Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison Study between Flat Solenoid Coupler and Planar Square Coupler for WPT Systems

Loosely coupled transformers (LCTs) play an important role in wireless power transfer (WPT) systems. The flat solenoid coupler and planar square coupler are two most commonly utilized LCTs. To compare the performance of these two structures, simulation using ANSYS Maxwell is conducted. For the sake of fairness, the length, width and height of the ferrite core, the length of the air gap, and the specification of the Litz wire are consistent. The coil turns is optimized to make the self-inductance of these two LCTs equal. Finally, the two optimized LCTs are comprehensively compared in terms of self-inductance variation, coupling coefficient, misalignment tolerance, leakage magnetic flux intensity, and cost.
Development of beltless respiration and heartbeat sensor based on flexible piezoelectric film

The main goal of this work is to report initial development on a respiration and heartbeat measurement sensor that can be used in continuous monitoring conditions at a minimal impact on the patient. General description of the sensor, consisting of a PVDF film and the bonding layer, is given. Open-circuit voltage generated by the sensor is estimated by analytical and numerical calculations. Analog and digital interface used to extract the bio-data is briefly described. Finally, signal conditioning with digital filters, as well as, measurements of respiration and heart rate at two locations are presented and discussed.
Reassessing cotton pricing policy in Burkina Faso: How important is price stabilization?

This paper focuses on the parastatal marketing of cotton in Burkina Faso. The parastatal companies have bought cotton at a guaranteed price, announced prior to planting, reducing a key element of risk for producers. The cotton sector reforms in the late 1990s and early 2000s have significantly improved the share of international price received by local producers. However, a number of problems must still be solved to improve the living conditions for rural agricultural producers. The purpose of this paper is to reassess parastatal cotton pricing in Burkina Faso by factoring the implicit benefit that producers have obtained from guaranteed prices which reduces the price variability risk. A mean-variance economic risk model was developed to measure the price risk that would have been associated with selling cotton on international markets rather than selling to parastatal companies at a guaranteed price. Results suggest that risk is often a significant factor in producers’ decision making, particularly over the past decade, when price volatility would have driven risk averse producers out of international markets. The viability of the parastatal markets, contrary to the prevailing literature which suggests that future policy shifts towards increased privatization, needs to consider price stabilization and the price variability risk associated with the international cotton market. Key words: Cotton, price risk, mean-variance model, risk premium, certainty equivalent.
Stochastic Optimal Control to Minimize the Impact of Manufacturing Variations on Nanomechanical Systems

This paper presents a control method intended to suppress the effects of manufacturing variations on nanomechanical systems. Often, the resonance characteristics of nanoscale devices are inconsistent, due to unavoidable variations in the fabrication process. This is important because resonant vibrations enhance the sensitivities of the devices. As such, the sensitivities of these systems can be degraded if the device characteristics are not identified. To address this fundamental problem, this paper presents a multidisciplinary method based on control theory, nanotechnology, and communication technology. A stochastic optimal feedback controller is employed to enhance an average sensitivity by regarding the variations as stochastic parameters. This method is applied to nanoscale receivers that detect transmitted binary data based on binary phase-shift keying in communication systems. The proposed method controls the vibrations of carbon nanotubes (CNTs) that serve as the antennas of the receiver. The proposed method is demonstrated via a numerical simulation using nanoscale receivers with the manufacturing variation. The simulation based on experimental data obtained from CNTs shows that the average performance of the devices is enhanced.
Design of Active Learning Framework for Collaborative Anomaly Detection

In this paper, we propose a collaborative anomaly detection system based on the Active Learning framework. In this system, multiple Edge nodes are responsible for monitoring and collecting data from the local users. To reduce the data to be transmitted, we adopt the Principal Component Analysis(PCA) method in the data preprocessing stage on each Edge node. Then each Edge node selects the most valuable samples based on the Uncertainty Sampling strategies. These samples are then uploaded to the Cloud server for anomaly detection based on the machine learning classification schemes. The samples are also used to train the sample selection model on the Cloud. The parameters of the Cloud classifier and sample selection model are then sent back to the Edge nodes to update their classifiers and sample selection models. This system allows us to reduce the cost in sample obtaining, shorten the bandwidth demand and lower the latency. We implement the proposed anomaly detection schemes in a practical system and provide experiment results to demonstrate the performances of the system.
Study on Performance Optimization of IGCT Device for DC Circuit Breaker

