Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Quantiﬁcation of the Mental Image of Visual Concepts for Multi-modal Applications

: The semantic gap is the lack of coincidence between the information one can extract from data and its interpretation. It is an yet solved issue for multimedia applications like image captioning, where it is often challenging to select the best ﬁtting wording out of a group of candidates. To create a measurement for the perceived diﬀerences between words, this doctoral research proposes the idea of analyzing crawled image data to gain a better semantic understanding of language and vision. Abstract words have a broad mental image due to them being less visually deﬁned, while concrete words with a rather narrow visual feature space are visually easier to grasp. The core goal of this research is to approximate this perceived abstractness of those words as a metric. The thesis proposes two methods, looking at both relative and absolute measurements. For the relative method, a data-driven approach is proposed, while the absolute measurements train a machine-learned model on existing data from Psycholinguistics. Each method is evaluated using crowd-sourced data and compared to related approaches. With this, the thesis presents methods to analyze the mental image of words from diﬀerent angles, targeting a way to quantify the semantic gap between vision and language.
J ENA E CONOMIC R ESEARCH P APERS

This paper studies the eﬀects of social comparison on risk taking behavior. In our framework, decision makers evaluate the consequences of their choices as changes with respect to both their own and their peers’ conditions. We test experimentally whether diﬀerent positions in the social ranking determine diﬀerent risk attitudes. Subjects interact in a simulated workplace environment, where they receive possibly diﬀerent wages as compensation for eﬀort and then undertake a risky decision that may give them an extra gain. We ﬁnd that social comparison matters for risk attitudes. In addition, risk aversion decreases with the size of social gains. As a consequence, subjects are less risk averse in social loss than in small social gain, whereas their risk attitudes do not diﬀer between social loss and large social gain.
University of Birmingham Signal regression in frequency-domain diffuse optical tomography to remove superficial signal contamination

Significance: Signal contamination is a major hurdle in functional near-infrared spectroscopy (fNIRS) of the human head as the NIR signal is contaminated with the changes corresponding to superficial tissue, therefore occluding the functional information originating from the cerebral region. For continuous wave, this is generally handled through linear regression of the shortest source-detector (SD) distance intensity measurement from all of the signals. Although phase measurements utilizing frequency domain (FD) provide deeper tissue sampling, the use of the shortest SD distance phase measurement for regression of superficial signal contamination can lead to misleading results, therefore suppressing cortical signals. Aim: An approach for FD fNIRS that utilizes a short-separation intensity signal directly to regress both intensity and phase measurements, providing a better regression of superficial signal contamination from both data-types, is proposed. Approach: Simulated data from realistic models of the human head are used, and signal regression using both intensity and phase-based components of the FD fNIRS is evaluated. Results: Intensity-based phase regression achieves a suppression of superficial signal contamination by 68% whereas phase-based phase regression is only by 13%. Phase-based phase regression is also shown to generate false-positive signals from the cortex, which are not desirable. Conclusions: Intensity-based phase regression provides a better methodology for minimizing superficial signal contamination in FD fNIRS.
Application of Magnetic Composite Materials in Windings to Reduce Alternating Current Resistance in Leakage Transformers

LLC resonant dc–dc converters are high-efficiency converters capable of low-loss switching. Leakage transformers that combine resonant inductors and transformers are effective for the miniaturization of LLC resonant dc–dc converters. However, they exhibit a substantial leakage magnetic flux due to low coupling between the primary and secondary windings, and they exhibit high alternating current (ac) resistance due to the leakage magnetic flux acting on the windings. Thus, this study proposes an approach to reduce the ac resistance of leakage transformers by inducing a leakage flux through the application of magnetic composite materials to the windings. Magnetic field simulation and fabrication of transformers are used to clarify the effect of the loading position of a magnetic composite material on the ac resistance of leakage transformers. The ac resistance at 1 MHz was reduced by 33% from 743 to 501 $\text{m}\Omega $ by loading the magnetic composite material at the appropriate position in the winding.
Inductive Heating Based on VHF-ISM Radio Band Frequencies as Technology Platform for Efficient Heating of Metallic Micro-Scaled Bonding Layers in MEMS Packaging

