Miracle-dz/UniFAR-FTUs huggingface dataset:
Elaborating Inductive Definitions and Course-of-Values Induction in Cedille.

In the Calculus of Dependent Lambda Eliminations (CDLE), a pure Curry-style type theory, it is possible to generically {\lambda}-encode inductive datatypes which support course-of-values (CoV) induction. We present a datatype subsystem for Cedille (an implementation of CDLE) that provides this feature to programmers through convenient notation for declaring datatypes and for defining functions over them by case analysis and fixpoint-style recursion guarded by a type-based termination checker. We demonstrate that this does not require extending CDLE by showing how datatypes and functions over them elaborate to {\lambda}-encodings, and proving that this elaboration is type- and value-preserving. This datatype subsystem and elaborator are implemented in Cedille, establishing for the first time a complete translation of inductive definitions to a small pure typed {\lambda}-calculus.
Shikonin induces colorectal carcinoma cells apoptosis and autophagy by targeting galectin-1/JNK signaling axis

Colorectal carcinoma (CRC) is the third most common malignant tumor pathology worldwide. Despite progress in surgical procedures and therapy options, CRC is still a considerable cause of cancer-related mortality. In this study, we tested the antitumor effects of shikonin in CRC and tried to identify its potential mechanism. The potential target, molecular mechanism as well as in vitro and in vivo antitumor effects of shikonin in CRC cells were determined by an integrative protocol including quantitative proteomics, RT-PCR, western blotting, RNA interference and overexpression, apoptosis and autophagy assays, etc. Galectin-1 was a potential target of shikonin from the iTRAQ-based proteomic analysis in shikonin-treated SW620 cell. The overexpression and RNA silencing of galectin-1 in two CRC cells suggested that the shikonin sensitivity was correlation to galectin-1 levels. The ROS accumulation induced by shikonin was important to the formation of galectin-1 dimers. Dimer galectin-1 was found to be associated with the activation of JNK and downstream apoptosis or autophagy. Moreover, through functional in vitro studies, we showed that differences in galectin-1 level affected tumor cell proliferation, migration, and invasion. In summary, shikonin induced CRC cells apoptosis and autophagy by targeting galectin-1 and JNK signaling pathway both in vitro and in vivo, which suggested a potential novel therapy target for CRC.
Electro-mechanical compensation of the temperature coefficient of the pull-in voltage of microstructures

The pull-in voltage of a suspended microstructure can be used as on-chip voltage reference in a compatible MEMS-IC process. Pull-in is detected using capacitive displacement measurement. The stability is affected by an initial parasitic charge build-up and a temperature sensitivity of -149 μV/K. A burn-in procedure is required to minimize the first effect. The temperature coefficient is compensated for by applying additional temperature dependent electrostatic energy to the microstructure. Devices fabricated in an epi-poly process and designed for a nominal pull-in voltage at 5 V have a measured value at 4.7424 V. Drift becomes negligible after 50 hours of operation. The temperature reproducibility is within the resolution of the readout at 100 μV over a temperature range between 20 C and 60 C.
Sub-THz On-Chip Dielectric Resonator Antenna with Wideband performance

This paper presents the design of a wideband on-chip dielectric resonator antenna (DRA) operating at sub-THz frequencies. The DRA consists of inverted E-shaped on-chip driver, a low-permittivity supporter, and a dielectric resonator (DR). Substrate integrated waveguide (SIW) cavity backed on-chip antenna with L-probe feeding mechanism is adopted for the driver at 350 GHz. A standard 130-nm SiGe BiCMOS back-end process is employed in its design. The input matching, gain, and radiation efficiency of the on-chip driver are enhanced by placing a supporter and a DR on top of it. From full-EM simulations, the DRA achieves the -10 dB impedance bandwidth of 65 GHz (18.5%) with peak gain of about 10 dBi and radiation efficiency of 75% at 350 GHz. The developed antenna is highly suitable for future broadband front-end systems operating above 300 GHz.
Reduced-Cost Gradient-Based optimization of Compact Impedance Matching Transformers in Highly-Dimensional Parameters Spaces

