Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanism Analysis of Particle-Triggered Flashover in Different Gas Dielectrics Under DC Superposition Lightning Impulse Voltage

When DC GIL in operation endures the lightning impulse voltage, the charge accumulation at the gas-solid interface area will seriously affect the insulation performance of the spacer. Considering that gas side conduction is one of the important factors affecting charge accumulation, for the purpose of clarifying of the insulation characteristics of gaseous medium in the flashover process of gas-solid interface, an experimental platform for simulating the working conditions of the spacer is built. The spacer flashover tests were carried out with and without aluminum particle in SF6, 4% C3F7CN /96% CO2 and 20% SF6/80% N2 gas mixture. The measurement and analysis of surface potential distribution behavior of the spacer was conducted. The experiment results show that the gas dielectric is not the factor which dominate the potential distribution process without aluminum particle, and there is little difference in potential distribution with various gaseous conditions. When the linear aluminum particle appears on the surface of the insulator, it will cause severe electric potential distortion and these potential distorted areas are located around the end of the metal particle near the central conductor, and along with flashover pathway. It has also demonstrated that the gaseous dielectric has influence on the surface charge accumulation behavior especially with metallic particle adhere to spacer surface. Under the C3F7CN/CO2 gas mixture, the surface flashover voltage decrease percentage is about 16.82% and may be lower. Besides, the insulation strength of the gaseous dielectric itself is also a key factor affecting flashover.
Adaptive impedance control with trajectory adaptation for minimizing interaction force

In human-robot collaborative transportation and sawing tasks, the human operator physically interacts with the robot and directs the robot’s movement by applying an interaction force. The robot needs to update its control strategy to adapt to the interaction with the human and to minimize the interaction force. To this end, we propose an integrated algorithm of robot’s trajectory adaptation and adaptive impedance control to minimize the interaction force in physical humanrobot interaction (pHRI) and to guarantee the performance of the collaboration tasks. We firstly utilize the information of the interaction force to regulate the robot’s reference trajectory. Then, an adaptive impedance controller is developed to ensure automatic adaptation of the robot’s impedance parameters. While one can reduce the interaction force by using either trajectory adaptation or adaptive impedance control, we investigate the task performance when combining both. Experimental results on a planar robotic platform verify the effectiveness of the proposed method.
2.5 to 10.0 GHz Band-Pass Non-Uniform Distributed GaN MMIC HPA

This paper reports on a wideband Gallium Nitride (GaN) Monolithic Microwave Integrated Circuit (MMIC) high power amplifiers (HPAs) operated in S to X bands. Two band-pass non-uniform distributed power amplifiers (NDPAs) are designed to obtain wideband and high power characteristics. One is a single-ended HPA which demonstrates output power of 17 to 26 W, power added efficiency (PAE) of 24 to 44% across 2.5 to 11.0 GHz with chip size of 4.2 mm2. The other is a two-way combined HPA which demonstrates output power of 27 to 61 W, PAE of 24 to 43% across 2.5 to 10.0 GHz with chip size of 9.6 mm2.
Geotecnologias na identificação de fatores ambientais relacionados à ocorrência da leishmaniose visceral americana em Conde, Bahia, Brasil

This study had as a goal to use geo-technologies in the identification of environmental factors associated with the space distribution of American visceral leishmaniasis in the municipality of Conde, Bahia, Brazil. During the period of study, 42.6% of the reported cases occurred in localities with normalized difference vegetation indexes of 0.67 to 0.75. The digital elevation model showed an inverse relationship between altitude and disease, suggesting that there is a higher concentration of flebotomines in the low-lying areas of the municipality. The land cover and land use map illustrated the predilection of the vector for areas with sparse vegetation and the tendency of this disease urbanization. This study points out the necessity for the development of multidisciplinary research regarding landscape epidemiology in association with geo-technologies for the identification of the factors associated to endemics and its risk areas.
Voice Recognition Using K-Means Clustering Based on Hidden Markov Model