This article presents a technique for selective and energy-efficient induction heating of aluminum (Al) frames to support and enhance the thermocompression bonding (TCB) for electronics packaging in the field of heterogeneous integration. The technological challenges include the use of an adapted induction coil for homogeneous heat distribution, the implementation of industrial, scientific, and medical (ISM) radio band frequencies in the high frequency (HF) and very high frequency (VHF) range up to <inline-formula> <tex-math notation="LaTeX">$f_{0}$ </tex-math></inline-formula> = 40.68 MHz, and the assembly of a heating system based on an RF generator and automatic matching unit for impedance modulation. Finite element analysis (FEA) was used to calculate the electromagnetic (EM) fields based on the coil design used. The inductive heating was successfully carried out using a generator power of <inline-formula> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula> = 100 W with coil currents in the range of <inline-formula> <tex-math notation="LaTeX">$I_{0}$ </tex-math></inline-formula> = 10.1–11.3 A (amplitudes). With this setup, a peak temperature of <inline-formula> <tex-math notation="LaTeX">$T_{f\_{}{\text {max}}}$ </tex-math></inline-formula> = 633 °C in the Al frames could be achieved after <inline-formula> <tex-math notation="LaTeX">$t_{h}$ </tex-math></inline-formula> = 10 s. This corresponds to an average heating rate of dT / dt = 63.3 K/s.
On the Survivability of a 28 - 32 GHz GaN Low Noise Amplifier

This paper presents a 28 - 32 GHz 2-stage low noise amplifier (LNA). The LNA was designed and fabricated using Ferdinand-Braun-Institut’s (FBH) $0.15 \mu \mathrm{m}$ GaN on SiC process. Three samples of LNAs were characterized showing a small-signal gain of 15.3 - 16.3 dB and noise figure of 2.8 - 3.2 dB within the bandwidth. The input and output reflection coefficients are found to be better than -7.4 dB and -9.5 dB, respectively. The LNA samples were stressed with an input power up to 34.4 dBm at 30 GHz CW. Post-stress measurements reveal only a threshold shift in the first stage transistor without any significant change in the small-signal and noise performance.
A Continuously Adjustable True Time Delay for D-Band Timed Antenna Arrays

This paper presents a fully integrated true time delay (TTD) circuit for beamforming applications based on the delay sum principle operating at a center frequency of 144 GHz with a 3 dB bandwidth of 26 GHz. It features a measured delay range of 1.75 ps whose resolution is only limited by the integrated digital-to-analog converter (DAC). A demonstrator has been manufactured in a 130 nm bipolar complementary metal-oxide-semiconductor (BiCMOS) technology, occupying 0.53 × 0.3mm2 of chip area including serial peripheral interface (SPI), bandgap reference and four DACs.
A Bulk-Controlled 12 GS/s Track and Hold Amplifier with >58 dBc SFDR and >53.5 dB SNDR in 22 nm FD-SOI CMOS

This paper presents a highly energy-efficient wideband 2x time-interleaved 12GS/s track-and-hold amplifier fabricated in a 22 nm FD-SOI CMOS process. A single swing-enhanced bulk-controlled front-end buffer is adopted to achieve a signal swing of 0.8Vppd, while minimizing bandwidth mismatch and kickback effects. Each bootstrapped 6GS/s top-plate sampler takes advantage of an active bulk-voltage modulation scheme, improving the measured tracking bandwidth of 15GHz during the on-phase while mitigating leakage-current effects in the off-state. The track-and-hold amplifier utilize offline TI calibration and maintains a single-tone SFDR and SNDR of 58dBc and 53.5dB respectively across the entire Nyquist band, while two-tone-test reveals an IM2 and IM3 tone of 63.5 and 66dBFS respectively. The estimated clock-jitter is only $\sigma \quad =28$ fs considering both the internal track-and-hold amplifier clock path as well as the external clock source. The total power consumption equals 142mW, drawn from a triple 2V, 0.9V, and -0.8V power supply.
Design and Performance of a Compact 3-D-Printed Magnetorheological Fluid Damper

