Miracle-dz/UniFAR-FTUs huggingface dataset:
A Pattern Reconfigurable Antenna Applied for Automobile 5G Communication

A pattern reconfigurable antenna is proposed to achieve four different radiation patterns by controlling the switching state of the PIN diodes. The structure is achieved by uniting a center-fed microstrip shorted patch and four parasitical monopoles, and eight PIN diodes are introduced to control monopoles. The monopole which is vertical to the substrate is working as an electric current source. The loaded monopoles break the symmetry of the center-fed microstrip antenna, then original patch antenna can work as in-phase equivalent magnetic current sources. Then complementary sources are generated by orthogonal magnetic current source and electric current source, which can ensure that the antenna has good unidirectional radiation characteristics in one state. By switching the ON/OFF states of the PIN diodes, four different modes with endfire radiation patterns can be obtained and then this antenna can be used to obtain equivalent omnidirectional coverage. The antenna works in the 5G frequency band, and the complete microstrip floor characteristics make it suitable for automobile 5G communication applications.
License Plate Detection and Recognition System for All Types of Bangladeshi Vehicles Using Multi-step Deep Learning Model

A robust license plate (LP) detection and recognition system can extract the license plate information from a still image or video of a moving or stationary vehicle. Bangla license plate recognition is a complicated subject of study due to no publicly available dataset and its specific characteristics with over 100 unique classes, including words, letters, and digits. This paper proposes a robust multi-step deep learning system based on You Only Look Once (YOLO) architecture that can extract license plate information from a real-world image. The resulting system localizes license plates using YOLOv4 object detector model, automatically crops the license plates using bounding box coordinates, enhances the extracted license plate image quality using Enhanced Super Resolution Generative Adversarial Networks (ESRGAN), and then recognizes the classes using YOLOv4 without segmenting the characters. Synthetic images have been used to make proposed method capable of recognizing the classes in unfavorable and complicated conditions. A complete two-part dataset named ‘Bangla LPDB-A’ is created in this study. This dataset includes Bangladeshi vehicle images with manually annotated license plates and cropped license plates with manually annotated words, letters, and digits. The proposed system is tested on this dataset that has achieved mean average precision (mAP) of 98.35% and 98.09% for final detection and recognition model, which has an average prediction time of 23 ms and 35 ms.
Experimental Assessment of Sliding Mode Current Control with Exponential Reaching Law for an Induction Machine Drive Fed by a Matrix Converter

Matrix Converters (MCs) are considered an exciting option in electrical motor drives for applications where size and weight are critical, for example aerospace or automotive. Several control techniques have been proposed to exploit the MC’s benefits and get the desired performance. Among them, Sliding Mode Control (SMC) is quite attractive due to its robustness and fast response. However, Chattering can appear in the SMC strategy. Consequently, the Exponential Reaching Law (ERL) is employed to solve this issue in this paper. The proposed control structure includes a modulation stage based on the space vector modulation technique and a Kalman filter-based rotor current estimator. Experimental results are provided to validate the proposed method using a custom test bench based on SiC-MOSFETs MC and a three-phase induction machine. A comparison between the proposed SMC-ERL and classic SMC is also provided to highlight the improvements obtained.
Instrument response measurements of ion mobility spectrometers in situ: maintaining optimal system performance of fielded systems

Ion Mobility Spectroscopy (IMS) is the most widespread detection technique in use by the military for the detection of chemical warfare agents, explosives, and other threat agents. Moreover, its role in homeland security and force protection has expanded due, in part, to its good sensitivity, low power, lightweight, and reasonable cost. With the increased use of IMS systems as continuous monitors, it becomes necessary to develop tools and methodologies to ensure optimal performance over a wide range of conditions and extended periods of time. Namely, instrument calibration is needed to ensure proper sensitivity and to correct for matrix or environmental effects. We have developed methodologies to deal with the semi-quantitative nature of IMS and allow us to generate response curves that allow a gauge of instrument performance and maintenance requirements. This instrumentation communicates to the IMS systems via a software interface that was developed in-house. The software measures system response, logs information to a database, and generates the response curves. This paper will discuss the instrumentation, software, data collected, and initial results from fielded systems.
Frequency and Duty Ratio Control of Bidirectional Class-E2 Converter

