Miracle-dz/UniFAR-FTUs huggingface dataset:
Adopting Machine Learning to Support the Detection of Malicious Domain Names

Nowadays there are many Domain Name System (DNS) firewall solutions to prevent users to access malicious domains. These can provide real time protection and block illegitimate communications. Most of these solutions are based on known malicious domain names lists (blocklists) that are being constantly updated. However, this way, it is only possible to block malicious communications for known malicious domains, leaving out many others that are malicious but have not yet been updated in the blocklists. In this paper we present a study on the usefulness of adopting machine learning to detect malicious domain names. From a large set of domain names classified in-advance as malicious or benign an enriched dataset with multiple features was created and analyzed. The exploratory analysis and the data preparation tasks were carried out and the results achieved by different machine learning classification algorithms. Depending on the classification algorithm, the accuracy results varied between 75% and 92% and the classification time ranged between 2.77 seconds and 5320 seconds. These results are interesting in that they make it possible to classify a new domain as malicious or not in a short time and with good hit rate.
High Power High Efficiency 475-520 GHz Source Based on Discrete Schottky Diodes

A 500 GHz source based on discrete Schottky diodes technology is reported in this work. The high frequency part developed by ACST consists of a high power and high efficiency doublet at 135-160 GHz and a tripler at 475-540 GHz. Both multipliers feature a single chip per module and do not use any power combining techniques. The 150 GHz and 500 GHz multipliers are able to handle more than 400 mW and 100 mW input power and provide more than 140 mW and 20 mW output power, respectively. This is the most powerful 500 GHz source reported based on discrete Schottky diodes without using power combining.
Criticality Analysis for the Verification and Validation of Automated Vehicles

The process of verification and validation of automated vehicles poses a multi-faceted challenge with far-reaching societal, economical and ethical consequences. In particular, fully automated vehicles at SAE Level 4 and 5 will be expected to operate safely in an arbitrarily complex, infinite-dimensional domain called open context. In order to give structure to the open context, we propose a methodical criticality analysis that maps an infinite-dimensional domain onto a finite and manageable set of artifacts that capture and explain the emergence of critical situations for automated vehicles. We propose a combined approach of expert-based and data-driven methods to identify relevant phenomena and explain the underlying causalities. Leveraging on abstraction, we define a clearly laid out process that converges towards a manageable set of artifacts based on two assumptions on the nature of traffic. A criticality analysis precedes the design phase of an automated vehicle and is therefore located outside the V-model. As the open context is analyzed independently of a concrete realization, it is relevant for any automated vehicle operating within that domain. Therefore, its results can subsequently be used to derive safety principles and mitigation mechanisms for automated driving and to set up a coherent safety argument for the homologation process.
A New Hybrid Multilevel Inverter Topology with Level Shifted Multi-carrier PWM Technique for Harvesting Renewable Energy

This paper presents a new hybrid multilevel inverter topology that offers several advantages such as reduced number of components, optimized costs, encapsulated size and light weight. The proposed compact cascaded inverter consists of six switches and three asymmetrical dc voltage sources that is able generate six positive voltage states, and multiple modules can be cascaded to generate a desired level of voltage. An H-bridge unit is connected between the load and the cascaded modules that helps to produce negative half cycle using the positive voltage states originated by the modules. Although the proposed compact cascaded inverter contains an H-bridge unit, it offers a moderate level of total standing voltage unlike the existing topologies, resulting in a decreased number of equipment and cost. A level shifted multi-carrier based PWM technique is used to drive the switches of the proposed inverter, which provides current with less total harmonic distortion (THD). Finally, the performance of the proposed compact cascaded inverter has been evaluated by the simulation tests carried out in MATLAB/Simulink and results presented.
A Real-time Emotion Recognition System Based on an AI System-On-Chip Design

