Miracle-dz/UniFAR-FTUs huggingface dataset:
Synchronous Sampled Data Modal Control and Stabilization of Linear Periodic Processes with Control Signal Delay

The article considers a single-loop MIMO system with a linear T-periodic continuous process and a digital controller with a sampling time T in the presence of a control signal delay. The necessary and sufficient conditions for the modal controllability are given. The problem of stabilization in the absence of controllability is taken into account.
CMOS Voltage Differencing Transconductance Amplifier with Linearly Adjustable Transconductance Gains

In this work, a circuit configuration for the realization the CMOS voltage differencing transconductance amplifier (VDTA) with linear tunable transconductance and wide-input dynamic range is introduced. The circuit design technique is achieved by squaring the long-tail bias current of the differential-input voltage-to-current converter circuit. In addition, the linearity region of the input signal is also improved by using source degeneration technique. The workability of the proposed linearly tunable VDTA has been shown on the construction of the electronically controllable first-order allpass filter circuit. The proposed circuit and its application are investigated and simulated with PSPICE software using TSMC $0.25-\mu \mathrm{m}$ CMOS technology.
Cardiac monitoring with a smart textile based on polymer-encapsulated FBG: influence of sensor positioning

In recent years, wearables are exploding in popularity as unobtrusive devices able to extend traditional healthcare delivery systems. Smart textiles are one of the main innovative types of wearables used for non-invasive and continuous monitoring of cardiac activity. A prominent solution is based on the detection of vibrations induced on the chest surface by the heart beating (i.e., precordial motions). In the literature, different sensor positions have been investigated, but it appears to be a lack of accepted standard points for the detection of heart-induced motions. In this work, a smart textile based on fiber Bragg grating (FBG) sensor has been proposed to detect the precordial motions on the chest. The feasibility of the smart textile for cardiac monitoring has been evaluated on three volunteers at three measurement points. Then, the influence of the measurement site on the response of the smart textile has been preliminarily assessed in terms of peak-to-peak amplitude of the signal. The signal amplitude is greater than the noise, so it allows detecting precordial motions. These promising results foster future investigations on the capability and performance of the system in estimating heart rate. Further tests will also be devoted to finding out the optimal measurement points to standardize the sensors positioning in this specific application.
Accuracy Enhancement of Total Force by Capacitive Insoles

A coherent understanding of plantar pressures is crucial in the field of sports research and clinical studies. Real-time and dynamic analysis of plantar pressures require sensors that are in a wearable form factor. Sensor insoles built on a variety of principles satisfy this condition. The accuracy of total force provided by commercially available sensor insoles is significantly low compared to that provided by force plates, the gold standard for force measurements. The current work discusses the limitations of insole based force measurement from the design standpoint alone. We further propose a learning-based model to improve the accuracy of the capacitive sensor based insoles for the task of total force measurement. A learning-based model is developed by training on data collected from sensor insoles for loads varying from 0 to 80 kg on each insole. The absolute mean percentage error of left and right soles of specific sized capacitive insoles as compared to the gold standard has reduced from 8.01 to 5.19 and 35.85 to 21.64 respectively. The learning based model has shown promising results providing a reliable scope towards the extension of the work under variable foot anatomies and pressure distributions.
Temperature dependence of the shear viscosity of mineral oils and natural esters

Over the past years, there has been an increasing interest in natural ester insulating liquids for application in power transformers, thanks to their higher environmental compatibility and lower fire point, as compared to conventional mineral oils. The main function of a transformer oil is its ability to dissipate heat, while ensuring electrical insulation. Among the various influencing parameters, it is well known that heat exchange in a liquid is also affected by its viscosity. Thus, the temperature dependence of the viscosity of an insulating oil should be carefully considered in the design of the cooling system of a power transformer. In this study the variation of the dynamic viscosity with temperature of commercially available natural esters and mineral oils is compared. Steady state rheological measurements are carried out, through a controlled shear rate rotational rheometer, in the 20°C ÷ 100° temperature range, under isothermal conditions. Temperature ramps are also performed, while fixing the shear rate, with the aim of investigating the variation of the steady shear dynamic viscosity over the whole temperature range. Results demonstrate that the viscosity of natural esters, though being higher at low temperatures, compared to mineral oils, strongly decreases for higher temperatures, thus favouring heat transfer and reducing the risk of hot-spots, which might lead to insulation-failures.
Optimal experiment design for static polynomial approximation of nonlinear systems