This paper presents a frequency and duty ratio control for a bidirectional class-E2 dc-dc converter to provide a wide range of output voltage and current for small satellite power systems and energy storage applications. A class-E2 resonant dc-dc converter consisting of the symmetrical design of a class-E inverter and a class-E rectifier using GaN FETs achieves high efficiency at MHz frequencies thanks to the soft-switching operation. Also, synchronous rectification in the converter produces a maximum 6% efficiency increase compared with a rectifier using a GaN FET as a diode. However, their operation is often limited to a narrow load range or small input and output voltage variations. Therefore, this paper proposes varying the switching frequency from 800 kHz to 1.5 MHz and the converter’s duty ratio to control the output current while varying the phase shift between the inverter and rectifier. We designed and implemented the bidirectional class-E2 dc-dc converter prototype using GaN FETs and an FPGA to vary the output power levels and the direction of the power flow with a combination of frequency, duty ratio, and phase. The converter’s efficiency in the forward direction is 91.5% for 256 W output power and 89.1% in the reverse direction for 242 W output power at a nominal frequency of 1 MHz.
Phase Locked Loop based Pulse Density Modulation Scheme for the Power Control of Induction Heating Applications

Resonant converters are well suited for induction heating (IH) applications due to their advantages such as efficiency and power density. The control systems of these appliances should provide smooth and wide power control with fewer losses. In this paper, a simple phase locked loop (PLL) based variable duty cycle (VDC) pulse density modulation (PDM) power control scheme for use in class-D inverters for IH loads is proposed. This VDC PDM control method provides a wide power control range. This control scheme also achieves stable and efficient Zero-Voltage-Switching (ZVS) operation over a wide load range. Analysis and modeling of an IH load is done to perform a time domain simulation. The design and output power analysis of a class-D inverter are done for both the conventional pulse width modulation (PWM) and the proposed PLL based VDC PDM methods. The control principles of the proposed method are described in detail. The validity of the proposed control scheme is verified through MATLAB simulations. The PLL loop maintains operation closer to the resonant frequency irrespective of variations in the load parameters. The proposed control scheme provides a linear output power variation to simplify the control logic. A prototype of the class-D inverter system is implemented to validate the simulation results.
A New Planar Multi-Fed High-Isolation Broadband Filtering Integrated Triplex Antenna

In this letter, a novel planar multi-fed high-isolation broadband filtering integrated triplex antenna is proposed. Based on the single-layer dumbbell-shaped slot antenna, the proposed antenna incorporates the functions of triplex, wideband, and filtering. The isolation between the ports of the antenna is maintained at a good level, by using different types of feed lines and loading the different microstrip stubs. Three ports of the antenna are designed with separate resonant frequencies, enabling multiple communication standards and communication functions to be met simultaneously. A prototype has been built and measured to verify the validity of the design. The measured results show that this antenna works at 2.96-4.49 GHz, 5.08-6.33 GHz, and 9.20-10.53 GHz with the 10-dB return-loss impedance bandwidths of 41%, 21.91%, and 13.48%. The port isolation in the operating band is higher than 26 dB.
Efficient Multi-Party Contact Tracing

Since the beginning of the Covid-19 Pandemic, Contact Tracing Apps have been implemented in many countries as a way to detect if someone has been in contact with a patient within a minimum amount of time. However, most existing solutions only consider users in pairs. Since many people meet at the same time in real-life scenarios, those applications aren't able to accurately reflect the situation. Moreover, extending current schemes to a multi-party setting could cause scaling problems and place a heavier load on the device. In this paper, we propose a new Contact Tracing protocol that works in a multi-party setting. We evaluate our scheme to show its efficiency. © 2022 Information Processing Society of Japan.
Efficiently computing Pareto optimal G-skyline query in wireless sensor network