In this paper, we developed and integrated a realtime emotion recognition system using an AI system-on-chip design. The emotion recognition platform combined three different physiological signals, Electroencephalogram (EEG), electrocardiogram (ECG), and photoplethysmogram (PPG) as the classification resources. A 3-to-1 Bluetooth piconet was deployed to transmit all physiological signals on a single platform access point and to make use of low power wireless technologies. The system then integrated an AI computing chip with a convolution neural network (CNN) structure to classify three emotions, happiness, anger, and sadness. The average accuracy for a subject-independent classification reached 72.66%. The proposed system was integrated with the RISC-V processor and AI SOC to implement real-time monitoring and classification on edge.
Dispersion in Millimeter-wave and THz Dielectric Waveguides: Modeling, Measurement and Performance Limitations

Polymer Microwave Fibers (PMF) are a promising type of dielectric waveguide, offering low loss for millimeter-wave signals while being simple to use and cheap to manufacture. However, published research on the topic has highlighted dispersion as a limit to the achieved data rate. This paper proposes a model to evaluate the impact of dispersion on a signal, and verifies the accuracy of the modeling technique by comparing its results with measurements. Furthermore, the model is used to analyze how a dielectric waveguide can be optimally used for communication applications. This analysis shows that co-designing the circuit and fiber can result in greatly improved throughput when compared to previous Polymer Microwave Fibers.
A Flip-Chip Packaged Design of Planar Antenna Array Based on Dual-feed Network for 77-GHz Automotive Radar

This paper presents a 77-GHz flip-chip packaged planar antenna array based on dual-feed network. The dual-feed network is consisted of a single substrate integrated waveguide line (SIW) and an array of microstrip line. Wideband transition between SIW and microstrip line is obtained by minimizing the active reflection coefficients. To improve equivalent isotropically radiated power (EIRP), the conventional method of antenna array and enlarged transmitted power are generally used for 77-GHz band. However, these methods will narrow the operating bandwidth, increase the circuit sizes and difficulty in transmitter design. The dual-feed network can simplify the design and decrease the insertion loss and circuit size. Moreover, the dual-feed network can maintain the same bandwidth as the single-feed network, and can also realize on-antenna power combining. In this work, a planar series-fed linear antenna array is taken as an example. By tapering the patch width, the desired radiation pattern is synthesized according to the Dolph-Chebyshev magnitude distribution. Then chip is flip-chipped onto the dual-feed network connecting with antenna array. Broadband flip-chip interconnection between chip and dual-feed network is achieved by properly designing the grounded coplanar waveguide (GCPW) line on PCB. The proposed flip-chip packaged antenna array based on dual-feed network has great potential for automotive radar.
Platoon String Stability: A Passivity Perspective

String stability is a vital property of vehicle platoons which ensures disturbances of system states are not amplified along the string of vehicles. In this paper, we discuss string stability in the frequency domain showing the platoon as a cascade of linear time-invariant subsystems. We show that a sufficient condition for string stability is that the Nyquist plot of the transfer function of each subsystem is within the unit circle. Also, an energy-based notion of string stability based on passivity is derived by showing output strict passivity as a bridge between passivity and string stability of a vehicle platoon. By constraining the output strict passivity index of each subsystem (vehicle) in a string to one or greater than one through proper control strategy, the condition for string stability is met. This is validated through numerical simulations.
Low-Power 4-Trit Current-Steering DAC for Ternary Data Conversion

A current-steering ternary DAC is proposed to reduce the power consumption and size while retaining better resolution than conventional binary DACs. By applying the method proposed in this paper, a 4-trit ternary DAC is designed. It operates at 100MHz sampling rate and 1.8V supply voltage, and is implemented in 180nm CMOS technology. Compared to 6-bit binary DAC [5], it reduces power consumption by 31.69% to 30.64 %, and reduces area by 75.48 %.
A Lightweight DNN for ECG Image Classification

Recent advances in the field of AI have proved that deep neural networks perform and recognize arrhythmia better than cardiologists when trained with a large chunk of data. However, despite the better performance, deep neural networks demand more resources. Therefore, in this paper, a new deep neural network using low resources has been proposed while maintaining high performance, and it is enhanced with a depthwise separable convolution layer for Electrocardiogram (ECG) classification. The algorithm is performed on the Physikalisch-Technische Bundesanstalt (PTB) diagnostic dataset taken from Physionet consisting of two classes: Myocardial Infarction (MI) and Normal (N). Our simulation results show that the proposed lightweight DNN provides high performance with almost the same accuracy as conventional SquezeNets.
BenzoCycloButene-based in-Package Substrate Integrated Waveguides for sub-THz Applications

