Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Effects of Electron Beam Irradiation on Nanoscale Adhesion

Electron microscopy allows for resolving of structure sizes far below the resolution limit of optical microscopes and is therefore increasingly applied as an in-situ imaging method during manipulation and characterization of nanomaterials. However, little is known about the influence of the electron beam used on the respective experiment, which can lead to considerable uncertainty about the repeatability of the relevant manipulation sequence or the accuracy of the characterization results obtained. Here we investigate the influence of electron beam irradiation on nanoscale adhesive interactions using piezoresistive force sensors decorated with individual colloidal particles. We can demonstrate that both electron beam-induced deposits as well as electrostatic forces can dominate the relevant adhesion mechanisms. The results thus clearly reveal the importance of considering effects originating from electron beam irradiation in the conduct and interpretation of in-situ experiments, which in turn is of significant relevance for the growing community of researchers involved in this methodology.
Transformerless Minimum Phase Interleaved Hybrid Converter with Low Leakage Current

Hybrid converters are predominantly used in modern residential distribution systems, as they are capable of supplying DC and AC loads simultaneously. But, the main concern in conventional transformerless hybrid converter is the common mode leakage current for photovoltaic applications, when they are connected to grid or their neutral point is grounded. Because of the flow of leakage current, the system losses increase, power quality decreases, and the nearby systems get affected from electromagnetic interferences. The other issues are non-minimum phase behavior due to presence of right hand plane zero in the transfer function of control to dc output voltage and narrow ranges of modulation index (Mi) and duty ratio (D) (i.e. D+Mi ≤ 1). Due to narrow range of modulation index (Mi) and duty ratio (D), there is a compromise between DC voltage gain and quality of AC output. A transformerless minimum phase interleaved hybrid converter is proposed in this paper to eliminate the above difficulties. A hybrid PWM technique is proposed for the proposed converter which helps not only to minimize the leakage current but also to obtain both AC and DC outputs simultaneously. Moreover, the proposed hybrid converter is operated both in D + Mi ≥ 1 and D+Mi ≤ 1 as well as it maintains the minimum phase behavior. A 210 W scaled down laboratory prototype of proposed converter is developed and verified in this work.
Vision based vehicle relocalization in 3D line-feature map using Perspective-n-Line with a known vertical direction

Common approaches for vehicle localization pro-pose to match LiDAR data or 2D features from cameras to a prior 3D LiDAR map. Yet, these methods require both heavy computational power often provided by GPU, and a first rough localization estimate via GNSS to be performed online. Moreover, storing and accessing 3D dense LiDAR maps can be challenging in case of city-wide coverage.In this paper, we address the problem of camera global relocalization in a prior 3D line-feature map from a single image, in a GNSS denied context and with no prior pose estimation. We propose a dual contribution. (1) We introduce a novel pose estimation method from lines, (i.e. Perspective-n-Line or PnL), with a known vertical direction. Our method benefits a Gauss-Newton optimization scheme to compensate the sensor-induced vertical direction errors, and refine the overall pose. Our algorithm requires at least 3 lines to output a pose (P3L) and requires no reformulation to operate with a higher number of lines. (2) We propose a RANSAC (RANdom SAmple Consensus) 2D-3D line matching and outliers removal algorithm requiring solely one 2D-3D line pair to operate, i.e. RANSAC1. Our method reduces the number of iteration required to match features and can be easily modified to exhaustively test all feature combinations.We evaluate the robustness of our algorithms with a synthetic data, and on a challenging sub-sequence of the KITTI dataset.
Analysis of Capacitor Current Stress in Five-Level Active Neutral Point Clamped Converter