Ortolan Bunting bird has various song-types. For time being, there are not so many systems which automatically cluster the song-type of Ortolan Bunting bird. Speech recognition is one example of technology development in the 20th Century which uses voice as the input. This research builds an automatic system to cluster the song-type of Ortolan Bunting bird automatically using K-means clustering algorithm based on Hidden Markov Models (HMM). Commonly, HMM is used on signal processing and for speech and speaker recognition on human voice. This research uses 5 song-types of bird, and every song-type is represented by 100 songs. The data will be the clustering using K-means based HMM with 3 feature extractions and the result validation employs index stability computation. The clustering parameter groups the data into 5 clusters with dissimilarity value of 8.2 %. It means that for several times of experiments there are 8.2 % data clustered into different group and 91.8% of cluster members which always gather in the same cluster. The highest similarity level was obtained using Greenwood function cepstral coefficients delta-acceleration (GFCC_D_A) feature with 36 parameters.
A Survey on Blockchain-based Identity Management and Decentralized Privacy for Personal Data

In the digital revolution, even secure communication between individuals, services and devices through centralized digital entities presents considerable risks. Having service providers continue to offer their centric solutions is inefficient in terms of duplication, has serious security lacunae and is cumbersome to the users. The self-sovereign Identity concept, which includes the individual’s consolidated digital identity and verified attributes, enables the users of data to exert their ownership and gain insights from their data’s usage. The authentication and verification of digital identity is essential to achieve the privacy and security of distributed digital identities. In this paper, we provide a coherent view of the central concepts of self-sovereign Identity, including the components of identity proofing and authentication solutions for different self-sovereign Identity solutions. We discussed an overview of Identity management approaches, introducing an architecture overview as well as the relevant actors in such a system and blockchain technology as solution for distributed user-centric identity. Finally, we discuss the existing solutions and point out the research gaps and elaborate challenges and trade-offs towards building a complete identity management system.
A New Design for Low Drop-Out Regulator With Broadband High Power Supply Rejection

This paper designs a high power supply rejection (PSR) and capacitor-less low drop-out (LDO) regulator that can be used for radio frequency (RF) modules. Its stability is guaranteed by a Miller-like compensation circuit with transient enhancement and a zero-point generation circuit. A PSR enhancement circuit module is used to effectively improve the PSR of high frequency. Based on the TSMC 0.13 pm RF CMOS technology with a power supply of 1.2 V, simulations were performed using the Cadence tool Spectre. The results show that the phase margin of the system is about 70° at no load, and the phase margin of the 1 rnA-100 mA load is above 80°, and the loop is stable; The drop-out voltage is 200 mV when delivering 100 mA to the load; In the range of 0.1 kHz to 8 MHz, the PSR is better than -40 dB, and in the range of 0.1 kHz to 1 MHz, the PSR is better than -50 dB.
Distributed H∞ Filtering Over Sensor Networks Subject to Randomly Occurred Nonlinearity and Time-Varying Topology

This article is concerned with the distributed <inline-formula> <tex-math notation="LaTeX">$H_{\infty } $ </tex-math></inline-formula> filtering problems with consensus for a class of systems subject to randomly occurred nonlinearity and time-varying topology in sensor networks where the nonlinearity considered can include the cyber attacks as a special case. A group of Bernoulli distributed random variables are utilized to describe the varying topology and missing measurements in a unified framework. In terms of two-dimensional (2-D) system theory in Rosser model, a nonlinear two-step filter is designed with consensus protocol where a multiple data strategy is used to improve the system performance. The desired filter parameters are obtained by LMI technique such that the filtering error system is asymptotically stable in the sense of mean square and meets a prescribed average <inline-formula> <tex-math notation="LaTeX">$H_{\infty } $ </tex-math></inline-formula> performance level. Finally, a simulation example demonstrates the effectiveness of the proposed algorithm.
A Feasibility Study on the Use of Microwave Imaging for In-Vivo Screening of Knee Prostheses