This paper introduces an experimental characterization of substrate integrated waveguide (SIW) components integrated in a benzocyclobutene-based interposer for WR10-band applications. High performance SIWs were experimentally validated, with a measured attenuation constant of 0.39 dB/mm and a quality factor of 27 at 90 GHz. The attenuation constant remains equal to 0.4 dB/mm between 85 GHz and 110 GHz and the quality factor reaches 40 in the upper end of the band. These results show the benefits offered by using benzocyclobutene 3D packaging for the realization of high performance passive circuits with lower cost and higher electrical performance as compared to standard CMOS technologies and concurrent packaging technologies.
Design of Quasi-Reflectionless Filters with Simple Topologies

An analysis and design method on a simple quasi-reflectionless (QR) filter topology is proposed. The topology of single-port QR filter is composed by a pair of coupled lines with bandpass response and a cascaded structure with bandstop response. The single-port QR bandpass filter (BPF) and bandstop filter (BSF) can be realized by replacing the corresponding port with lossy resistance in filter topology, and both of them have identical QR property. Finally, a two-port QR BPF is further analyzed and simulated, with good filtering performance and QR property.
A Dictionary-learning-based Denoising Algorithm with log-regularizer for MR Image

With the wide application of magnetic resonance imaging (MRI) technology in the medical field, MR image denoising draws a lot of research attention. The dictionary learning methods based on sparsity representation analysis models have been developed for image denoising recently. Despite these methods solve a class of challenging nonconvex and nonsmooth, it remains an hot topic to find a dictionary learning method that is not only empirically fast, but also has mathematically guaranteed strong convergence. In this paper, we employ log-regularizer instead of $\ell_{0}$ norm and $\ell_{1}$ norm sparsity regularizer, and than we propose a novel dictionary-learning-based denoising algorithm with log-regularizer for MR image. To solve the optimization problem efficiently, we divide MR image into local image patches. And then, we decompose the overall problem in matrix form into subproblems in vector form. In the final, we adopt alternating optimization scheme to update sparse vectors, dictionary atoms and the reconstructed MR image alternately. In addition, proximal operator algorithm and the least square method are employed to obtain the solutions of sparse vectors and dictionary atoms, leading to an efficient and fast algorithm. More importantly, a theoretical analysis shows the proposed algorithm satisfies the global convergence property. Experiments also show that the proposed algorithm achieves better results compared with other dictionary-learning-based denoising algorithms.
Coupled-Resonator Bandpass Power Dividers Based on Connected-Coupling Mechanisms

The bandpass power dividers designed based on the coupled-resonator approach using connected-coupling mechanism are proposed in this study. The resonator tanks are inserted into appropriate nodes of the transmission-line power divider and the quarter-wave transformers are utilized as coupling elements for coupled resonators. The circuit design parameters required can be completely acquired through the provided analytical design formulas. Specifically, two 2nd-order filtering power dividers are designed and verified thus validating the developed design approach. The simulation and measurement results show satisfactory agreement.
Mapping Surface Deformation Over Tatun Volcano Group, Northern Taiwan Using Multitemporal InSAR

The Tatun Volcano Group (TVG) is located at the northern coast of Taiwan Island with only 15 km to the Taipei metropolis. Recent geothermal and geochemical studies suggest that the TVG is dormant-active rather than extinct, implying the eruption potential to devastate the nearby area of 7 million inhabitants. Although some geodetic tools (e.g., global positioning system and precise leveling) have been utilized to analyze the activity associated with volcanism, it is still challenging for conventional interferometric synthetic aperture radar (InSAR) technique to obtain clear ground surface movement at the TVG due to decorrelation and complex atmospheric delay. In this study, we present an improved multi-temporal InSAR (MTInSAR) approach to explore the temporal evolution and spatial extent of displacement at the TVG from 19 L-band ALOS/PALSAR images acquired between 2007 and 2011. Stratified atmospheric delays and orbit error are corrected with a patch-based joint model as different phase components can be separated according to their distinct spatiotemporal characteristics. The spatial deformation patterns indicate an uplift of 10 mm/year at the SW-NE ridge and subsidence with a rate of 10 mm/year at the E-W ridge. The temporal deformation variations at Mt. Chihshin and Huangzuei have high similarity with correlation coefficients of 0.9 above. This indicates that the subsidence at Mts. Chihshin and Huangzuei might be caused by released hydrothermal fluids related to tectono-magmatic activity within the hydrothermal system beneath the TVG.
Establishing Realistic Testbeds for DC Microgrids Studies Validation: Needs and Challenges