Design of miniaturized microstrip circuits is heavily based on full-wave electromagnetic (EM) simulation tools. This is especially the case for components involving slow-wave compact cells, in which considerable EM cross-coupling effects cannot be adequately accounted for using simpler representations, e.g., equivalent network models. In this paper, a gradient-based procedure with numerical derivatives for accelerated optimization of miniaturized impedance matching transformers in highly-dimensional parameter spaces is proposed. Our approach allows for reducing the number of expensive EM simulations in the course of the optimization process by restricting the use of finite differentiation. This is achieved through a selective execution of a Broyden formula, applied for parameters that satisfy appropriately defined alignment conditions w.r. t. design relocation between the algorithm iterations. Furthermore, to facilitate handling of circuits of various complexities, the acceptance criteria for the mentioned alignment verification are made dependent on the search space dimensionality. The presented methodology is validated using three compact impedance matching transformers. A demonstrated computational speedup is as high as fifty percent as compared to the reference algorithm.
A Nonparametric Bayesian Approach for Probabilistic Representation of Power Uncertainties

This paper develops a nonparameteric Bayesian approach for the probabilistic representation of power system uncertainties involved with wind, solar and load power. The developed approach based on Dirichlet process mixture model (DPMM) analytically formulates the probability distributions of power uncertainties without prior knowledge of the number of mixture components. This provides a great improvement in probabilistic representation of power uncertainties as the proposed model can accommodate the ever growing power data. A computationally efficient VBI method is exploited to estimate the parameters involved with DPMM. Moreover, a novel truncated DPMM is designed to fit the special truncation feature of wind power distributions. The performance of proposed probabilistic representation approach for power uncertainties on real datasets of wind, solar and load power are validated and illustrated in the numerical simulations.
Object Detection and Distance Estimation Tool for Blind People Using Convolutional Methods with Stereovision

in this research, a tool that can provide information about object around is made. This tool can also estimate distance of detected object through camera which is combined with glasses, to ease blind people who use it. This tool is certainly can help them to identify object around and improve their skill and ability. This tool use camera as main sensor, which works like human eyes, to provide real time video as visual data. The RGB visual data is processed using Convolutional Neural Network which has 176x132 pixels by convoluting 2 times. It produces smaller pixels with size 41x33 pixels, so weights is obtained for classification using back propagation and determined dataset. After getting detection result, the next step is a find centroid value as center point for measuring the distance between objects and cameras with Stereo Vision The results is converted into sound form and connected to earphones, so blind people can hear the information. The test results show that this tool can detect predetermined objects, namely humans, tables, chairs, cars, bicycles and motorbikes with an average accuracy of 93.33%. For measurements of distances between 50 cm to 300 cm it has an error of around 6.1%
A Beam-Steering Transmitarray Antenna for 5G MIMO Channel Sounding in V-band

A beam-steering transmitarray antenna operating in V-band (57 - 64 GHz) is proposed for channel sounding applications and massive multiple-input multiple-output (M-MIMO) systems. The proposed antenna system consists of a transmitarray panel made of 8-phase state unit-cells and illuminated by a 2×2 element focal plane array. The antenna beam is scanned by displacing the focal plane array in the focal plane. The experimental characterisation of the fabricated prototype demonstrates a very satisfactory agreement with the numerical predictions. The measured results demonstrate a peak gain of 21.2 dBi at broadside at 60 GHz and a wide scan range (up to ±50°) with scan loss of about 4.2 dB in H-plane at ±35°.
A 0.41mW Band-Tunable 6th-Order IF Filter with 40 ns Settling Time in 45 nm CMOS RFSOI