There are much data transmitted from sensors in wireless sensor network. How to mine vital information from these large amount of data is very important for decision-making. Aiming at mining more interesting information for users, the skyline technology has attracted more attention due to its widespread use for multi-criteria decision-making. The point which is not dominated by any other points can be called skyline point. The skyline consists of all these points which are candidates for users. However, traditional skyline which consists of individual points is not suitable for combinations. To address this gap, we focus on the group skyline query and propose efficient algorithm to computing the Pareto optimal group-based skyline (G-skyline). We propose multiple query windows to compute key skyline layers, then optimize the method to compute directed skyline graph, finally introduce primary points definition and propose a fast algorithm based on it to compute G-skyline groups directly and efficiently. The experiments on the real-world sensor data set and the synthetic data set show that our algorithm performs more efficiently than the existing algorithms.
Paternal Feelings and Child’s Anxiety: The Mediating Role of Father–Child Insecure Attachment and Child’s Emotional Regulation

The study introduces a path model that links between paternal feelings and child’s anxiety symptoms, aiming to test the mediational role of father–child insecure attachment and the child’s difficulties in emotional regulation in the occurrence of anxiety disorders among a sample of 148 fathers and their children (65 boys and 83 girls aged 8–18) attending the child psychiatric center of a public hospital. Participants completed a battery of diagnostical and research questionnaires, including the Parental Feelings Inventory (PFI), the Difficulties in Emotion Regulation Scale (DERS), the Screen for Child Anxiety–Related Emotional Disorders (SCARED), and the Experiences in Close Relationships Scale–Revised Child version (ECR-RC). Using structural equation modeling, we found father’s anger to be associated with father–child anxiety attachment, while the latter simultaneously mediated the link to the child’s anxiety both directly and indirectly (through emotion regulation [ER]). Consistent with previous evidence, we found insecure attachment and emotional regulation to be uniquely associated with the child’s anxiety. The current findings are among the first to demonstrate the interrelations between these variables in the context of father–child relations, suggesting that the child’s exposure to paternal anger might contribute to developing difficulties in ER and elevated anxiety due to a father–child insecure-anxious attachment relationship. The theoretical and practical implications of the findings are discussed in light of parental gender.
A New Preprocessing Approach to Reduce Computational Complexity for Time Series Forecasting with Neuronal Networks: Temporal Resolution Warping

In modern manufacturing environments huge amount of sensor data from machines have to be analyzed in the time domain. Applications for process control are to observe the stability, to predict behavior of mechanical components or to detect abnormal behavior of the manufacturing process. For that, time series forecasting is important to make manual or automated decisions. In this paper, we introduce a preprocess method which we call “temporal resolution warping” (TRW). It is used for signal pre-and post-processing before and after applying the neural network. Thus, the computation complexity of the used network is reduced by compressing the time series in a certain way. We will show the computation reduction capability of our approach. For verification of our approach feed forward and convolution neural networks with residual layers are used to forecast reference time series of different applications. We will demonstrate that the training is speed up more than 26% with our pre- and post-processing technique.
Researchers’ Perceptions About Methodological Innovations in Research Oriented to Social Impact: Citizen Evaluation of Social Impact