Microgrids are expected to be the skeleton of future modernized electrical grids, and they are receiving increased attention due to their advantages over conventional electrical grids. This paper presents the major needs and challenges of establishing realistic and accurate experimental DC microgrids testbeds. In addition, a DC microgrid experimental setup is built using combined Power-Hardware-in-the-Loop (PHIL) and controller-in-the-Loop (CIL) typology, where the dynamics of renewable energy sources and storage devices are considered. The experimental DC microgrid testbed consists of a real-time digital simulator (RTDS) that communicates with a dSPACE MicroLabBox controller via Ethernet connection, which eliminates the need for physical connections between the two. Moreover, the control of the energy sources in the DC microgird is improved by the application of result adaptive proportional integral control. The adaptive controller enhances both transient and steady-state performances of the bidirectional dc-dc converters used to control the power flow of the energy sources in the DC microgrid. The real-time simulation and experimental results show the accuracy of developed DC microgid testbed and its feasibility for expansion and validating advanced microgrids studies.
250 GHz SiGe SPDT Resonator Switch

This work demonstrates a single-pole double-throw resonator switch designed at 250 GHz in 0.13-µm SiGe BiCMOS technology with ft/fmax of 300/500. The resonator switch demonstrates a minimum measured de-embedded insertion loss of 4.2 dB, maximum isolation of 29 dB and minimum input and output reflection coefficient of 16 dB and 20 dB, respectively. The resonator utilizes reverse saturated HBTs.
Dual PWM Control for High Step-Up DC-DC Converters

A dual PWM control scheme is presented to design the high step-up DC-DC converter. Both high frequency and low-frequency PWM waveform generators are utilized to synthesize the required dual PWM control. This resulting PWM waveform will lead to various switching cycles. Five operation modes will be defined accordingly. The basic operational principle of the proposed converter and the corresponding small-signal switched model are studied in details. The high step-up conversion ratio can be achieved as the duty cycle of the high-frequency PWM is exactly equal to that of the low-frequency PWM through exploring the voltsec balance condition. Simulation studies and hardware prototype implementations are conducted to validate the proposed design with satisfactory performance.
Respiratory Frequency Estimation Method Based on Periodic Features Using UWB Radar

In this paper, we propose an algorithm for adaptively extracting respiratory waveform and estimating respiratory rate in different target states based on ultrawideband (UWB) radar. At present, the respiratory rate can be estimated in most algorithms only when the target is stationary. The proposed algorithm performs target state determination through fast time and slow time matrices respectively. The two detection procedures are cascaded to determine the target's state (namely, target absence, motion and breathing) and the human breathing area. In the following, the proposed algorithm adaptively extracts the respiratory waveform through the features of respiratory periodicity, which can overcome the shortcoming caused by the maximum energy range bin approach in the case of low signal-noise ratio (SNR). Finally, the respiratory frequency is estimated by the frequency time phase regression (FTPR) method. The experimental results show that the mean square error (MSE) between the estimated respiratory rate and the result of the multi-channel physiological recorder is 0.4664 breathvmin,
A Sub-1-mW Fractional-N Phase-Locked Loop For Mixer-Based Wake-up Receiver In Wireless Sensors

