Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Evaluation of ARCP and Three-Level TCM Soft-Switching Bridge-Legs for High-Frequency SiC Converter Systems

Soft-switching bridge-legs facilitate high-efficiency three-phase PV inverters or PFC rectifiers. By extending a half-bridge with a resonant auxiliary circuit, including two additional transistors, zero-voltage switching (ZVS) of the main transistors can be realized (Active Resonant Commutated Pole, ARCP). Alternatively, a similar T-type bridge-leg structure achieves ZVS by operating the output filter inductor with a sufficiently high current ripple (with 3-level Triangular Current Modulation, 3L-TCM). We provide a comparative evaluation of these two concepts for the realization of 2.2 kW (per phase), 800 V DC bridge-legs with latest-generation 1200 V and 650 V SiC MOSFETs, discussing chip-area optimization, filter design for compliance with current and future EMI limits, and qualitative limits and design criteria. The calculated loss-vs.-volume Pareto fronts indicate advantages for the 3L-TCM approach, with peak switching frequencies of 72 kHz or 144 kHz and an efficiency (semiconductors and EMI filter) of about 99.6 %. The ARCP concept seems more suitable for applications that do not necessarily require EMI filters but benefit from limited switch-node $dv/dt$ (in the order of 1.5 V/ns) such as variable-speed drives.
Global Intellectual Impairment Does Not Accelerate With Age in Patients With Schizophrenia: A Cross-Sectional Analysis

Neuropsychological studies show impairment in intellectual functions in schizophrenia patients. It is still unclear, however, whether intelligence scores decline progressively during the illness as compared to healthy subjects' scores. Longitudinal studies conducted so far have been restricted to relatively short time spans. The aim of this study is to investigate whether changes in intelligence scores accelerate with age in schizophrenia patients. In a cross-sectional design, performance of four subtests of the Wechsler Adult Intelligence Scale (WAIS) was analyzed in 112 schizophrenia patients and compared to that of 70 healthy subjects, across an age span of 40 years (16-56 years). A linear regression analysis was performed. A main effect on the total ratio score of the four tests was demonstrated between the two groups. No main effect of age and no interaction effect of age with group for the total ratio score were found. The results confirm that there is global intellectual impairment in schizophrenia patients at the onset of illness but no age-accelerated decline and are consistent with the neurodevelopmental hypothesis of schizophrenia.
Flux Control Modulation for Three-Phase Dual-Active-Bridge DC-DC Converters

Flux control modulation (FCM) is a frequen-cy-variable modulation technique that has been originally in-troduced for the single-phase dual-active bridge (DAB). The peak flux linkage in the transformer decreases with increasing power, allowing the switching frequency to be reduced, which lowers the switching and conduction losses in contrast to the traditional single phase shift (SPS) modulation that operates at constant frequency. This paper derives FCM for the three-phase DAB. It is shown that all advantages of FCM also apply to the three-phase topology. In comparison with SPS modulation, FCM not only lowers the switching and conduction losses of the converter, but also allows a larger power rating without any increase in conduction or switching losses, while never violating saturation boundaries. Moreover, significant overload capabilities are possible with FCM. Thus, FCM has a great potential to increase the efficiency, the power rating, and overload capabilities in dc power distribution systems and high-power applications in general. The findings are validated by experiment, revealing 26 % lowered full-load losses in contrast to SPS modulation.
Development of a new speed measurement technique based on deep learning

The more pervasive use of Artificial Intelligence (AI) has enabled feature extraction enhancement in several fields, particularly in image processing applications. Thanks to AI, it is possible to use low-cost devices (e.g., webcams and surveillance cameras in complex scenarios) like vehicle speed measurement, obtaining a significant reduction of instrument costs and a great spread of their use. The paper presents a new industrial measurement instrument for vehicle speed based on non-dedicated hardware devices and innovative image processing methods like Regional CNN (Convolutional Neural Network). The proposed hardware is based on a generic surveillance camera or even a simple webcam and an R-CNN to transform it into an intelligent tool capable of estimating the speed of a vehicle and tracking its movement under controlled conditions. One of the essential aspects of the work concerns the metrological characterization of the proposed method. Measurement uncertainty has been evaluated. The metrological characterization of approaches using artificial intelligence can be fundamental for spreading such technologies in practical scenarios and impulse the industrial development of enhanced tools that can comply with legal regulations for speed measurement. The measured velocities of a car under test have been compared with a reference constituted by the vehicle speed retrieved by the ABS ECU.
On the Implementation of Location Obfuscation in openwifi and Its Performance

