Miracle-dz/UniFAR-FTUs huggingface dataset:
A resonant Class E power amplifier for low resistance load

In some applications such as radio transmitters with loop antennas, h.f. drivers for RFID transmitting coils, wireless h.f. power supplies for biomedical implants and endoscope capsules etc. resonant power amplifiers operate with high-reactance and low-resistance load. The paper analyses an off-nominal Class E ZVS amplifier to identify conditions for its high-efficiency operation with low-resistance load. Power loss of the transistor switch in Class E amplifiers with normalized transistor turn-on time D= 0.5 operating in nominal and off-nominal conditions are compared. Analytical closed-form estimations for power losses in the transistor switch in the off-nominal amplifier are given. Theoretical results experimentally validated have demonstrated that by designing the off-nominal Class E amplifier for a high enough dc supply voltage the power losses in the transistor switch can be significantly reduced. This makes the circuit useful in those applications that require the amplifier to operate with high output current and/or low-resistance load. A laboratory model of the off-nominal amplifier was designed and built to operate at the frequency 140 kHz with output power 50 W, dc supply voltage 24 V, load resistance 2 n and D= 0.5. Its measured efficiency was 96 %.
Advanced Secure Architecture for The Internet of Things based on DTLS Protocol

This study presents an authentication security scheme for implementation on the Internet of Things (IoT). This scheme is reliant on the prevailing Internet standards, particularly on the Datagram Transport Layer Security (DTLS) protocol. The reliance of this scheme on an existing standard facilitates the reuse of the existing engineering techniques, implementations, and security features in the new scheme, thereby enabling easy security uptake. The scheme proposed in this study is based on RSA, which is the commonly used public-key cryptographic framework. Its design supports execution over the standard communication stacks that offer UDP/IPv6 networking for 6LoWPANs. In this study, DTLS was implemented from the perspective of a systems framework. The feasibility of the scheme in terms of high interoperability and low overheads is also proven via several evaluations on a suitable hardware platform for IoT.
Inverse memrsitor emulator active Realizations

The paper aims to propose three different inverse memristor emulators based on serveral active blocks. One of the presented emulator realizes employing second generation current conveyor (CCII) andcanalog voltage multiplier with passive elements. The other two introduced emulators are designed using cureent feedback operational amplifier (CFOA) with two switches or two BJT transistor. One of the proposed emulators has the advantages that it switches between the inverse and memristor at the same time but in different frequency with less number of components. The introduced circuitry are simulated to validate the concept of inverse memristor showing the pinched hysteresis loop in the I-V plane. Selected emulator is verified experimentally. A comparison of the three proposed emulators is presented to highlight the number ofcactive, passive components, and the range of frequency.
A Comparative Investigation of the Mechanical Properties of Mild Steel Rods Produced by two Local Steel Manufacturers in Nigeria

Recent increases in the unexpected collapses of residential buildings necessitated an investigation as well as a comparison of the mechanical and chemical properties of local steel bars produced by various firms in Nigeria. A number of tests such as hardness, impact and tensile tests and also chemical compositions were carried out on those steel bars received from Kastina and Sharada steel manufactures. Results revealed that the carbon contents of the samples varied between 0.35 - 0.41 %, i.e. above those limits recommended by the ASTM standards for reinforcing steel bars. The hardness values were found to be more than the estimated standard values and increased with the carbon content. The ultimate tensile strengths and yield strengths were noted as 621.6 MPa and 441.1 MPa for Sharada and 473.7 MPa and 324.5 MPa for Kastina mills, respectively. The ASTM and NQSA standards required ultimate tensile strengths as 620 MPa - 690 MPa and this was fulfilled by the Sharada company. The yield strength of samples from both steel producers were below the recommended values, i.e. 420 MPa – 520 MPa of the standards. It can be recommended that strict laws and regulations are needed to guide and control the production and application of steel reinforcement bars.
BAT Algorithm With fuzzy C-Ordered Means (BAFCOM) Clustering Segmentation and Enhanced Capsule Networks (ECN) for Brain Cancer MRI Images Classification