This paper derives analytical expression for current stress on capacitors of Five-Level Active Neutral Point clamped Converter (5L-ANPC) connected on load side. In hybrid multilevel structure, semiconductor devices operate at different switching frequencies and may not conduct even when they are gated on. Therefore, the duty ratio expressions used to evaluate current stress in DC-link capacitors may not result a correct expression. Also there is a flying capacitor in the circuit. Expressions are obtained using conduction functions $(G)$. Conduction function is obtained by combination of switching functions $(S)$ of appropriate switches. Results of derived expressions are compared with MATLAB Simulink results to validate the expressions. Difference in current stress on flying capacitor and DC-link capacitor in the same converter leg over sizing, lifetime expectancy and voltage ripple is discussed.
TriP: Misbehavior Detection for Dynamic Platoons using Trust

Platooning is able to improve fuel efficiency and reduce road congestion. But to maximize the concept’s impact, platoons need to be created dynamically whenever feasible. Therefore, vehicles have to cooperate with unknown and possibly malicious partners, creating new safety hazards. Hence, vehicles need to be able to determine the trustworthiness of their cooperators. This paper proposes TriP, a trust model which rates platoon members by the divergence of their reported to their actual behavior. The proposed model is evaluated against attacks from literature. The evaluation demonstrates that TriP detects all attacks and prevents harm by deploying countermeasures thus mitigating safety hazards.
The role of the gluteus maximus during prone hip extension

The purpose of this study was to compare electromyographic analysis of the gluteus maximus, bicep femoris and lumbar erector spinae muscle activation sequences in young healthy netball players. Eighteen women performed bilateral prone (PHE), quadruped (QALE) and single limb (SQT) functionally loaded hip extension exercises while surface electromyography was recorded from hip and lumbar spine extensor musculature. No consistent activation sequence was noted during the three exercises. Gluteus maximus onset was earlier than bicep femoris for dominant PHE (p 0.05). The muscle activation sequences were contradictory to that proposed by Janda (1991) during prone, quadruped and single limb functionally loaded hip extension exercises. Stellenbosch University https://scholar.sun.ac.za
Model-based Offline Vehicle Tracking in Automotive Applications Using a Precise 3D Model

Object tracking aims at estimating the state of moving objects based on remote measurements. To evaluate online algorithms in automotive systems, ground truth data must be acquired, which is a time-consuming and expensive approach. We propose a novel offline approach to generate ground truth data from existing sensor measurements using CAD models. In our approach, we provide error bounds for the localization of the objects based on the measurement noise of a single laser beam and the sensitivity of the point cloud registration. To estimate accurate kinematic states of the vehicle, we apply an extended Rauch-Tung-Striebel smoother on the stored measurements. In experiments with real sensor data, we demonstrate that the performance of the proposed approach is superior to DGPS within the near range.
A Review on Sucker Rod Pump Monitoring and Diagnostic System

Development of accurate and reliable monitoring and fault diagnosis system for sucker rod pumping system is vital in order to reduce component failure and determine optimal operating point. This paper reviews the features of different supervising techniques. The principles, advantages and limitation of various sensors used in measuring polished rod load and displacement of polished rod are discussed. The features and potential of wattmetrogram in monitoring and diagnosis of sucker rod pump are also described. Finally, a comparison on the various feature extraction and classification methods are presented. The paper outlines essential recommendations for efficient and reliable monitoring and diagnostic system for sucker rod pump systems.
Level-shift Modulation and Control of a Dual H-bridge Current Flow Controller in Meshed HVDC systems

The dual H-bridge current flow controller (CFC) has been proposed as a cost-effective solution to regulate current flows in a meshed high-voltage direct-current (HVDC) system. With an interline connection, this device may increase or decrease the magnitude and even reverse the directions of transmission line currents in a meshed dc grid. However, it needs to be modulated in a different manner when its operating region changes, which makes its control more complex. This paper investigates a modulation method for the dual H-bridge CFC. The buck and boost regions of operation for the device are analyzed first. A level-shift modulation method based on pulse width modulation is proposed. This method ensures that only one bridge of the CFC is switching for each operating region, which simplifies the control of the device. In addition, the method ensures a smooth transition between the operating regions, which can enhance the reliability of the CFC. For completeness, the presented modulation and control methods are verified through time-domain simulations conducted in PSACD/EMTDC.
Right-Angle Black Phosphorus Tunneling Field Effect Transistor