Wi-Fi sensing as a side-effect of communications is opening new opportunities for smart services integrating communications with environmental properties, first and foremost the position of devices and people. At the same time, this technology represents an unprecedented threat to people’s privacy, as personal information can be collected directly at the physical layer without any possibility to hide or protect it. Several works already discussed the possibility of safeguarding users’ privacy without hampering communication performance. Usually, some signal pre-processing at the transmitter side is needed to introduce pseudo-random (artificial) patterns in the channel response estimated at the receiver, preventing the extraction of meaningful information from the channel state. However, there is currently just one implementation of such techniques in a real system (openwifi), and it has never been tested for performance. In this work, we present the implementation of a location obfuscation technique within the openwifi project that enables fine manipulation of the radio signal at transmitter side and yields acceptable, if not good, performance. The paper discusses the implementation of the obfuscation subsystem, its performance, possible improvements, and further steps to allow authorized devices to “de-obfuscate” the signal and retrieve the sensed information.
Performance Analysis of Various Ionospheric Delay Corrections in Single-frequency GPS Positioning solution at a low latitude Indian location

Ionospheric delay is the most critical factor in satellite-based communication and navigation applications, often imparting serious threats to the trans ionospheric signal to affect the accuracy of measurements in the allied applications. The current technological advancements and diverse usages of single-frequency global positioning systems (GPS) based navigation and positioning applications in the mass market emphasize effective mitigation of ionospheric delay error as they are often restricted with precision-limited models. In the present paper, the performance of single-frequency positioning at a low latitude location Bangalore, India (Geographic coordinate: 13.02°N, 77.57°E) during 10-12 October 2021 by using five different ionospheric delay error mitigation techniques through RTKLIB, an open-source program package for standard and precise positioning through global navigation satellite system (GNSS) observations is evaluated. The number of satellite visibility, ground tracks of receiver locations, and deviations in East-West, North-South, and Up-Down directions are analyzed by implementing different ionospheric error mitigation models to suggest the best possible option in a single-frequency GPS positioning solution. The analysis shows that among all the available options, the broadcast Klobuchar model signifies relatively improved corrections in 2-dimensional positioning (N-S and E-W) despite limitations in its model specifications whereas the vertical error is relatively better estimated by the international GNSS service’s final global ionosphere maps (IGS-GIMs), followed by the broadcasted Klobuchar model coefficients. The outcome of this work supports the concerted efforts towards better navigation and positioning accuracies for the single-frequency GNSS users over the region.
Descriptor formulation for a robust static output feedback $H_{\infty}$ control for polytopic discrete-time system

This paper investigates the problem of robust static output feedback (SOF) $H_{\infty}$ controllers for polytopic uncertain discrete-time systems. The descriptor redundancy approach and linear matrix inequality (LMI) techniques are applied to solve the static output feedback $H_{\infty}$ controllers problem. By considering auxiliary slack variables with free structure, new sufficient conditions for static output feedback $H_{\infty}$ design are presented in terms of linear matrix inequalities (LMIs), which guarantee the robust stability of the closed-loop systems under prescribed $H_{\infty}$ performances. Numerical ex-amples are given to illustrate the advantages of the proposed procedure when compared with other methods available in the literature.
Geometric Power and Poynting Vector: a Physical Derivation for Harmonic Power Flow using Geometric Algebra

This document aims to establish an alternative physical formulation for the harmonic power flow in electrical systems provided by Geometric Algebra (GA) and the Poynting Vector (PV) and Poynting Theorem (PT). Given the traditional definition of PV (Abraham approach) as the vector product of the electric field and magnetic field, we exploit the property of the vector product as a dual form of the much more powerful wedge product operator from exterior algebra. Using concepts of vector spaces, we develop a completely GA-based approach founded on top of the isomorphism among periodic time-domain signals and Euclidean spaces. Our investigations shed more light on the long-running discussion of electric power flow in non-sinusoidal and non-linear electrical power systems.
Blink and saccade detection from forehead EEG

Ocular artifacts that are commonly found in electroencephalography (EEG) recordings are typically discarded as noise; however, this ocular data has the potential to assist with neuroergonomic assessment of cognitive state. In this paper, we develop and evaluate regression models to extract ocular data (e.g., blink rate, saccade rate) from EEG recordings. We used EEG data recorded from participants performing the Multi-Attribute Task Battery simulation at low, medium, and high workloads, with electrooculography (EOG) data recorded simultaneously as a ground truth. Linear regression models were developed to predict EOG data from forehead EEG channels. EOG data were predicted with correlations between 0.72 and 0.94. Blinks were detected in 45×5 min EEG segments per participant with mean precision and recall of 81% and 79% respectfully. Saccades were detected with mean precision and recall of 75% and 76%, respectfully. Blink rates were identified from EEG at similar rates and relationships across workloads. The saccade rate was more varied depending on the participant and may require further investigation to improve.
Generate don’t evaluate: how can codesign benefit communication designers?