In this study, magnetorheological fluids (MRFs) were encapsulated in a compact 3-D-printed fluid damper, and the field-dependent mechanical properties, such as stiffness and damping, of the MRF damper were experimentally evaluated. To this end, an MRF prepared with a 40% volume fraction of iron particles and silicone oil was injected into the 3-D-printed acrylonitrile butadiene styrene (ABS) encapsulant with an elastic thermoplastic polyurethane (TPU) compression layer. A fluid channel was fabricated between the top and bottom reservoirs, and a field-induced magnetorheological (MR) effect was controlled in the channel, resulting in variable stiffness and damping. The bottom side of the bottom reservoir had a thin elastic layer bonded to its perimeter so that upon compressive loading of the upper TPU surface, pressurized MRF could flow and be accumulated in the lower reservoir. External magnetic fields of 0–58 kA/m were applied to the 3-D-printed MRF damper while conducting uniaxial compression tests. The 3-D-printed MRF damper was characterized via force–displacement tests at a 0.1 mm/s displacement rate. Results showing the effect of varying magnetic fields on the mechanical properties of the 3-D-printed MRF damper are discussed.
Development of a Process Oriented Calibration Scheme for the HBV Hydrological Model

A process oriented calibration scheme (POC), developed for the HBV hydrological model is presented. Twelve parameters were calibrated in two steps. Firstly, initial parameter estimates were made from recession analysis of observed runoff. Secondly, the parameters were calibrated individually in an iteration loop starting with the snow routine, over the soil routine and finally the runoff-response function. This was done by minimizing different objective functions for different parameters and only over subperiods where the parameters were active. Approximately three hundred and fifty objective function evaluations were needed to find the optimal parameter set, which resulted in a computer time of about 17 hours on a 386 processor PC for a ten-year calibration period. Experiments were also performed with fine tuning as well as direct search of the response surface, where the parameters were allowed to change simultaneously. A calibration period length of between two and six years was found sufficient to find optimal parameters in the test basins. The POC scheme yielded as good model performance as after a manual calibration.
Rendering Involved and Machine-Learning-Based Environment Interpretation Applying Depth Estimation

In my previous studies, I researched how a moving robot agent recognizes space with a depth obtained by a tiltable RGBD camera equipped with IMU. To interpret the 3D point cloud obtained from the sensor, I am currently researching a general method of recognizing environments by identifying objects through machine learning like CNN classifiers and manipulating symbols on the rendering engine with reinforcement learning to align location, size, and posture. However, it is difficult to give up the goal of interpreting space-only camera images because humans recognize most of the scenes only with their eyes, which are optical sensors, not distance information obtained from sensory organs. Therefore, in this study, instead of the depth obtained from the sensor, an image of a single camera is applied to the 3D point cloud obtained by depth estimation to perform the recognition process. I then performed an analysis and compared the results with those recognized by an RGBD camera. Previous studies have also assumed that it's possible to point to the ground by declining the angle of the camera; therefore, it has always been assumed that the robot knows the part of the ground where it can move. Additionally, the scale of the depth estimation can be adjusted by adding an assumption that the height of the camera is also known. Subsequently, the same recognition steps of previous research are conducted to process the point cloud. In the experiments, my study compares the accuracy of the depth estimation between points with an RGBD camera, the recognition results, and the accuracy of performing ICP between a rendered scene and point clouds.
Investigation of ionospheric scintillation effects on RTK in Brazil