We report experimental demonstration of a right-angle black phosphorus (BP) tunneling field effect transistor (TFET). This device utilizes the effective mass anisotropy between the armchair (AC) and zigzag (ZZ) crystal orientations in BP as a means of inducing asymmetry between source and drain tunneling. As a result of this asymmetry, the BP TFET displays a higher <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}} / {I}_{ \mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula> ratio by 2 orders of magnitude and steeper <italic>SS</italic> than BP TFETs oriented along either the AC or ZZ direction only.
Ladder Transformerless Stacked Active Bridge Converters

This paper presents transformerless stacked active bridge (TSAB) converters derived from N-to-1 ladder switched capacitor (SC) converters by addition of small ac inductors. The ladder-TSAB (L-TSAB) converters feature soft charging of all flying capacitors and zero-voltage switching of all switches. The use of small ac inductors and low voltage devices is enabled by low volt-seconds applied to inductors and low device voltage stresses equal to 1/N of the supply voltage. Output regulation and flying capacitor voltage balancing can be achieved through phase-shift control. Experimental results are presented for a 3-to-1 L-TSAB prototype in two application scenarios: 12-to-4 V, 10 A, and 36-to-12 V, 15 A. In the 12-to-4 V prototype, the peak measured efficiency is 98.7%, while the full load efficiency is 92.4%. In the 36-to-12 V case, the peak efficiency is 98.7% and the full-load efficiency is 96.3%.
High-Frequency Noise Suppression in a Buck-Converter System Based on SiC Devices

High switching speed in next-generation power devices such as silicon carbide allows increased switching frequencies in power converters. Higher switching frequencies increase power densities, but also increase frequencies of electromagnetic noise accompanying switching operations, resulting in more serious electromagnetic interference (EMI). Radiated EMI will thus soon become a major concern when developing power converters. Most previous works have focused on conducted EMI, resulting in a dearth of research on radiated EMI from power converters. We thus investigated the generation mechanism of radiated noise from power converters to identify effective reduction methods. We identify two propagation paths of high-frequency (HF) common-mode (CM) noise currents, primary CM (PCM) and secondary CM (SCM). SCM constructs a large propagation loop, thus becoming a major source of radiated noise. To suppress HF CM current flow through each mode, we fabricate two types of CM inductors (CMI). HF CM currents are measured in a simple buck converter system. CM current measurements verify the effectiveness of CMI for reduction of HF CM currents and clarify how SCM voltage source is generated. The described generation mechanism of SCM voltage source and radiated noise is verified by measurements of radiated noise in a fully anechoic chamber.
Simultaneous Differential Interrogation for Multiple FBGs Based on Crossed Sagnac Loops and Microwave Network

Conventional intensity-based fiber Bragg grating (FBG) demodulation systems are usually vulnerable to the power fluctuations and not convenient to locate the positions of the gratings, which set drawbacks to their large scale sensing applications. Here, we present and demonstrate a simultaneous differential interrogation method for multiple FBGs based on crossed Sagnac loops and microwave networks for the first time. With the help of the unique characteristics of the Sagnac filters, Gaussian-shape nature and numbers of passband channels, a linear behavior can be achieved. What's more, the utilization of the microwave network can not only contribute to the positioning of the gratings, but also increase the response speed and cut down the cost for the mature microwave technology. The experimental results exhibit high linearity and good immunity to the interference between adjacent gratings and the variations of power. A strain sensitivity of ∼0.0034 dB/μϵ in the range from 0 to 2000 μϵ and a spatial resolution for FBG locating of 0.1 m have been obtained. The changes of the impulse peak ratios are less than 0.02 dB when 2 dB power reduction is introduced. Furthermore, numerical studies about the influences of several important parameters to the capacity and performance of the sensing system have also been carried out, indicating that it has the ability of multiplexing thousands of FBGs covering at least several kilometers.
Selecting Components for Bidirectional DC-DC Converter of Photovoltaic Power Supply System