Cancer is a second foremost life-threatening disease next to cardiovascular diseases. In particular, brain cancer holds the least rate of survival than all other cancer types. The categorization of a brain tumor depends upon the various factors such as texture, shape and location. The medical experts have preferred the appropriate treatment to the patients, based on the accurate identification of tumor type. The process of segmenting the Magnetic Resonance Imaging (MRI) has high complicacy during the analysis of brain tumor, owing to its variable shape, location, size, and texture. The physicians and radiologists can easily detect and categorize the tumors if there exists a system by combining Computer Assisted Diagnosis (CAD) as well as Artificial Intelligence (AI). An approach of automated segmentation has proposed in this paper, which enables the segmentation of tumor out of MRI images, besides enhances the efficiency of segmentation and classification. The initial functions of this approach include preprocessing and segmentation processes for segmenting tumor or tissue of benign and malignant by expanding a range of data and clustering. A modern learning-based approach has suggested in this study, in order to process the automated segmentation in multimodal MRI images to identify brain tumor, hence the clustering algorithm of Bat Algorithm with Fuzzy C-Ordered Means (BAFCOM) has recommended segmenting the tumor. The Bat Algorithm calculates the initial centroids and distance within the pixels in the clustering algorithm of BAFCOM, which also acquires the tumor through determining the distance among tumor Region of Interest (RoI) and non-tumor RoI. Afterwards, the MRI image has analyzed by the Enhanced Capsule Networks (ECN) method to categorize it as normal and brain tumor. Ultimately, the algorithm of ECN has assessed the performance of proposed approach by distinguishing the two categories of the tumor over MRI images, besides the suggested ECN classifier has assessed by the measurement factors of accuracy, precision, recall, and F1-score. In addition, the genetic algorithm has applied to process the automatic tumor stage classification, which in turn classification accuracy enhanced.
Extracting mechanical Q factor of the pure AlN, ScAlN, and ZnO films without etching substrate

The demand for the sharp RF filters is increasing to prevent interference in crowded frequency bands of the mobile communication. When other electrical loss and lateral acoustic wave leakage are adequately suppressed, the sharpness of BAW filters is determined by mechanical Q factors (Qm) of piezoelectric thin films. However, the Qm of various piezoelectric are not well known probably because a self-standing film structure (FBAR structure) are necessary to extract Qpiezo (Qm of the piezoelectric films). In this study, we grew pure AlN, ScAlN (40%), and ZnO thin films and ScAlN thin films with different Sc concentrations. In addition, we extracted the Qm of pure AlN, ScAlN, ZnO thin films, and ScAlN thin films with different Sc concentrations by using the method which can estimate Qm without removing substrates [1]. As a result, Qm of pure AlN thin film is higher than that of ScAlN and ZnO thin films and Qm of ScAlN and ZnO thin films are not different much. In addition, it was confirmed that the Qpiezo decreased with increasing Sc concentration.
QDR: A Quadrotor Dead Reckoning Framework

Quadrotors are used for variety of applications both outdoors and indoors. Among them are - deliveries, surveillance, transportation, mapping and more. To accomplish its tasks an accurate navigation solution is required. To that end, most quadrotors apply fusion between an inertial navigation system and other external sensors, such as global navigation satellite systems (outdoors) or vision (indoors/outdoors). Due to environmental or sensor constraints, in some portion of the trajectory, the navigation solution relies only on the inertial navigation system solution. Consequently, the navigation solution drifts in time due to errors and noise in the inertial sensors measurements. Motivated from the pedestrian dead reckoning approach, we propose the quadrotor dead-reckoning framework to mitigate the navigation solution drift in situations of pure inertial navigation. There, instead of a straight line trajectory, the quadrotor is flown with a periodic motion to enable peak to peak distance estimation. Simulation and experiments results show that the proposed approach greatly improves the accuracy of the navigation solution.
Accessibility Analysis of Unmanned Aerial Vehicles Near Airports with a Four-Dimensional Airspace Management Concept

The demand for UAS operations is increasing in recent years, as well as the traffic volume of civil aviation. The operations of both traffic modules are based on the utilization of airspace resources. Currently Unmanned Aircraft Systems (UAS) are not allowed to operate close to airports, where potential conflicts between UAS and manned aircraft may happen. This rule is constraining the application of UAS. Therefore, it is necessary to study the current airspace utilization pattern near airports, before the boundary determination of UAS operation to allow the UAS accessing airspace safely without conflicts. In this paper, a data-driven analysis on historical trajectories at Changi Airport in Singapore was carried out. Trajectory data have been clustered to recognize the utilization patterns of airspace. Discussions on the boundary of UAS operation were presented based on both current airspace utilization patterns and the estimated capacity. The airspace utilization was further modeled in an urban airspace management framework, and quantifiable area for potential UAS operation was analyzed. As this is the first research study to present the initial concept, more operational and other factors should be considered in the future study for the generation of potential boundary of UAS operations.
Reliability of Bio-Inspired Ultra-Dense Networks

In this work, the authors focused on assessing the reliability of the dense wireless network that draws inspiration from the human nervous system. The concept of such a network was created using the action of a glial cell, i.e. microglia, which is involved in the damaged nerve connections repair process. To assess reliability, the authors used the percolation theory, in particular the percolation threshold. This approach makes the results of simulations independent of the specific network topology. In the simulations carried out, the reliability level of the analyzed systems were also appointed.
TrustedID: An Identity Management System based on OpenID Connect Protocol