The ionospheric irregularities lead to rapid fluctuations in the amplitude and/or phase of radio signals commonly referred to as ionospheric scintillation, which can reduce the accuracy and reliability of Global Navigation Satellite System (GNSS) and even lead to complete loss of signal lock in GNSS receivers. At low latitudes, where anomalous ionospheric disturbances are more frequent, strong scintillation can last up to several hours. This paper investigates the impact of scintillation on the Real Time Kinematic (RTK) positioning of the Global Positioning System (GPS) using ionospheric scintillation data collected in Brazil during the solar maximum year 2014. Significant positioning errors are observed when dynamic RTK processing strategies are used during strong scintillation. The maximum positioning deviations in the east, north and upper directions reach 2.29, 1.84 and 1.37 m, respectively. At the same time, the Double Differential (DD) carrier phase residuals also increase. By contrast, when using static RTK processing strategy during strong scintillation, the positioning error is less than 5 mm at all time. However, there is a significant increase in DD phase residuals. The relationship between the standard deviation of the one-minute carrier phase residuals and the scintillation index S4 is investigated. A significant correlation is found between the phase residuals standard deviation and S4, which thus can be used to indicate the occurrence of scintillation. This study is important for a better understanding of scintillation characteristics and their impact on real-time differential positioning at low latitudes. It can also be used to develop scintillation mitigation methods for GNSS differential positioning.
Winding Magnetization Design of Single-Phase Capacitor-Run Induction Motor for Submersible Pump Application

This article provides a systematic stator winding design scheme that can effectively improve the operational efficiency of commercial single-phase capacitor-run induction motors (IMs). Without changing the circuit components and structural constraints, the motor’s stator windings will be rearranged based on the devised theoretical basis and design objectives. The design scheme supported by the finite-element emulations will be supplied to show the efficiency improvement of a commercial single-phase two-pole IM. In addition, experimental hardware validations will be accomplished from the motor with rewound stators, and evident performance advances from measurements confirm the design.
A novel partitioned stator flux reversal permanent magnet linear machine

A novel partitioned stator flux reversal permanent magnet (PS-FRPM) linear machine with segmented iron mover is introduced. The operation principle of the PS-FRPM linear machine is described, and the optimisation of the machine leading design parameters for maximum thrust force using genetic algorithm has been carried out. Moreover, in order to investigate the longitudinal end effect on the machine performance a periodic model has been employed to compare with the real model. It is found that the end effect has a significant impact on the machine performance, particularly in terms of unbalanced magnetic circuit and cogging force. Additionally, the influence of the mover iron pole numbers on the electromagnetic performance of PS-FRPM linear machines has been examined, i.e. 6/4, 6/5, 6/7, 6/8, 6/10 and 6/11 stator/mover pole combinations are designed and compared. It is concluded that the machine with a mover pole pitch which is closer to the stator slot pitch exhibits the best performance among the others.
E ﬀ ects of Physical Exercise on Cerebral Blood Velocity in Older Adults: A Systematic Review and Meta − Analysis

: As the older population grows, there is an increasing interest in understanding how physical exercise can counteract the changes seen with aging. The bene ﬁ ts of exercise to general health, and especially to the cardiovascular system, have been a topic of discussion for decades. However, there is still a need to elucidate the e ﬀ ects of training programs on the cerebrovascular blood velocity in older people. This systematic review and meta-analysis aimed to investigate the e ﬀ ect of physical exercise on the cerebral blood velocity in older people (PROSPERO CRD42019136305). A search was performed on PubMed, Web of Science, EBSCO, ScienceDirect, and Scopus from the inception of this study to October 2023, retrieving 493 results, of which 26 were included, analyzing more than 1000 participants. An overall moderate risk of bias was found for the studies using the Cochrane risk-of-bias tools for randomized and non-randomized clinical trials. The pooled results of randomized trials showed that older people who underwent physical exercise presented a statistically signi ﬁ cant increase in cerebral blood velocity (3.58; 95%CI = 0.51, 6.65; p = 0.02). This result indicates that physical exercise is important to help maintain cerebral health in older adults.
Experimental Validation of Class F Waveform Engineering in Class C Biasing Condition