Abstract Communication designers have historically been accused of neglecting end-user perspectives, believing designers are experts at creating inspired designs. Codesign has been applied to many design fields, however developing methods for engaging end-users have had little traction in communication design practice. In an era of end-user engagement, communication designers are left wondering how and when to include end-users in the design process and if codesign offers any benefits to project outcomes. This study trialled codesign workshops across two communication design case studies. Both studies involved non-profit contexts where designers and staff co-created communication design strategies, one for sustainable cleaning in childcare centres and the other for asthma management and awareness. The findings reveal that structured, hands-on generative toolkits conducted in small groups, sparked conversation and prompted innovative ideas whereas evaluating ideas with ranking toolkits blocked dialogue and hindered idea progression. Evaluation tooolkits based on ranking ideas created unexpected barriers to engagement, as end-users disengaged from the codesign process. I argue codesign can benefit communication design when structured hands-on generative toolkits simulate a perceived familiar environment, creating a conversational forum for ideas to flow while participants enjoy creating things with their hands.
On-board Antenna Tracking System for HTS Satellites: ISRO’s First In-Orbit Success on GSAT-19

This paper presents ISRO’s and India’s first successful development and validation of a space borne Antenna Tracking System technology on its experimental HTS satellite GSAT-19. Onboard tracking system demonstration is an enabling technology for a High Throughput Satellite (HTS) program as it is essential to maintain beam coverage of high-gain sharp multiple beam antennas locked to specific coverage zones on the ground to ensure edge-of-coverage gains and variations in spite of spacecraft roll & pitch stability residues. The tracking system senses such fine angular offsets and generates proportional DC error voltages that are used to apply the required correction to the antenna axes through appropriate drive motors. The system has been designed & tested for the tracking accuracy better than 0.01°. The technology has been successfully developed and proven for the first time on an ISRO satellite, paving the way for full-fledged follow-on HTS satellites (GSAT-11, GSAT-20 etc).
On Ultra-reliable Low Latency Communication between Energy Harvesting Transmitter and Receiver with OS Decoder

In this work we investigate the design of energy harvesting (EH) communication systems for ultra-reliable low-latency communication (URLLC). We consider a point-to-point communication system with an EH transmitter and receiver with an order-statistics based decoding. We highlight the various trade-offs involved in the design of energy harvesting URLLC system and present many new insights into the design of EH URLLC systems.
Flexible Self-Powered Tactile Sensors Based on Hydrothermally Grown ZnO Nanorods

Flexible tactile sensors with high sensitivity and good flexibility are urgently required in modern biomimetic robots’ electronic skin, and artificial intelligence interaction. In this work, a flexible piezoelectric tactile sensor was fabricated using hydrothermally grown ZnO nanorods (ZnO NRs) on Cu-coated polyimide (PI) substrate. Structural and morphological properties of the ZnO NRs were investigated by SEM, XRD. The piezoelectric response properties of the sensors by using the pasted Cu/PI electrode and directly screen-printed Ag electrode were compared. The results show the sensor with the screen-printed Ag electrode exhibits a high sensitivity of 974 mV/N, which is higher than the pasted Cu/PI electrode, and the response of all sensors to the applied pressure is almost linear in the range of 0.1-1 N. Meanwhile, the sensor can be employed to detect human movements such as bending/stretching motion of fingers and the vibration of the vocal cords and pulse, and realize the conversion from mechanical energy to electrical energy. It is demonstrated that the sensor has great potential applications in wearable health monitoring systems and self-powered devices.
Some Thoughts on Designing Eye Movement Studies for Novice Programmers

I first describe my three-stage model of how novices understand code. In the first stage, the novice cannot trace code. In the second stage, the novice has mastered tracing, but, crucially, that is the only skill they have mastered. It is only when novices reach the third stage that they begin to reason about code in a more general, abstract way. Most programming instructors mistakenly assume that all students begin at the third stage. Having described the three-stage model, I then explore implications of the model for the design of eye movement studies. I also provide some pieces of code that would make for interesting eye movement studies.
NLBSE’22 Tool Competition