Today, authentication and non-repudiation of actions are essential requirements for almost all mobile services. In this respect, various common identity systems (such as Facebook Login, Google Sign-In, Apple ID and many other) based on OpenID Connect protocol have been introduced that support easier password management for users, and reduce potential risks by securing the service provider and the user. With the widespread use of the Internet, smartphones can offer many services with rich content. The use of common identity systems on mobile devices with a high security level is becoming a more important requirement. At this point, MNOs (Mobile Network Operators) have a significant potential and capability for providing common identity services. The existing solutions based on Mobile Connect standard provide generally low level of assurance. Accordingly, there is an urgent need for a common identity system that provide higher level of assurance and security for service providers. This study presents a multi-factor authentication mechanism called TrustedID system that is based on Mobile Connect and OpenID Connect standards, and ensures higher level of assurance. The proposed system aims to use three identity factors of the user in order to access sensitive mobile services on the smartphone. The proposed authentication system will support improvement of new value-added services and also support the development of mobile ecosystem.
Fiber wireless and optical wireless communications using high-speed photonic devices

High data rates and low latencies will be indispensable in next generation communication devices. In order to achieve these targets, the use of wireless communication technology combined with photonics and optics is expected to have significant potential. In this paper, we present a key device for advanced fiber wireless and optical wireless communications. A new device integrated with a 100 GHz uni-travelling carrier photodetector and a 100 GHz pHEMT amplifier is introduced for high data rate fiber wireless communication applications operating at data rates above 20 Gbps. For optical wireless communication applications, another novel two-dimensional photodetector array (2D-PDA) device is introduced, and demonstrated for 100 Gbps high data rate communications using the wavelength division multiplexing (WDM) technology in free-space.
Performance comparison between PD and PID Controller in an upper limb Exoskeleton by analyzing an arm trajectory modeled with Image Recognition

This paper presents a performance comparison between PD and PID controllers of a 3-DOF (3 Degrees of Freedom) upper-limb exoskeletons by analyzing an arm trajectory during a rehabilitation task. Trajectory was recorded and modeled by an image recognition algorithm for its identification. 2-DOF were considered and associated with the shoulder and the elbow joints. The trajectory, used in rehabilitation, is based on a basic activity of daily life. By using the collected data, we obtained the tracking error variance of PD and PID controllers for each body joint in the arm in order to make a suitable performance comparison according to quantitative results. Besides, this study is relevant because this sort of robotic system aims to assist patients by allowing more reliable and fast recovery of arm mobility.
When FPGAs Meet Regionless Explicit MPC: An Implementation of Long-horizon Linear MPC for Power Electronic Systems

This paper presents a novel real-time implementation of linear model predictive control (MPC) schemes based on region-less explicit MPC (RL-EMPC). RL-EMPC is a recently proposed explicit MPC solution for achieving a low memory footprint compared to other explicit MPC methods. Thus RL-EMPC can effectively handle systems with high sampling rates even for large-size MPC problems, i.e. systems with many states and/or constraints. An architecture for an implementation on an FPGA device is presented and validated with two application examples (buck-boost converter, modular multilevel converter). Simulation results on FPGA hardware-level demonstrate that long-horizon linear MPC can be implemented on low-cost FPGAs with the proposed architecture for various power electronic systems.
Maximum Constant Boost Control of Four Switch Switched Boost Inverter

A new control strategy for the four switch switched boost inverter is presented in this paper. A quasi-switched boost inverter is modified in order to derive the inverter structure. A maximum constant boost control technique is suggested for the four switch switched boost inverter. Therefore, it can work properly in non shoot-through as well as shoot-through modes and operate as a single stage boost inverter. Besides the voltage gain of the inverter can be improved and the maintenance of low voltage stress across the switching elements can also be obtained under a given modulation index. Analysis of control technique, relationships in between the voltage gain of the inverter and modulation ratio, voltage stress of switching devices and voltage gain are detailed and are substantiated by simulation results.
Predicting Safety Logic Device Solutions via Decision Trees and Rules Algorithms

Considering the extensive data sets and statistical techniques, a digital factory (plant) embodies a branch of machine learning that has an impact on machine safety. We propose a study based on an application of decision trees and rules algorithms (JRIP, J48, Random Forest, Random Tree, and PART). Our experimental data were collected from various industrial machine safety solutions. Diverse validation techniques were employed to derive the classification performance of each method; the approach is expected to simplify the user choice of a suitable safety logic device type. In this study, the overall classification methods proportion of individual safety logic device solutions were correctly assigned by using the training-evaluated test mode, and the prediction accuracy reached 100%; further, when assessing the 5-fold cross-validation test mode, we obtained the success rate of 82% (JRIP and PART). PART as the best method was correctly assigned for the 10-fold cross-validation test mode (85%). New developments within the broad province of machine learning, including the concepts characterized in our study, may facilitate effective assessment of machine safety systems.
A Sequentially Rotated Array of Polarization-Conversion Patch Antenna Using Metasurface