The DC circuit breaker is the key equipment in the DC power transmission and distribution system. IGCT devices have important application prospects in DC breaking, providing the advantages of large surge current capability and low current conduction losses. Aiming at the on-off electrical characteristics of IGCT, this paper provides the optimized design method for improving the current turn-off capability and reducing the on-state voltage drop of IGCT, in which the GCT longitudinal optimization structure for DC breaking conditions is obtained. Meanwhile, for IGCT compact modular application, the gate unit (GU) is miniaturized and isolated, and GU can be replaced without decompression. Moreover, the GU power supply, series-parallel application and control protection technology optimization are carried out for the practical application requirements. Finally, the validity and feasibility of proposed method are verified by simulation and module test.
Using Procedural Content Generation for Storytelling in a Serious Game Called Orange Care

It is well known that the use of Procedural Content Generation (PCG) techniques is commonly used in the digital gaming industry because of its efficiency in solving problems and consequently reducing development costs and time. In particular refers to a computer program that automate the game's content creation process, reducing the manual effort of human work. The choice of the technique also can be useful in other situations like compression of game data, save memory space, and others, but the implementation of the PCG technique requires a mastery over the problem that will be solved, because for each type of problem there is a type algorithm to be considered. The proposal of this research consists in the application of such technique for the automation of construction of characters and scripts for a serious game. The objective of this game is to convey educational content about skin lesions to primary care physicians. Within the game there are characters who are patients that have different phenotypes and skin blemishes, and the player must analyze if the stain contained in a patient is a cancer (melanoma), and subsequently decide if that patient should be referred to the dermatology sector or not. The implementation of the technique is based on generating these patients and the scripts with different peculiarities, taking into consideration the level of knowledge about the skin lesions that the player possesses to provide education and fun adapted to him. The results presented in this work are just tests of the implemented algorithms, but can be considered as in-game practical results, since the game was not tested with the main public yet.
Grid Connection Approach for Very Small-Scale Pico-Hydro Systems Using PV Microinverters

The use of renewable energy sources has grown significantly in recent decades, with emphasis on resources that have a low environmental impact in the energy production process. Small-scale pico-hydro systems have great potential and are also in line with increasing environmental requirements. Microgrids can integrate this type of solution into self-supporting systems and electrification of remote locations. This paper presents and discusses an approach for very small-scale pico-hydro systems, up to 300W, for grid connection, using photovoltaic microinverters recently launched on the market. Experimental validation was performed on a test workbench and a laboratory platform. The results were carried on applying different input power values. The laboratory platform consists of a water wheel prototype with specific water flow and head. Data from two generators, three microinverters, and a passive load were collected during the laboratory experiments. This approach presents encouraging results for the exploration of the emerging energy potential of pico-hydro systems of very small pico-hydro systems, with power available 24 hours per day. This work is a contribution to the dissemination of this approach, which can be easily widespread and contribute to environmentally friendly energy production.
Design of Proportional-Integral Controller of Hybrid Grid-Connected Inverter for Active Power Injection and Unbalanced Non-Active Power Compensation

With the characteristics of a low dc-link operating voltage of the active inverter part and thyristor controlled passive part, the hybrid-coupling grid-connected inverter (HGCI) can reduce the system and operational costs as well as extend the operational range compared with the conventional inductive-coupling grid-connected inverter (IGCI) and capacitive-coupling grid-connected inverter (CGCI) for the renewable energy generation. In this paper, a control strategy by using proportional-integral (PI) controller of the HGCI for active power injection and unbalanced non-active power compensation will be proposed and presented, which can reduce the switching current ripple and obtain better active and non-active power compensation compared with the conventional hysteresis current controller. Finally, simulation and experimental results are provided to verify the performance of the designed PI controller for the HGCI under unbalanced loads operation.
Analysis and Performance Evaluation of Novel Microstrip Patch Antenna Based on Two Parasitic Ring Resonators and Partial Ground Plane for Multiband Applications

In this paper, a novel planar monopole antenna for multi-band applications is proposed. The simulated results show that the proposed antenna operates at multiband resonance frequencies, which covers different wireless communication applications. The proposed antenna consists of a quasi-modified rectangular radiating patch with a partial ground plane and two parasitic elements (open-loop-ring resonators) to serve as coupling-bridges. A stepped cut at the partial ground plane is used, to achieve the multi-band features. The proposed antenna is simulated and optimized using High-Frequency Simulation System (HFSS). The antenna topology possesses an area of 30×30 ×1.27 mm3. The measured results demonstrate that the proposed antenna has impedance bandwidths for −10 dB return loss which meet the requirements of worldwide interoperability for microwave access (Wi-MAX), C- (Uplink), X (Uplink) and Ku- (Uplink) band applications. An Acceptable agreement is obtained between measurement and simulation results. Experimental results show that the antenna is successfully simulated and measured.
Offloading With Hybrid Cell Association in Non-Uniform Heterogeneous Cellular Networks: Modeling and Performance Analysis