Most real systems do not belong to a known model class and thus identification boils down to approximation. Universal approximators are often used, e.g. polynomial nonlinear models whose number of parameters tends to increase very fast with the model complexity. In view of the potentially high number of parameters to be identified and more in general to the nonlinearity, choosing the appropriate excitation is not trivial but indispensable. In this paper, we consider a simplified setup limited to static polynomial systems. We show the limits of classical design of experiments (DOE) in terms of prediction error even for this simple case. Against this background, we first suggest to use a more suitable optimization criterion based on the prediction error and show that it is a generalization of the well-known V-optimality criterion, if the system belongs to the model class. Second, we show that it makes sense to design the excitation on the basis of a higher degree model than the one to be identified. NOx emission measurements from a BMW 2-liter Diesel engine are used to confirm this approach.
An Efficient Seismic Data Acquisition Based on Compressed Sensing Architecture With Generative Adversarial Networks

Recently, large scale seismic data acquisition has been a critical method for scientific research and industrial production. However, due to the bottleneck on data transmission and the limitation of energy storage, it is hard to conduct large seismic data acquisition in a real-time way. So, in this paper, an efficient seismic data acquisition method, namely, compressed sensing architecture with generative adversarial networks (CSA-GAN), is proposed to tackle the two restrictions of collecting large scale seismic data. In the CSA-GAN, a data collection architecture based on compressed sensing theory is applied to reduce data traffic load of the whole system, as well as balance the data transmission. To make the compressed sensing procedure perform well in both data quality and compression ratio, a kind of generative adversarial networks is designed to learn the recovering map. According to our experiment results, a high data quality (about 30 dB) at the compression ratio of 16 is achieved by the proposed approach, which enables the system to afford 15 times more sensors and reduces the energy cost by means of data collection from N(N + 1)/2 to N2/16. These results show that the CSA-GAN can afford more sensors with the same bandwidth and consume less energy, via improving the efficiency seismic data acquisition.
SEABIG: A Deep Learning-Based Method for Location Prediction in Pedestrian Semantic Trajectories

Pedestrian destination prediction of a user is known as an important and challenging task for LBSs (location-based services) like traffic planning and travelling recommendation. The typical method generally applies statistical model to predict the future location based on the raw trajectory. However, while predicting, existing approaches fall short in accommodating long-range dependency and ignore the semantic information existing in the raw trajectory. In this paper, we proposed a method named semantics-enriched attentional BiGRU (SEABIG) to solve the two problems. Firstly, we designed a probabilistic model based on the GMM (Gaussian mixture model) to extract stopover points from the raw trajectories and annotate the semantic information on the stopover points. Then we proposed an attentional BiGRU-based trajectory prediction model, which can jointly learn the embeddings of the semantic trajectory. It not only takes the advantage of the BiGRU (Bidirectional Gated Recurrent Unit) for sequence modeling, but also gives more attention to meaningful positions that have strong correlations w.r. t. destination by applying attention mechanism. Finally, we annotate the most likely semantic on the predicted position with the probabilistic model. Extensive experiments on Beijing real datasets demonstrate that our proposed method has higher prediction accuracy.
Exploration of an EEG-Based Cognitively Adaptive Training System in Virtual Reality

Virtual Reality (VR) is effective in various training scenarios across multiple domains, such as education, health and defense. However, most of those applications are not adaptive to the real-time cognitive or subjectively experienced load placed on the trainee. In this paper, we explore a cognitively adaptive training system based on real-time measurement of task related alpha activity in the brain. This measurement was made by a 32-channel mobile Electroencephalography (EEG) system, and was used to adapt the task difficulty to an ideal level which challenged our participants, and thus theoretically induces the best level of performance gains as a result of training. Our system required participants to select target objects in VR and the complexity of the task adapted to the alpha activity in the brain. A total of 14 participants undertook our training and completed 20 levels of increasing complexity. Our study identified significant differences in brain activity in response to increasing levels of task complexity, but response time did not alter as a function of task difficulty. Collectively, we interpret this to indicate the brain's ability to compensate for higher task load without affecting behaviourally measured visuomotor performance.
A virtual synchronous generator adopting dynamic damping without frequency detection

The grid-connected inverter implementing the virtual synchronous generator (VSG) controller can take advantage of the virtual inertia and damping winding to improve the stability of the frequency and voltage of the power grid. However, PLL in virtual damping winding weakens the damping effect during the transient and increases the complexity of the system. In this paper, a leading-network based damping controller without PLL is proposed after analyzing the inverse effect of PLL on the performance of the damping winding using VSG small-signal models. A phase margin-constrained straightforward parameter setting method for proposed VSG is presented. The correctness of the design is verified on a 5kW hardware-in-loop inverter platform.
Unified SVPWM Strategy for Post-Fault Three-Level NPC Voltage Source Inverters