This paper presents a 750 µW fractional-N Phase-Locked Loop (PLL) for Wake-up Receiver (WuR) architecture. The frequency synthesizer operates from 1.5 to 2.3 GHz and the proposed quadrature phase generator provides four local oscillator signals with the frequencies of 263 MHz, 433 MHz, 868 MHz, and 920 MHz. Several techniques are adopted to facilitate ultra-low-power operation. Inside the Voltage-Controlled Oscillator (VCO), the inductance for the resonance is maximized to provide low power consumption and the capacitor banks are optimized to cover the whole frequency range considering process, voltage, and temperature variations. Controllable tail transistors adjust the current consumption of the VCO and prevent swing reduction due to the large equivalent capacitance of the capacitor banks at the lower frequencies. Furthermore, the power consumption of the digital parts is reduced by operating with a lower supply voltage generated by an on-chip voltage regulator. The PLL is implemented using a 60 nm CMOS process with a core size of 0.5 mm × 0.7 mm. The whole PLL consumes 750 µW and the VCO offers the phase-noise performance of -93.9 and -116.1 dBc/Hz at 100 kHz and 1 MHz offset frequencies from the carrier frequency of 1.85 GHz.
A 400-GHz Octagonal-Slotted Dielectric Resonator Antenna with 10 dBi Gain in 0.13-μm CMOS SOI

This paper presents the design of a 400-GHz integrated dielectric resonator antenna (DRA) in 0.13$-\mu$m CMOS SOI technology. A substrate integrated waveguide (SIW) cavity type on-chip antenna is loaded with complementary open-loop octagonal-shape slot resonator to enhance the gain and radiation efficiency of the antenna. A low dielectric constant Teflon substrate and a high permittivity ceramic substrate are stacked on the antenna to further improve the directivity and radiation efficiency. The proposed antenna shows a peak gain of 10 dBi and radiation efficiency 55% at 400 GHz in full-wave simulation. The overall antenna has a compact size of 0.88$\times$ 0.88mm2.
A Flexible Wearable Linear-to-Circular Polarizer for GNSS Application

This paper presents a single-layered fabric-based flexible linear-to-circular polarizer for GNSS application operating at 1.575 GHz. The structure presented here is based on a square aperture with an E-shaped patch structure on the reverse side. The size of the structure is 0. 21λ0 ×0. 26λ0 × 0. 01λ0 The complete structure is flexible, and the frequency of operation is centered at 1.575 GHz, with a minimum value of the axial ratio achieved is 0.06 dB. The 3 dB axial ratio fractional bandwidth is 3.81% (1.54-1.60 GHz) and the conversion efficiency fractional bandwidth covering 90% is 5.09% (1.53 to 1.61 GHz).
User-Preference-based Proactive Caching in Edge Networks

Recently, with the rapid growth of data traffic, caching in the edge networks is considered a promising approach which provides low latency and improves user’s quality of service (QoS). However, user preference diversity can be a challenge for developing an effective caching algorithm with limited cache capacity. In this paper, we propose a proactive caching scheme considering user preferences to maximize the cache hit ratio using long short-term memory networks (LSTM). First, each demographic user group is trained on an LSTM model for predicting user demand for movie genre. Then, the results are combined by averaging to obtain the average demand over user groups to generate an efficient caching policy. The experimental results show that our caching algorithm outperforms benchmark schemes in terms of the cache hit ratio. The proposed control provides up to 35% higher cache hit ratio than benchmark algorithms and near-optimal cache hit ratio within around 12% of the optimal scheme with perfect prior knowledge of movie popularity.
A 30-36.6 GHz Low Jitter Degradation SIL QVCO with Frequency-tracking Loop in 65 nm CMOS for 5G Frontend Applications

In this paper, a low jitter degradation subharmonically injection-locked (SIL) quadrature voltage-controlled oscillator (QVCO) with frequency-tracking loop is presented using 65 nm CMOS process for 5G frontend applications. The QVCO is designed using a modified self-injection coupling technique to enhance the quadrature accuracy. An analog-based frequency-tracking loop is employed in the QVCO to adaptively align the control voltage. As the subharmonic number is 4, the locking frequency is from 30 to 36.6 GHz with a 19.6% fractional bandwidth. The phase noise at 1 MHz offset is −130.3 dBc/Hz, and the jitter integrated from 1 kHz to 40 MHz is 8.7 fs with a degradation of within 7 fs. When the temperature is between 20°C and 70°C, the variations of phase noise, jitter, output power are within 2.5 dB, 5 fs, and 1.5 dB, respectively. The quadrature errors are within 0.5 dB and 0.9°.