This work presents the design and implementation of a fully-differential 6th-order intermediate frequency (IF) bandpass filter (BPF) in 45 nm CMOS RFSOI. Its application targets are wake-up receivers (WuRX) that employ aggressive duty cycling. The fabricated filter with all bias circuits consumes a current of only 0.41mA from a 1V supply. Its center frequency is adaptive between 70 and 120 MHz, and the 3 dB-bandwidth is 20MHz. The BPF can settle within 40 ns. It occupies an area of 0.03mm2. To the authors’ best knowledge, this circuit provides the lowest DC-power, the lowest DC-power per pole, the shortest settling time and the fewest area for IF BPFs reported to date.
A High-Speed Millimeter-Wave QPSK Transmitter in 28nm CMOS FD-SOI for Polymer Microwave Fibers Applications

Benefiting from considerable progress in the design of low-power, low cost and high-speed millimeter-wave circuits, Polymer Microwave Fibers (PMF) are gaining interest in the context of serial links. In this work, an innovative dual-band Quadrature Phase Shift Keying (QPSK) architecture, which is based on integrated wideband and low loss differential hybrid couplers, is proposed to increase data rate capability while still preserving low power and moderate range potentials. A circuit demonstrator in 28 nm CMOS FD-SOI is presented to validate the concepts. It achieves fifth harmonic locking on a wide continuous locking range and realizes 9 Gb/s data rate in the E-band.
Analysis and Design of a Full-Duplex Two-Element MIMO Circulator-Receiver With High TX Power Handling Exploiting MIMO RF and Shared-Delay Baseband Self-Interference Cancellation

In this article, we present how full-duplex (FD) operation can be integrated with multi-input multi-output (MIMO) operation using RF and baseband (BB) self-interference cancellation (SIC). MIMO operation increases the SIC requirements by a factor of <inline-formula> <tex-math notation="LaTeX">$N^{2}$ </tex-math></inline-formula>, resulting in severe area, power consumption, and noise penalty. We present the detailed analysis, design, and implementation of RF/BB cancellers that address this challenge, as well as a bootstrapping technique to enhance the power handling of integrated circulator-receivers (circ.-RX). A 65-nm CMOS scalable two-element MIMO FD circ. -RX array with integrated <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>-path-filter-based nonmagnetic circulators is described that: 1) exploits bootstrapping in the circulator <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula>-path filters to enhance Transmitter (TX) power handling by 8 dB and 2) features area- and power-efficient passive RF and active BB wideband MIMO cancellation with shared-delay elements to address the O(<inline-formula> <tex-math notation="LaTeX">$N^{2}$ </tex-math></inline-formula>) cancellation challenge. The prototype exhibits: 1) up to 35-/45-dB average SIC across 40-/20-MHz BW; 2) more than 42-/53-dB average crosstalk (CT)-SIC across 40-/20-MHz BW with <2.1-dB degradation in RX NF; and 3) overall TX power handling of +14 dBm enabled by clock bootstrapping.
DynaPro: Dynamic Wireless Sensor Network Data Protection Algorithm in IoT via Differential Privacy

With the advent of the era of intelligent Internet of Things (IoT), more and more personal information are collected in the process of deploying IoT in various domains. This brings the problem of data protection in IoT. To address this problem, we propose a data protection algorithm, called DynaPro, based on differential privacy for dynamic wireless sensor networks (WSN), which is the sensor layer of IoT. DynaPro has addressed two issues in data protection of wireless sensor networks. The first issue is the dynamic topology of the network. In order to solve this problem, DynaPro has adopted methods like time window, hierarchical sampling, and graph similarity to process the snapshots of the dynamic network topology. The second issue is addition of noise in differential privacy. To address this issue, DynaPro uses Hierarchical Random Graph (HRG) as middleware to apply differential privacy protection. Instead of adding noise to network data and topology directly, DynaPro adds noise to HRG. In this way, DynaPro can hide the network topology but retain the necessary structural information to support data analysis. Theoretical analysis and experimental results show that DynaPro can preserve the important network features of the original network topology under the premise of the differential privacy protection model.
Experimental Evaluation of a 60 GHz Beamforming Solution with 32-Dipole Printed Array