This article provides a concept study on the feasibility of microwave imaging for in vivo screening of knee implants. Using microwave imaging for condition monitoring avoids patients' exposure to X-ray, which is hazardous to human health. Therefore, investigating the potentials of such a technique is worthwhile. Two essential aspects were investigated in the study: 1) the propagation properties of human tissue and 2) the imaging capabilities of microwave synthetic aperture radar (SAR) for screening polyethylene knee inlays. The first point addresses the challenge of strong absorption in tissue, which contains a high percentage of water. Quantitative investigations were performed. For imaging, SAR with a cylindrical synthetic aperture was constructed to account for the convex geometry of the human knee. An imaging concept that considers material properties and refraction was developed to yield a highly focused image. From the results of the two issues, an imaging concept was deduced that could enable a microwave-based screening of the human knee in the future.
A Virtual Reality-Based Framework for Enhancing Walking abilities Using Exoskeleton

This article is to develop virtual reality-based framework for enhancing walking abilities using exoskeleton robotics. On one hand, China will face an ever-increasing and unprecedented demand for rehabilitation treatment and training for a long period of time in the future; on the other hand, backward and shortage of rehabilitation training resources urgently need to be rapidly upgraded through scientific and technological progress. A lightweight and intelligent system for indoor walking abilities rehabilitation training that combines virtual reality and exoskeleton robotics will effectively improve the rehabilitation training conditions, efficiency and effects through scientific and technological means. Through in-depth analysis and tracking of the training plan, combined with the research results of gait theory, the article describes a customized exoskeleton with VR glass and local cloud, and the sensing process, virtual scene establishment and presentation, human-robot interaction mechanism, virtual training and performance evaluation, and constraints are elaborated. Large-scale system testing and data collection and analysis, and the heterogeneity of rehabilitation training with this method will be the focus of future research.
Gender Differentiated Convolutional Neural Networks for Speech Emotion Recognition

This paper proposes a two-stage gender-differentiated system for Speech Emotion Recognition using Mel-frequency Cepstral Coefficients and Convolutional Neural Networks. Acoustical variances between male and female speakers pose a problem and it is established that gender-dependent emotion recognizers perform better than gender-independent ones. The provided solution can recognize seven emotions (anger, disgust, fear, happiness, sadness, surprise, and neutral state). Data augmentation is used to compensate for the lack of quality data, with the raw speech samples derived from four datasets, namely: RAVDESS, CREMA-D, SAVEE, and TESS. The system is composed of two stages: 1) gender classification and; 2) emotion classification. The output of the gender classifier in the first stage determines the gender-specific classifier for the second stage. The experimental evaluation displays the performance in terms of the correct emotion recognition rate of the proposed SER model. The results demonstrate that a gender-differentiated system significantly improves performance. The obtained results also show that using Global Average Pooling instead of a fully-connected network at the end of the CNN classifier further improves the performance. Future implementations of this proposed system may allow effective human-computer intelligent interaction.
Considerations Regarding Simulator Design for Electromagnetic Measurement Systems

In this paper a concept for a simulation specialized in electromagnetic wave interaction on multiple scales is proposed. The approach is based on the complex source point beam (CSPB) expansion of the electromagnetic field. Based on the CSPB expansion, a domain decomposition which enables efficient multi scale simulations is used. Furthermore, each of the basis functions for the expansion is highly directive which has significant advantages, because it reduces the amount of interactions that need to be considered.
A Synthesis-Based Design Procedure for Waveguide Duplexers Using a Stepped E-Plane Bifurcated Junction