The article presents a selection procedure for the components selection of a bidirectional DC-DC. The converter is used to implement energy storage system as part of a photovoltaic power supply system. The storage system provides energy balance and smooth voltage oscillations in the power supply system's DC link via controlling energy flows. The considered approach can be used in photovoltaic and electric vehicles and electric drives applications. The paper includes a description of power components selection based on physical properties and power supply system requirements. Besides, an economic analysis of components as a part of power supply system is considered.
Impacts of Ta Buffer Layer and Cu–Ge–Te Composition on the Reliability of GeSe-Based CBRAM

We analyze the switching and retention properties of 65-nm integrated Cu(-Ge-Te)/(Ta)/GeSe conductive bridge random access memory devices operated at <inline-formula> <tex-math notation="LaTeX">$50~\mu \text{A}$ </tex-math></inline-formula>. We evidence the crucial role played by a Ta buffer layer inserted between the Cu alloy and GeSe layers in decreasing the preforming current and in significantly improving the low-resistance state retention. Cu alloys of different compositions are tested to reveal lower device variability and longer retention with Cu<sub>2</sub>GeTe<sub>3</sub> active electrode.
A Generalized Voltage Balancing Algorithm for Modular Multilevel Cascaded Converters

The use of an inter-cell voltage balancing scheme to evenly distribute the total dc-link voltage among the multiple floating capacitors is crucial in modular multilevel cascaded converters (MMCs). This paper presents an intuitively simple and computationally efficient sorting-based modulation algorithm for capacitor voltage balancing applicable to any MMC. The proposed modulation stage is inherently decoupled from the upper-level control scheme and it is able to both generate the required converter output voltage and balance the capacitor voltages suitably. Furthermore, it maintains a constant harmonic performance even as the number of switching transitions is varied to achieve voltage balance under different loading conditions with minimum incurred switching losses. The effectiveness of the proposed algorithm is validated on an experimental seven-level 350-VA single-phase cascaded H-bridge working as a static compensator. In addition, a simulated 350-VA system is used to obtain complimentary results.
Circulating Currents Suppression and Neutral-Point Potential Balancing Strategy for Parallel Three-Level T-type DC-AC Converters

Parallel operation of three-level T-type converters is a promising way to provide higher power capacity, higher reliability and lower output waveform harmonics. However, zero-sequence circulating currents (ZSCCs) are generated which distort output currents and reduce the converter efficiency. In addition, the three-level converters have an inherited problem of the neutral-point (NP) voltage unbalancing because of the spilt dc-link capacitors, which degrades the output waveform quality. Compared with the space vector modulation (SVM) schemes which are widely used to address these two issues, the carrier-based discontinuous pulse-width modulation (CB-DPWM) can improve the efficiency and can be easily realized in practical applications. In this paper, a CB-DPWM method, which injects the calculated zero-sequence voltages to original modulation signals, is proposed to achieve NP voltage balancing and low-frequency ZSCCs suppression for parallel three-level T-type converters. Validity and utility of the proposed modulation method are also demonstrated.
Tumor Detection Method with Traceable Decision Process

Over the last few years, tumor detection with deep learning has attracted ample attention, and various models have been proposed. Some models obtain output images directly from end-to-end models. Other models consist of a complicated network structure. However, it is difficult for doctors to understand the detection procedures of these models. This difficulty hinders their practical implementation. In this paper, therefore, we propose a model that detects tumors in a way that is easy for doctors to understand. The proposed deep neural network model was inspired by a way that doctors interpret images. It consists of two processes: tumor position estimation, and tumor/non-tumor classification. To evaluate the proposed method, we used magnetic resonance images actually collected by a hospital. The output images reveal that the proposed method’s procedure of tumor detection is consistent with the way that doctors detect tumors. Likely tumor positions are first estimated. Then, these likely positions are narrowed down to the correct tumor positions. Our proposed method detected tumors with 94.14% accuracy and 93.44% recall.
An Approach of Code Pointer Hiding Based on a Resilient Area

