utilisant un concept de densite locale dans un voisinage.
Gaussian process based approaches for survival analysis

Traditional machine learning focuses on the situation where a fixed number of features are available for each data-point. For medical applications each individual patient will typically have a different set of clinical tests associated with them. This results in a varying number of observed per patient features. An important indicator of interest in medical domains is survival information. Survival data presents its own particular challenges such as censoring. The aim of this thesis is to explore how machine learning ideas can be transferred to the domain of clinical data analysis. We consider two primary challenges; firstly how survival models can be made more flexible through non-linearisation and secondly methods for missing data imputation in order to handle the varying number of observed per patient features. We use the framework of Gaussian process modelling to facilitate conflation of our approaches; allowing the dual challenges of survival data and missing data to be addressed. The results show promise, although challenges remain. In particular when a large proportion of data is missing, greater uncertainty in inferences results. Principled handling of this uncertainty requires propagation through any Gaussian process model used for subsequent regression.
Using directional change for information extraction in financial market data

Directional change (DC) is a new concept for summarizing market dynamics. Instead of sampling the financial market at fixed intervals as in the traditional time series analysis, by contrast, DC is data-driven: the price change itself dictates when a price is recorded. DC provides us with a complementary way to extract information from data. The data sampled at irregular time intervals in DC allows us to observe features that may not be recognized under time series. In this thesis we propose our new method for the summarizing of financial markets through the use of the DC framework. Firstly, we define what is the vocabulary needed for a DC market summary. The vocabulary includes DC indicators and metrics. DC indicators are used to build a DC market summary for a single market. DC metrics help us quantitatively measure the differences between two markets under the directional change method. We demonstrate how such metrics could quantitatively measure the differences between different DC market summaries. Then, with real financial market data studied using DC, we aim to demonstrate the practicability of DC market analysis, as a complementary method to that of time series, in the analysis of the financial market.
A methodology with a distributed algorithm for large-scale trajectory distribution prediction

ABSTRACT In this paper, we propose a method for predicting the distributions of people’s trajectories on the road network throughout a city. Specifically, we predict the number of people who will move from one area to another, their probable trajectories, and the corresponding likelihoods of those trajectories in the near future, such as within an hour. With this prediction, we will identify the hot road segments where potential traffic jams might occur and reveal the formation of those traffic jams. Accurate predictions of human trajectories at a city level in real time is challenging due to the uncertainty of people’s spatial and temporal mobility patterns, the complexity of a city level’s road network, and the scale of the data. To address these challenges, this paper proposes a method which includes several major components: (1) a model for predicting movements between neighboring areas, which combines both latent and explicit features that may influence the movements; (2) different methods to estimate corresponding flow trajectory distributions in the road network; (3) a MapReduce-based distributed algorithm to simulate large-scale trajectory distributions under real-time constraints. We conducted two case studies with taxi data collected from Beijing and New York City and systematically evaluated our method.