In this paper, the experimental verification of suitable input harmonic injection to achieve class F operating conditions in class $\mathbf{C}$ (under pinch-off) biased active devices is discussed. In detail, it is demonstrated that by generating a third harmonic component $V_{g, 3}$ with a proper phase relationship with respect to the fundamental one $V_{g, 1}$, it is possible to change the phase of the resulting output harmonic components, and in particular of the third one $I_{D, 3}$, thus generating the proper squaring of the output voltage. Experimental results at device level have shown an improvement in terms of output power and efficiency from 2.24W to 3.00W and from 72.2% to 79.3%, respectively. The proposed approach could play a key role in the maximization of the achievable efficiency of Doherty power amplifiers, where the auxiliary branch needs to be biased in class C for a exploitation of the architecture.
A Compact 120 GHz LNA in 22 nm FD-SOI with Back-Gate Controllable Variable-Gain

This paper describes the design and implementation of a 113.5-127 GHz D-band LNA using GlobalFoundries’ 22 nm FD-SOI technology. The proposed design achieves 6.6 dB of minimal noise-figure in-band for a peak gain of 17.5 dB at its nominal bias for a 27.5 mW power-consumption using a low supply voltage of 0.75 V, and can achieve an NF down to 6.1 dB and gain up to 19.1 dB in a high-performance state. On top of that, the LNA can be configured as a variable-gain device by making use of the unique back-gate bias node of the 22FDXO technology. In that case, a 9. 7dB gain-control is achieved over a 2 V bias range at the back-gates. The design achieves a low area of 0.039 mm2 thanks to its layout based on compact transformers.
Magnetic Hammer Testing With Tunnel Magnetoresistive Sensors

The magnetic hammer test (MHT) technique was developed using tunnel magnetoresistive (TMR) sensors that detect very weak magnetic signals generated by the natural vibration of steel plates. For the non-destructive testing (NDT) of infrastructures, which requires high accuracy and energy conservation, TMR sensors with high sensitivity have the potential to meet the NDT requirements. TMR sensors detected weak signals of nanotesla due to natural vibration and accurately evaluated the size of steel plates from the natural frequency. In addition, a finite element method (FEM) simulation analysis was conducted to elucidate the mechanism of the magnetic signals generated by the MHT. We concluded that the MHT technique using TMR sensors can be applied as a novel NDT method for detecting small fractures and corrosion in steel materials.
Computationally Efficient Estimation of PWM-Induced Iron Loss of PMSM Using Deep Transfer Learning

As the demand for increasing the efficiency of traction motors for increasing the mileage of electric vehicles, it is necessary to accurately estimate the efficiency of traction motors at the early design stage. Since the iron loss of the traction motor is highly affected by the pulse width modulation (PWM) frequency, the PWM current should be considered when designing the motor. However, it is difficult in considering the PWM current at the early design stage because of its high computation cost due to the small time step for representing the high-frequency harmonics. Therefore, we propose a method to reduce the computation cost for the calculation of PWM-induced iron loss using deep transfer learning (DTL) even with a small amount of data. The proposed method can be achieved by training a deep neural network (DNN) that can predict PWM-induced iron loss accurately using a large amount of sinusoidal current-based iron loss and a small amount of PWM-induced iron loss. As a result, the PWM current can be practically considered in the design stage of the traction motor because the computation cost can be decreased by using the proposed method.
A D-band Low-Noise Amplifier in 28-nm CMOS Technology for Radio Astronomy Applications

This paper describes a broadband 129-157.5 GHz low-noise amplifier for radio astronomy applications in TSMC 28nm CMOS technology. In order to enhance the maximum stable gain in D-band, the gain-boosting technique is adopted at the third, fourth, and fifth stage, enabling high gain performance over a wideband. According to the measurement results, the proposed work demonstrates competitive performances with 16.3-dB peak gain and 9.6-12.1-dB noise figure across the 3-dB bandwidth from 129 to 157.5 GHz.
Labor Market Matching under Imperfect Information Labor Market Matching under Imperfect Information

Recent research has shown that the standard labor matching model has di¢ culties in reproducing the co-movement patterns observed in US data. This is due to the fact that the standard model lacks su¢ cient propagation of shocks. This paper shows that re…ning the informational structure of the model leads to improvements along this dimension: when agents cannot separately identify persistent and transitory technology shocks on impact (so that they must solve a signal extraction problem), shocks are propagated. Under this speci…cation the standard matching model even manages to make recoveries initially jobless, as in the data.