Code reuse attacks can bypass the DEP mechanism effectively. Meanwhile, because of the stealthy of the operation, it becomes one of the most intractable threats while securing the information system. Although the security solutions of code randomization and diversity can mitigate the threat at a certain extent, attackers can bypass these solutions due to the high cost and coarsely granularity, and the memory disclosure vulnerability is another magic weapon which can be used by attackers to bypass these solutions. After analyzing the principle of memory disclosure vulnerability, we propose a novel code pointer hiding method based on a resilient area. We expatiate how to create the resilient area and achieve code pointer hiding from four aspects, namely hiding return addresses in data pages, hiding function pointers in data pages, hiding target pointers of instruction JUMP in code pages, and hiding target pointers of instruction CALL in code pages. This method can stop attackers from reading and analyzing pages in memory, which is a critical stage in finding and creating ROP chains while executing a code reuse attack. Lastly, we test the method contrastively, and the results show that the method is feasible and effective while defending against ROP attacks.
Group Decision Making with Collaborative-Filtering ‘in the loop’: interaction-based preference and trust elicitation

Recommender systems have been one of the main methods to overcome the information overload problem in many domains including tourism. A solo traveller may easily create an itinerary according to his or her taste. However, when it comes to a group of people, it is often difficult to find the most suitable places to please everyone’s preferences, not only because of lack of prior information about a place but also owing to the difficulty to take influence among group members into account. In our work, we introduce a model for Group Decision Making that uses YouTube API to gather rich video contents associated with a finite set of alternatives, e.g. travel destinations. Instead of eliciting subjective opinions on alternatives directly, preferences are built upon a Collaborative Filtering approach, based on each participant’s watch history and interaction with items. Randomly chosen videos from different group members are also recommended to each target user in order to infer trust information within the group. We then use trust information to obtain an aggregated group preference for determining places to visit. An application example based on YouTube API shows that a higher degree of interaction consolidates a trust network, resulting in informed decision results.
Designing LABORe: a Platform for the Collaborative Assessment of Technological Change in the 4th Industrial Revolution

In the long run, technologies positively impacted work and, in general, brought benefits to society as a whole. However, history also shows that the first generations coexisting with new technologies had their jobs profoundly impacted both in terms of quantity and quality. As we enter the 4th Industrial Revolution, computing has been one of the key technologies that impact work and its advancements must be accompanied with special care. Computation not only impacts work but is also a powerful tool to support the construction of knowledge and proposition of actions on the technologies that disrupt work. This paper proposes the development of a computer system that allows workers themselves to evaluate the technologies that will impact work in the future. We present each stage of the application of the Design Science Research methodology for developing the system. The artificial evaluation of the resulting prototype shows its utility and opportunities for improvement.
Polynomial Regression method-based Remaining Useful Life Prediction and Comparative Analysis of Two Lithium Nickel Cobalt Manganese Oxide Batteries

Most of the sensor data in the battery energy storage system (BESS) is nonlinear, and polynomial regression method is an appropriate method for learning such nonlinear data. In this paper, we propose a method to predict the remaining useful life (RUL) by applying the internal resistance (IR) voltage and capacitance correlation to the polynomial regression method. In addition, the accelerated deterioration and the electrochemical impedance spectroscopy (EIS) test were carried out using lithium nickel cobalt manganese oxide (LiNixCoyMn1-x-yO2) batteries with different nickel (Ni) content. Through these experiments, life characteristics and impedance characteristics of two NCM batteries were analyzed.