A novel design procedure for waveguide duplexers using stepped E-plane bifurcated junctions is presented. First, a simple model of this junction is devised, suited for the synthesis of star-junction diplexers (a novel procedure has been developed). The characteristic polynomials of the channel filters obtained by this procedure are then employed for the synthesis of the channel filters. To allow transmission zeros in the response, an in-line topology with frequency-dependent (resonant) couplings is adopted. The filters are synthesized with a recently proposed technique (here adapted for waveguide implementation). Furthermore, a new type of resonating coupling structure is adopted (the stopband singlet), allowing the positioning of the transmission zeros very close to the passband. The novel design technique is demonstrated with a Ka-band duplexer for satellite applications.
Guidelines for Using Machine Learning Technology to Ensure Information Security

Artificial intelligence is a technology that allows you to automate and optimize any process in all areas of human life. Machine learning allows you to create irreplaceable and highly effective assistants that can perform various actions, even those that cannot always be performed by humans. The use of this technology in the field of information security today is a promising and actual tasks for solution, development and implementation, since every day more and more serious threats to cyberspace appear, new vulnerabilities of web pages and operating systems and even antivirus programs are found, and often a person does not have time to track all of them. This is why using automated assistants to track potential threats and attacks can reduce the risk of breaches and information leaks for virtually any enterprise and company.
Microcontrollers for IoT: Optimizations, Computing Paradigms, and Future Directions

Internet of Things (IoT) is a paradigm covering almost every area of life, from education to health, from services to products, and from home to smart cities invading any area in which IoT is applicable, like automotive, infrastructure and business. But many challenges remain to be met, ranging from sensor energy autonomy, to data security, to interoperability of numerous objects. The high computation capability is a crucial contributor to the progress of IoT solutions. So maximizing the processing resources in a single CPU. This paper reviews the recent microcontrollers architectures employed in the context of wireless sensor networks and IoT, and outlines many of the low-power techniques allowing a wide range of applications. An overview of the foremost recent research topics and future trends are also discussed.
Development and Evaluation of Mixed Reality Co-eating System: Sharing the Behavior of Eating Food with a Robot Could Improve Our Dining Experience

Eating with others enhances our dining experience, improves socialization, and has some health benefits. Although many people do not want to eat alone, there is an increase in the number of people who eat alone in Japan due to difficulty in matching mealtimes and places with others.In this paper, we develop a mixed reality (MR) system for coeating with a robot. In this system, a robot and a MR headset are connected enabling users to observe a robot putting food image into its mouth, as if eating. We conducted an experiment to evaluate the developed system with users that are at least 13 years old. Experimental results show that the users enjoyed their meal and felt more delicious when the robot ate with them than when the robot only talked without eating. Furthermore, they eat more when a robot eats, suggesting that a robot could influence people’s eating behavior.
Rapid Generation of Emergency Response Plans for Unconventional Emergencies

Unconventional emergencies can lead to unforeseen disastrous penalties. Due to their unrepeatable, complex, and unpredictable nature, it is generally hard to establish high-quality Emergency Response Plans (ERPs) for unconventional emergencies, thus posing great challenges for unconventional emergency response. This work proposes a rapid ERP generation approach for unconventional emergencies so as to provide support for emergency decision-making. The generation of ERPs is achieved by exploitation of existing ERPs that contain much emergency response experience. First, a number of ERPs are collected and structurally organized to construct an ERP repository. Then, the applicability of each ERP segment in the repository to a given unconventional emergency is evaluated by a proposed ERP similarity measure and emergency scenario matching mechanism, in which the semantic relevance and the scenario consistency of an ERP segment are taken into account, respectively. Applicable ERP segments are obtained for each section of ERPs, and combined to form a new ERP with the guidance of pre-defined ERP structure. Furthermore, we design an ERP assessment method and perform a case study on the proposed approach which presents encouraging experimental results.
A 24 - 30 GHz Ultra-Compact Phase Shifter Using All-Pass Networks for 5G User Equipment