This paper presents a 60 GHz beamforming (BF) solution based on a 8-channel BF chip with an on-board dipole array antenna. A single BF chip has a Tx OP1dB of 1 dBm and an Rx IP1dB of -23 dBm per RF channel, occupying a silicon area of 27 mm2. The antenna array is based on eight in-line 4×1-dipole elements and it has a measured peak gain of 17 dBi across the 55–66 GHz band. The measurement results of the integrated solution show ±45° azimuth steering with an EIRP of 23 dBm.
A Transmission Line Based Microwave Heater at 25 GHz for Continuous Flow Microfluidics Fabricated on Silicon

In this work, a co-planar waveguide (CPW) microwave transmission line on high-resistivity silicon is employed as a microwave heater at 25 GHz to heat a sub-microliter volume of 0.23 μL. The CPW heater and fluidic layout are co-designed using COMSOL Multiphysics to achieve rapid, contact-less and uniform heating. The manufactured device is bond-wired and experimentally tested using the simultaneous microwave excitation and optical investigation. Heating performance is evaluated using a fluorescent mixture of Rhodamine B and deionised water loaded in the fluidic channel. A heating rate of 12°C/s is achieved with 1.58 W of power at 25 GHz and the heating uniformity of ±2°C is maintained during 10 seconds of heating.
Security Issues in IoT: A Survey

Internet of things (IoT) could be found on everywhere in today live. It is used in smart cities like roads, hospitals and in smart homes like controlling door or air conditioner unit or preventing fires and much more. These devices that use IoT are connected to the internet and send and receive many of important data through the network. This open the attacker's starvation to invade the IoT networks and got its valuable data. The problem with the IoT devices is the limited performance components that make it difficult to apply the existing security method on it. This limitation requires a need to present lightweight algorithms which support the IoT devices. The survey in this paper reviewed several proposed algorithms and authentication methods in IoT to stop many kinds of attacks with considering the limitation of the IoT system.
Dynamic Human Body 3D Reconstruction using Laplacian Deformation

Dynamic 3D reconstruction of human body is a key issue in the field of computer vision, especially in the case that human body is undergoing large deformation. A novel human body 3D reconstruction method using Laplacian deformation is proposed for fine reconstruction in the region of large deformation. The preliminary reconstructed model is firstly achieved through warp field. Then large deformed region is detected and fine reconstruction model is finally obtained by use Laplacian deformation in the detected large deformed region. The proposed method is verified in different datasets for reconstructing the whole human body and the human body parts. Laplacian deformation improves the reconstruction accuracy in the detected large deformed region.
Sizing Energy Storage Based on a Life-Cycle Saving Dispatch Strategy to Support Frequency Stability of an Isolated System With Wind Farms

Wind power fluctuations usually cause grid frequency deviations, which could have a significant impact on an isolated power system. This paper proposes a dispatch strategy of the energy storage (ES) to support grid frequency stability of the isolated power system. The dispatch strategy of the ES is based on the forecasted mean wind speed and the corresponding standard deviation. Based on the dispatching scheme, a power spectrum density (PSD)-based method has been developed for sizing the ES and validated through system simulations based on the actual wind speed data and real isolated system in China. Results presented in this paper have shown demonstrated that the cycle-life of the ES can be significantly saved by using the proposed dispatch strategy. The developed ES sizing method has taken the random characteristics of wind power fluctuations and the frequency responses of the system into full consideration. Therefore, the proposed dispatch strategy and sizing method of the ES is general and can be applied to other isolated power systems with the ES being used to support grid frequency stability.
Coupling Matrix Extraction by Entries Deviation and with Use of Sherman-Morrison Formula

This paper presents a new method of coupling matrix extraction. In this method it is assumed that we have scaterring or admittance parameters at single frequency point for each entries of coupling matrix deviated by any of two different values from the proper value. By using Sherman-Morrison matrix formula for the elements of inverse coupling matrix and corresponding scattering or admittance values it is possible to obtain one by one all entries of the entire inverse matrix to the coupling matrix. Finally by inverse of resulting matrix the extracted coupling matrix is obtained. Additionally it is shown that the coupling matrix can be fully extracted using of one scattering parameter only, i.e. reflection or transmission, assuming that all coupling matrix entries are deviated including those equal to zero. Numerical experiment presented in the paper proved the correctness of the proposed approach.
Compact and performing transmission lines for mm-wave circuits design in advanced CMOS technology