In this paper, metasurface-based patch antennas are arrayed in a sequentially-rotated layout for a high gain and broadband circularly polarized (CP) radiation. The single element is a rectangular patch, which is incorporated with a metasurface composed of 4×4 rectangular loops with diagonal strip in order to convert linearly-polarized wave from the patch into a CP wave. The array is fed by a sequential phase network based on series-parallel strips. The ANSYS Electronic Desktop is used for the simulations through this work. The final design has been realized and tested. The prototype yields a measured |S11| < −10 dB at 8.6 – 10.5 GHz, which agreed rather closely with the simulated value of 8.45 – 10.5 GHz. Moreover, the antenna achieves a broadband right-hand CP radiation; i.e., it yields a 3-dB axial ratio bandwidth of 15.38% (8.88 – 10.36 GHz), the peak broadside gain of 11.8 dBic, and a radiation efficiency of > 80%.
Role of central 5-HT2C receptor in the control of basal ganglia functions

The basal ganglia are a highly interconnected group of subcortical nuclei in the vertebrate brain that play a critical role not only in the control of movements but also in some cognitive and behavioural functions. Several recent studies have emphasized that serotonergic pathways in the central nervous system (CNS) are intimately involved in the modulation of the basal ganglia and in the pathophysiology of human involuntary movement disorders. These observations are supported by anatomical evidence demonstrating large serotonergic innervation of the basal ganglia. In fact, serotonergic terminals have been reported to make synaptic contacts with both dopamine (DA)-containing neurons and γ -aminobutyric acid (GABA)-containing neurons in the striatum, globus pallidus, subthalamus and substantia nigra. These brain areas contain the highest concentration of serotonin (5-HT), with the substantia nigra pars reticulata receiving the greatest input. Furthermore, in these structures a high expression of 5-HT different receptor subtypes has been revealed. In this paper, evidence demonstrating the serotonergic control of basal ganglia functions will be reviewed, focusing on the role of the 5-HT 2C receptor subtype. Moreover, the involvement of 5-HT 2C receptors in neurological disorders such as Parkinson’s diseases and other related motor disorders, and their management with drugs acting on 5-HT 2C receptor will be discussed.
High-precision Sensorless Control Based on Magnetic Flux/Current Method for SRM Starting/Generating System

As an important part of the future multi-electric aircraft, the reliability of switched reluctance motor (SRM) starting/generating system is one of the most concerned performances. SRM control is inseparable from the position signal, but the presence of the axis position sensors brings reliability risks. Based on direct instantaneous torque control (DITC), this paper studies the position sensorless technology of SRM in the electric / generation state. Based on the current waveform of the motor in the electric/ generation state, the position partition methods suitable for two states individually are proposed to avoid low-quality position signals in the aligned and unaligned position areas. In each position area, the magnetic flux and current signals corresponding to the conducting observation phase are calculated in real time, and the position signal is obtained by looking up the table. As for the position delay caused by filtering, the speed feedback is to introduced to realize adaptive compensation. After simulation verification, compared with the single-cycle single-point position sensorless detection method, the partition position detection method based on magnetic flux/ current method is suitable for wider range of speed and has better dynamic response.
Fault Detection of Supermarket Refrigeration Systems Using Convolutional Neural Network

The functionality of supermarket refrigeration systems (SRS) has a significant impact on the quality of food products and potentially human health. Automatic fault detection and diagnosis of SRS is desired by manufacturers and customers as performance is improved, and energy consumption and cost is lowered. In this work, Convolutional Neural Networks (CNN) are applied for fault detection and diagnosis of SRS. The network is found to be able to classify the fault with 99% accuracy. The sensitivity of the designed model to data quality is also assessed. The results show that the model can classify faults at low sample rates if the training set is large enough. Moreover, the model displays low sensitivity to data quality such as noisy and perturbed validation data, and the frequency of false positives is satisfactorily low as well.
Achieving Flexible Digital Production with the Arrowhead Workflow Choreographer

Arrowhead is an IIoT (Industrial IoT) framework that dynamically and flexibly supports automated manufacturing processes following Industry 4.0 expectations. This technical paper describes how its workflow management system, i.e., the Workflow Choreographer supports automated production. The motivation behind this work is to make production workflow management and execution more flexible by applying the SOA (Service-Oriented Architecture) principles that help information exchange between various, loosely coupled systems through late binding and lookup of their services. This paper further details the functions of the Workflow Choreographer system and shows how it applies the identified workflow levels in practice to provide a solution for the given challenge. To validate its feasibility, the paper presents simple use cases where the Workflow Choreographer manages typical production processes under laboratory conditions.