Flexible/biased cell association in uniform Heterogeneous Cellular Network (HCN) can lead to poor offloading, particularly near to the Macrocell Base Station (MBS). Additionally, in the cell-edge region, a user might offload to an SBS even if unbiased cell association is employed. In this paper, firstly, we consider a Non-uniform HCN (NuHCN) model in which SBSs are not deployed in a circular region around each MBS within a predefined radius, which we call the inner region. Secondly, we define the outer region, which is disjoint to the inner region, as the cell-edge region. In these two regions, based on maximum received power; we propose hard cell association scheme, where users located in the inner region shall only be served by MBS, whereas users located in the outer region shall be served only by SBS. Finally, for the region between the inner and the outer region, called the annular region, we shall use the flexible cell association scheme. Based on the proposed system model, analytical closed forms for the downlink coverage and single user throughput are derived. It is observed that with non-uniform deployment of SBSs and precisely selecting the size of inner, annular, and outer region, both coverage and single user throughput are significantly improved compared to uniform HCN.
How you type is what you type: Keystroke dynamics correlate with affective content

Estimating the affective state of a user during a computer task traditionally relies on either subjective reports or analysis of physiological signals, facial expressions, and other measures. These methods have known limitations, can be intrusive and may require specialized equipment. An alternative would be employing a ubiquitous device of everyday use such as a standard keyboard. Here we investigate if we can infer the emotional state of a user by analyzing their typing patterns. To test this hypothesis, we asked 400 participants to caption a set of emotionally charged images taken from a standard database with known ratings of arousal and valence. We computed different keystroke pattern dynamics, including keystroke duration (dwell time) and latency (flight time). By computing the mean value of all of these features for each image, we found a statistically significant negative correlation between dwell times and valence, and between flight times and arousal. These results highlight the potential of using keystroke dynamics to estimate the affective state of a user in a non-obtrusive way and without the need for specialized devices.
Modelling and Passivity Analysis of VSC Output Impedance under SRF and αβ Control Frames

Passivity property of input impedance of grid connected Voltage Source Converter (VSC) is a good measure for ensuring small signal stability of the power system composed of numerous interconnected dynamical system. It is well known that a pure passivity for a VSC is impossible to obtain, however, if the frequency range of the negative admittance from VSC terminal can be minimized, the possibility instability due to grid side impedance interacting with the VSC system can be reduced. For a VSC, there are two major design alternatives for the current controller;a decoupled dq current controller and αβ frame Proportional Resonant controller. This paper compares these two current controller alternatives for VSC, based on their passivity property. The small signal model of LCL filter equipped VSC with the two types of current controller is also derived. Some design recommendations using the considered current controllers, for reducing non-passive frequency range is also presented.
Operation Analysis and Comparison of T-type NPC Si IGBT and SiC MOSFET Inverter-Based Highspeed Drives

Wideband-gap (WBG) power devices such as silicon carbide (SiC) switches have become increasingly popular, due to their ability to increase efficiency and reduce size of power electronic converters. They can viably supply high-speed electrical drives, with profitable application in aeronautical or electric vehicles. High frequency operation of the SiC devices, emphasizes the effect of parasitics, which generates reflected wave transient overvoltage on motor terminals, significant in the case of long-shielded cable which connects the inverter and the induction motor. In this paper SiC MOSFET-based inverter is systematically studied and compared to the performance of Si-based inverter for low-voltage induction motor loads, in terms of efficiency and switching performance. In particular, Si-based inverter configuration is the T-type Neutral Point Clamped (T-NPC) 3-level (3L) inverter, and SiC-based inverter is standard 2-level (2L) configuration, which can eventually replace the 3L topologies. The fair comparison of the two inverters has been introduced and switching performance, overvoltages, and power losses have been analyzed. Simulations are carried out by realistic models of power switch modules.
3D-FHNet: Three-Dimensional Fusion Hierarchical Reconstruction Method for Any Number of Views