This work presents a 24–30 GHz phase-shifter with 0.028 mm2 of area for 5G mobile applications. The small size is achieved by employing variable-phase all-pass networks, which enables the embedding of switches within all-pass networks when implementing switched-type phase-shifters. The proposed PS was implemented and manufactured using 0.25 µm BiCMOS. Measurements were performed, showing an insertion loss of 4.49 ± 0.27 dB at 27 GHz, an RMS gain error below 0.5 dB and an RMS phase error below 7° across the whole frequency band.
Maximum Likelihood Detection in the Presence of Non-Gaussian Jamming

We consider a scenario in which a transmitter sends complex symbols drawn from multi-dimensional constellations to a receiver in the presence of a jammer emitting proactively and continuously a zero-mean complex Gaussian signal over an unknown complex Gaussian channel. The complex Gaussian signal transmitted over the unknown complex Gaussian channel induces a non-Gaussian signal at the receiver. For this scenario, we develop the optimal maximum likelihood (ML) detector for cases corresponding to whether the receiver has full channel state information (CSI), full channel distribution information (CDI), or partial CDI about the transmitter channel. The jammer CDI is assumed to be either partially or fully available at the receiver. Using the derived likelihood expressions, we identify cases in which the non-Gaussian signals resulting from the jammer's transmission can be approximated by Gaussian signals without affecting the efficacy of the ML detector. In these cases, we show, analytically and numerically, that the exact and Gaussian approximation detectors are equivalent, but the ML detector based on the Gaussian approximation is computationally superior to its exact counterpart. Furthermore, we identify cases in which the Gaussian approximation ML detector is not equivalent to the exact ML detector. In these case, our numerical results suggest that the advantage of the exact ML detector over the Gaussian approximation one can be significant.
Optimization of a Balanced Antipodal Vivaldi Antenna for Dual Polarization Ground Penetrating Radar

In this work, a novel Balanced Antipodal Vivaldi Antenna (BAVA) with 3 Elliptical Slots at the Edges (ESE) is proposed for application in a Dual Polarization Ground Penetrating Radar (DP-GPR). The several antenna parameters were optimized such as; bandwidth which was increased by lowering the Lower Cutoff Frequency (LCF) to 0.379 GHz; Cross-Polarization (CP) was reduced to less than -160 dB and the realized gain was increased by 224.9% at low frequencies and by 49% at mid frequencies. The antenna was designed and simulated on FR4 in a commercial electromagnetic field simulator.
Noise Immunity evaluation for DPSK-k non-coherent receivers (SISO and MIMO cases)

The amount of different environments where wireless communications is required has grown significantly, channel estimation has been known to be the path to take, but the necessity of Multiple-Input Multiple-Output (MIMO) systems has created a complex process of demodulation for the coherent paradigm. Non-coherent receivers achieve data detection without the overhead and computational complexity required by pilot-based reception mechanisms. Additionally, difference modulation has some interesting properties of invariance that may be used against Doppler shifts and Carrier Frequency Offset. That is why, having an analytical approximation of the probability of error in terms of Bit Error Rate (BER) will be very useful. In this work, Chernoff Boundaries are proposed for an autocovariance receiver, which are easily scalable to any order of difference modulation. Also, the upper bound proposed could be calculated even when there is diversity at the receiver, that could be in time, frequency or space.
Integrating a Social Robot in Higher Education – A Field Study

The benefits of social robots in educational contexts were mainly investigated with children, but also bear great potential to support learners and teachers in higher education. To further explore the potential of social robots in the context of university teaching, we implemented a robot-supported learning environment as a complementary training to a university course. To learn more about the students’ perspective and attitudes towards the integration of robots in their education, we conducted a field study with qualitative interviews as data collection method. Our results show a clear positive perception of the robot-supported learning environment, and indicate a positive impact on the learning outcomes. Most students suppose an additional value in the presence of the robot compared to traditional on-screen scenario or self-study, and perceived the robot to increase their motivation, attention and concentration. We found a clear interest of the students to use the learning environment again in the future. However, more individualized feedback was desired.