Current scientific literature is outlining a profound and accelerated transformation in the relationships between qualitative methodologies of research, citizens, society and social theories. The evolution towards a more dialogic society has led to a less talked about methodological advancement: Citizen participation in the evaluation of the social impact of research. Social impact is a priority of the current scientific research programs that also emphasize co-creation. The co-creation of the evaluation of this social impact requires both, qualitative methodologies and innovation, in order to make them able to optimize the social impact of research. This study, aimed at presenting the first meta-analysis of such methodological innovation from researchers’ view, includes interviews with seven researchers conducting research with social impact. In order to contrast citizens’ voices, results from the interviews have been validated by seven citizens who have participated in the dialogic citizen evaluation of the social impact of research. Findings can be summarized in three main categories: first, that the participation of citizens in the evaluation of the social impact of research is possible when researchers develop their contributions within the international scientific community and by integrating the voices of citizens, which facilitates the identification of transformative realities, as well as of pseudoscientific theories that have negative consequences for society. Second, that such evaluation is grounded on dialogic interactions open to everyone and based on arguments rather than on power interactions. Third, that both citizens and researchers report impacts of participating in the dialogic evaluation of social impact, such as modifying the way in which interviews are conducted, demanding more scientific evidence, or transforming their professional practice and lives.
DALTA: A Decomposition-based Approximate Lookup Table Architecture

A popular way to implement an arithmetic function is through a lookup table (LUT), which stores the pre-computed outputs for all the inputs. However, its size grows exponentially with the number of input bits. In this work, targeting at computing kernels of error-tolerant applications, we propose DALTA, a reconfigurable decomposition-based approximate lookup table architecture, to approximately implement those kernels with dramatically reduced size. We also propose integer linear programming-based approximate decomposition methods to map a given function to the architecture. Our architecture features with low energy consumption and high speed. The experimental results show that our architecture achieves energy and latency savings by 56.5% and 92.4%, respectively, over the state-of-the-art approximate LUT architecture.
Frequency decoupled coding meta-mirror by combining propagation phase with geometric phase

Frequency decoupling in single resonance is crucial for various applications both in optical and microwave regions. Here, we develop a completely dual-frequency decoupled strategy in single meta-atom for independent phase and amplitude control by combining propagation with geometric phases. As a proof of concept, the bi-functionalities of multifocal shaping with uniform amplitude at two different frequencies have been experimentally demonstrated. This scheme may pave a new route for multi-mode detection, communication and imaging applications.
Derivation of a Pharmacokinetic Model to Include a Plasma-Derived, von Willebrand Factor-Containing Factor VIII (Koate®-DVI) Concentrate and its Low-Dose Use

Background Population pharmacokinetics (popPK) has been reliably leveraged to generate individual PK in hemophilia patients. Specific popPK models are suited to predict individual PK under a variety of scenarios that may not be captured by clinical trials, allowing for individualized prophylactic treatment. The Web-Accessible Population Pharmacokinetic Service-Hemophilia (WAPPS-Hemo) project generates individually predicted pharmacokinetic profiles relying on concentrate-specific popPK models used for Bayesian forecasting. Objective Specification of a popPK model for the plasma-derived factor VIII (FVIII) concentrate Koate-DVI and its suitability for pharmacokinetic estimation in low-dose scenarios. Methods A popPK model was developed for Koate-DVI WAPPS-Hemo PK data in combination with the existing WAPPS-Hemo Fanhdi/Alphanate model derivation dataset using nonlinear mixed effects modelling, and was validated via cross-validation and prediction-corrected Visual Predictive Checks (pcVPC). Bootstrap and PK outcomes between the Fanhdi/Alphanate and the Fanhdi/Alphanate/Koate models were compared, and the relative error distributions from a limited sampling analysis (LSA) under the latter model for low and normal doses (10 vs 50 IU/kg) and inclusion/exclusion of pre-dose measurements. Results A Fanhdi/Alphanate/Koate model was derived (126 patients, ages 1–71 years) after deeming a Koate-brand covariate not clinically significant, resulting in similar parameter estimates than the Fanhdi/Alphanate model with satisfactory goodness of fit, cross-validation and pcVPC results. Low-dose predictions resulted in a higher accuracy and slightly lower precision of half-life ( β -phase) and time to 2% trough (TAT2%) estimates than normal dose (median absolute bias for half-life: 0.12 vs 0.5%; median interquartile range, IQR: 11.79% vs 9.95%). Precision improved under pre-dose designs by 2 to 3% and remained similar between 5- and 2-sample designs (IQR reduction<1.8%). Conclusions The Fanhdi/Alphanate/Koate model is appropriate for Bayesian forecasting in the WAPPS-Hemo platform, providing a comparable prediction capability for low and normal dosing regimens (10 vs 50 IU/Kg).
A Novel Dual-Band Mixer Using Arbitrary Impedances-Matching Coupler for Long-Term Evolution Applications