The research field of reconstructing 3D models from 2D images is becoming more and more important. Existing methods typically perform single-view reconstruction or multi-view reconstruction utilizing the properties of recurrent neural networks. Due to the self-occlusion of the model and the special nature of the recurrent neural network, these methods have some problems. We propose a novel three-dimensional fusion hierarchical reconstruction method that utilizes a multi-view feature combination method and a hierarchical prediction strategy to unify the single view and any number of multiple views 3D reconstructions. Experiments show that our method can effectively combine features between different views and obtain better reconstruction results than the baseline, especially in the thin parts of the object. Our source code is available at https://github.com/VIM-Lab/3D-FHNet.
Ultrasonic Surface Acoustic Wave platform for targeted pulmonary delivery of nano drug vehicles

This work shows a new method that employs surface acoustic waves (SAW) to form liposomes and simultaneously create a narrow distribution of inhalable aerosols that falls within the ideal respirable range size. The main advantage of using SAW is that, in one step, we can control the aerosols droplet size distribution and simultaneously create drug carriers of biological and active compounds, which are often degraded in alternative nebulisation methods. To corroborate the effectiveness of the proposed SAW nebulisation platform, nucleic acids were nebulised and deliver to lung cancer cells.
Joint Caching and Trajectory Design for Cache-Enabled UAV in Vehicular Networks

Cache-enabled unmanned aerial vehicles (UAVs) are envisioned as a key enabler to flexibly serve the ground traffic demand while eliminating the limited wireless backhaul links. However, how to utilize UAVs in highly dynamic vehicular networks is not well studied yet challenging with limited UAV energy and storage capacity. In this paper, considering the vehicle mobility and content requests, we study the problem of proactive content placement, trajectory design, and content delivery for cache-enabled UAV. This problem is formulated as an optimization problem aiming at maximizing the overall network throughput improvement under the UAV energy constraint, which is non-convex and difficult to solve. To tackle this problem, we propose an efficient algorithm with a two-layered structure. First, given a content placement strategy, we devise a time-based graph decomposition method to jointly optimize the content delivery and trajectory design. Next, with the optimized content delivery and trajectory, we then leverage the particle swarm optimization (PSO) algorithm to further optimize the content placement. Numerical results show that the proposed scheme can efficiently solve the joint optimization problem and adapt to the dynamic network conditions.
Facial Expression Recognition with Identity and Spatial-temporal Integrated Learning

Spatial-temporal structure of expression frames plays a critical role in the task of video based facial expression recognition (FER). In this paper, we propose a 3D CNN based framework to learn the spatial-temporal structure from expression frames for video-based FER. First, we use the data labeled with identities to train an identity network to capture the facial biometric features from expression frames. Second, we remove the impact of facial biometric features from the expression features and construct typical facial expression (TFE) features. Then, we feed the TFE features to a 3D network to discover spatial-temporal structure of expression frames. In the end, we feed the spatial-temporal vector to a fully-connected layer to get a vector for classification. The proposed method achieves comparable accuracy with the state-of-art of 88.54% on Oulu-CASIA, and is efficient to be used for the task of video-based FER.
DOTFloor–A Diffusion Oriented Time-Improved Floorplanner for Macrocells

This work presents a unique time-efficient and reliable floorplan algorithm DOTFloor (Diffusion Oriented Time-improved Floorplanner), built around a SA (Simulated Annealing) engine and targeted to optimize the peak on-chip temperature along with the traditional design metrics like chip area and wire length. This paper also proposes a novel heat-diffusion based stochastic thermal model called the FATT (Fast Assumption Technique for Temperature) which provides a fast assumption of the degree of hotness during the optimization process. The incorporation of FATT in DOTFloor results in a significant improvement in the run time of the optimization process. Upon experimentation on MCNC (Microelectronics Center of North Carolina) benchmark circuits with the proposed floorplanner, a good optimization in area, wire length metric and peak on-chip temperature with a significant reduction in execution time have been achieved over the existing floorplanning tool, the HotFloorplan.
Protocol for Eliciting Driver Frustration in an In-vehicle Environment

A state of frustration can impair a driver's ability to make decisions that optimize the safety of the driver as well as that of those around him or her. Equipping a car with the capability of detecting signs of driver frustration and responding with appropriate interventions can be an effective method to improve driver safety. In this paper, we first describe the design and implementation of a novel protocol used to elicit true frustration of varying intensities in participants interacting with an in-car Human Machine Interface (HMI) while driving in a simulator. We detail the instrumentation that was used to capture the participants' interactions with the HMI. We provide a computational analysis of signs of frustration displayed by participants in the facial and vocal modalities and discuss trends that were observed. Finally, we present baseline machine learning methods trained on features computed from facial and vocal modalities to predict the difficulty of the completed task and whether the participant is multitasking, validating the assumptions that informed our protocol design.