We report on the organization and results of the first edition of the Tool Competition from the International Workshop on Natural Language-based Software Engineering (NLBSE’22). This year, five teams submitted multiple classification models to automatically classify issue reports as bugs, enhancements, or questions. Most of them are based on BERT (Bidirectional Encoder Representations from Transformers) and were fine-tuned and evaluated on a benchmark dataset of 800k issue reports. The goal of the competition was to improve the classification performance of a baseline model based on fastText. This report provides details of the competition, including its rules, the teams and contestant models, and the ranking of models based on their average classification performance across the issue types.
Non-Linear Model Predictive Control for Modular Multilevel Converters

In this paper, non-linear model predictive control (NMPC) without an explicit modulator is applied to modular multilevel converters (MMCs) in the abc reference frame. NMPC can easily be extended for longer prediction horizons as opposed to finite control set model predictive control (FCS-MPC). However, NMPC applied to power converters in previous studies uses a modulator, which limits the transient response compared to FCS-MPC. Therefore, to avoid the modulator, two strategies are presented. In the first strategy, the continuous solution (number of inserted submodules per arm) obtained from NMPC is simply rounded off to the nearest integer for both the arms of each phase. In the second strategy, the optimal solution obtained from the NMPC is further evaluated by rounding it up and down for both arms. This requires four simulations per time step, independently from the number of SMs per arm. The evaluation of the four cases is conducted only for the initial time step within the prediction horizon. Then the solution that minimizes a pre-defined cost function is applied to MMC. The second strategy offers the fastest response and provides similar dynamic performance as indirect FCS-MPC, while both strategies offer similar steady-sate performance. Simulations are performed to validate the performance of the proposed methods compared to the FCS-MPC.
Respiration Rate Estimation from Thermal Video of Masked and Unmasked Individuals Using Tensor Decomposition

Respiration rate (RR) measurement is a crucial part of health monitoring. Long-term monitoring requires a non-contact solution to avoid inconveniencing patients and to promote compliance. This study examines the use of thermal video for RR estimation since it is more privacy-preserving than visible light cameras. In this study, tensor decomposition is implemented on the whole frame of thermal camera video, avoiding the need to define a specific region of interest (ROI). The proposed method automatically finds a loading vector of the decomposed tensor from which a time series respiratory signal may be reconstructed. The mean absolute difference between the estimated breaths per minute (BPM) from tensor decomposition and the ground truth measurement was used to evaluate the model. Data were recorded from 22 subjects with and without a mask while sitting or standing using a thermal camera; concurrent recordings with a respiratory effort belt provided gold standard RR. Results show that when subjects are seated and wearing a face mask, tensor decomposition can detect RR with an average error of 0.3 BPM over the 22 subjects. In the worst scenario (standing without a mask) the average error is 8.0 BPM. This study shows that tensor decomposition can be a useful tool for automatic non-contact RR estimation without using any pre-defined ROI, particularly for seated subjects wearing a face mask.
An Effective Detection of Version Number Attacks in the IoT using Neural Networks

Day by Day human dependency on connected technology is rapidly growing with the deployment of IoT based real-time sensing applications that serve various business or human requirements. Therefore, there are various researches to secure connected devices like IoT from a wide range of attacks like Version Number Attack. Detection of Version Number Attack in the network infrastructure is the impart part of the cyber security to watch and block the malicious traffic flows on the IoT network. To overcome this major issue, proposing a machine learning and deep learning approach. First, implement a qualitative feature extraction approach based on filter technique that are independent of any classifiers. Therefore, the selected features are not dependent on any Machine Learning and Deep Learning algorithm. Next, implemented a SMOTE Oversampling technique to overcome the imbalanced dataset problem. The proposed approach has greater benefits in terms of Higher ROC and can be effectively implemented in a real world complex IoT network as a unified framework for detecting Version Number attacks.
CONCRETE CAPACITY DESIGN (CCD) APPROACH FOR FASTENING TO CONCRETE

A user-friendly, highly transparent model for the design of post-installed steel anchors or cast-in-place headed studs or bolts, termed the concrete capacity design (CCD) approach, is presented. This approach is compared to the well-known provisions of the American Concrete Institute (ACI) 349-85. The use of both methods to predict the concrete failure load of fastenings in uncracked concrete under monotonic loading for important applications is compared. Variables included single anchors away from and close to the edge, anchor groups, tension loading, and shear loading. A data bank including approximately 1,200 European and American tests was evaluated. The comparison shows that the CCD method can accurately predict the concrete failure load of fastenings for the full range of investigated applications. On the other hand, depending on the application in question, the predictions of ACI 349 are sometimes unconservative and sometimes conservative. The CCD method is more user-friendly for design. Based on this, the CCD method is recommended as the basis for the design of fastenings.