Eight switch three-phase inverters (ESTPIs)are the reconfigured topologies of the three-level neutral-point-clamped (NPC)inverter with a failure leg. This failure leads to different topologies of ESTPIs, which can be controlled by different space vector pulse width modulation (SVPWM)strategies. By analyzing the relationship of three SVPWM strategies for different ESTPIs, a unified coordinate transformation is proposed, which can make one of the three SVPWM strategies be a unified control strategy of ESTPIs. And the unified coordinate transformation is suited for two different SVPWM strategies for ESTPIs. Consequently, the unified strategy not only simplifies the control strategy, but also makes the fault tolerant control strategy more flexible. Simulation and hardware-in-the-loop (HIL)test results have shown the validity and feasibility of the proposed unified SVPWM strategies.
Terahertz metamaterial sensor integrated with microfluidic channel

We design a terahertz sensor integrated with microfluidic channel and metamaterials. We simulate the transmission spectra of the sensor filled with three kinds of polar liquids – methanol, ethanol and 1-propanol respectively. By observing the frequency shift and the amplitude difference of the transmission spectra, the different analytes can be conveniently identified. The results manifest that the sensor can be applied to fast and real-time detection, which will develop the terahertz applications in biosensor, material identification and drug reaction monitoring.
A Self-Packaged SISL Coupler Using Patterned Ground Structure With Stopband

This paper presents a self-packaged branch-line coupler based substrate integrated suspended Line (SISL) platform. Patterned ground structure is designed to achieve good stopband property. As compared with the previous defected ground structure (DGS) which needs additional shielding or supporting structures for practical engineering, the proposed patterned ground structure is embedded inside the self-packaged SISL multi-layer structure, and no additional shielding structure is required. Fabricated by using standard printed circuit board (PCB) process, the implemented SISL branch-line coupler is in a self-packaged form. The measured stopband is up to 3 times of the center frequency of 2.79 GHz. In a bandwidth of 48%, the measured return loss and isolation are better than 14.5 dB. This paper shows a good application method of using the patterned ground structure on SISL platform.
Exploiting Double-Barrier MTJs for Energy-Efficient Nanoscaled STT-MRAMs

This paper explores performance and technology-scalability of STT-MRAMs exploiting double-barrier MTJs (DMTJs) as comparatively evaluated with respect to conventional solution based on single-barrier MTJs (SMTJs). The comparative study was carried out at different design abstraction levels: (i) a bitcell-Ievel analysis relying on the use of Verilog-A compact models, and (ii) an architecture-level analysis for various memory sizes. Overall, our simulation results point out that, thanks to the reduced switching currents, DMTJ-based STT-MRAMs allow reducing write latency of about 60% than their SMTJ-based counterparts. This is achieved while assuring lower energy consumption under both write (-40%) and read (-27%) accesses, at the cost of reduced sensing margins.
Robust Estimation of a SOPDT Model from Highly Corrupted Step Response Data

Most industrial processes, even though complex in nature, can be represented using second order plus dead-time models, usually determined from step response data, which capture the essential process dynamics. The parameters of these models are computed based on specific algorithms. However, the great majority of these algorithms require system identification basic knowledge and are thus difficult to be used by the process engineer. The focus of this paper is to introduce a new method for computing the parameters of such models. The major advantage over existing methods is that it does not require any system identification expertise, being fully automatic. Additional advantages include robustness to noise, disturbances and system order. All of these are emphasized through several numerical examples, as well as an experimental validation.
New Derivation of the least squares deterministic filter and some interesting consequences: the continuous time case

A new derivation of the least squares deterministic filter is presented in this paper in the case of a continuous-time model with continuous measurements. This entirely elementary derivation leads in a natural manner to the information form of the Kalman filter. In addition, some interesting consequences can be deduced directly from this derivation, which are of theoretical and of practical interest.
Distributed Control for Microgrid Batteries Communicating over Network with Aperiodically Sampled Data with Time Delays

This paper proposes aperiodically sampled and time delayed data based distributed control system for frequency restoration, state of charge balancing and voltage restoration, in a microgrid with distributed batteries. Lyapunov-Krasovskii functionals and linear matrix inequalities are used to calculate the control system parameters. Real-time simulations using RTDS are used to verify the proposed control method on a European benchmark microgrid.
Efficacy Study on Interactive Mixed Reality (IMR) Software with Sepsis Prevention Medical Education