Abstract A novel microstrip dual-band down-conversion mixer is proposed in this article, which uses an inherent arbitrary impedances-matching coupler and a high-performance lowpass filter for long-term evolution (1.7–1.9 and 2.5–2.7 GHz) applications. Based on the accurate terminated impedances design method, the designed coupler can be directly used as an inherent matching network. In this article, the proposed dual-band mixer is fabricated and experimentally measured to show good agreement between simulated and measured results. This proposed mixer features a compact size and high linearity performance and achieves best power conversion gains of –15 and –10 dB in two bands, respectively. The input 1-dB compression point (P1dB) for two bands of the mixer are approximately –3 and –6 dBm, while the measured input third-order intercept point (IIP3) in two bands are 11 and 3 dBm, separately.
Refined Beam Models for Static and Dynamic Analysis of Wingsand Rotor Blades

This paper presents the finite element analysis of slender thin-walled bodies by means of different finite element models. The beam formulation is given in the framework of the Carrera Unified Formulation, CUF, which considers the order of the theory, N, as a free parameter of the analysis. N is the order of the 1D displacement expansion. The displacement components are, in fact, expanded in terms of the cross-section coordinates, (x, z), by using a set of 1D generalized displacement variables. The refined kinematic models are based on Taylor-type polynomials. The finite element formulation is exploited in order to be able to face arbitrary cross-section geometries. FE’s matrices are obtained in terms of a few fundamental nuclei which are formally independent of both N and the number of element nodes. A cubic (4 nodes) approximation along the beam axis, (y), is used. Structural analyses are conducted starting from classical beam theories, refined models are then introduced to evaluate non-classical effects. Aircraft wing and wind turbine blade models are analyzed. Static and dynamic analyses are conducted. It has mainly been concluded that the enhanced refined beam element, which has been formulated via CUF, is able to detect the so-called shell-like mechanical behaviors, that is, shell-like results can be obtained using higher-order beam elements. The shell-like capabilities include the detection of the local displacement field induced by a concentrated load, and natural modes characterized by the presence of waves along the cross-section contour.
Hardware-in-the-Loop Experimental Setup of a LCL-Filtered Grid-Connected Inverter with Digital Proportional-Resonant Current Controller

This paper presents a Hardware-in-the-Loop setup of a LCL-filtered grid-connected inverter with digital Proportional-Resonant current controller. The power structure of the system, i.e. the power DC source, the transistor-based inverter, the LCL filter, the sensors and the grid are emulated in the Real-Time Simulator HIL402 from Typhoon-HIL, while the control strategy is embedded in the Digital Signal Controller TMS320F28335 from Texas Instruments. Descriptions of how to design the PR controller is presented. Details about the settings of the RTS are also described. The HIL verification consists of applying several real time test cases along the power structure as well as in the control strategy, allowing designers to rapidly evaluate the efficacy of the PR controller. Some modifications are: inclusion of an oscillation at the DC-link voltage, frequency variation at the grid voltage, variation of grid impedance, current reference step, among others. Results show that the HIL verification is an attractive tool for evaluating the PR current controller of a LCL-filtered grid-connected inverter.
A virtual instrument for the measurement of the characteristics of magnetic materials

The authors present a completely digital method for fast and accurate measurement of the magnetic characteristic (magnetization curve, hysteresis loop and total losses) of magnetic materials under cyclic magnetization. The mathematical basis of the method is discussed and applied to the realization of a virtual instrument for these measurements. The results of experiments on ferrosilicon plates and on amorphous materials are reported and their accuracy and sensitivity are discussed. The validity of the proposed method is demonstrated. <<ETX>>