This work presents a comparative study of conventional and slow wave (SW) transmission lines implemented in an advanced 22-nm CMOS process. Both microstrip (MS) and coplanar waveguides (CPW) were analysed through simulations and measurements. A classical SW approach was used for the implementation of the SW CPWs while the SW effect was generated in the MS lines using bed of nails integrated in the CMOS process. As a proof of concept, the proposed SW MS approach was employed to design a new artificial quarter-wave TL section. The proposed configuration was created loading a meandered MS line with open ended S-MS stubs acting as discrete capacitive loads. Results show that the proposed methodology offers an attractive form factor and good performance.
Multi-Level Metric Learning Network for Fine-Grained Classification

The application of fine-grained image classification can be problematic due to subtle differences between classes. The existing global feature-based methods have worse accuracies than regional feature-based methods, because regional feature-based methods focus on the determination of differentiated features within local regions. To learn more discriminative global features, in this paper, we proposed the use of L2 normalization to tackle a neglected conflict between the widely used metric loss (triplet loss) and classification loss (softmax loss) in global feature-based methods. Furthermore, a multi-level metric learning network (MMLN) is proposed for fine-grained image classification based on global features. In the MMLN, multi-level metric learning objectives and classification objectives are present at multiple high-level layers. The multi-level metric learning objectives work together to supervise the network in order to learn highly discriminative features. In addition, a new probability aggregation strategy (PAS) is proposed to produce a fused prediction by combining the multi-level predictive probabilities. Experiments were conducted on three standard fine-grained classification datasets (CUB-200-2011, Stanford Cars, and FGVC-Aircraft). Results demonstrated that our MMLN achieved accuracies of 88.0%, 94.6% and 92.4% respectively and outperformed state-of-the-art methods, substantially improving fine-grained classification tasks. Besides, gradient-weighted class activation mapping (Grad-CAM) shows that the MMLN is able to pay more attention to the discriminative local regions due to the application of multi-level metric learning.
Phased Array Antenna Calibration Technique Based on Center-Null-Tracking (CNT) Method

In this paper, a new phased array antenna calibration technique using a center-null-tracking (CNT) method is proposed. The proposed CNT method is based on the comparison of two antenna elements in array with a phase difference of 180°. The deviation from 180° phase difference can be considered as a phase error and can also be detected. Since the radiation pattern of two antenna elements in 180° phase difference generates a null in the center, tacking the null location by monitoring the magnitude of the null can determine the unwanted phase error. Once the phase error is found, the magnitude error between the antenna element can also be determined by measuring the magnitude of the null again by changing attenuation level in the phased array. If the two elements have an imbalance in magnitude, the null magnitude is not at minimum. So, by controlling attenuators to see whether the null magnitude decreases or increases, magnitude balance can also be achieved. In order to verify the proposed calibration technique, 1x4 array antenna is simulated and tested at 5.8 GHz. Both of the simulated and measured result show excellent performance comparing to the conventionally used Rotating-Element Electric-field Vector (REV) method.
Data-based Analysis on Traction Energy for Urban Rail Transit Using Clustering and Classification Methods

The energy consumption of urban rail transit is increasing gradually in recent years. Accurate data analysis of traction energy is in urgent demand for improving energy-efficiency, thus it becomes an essential research subject for the metro system. According to the characteristics of the subway, this paper analyzes the traction energy consumption data based on the clustering and classification methods. The energy data collected by the energy consumption metering device is a line from Beijing Subway. The energy data feature vectors are obtained after simply pre-processing the raw data. Cluster algorithms are applied to divide the feature vectors into several sets with the same characteristics. The energy patterns is generated by decision tree algorithm. Finally, the outliers of traction energy under the same energy pattern are selected based on local outlier factor (LOF). The analysis results show that the traction energy data can be divided into four patterns and the outliers are detected under finer clusters than before, which can help the metro companies manage the energy data delicately.