Objective: In recent years, the training of novice medical professionals with simulated environments such as virtual reality (VR) and augmented reality (AR) has increased dramatically. However, the usability of these technologies is limited due to the complexity involved in creating the clinical content. To be comparable to a clinical environment, the simulation platform should include real-world learning parameters such as patient physiology, emotions, and clinical team behaviors. Incorporating such nondeterministic parameters has historically required faculty to possess advanced programming skills. Lack of effective software for instructors to easily develop VR curriculum content is a hurdle in developing VR based curriculum. Method: We address this challenge through a software platform that simplifies the creation of Interactive Mixed Reality (IMR) scenarios. Three educational components we were able to embed into an IMR scenario includes 1) integrated 360-degree video recording of a clinical encounter to provide a first-person perspective, 2) rich annotated knowledge content, and 3) assessment questionnaire. We developed a sepsis prevention education scenario using the IMR software to demonstrate the potential of enhancing simulated medical training by accelerating clinical exposure for novice students. Result: An IRB approved study was conducted with a group of 28 novice students to evaluate the efficacy of the IMR technology. The participants provided feedback by answering demographics, NASA-TLX and system usability scale questionnaires. Significance: Our software is a step towards improving VR based education content development process. Conclusion: The studies conducted here provide preliminary evidence that the IMR software is a usable technology based on the NASA-TLX and system usability studies conducted. Future work will compare our new educational strategy for medical training with live simulation scenarios inside a hospital room and a simple video-based curriculum.
An Ultra-Broadband Quadruple-Stacked CMOS Power Amplifier

This paper presents a 0.1–2 GHz ultra-broadband radio frequency (RF) power amplifier (PA) with 50Ω input and output matching using 0.18 μm CMOS technology. To obtain a good gain flatness and broadband matching with a small chip size, this PA employs a two-stage stacked-FET structure with combinations of matching resistor and feedback resistor. To overcome the low breakdown voltage, 4 FETs are connected in series to form a quadruple-stacked structure. The measurement results show a gain flatness of 18.1±0.6dB, the maximum input return loss (S11) of -10.5 dB, the maximum output return loss (S22) of -12.6 dB, and 20dBm saturated output power with the corresponding power added efficiency (PAE) of 12%. To our knowledge, this is the first CMOS PA ever reported which achieves this combination of instantaneous bandwidth, gain flatness, output power and broadband matching, within a chip size of 0.62 mm2.
Design of a 110 GHz broadband frequency tripler using planar varistor Schottky diodes

This paper presents the design and demonstration of a 110GHz broadband varistor tripler utilizing two commercial gallium arsenide Schottky diodes from United Monolithic Semiconductor (UMS) Inc. Anti-parallel configuration eliminates even harmonics and thus no additional output filtering is needed. An accurate threedimensional electromagnetic (3D-EM) model is established to characterize the high-frequency parasitic effect of diodes. Linear and nonlinear simulations are performed iteratively to design the embedding circuit for high efficiency conversion. The whole circuit of the tripler is fabricated on RT/Rogers 5880 substrate with thickness of 0.127mm, housed in split waveguide blocks. The measured results show that with 20~22dBm input power at Ka-band, the tripler reaches maximum 9 dBm output power at 106 GHz and achieves 2.3%~5.5% efficiency across 90~120 GHz frequency band.
How prosodic cues could lead to information center in speech - An alternative to ASR

It has been reported in ASR literature that prosody helps retrieve important textual information by word. We therefore believe that prosodic information in the speech signal could be used to facilitate speech processing more directly. The prosodic word, a perceptually identifiable unit which is usually slightly larger in size than lexical word, can be a possible alternative to help locate important information in speech. Acoustic analysis across labels of perceived prosodic highlighted part in prosodic words and semantic foci in words are compared. The results demonstrate that prosodic highlights occur before targeted key information and function as advanced prompts to outline upcoming sematic foci ahead of time. Semantic saliency of targeted words are thus enhanced beforehand while correct anticipation can be facilitated prior to detailed lexical processing. Further automatic identification approach of key content by prosodic features also shows the possibility to retrieve important information through prosodic words. We believe the results demonstrate that not all information is equally important in speech, locating information center is the key to speech communication, and the contribution of prosody is critical.
The Method of Reducing Phantom Limb Pain Using Optical See-Through Head Mounted Display

One of the possible causes of the phantom limb pain (PLP), which have not been clarified medically, is said that a brain is unable to adapt to the loss of limbs. Even though a brain sends a signal to move limbs, the feedback on the signal is not given because the limbs to which a brain sent the signal are no longer in existence. Recently, some kinds of treatment are introduced, which is making patients feel that their phantom limbs are in existence and they are able to move the phantom limbs actually by their own will, but each of them has some difficulty. In this research, we propose the method of PLP treatment using an optical see-through Head Mounted Display (HMD) that can adapt to the telescoping of phantom limbs and make it easy for patients to communicate with people around them.