Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-Circuit Capability Prediction and Failure Mode of Asymmetric and Double Trench SiC MOSFETs

In this article, short-circuit capability prediction and failure mode of 1200-V-class SiC MOSFETs with a double and asymmetric trench structure are proposed under single-pulse short-circuit stress. A short-circuit prediction model is established to evaluate short-circuit withstand time and corresponding critical energy of devices under various dc bus voltages. This model can provide quick predictive guidance even if there are few test results, and the predicted values are consistent with practical values. Furthermore, two failure modes are investigated in a short-circuit test. For asymmetric trench SiC MOSFETs, failure modes are gate damage at lower dc bus voltages and thermal runaway at higher dc bus voltages; whereas failure mode for double trench SiC MOSFETs is thermal runaway at all dc bus voltages. In addition, the internal thermal-electro stress of the device is analyzed until it fails during short-circuit condition, and proves that failure mode depends on the dc bus voltage and peak short-circuit current of the device. Finally, the top view of failed devices confirms the two failure modes of trench SiC MOSFETs by the postdecapsulation.
A Home Security Camera System with Container-based Resource Allocation on Raspberry Pi

Recently, Deep Learning (DL)-based image processing on edge computing devices has been studied actively. Modern edge devices are equipped with multiple cores in order to achieve both performance and energy efficiency, and how to efficiently utilize the multiple cores is crucial in the design of DL-based image processing systems. This paper presents a DL-based home security camera system on a Raspberry Pi edge computing device. Containers are utilized for efficient resource allocation on the Raspberry Pi device. Our experimental results show the effectiveness of our developed system.
An LCC-AAC Hybrid High-voltage DC Transmission System

This article develops a hybrid HVDC transmission system based on the line-commutated converter (LCC) and the alternate arm converter (AAC). The basic operating principles and control methods of the proposed LCC-AAC hybrid HVDC system are demonstrated together with system design considerations and parameter selection. The operation and performance of both converters in such a hybrid HVDC configuration are verified through a detailed set of results based on a 2000 MVA LCC-AAC hybrid HVDC system including steady state operation, ac-grid harmonics & dc-side ripple analysis at both terminals of the HVDC system. The proposed hybrid LCC-AAC HVDC transmission system lays preliminary steps for research on complex mixed converter multiterminal dc configurations in future dc super grids.
Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs.
Understanding of BBRv2: Evaluation and Comparison With BBRv1 Congestion Control Algorithm

Google proposed a bottleneck bandwidth round-trip propagation time (BBR) for TCP to replace the loss-based congestion control algorithms, such as Reno and CUBIC. Unlike the loss-based algorithms, BBR models a network path from source to destination and dynamically controls the sending rate using control parameters, such as pacing rate, congestion window, and quantum to achieve high throughput and low latency. However, many studies have reported performance issues in BBR operation, such as excessive packet loss in shallow buffers, the unfairness among different RTT flows, the unfairness with loss-based algorithms, and so on. Google is developing a new version of BBR, BBRv2, to resolve these performance issues. In this study, we evaluate and compare two versions of BBR on a Mininet emulator and a physical testbed, focusing on whether the BBRv2 alpha can alleviate the performance issues of BBRv1 and whether other novel issues will arise in BBRv2. The experiment results show that BBRv2 improves the unfairness and aggressiveness in small buffer less than 1 BDP. Moreover, multiple BBRv2 flows not only show better fairness in bandwidth sharing, but also reduce the amount of packet retransmissions. However, we observed that the challenging issues such as RTT unfairness, coexistence with loss-based algorithms, and synchronization between BBRv2 flows still exist. This study explores BBRv2’s current behavior in various network scenarios and compares the performance of BBRv2 with the BBRv1 congestion control algorithm.
Use of Image Processing Techniques to Investigate the Behaviour of Driven Piles

Steel driven piles having either open-ended and closed ends have been used widely in onshore and offshore pile foundations. But the behaviour of open-ended piles is complicated than closed-end piles due to the formation of soil clogging phenomenon. The current work examines the effect of pile dimensions and its related clogging behaviour through image analysis. Solid and hollow half-section aluminium piles of different elastic modulus and dissimilar cross-sectional areas are used for the study. A scaling factor of 10 has been used for modelling the pile. The modelled piles are subjected to Standard Penetration Test (SPT) which simulates the application of impact loads in crushed stones (4.75-2.36 mm) of various soil densities. The experimental progression is grabbed through the digital single-lens reflex camera and sequential pictures captured during the test are analyzed through open-source software GeoPIV which is based on Digital Image Correlation technique (DIC). The GeoPIV software helps in measuring deformation behaviour and strain path over a Region of Interest (ROI). The examination of DIC test results revealed that for hollow piles there is a surge in volumetric shear strain contours about pile shaft region. This could be due to the soil plug formation at the tip of hollow pile irrespective of infill density. For solid piles, strain concentrations are observed closer to pile head due to its greater flexural rigidity than hollow piles.
Fast silicon etching using an expanding cascade arc plasma in a SF6/argon mixture

An expanding cascaded arc is used as a fluorine atom source for fast etching of silicon. Extremely high etch rates up to 1.3 μm/s have been obtained. A reactor parameter study has been performed. The obtained selectivity Si/SiO2 is ∼11 for substrate temperatures of 600 °C, increasing to ∼20 at 100 °C. The etching proces is fully isotropic.
Integration of D2D, Network Slicing, and MEC in 5G Cellular Networks: Survey and Challenges

With the tremendous demand for connectivity anywhere and anytime, existing network architectures should be modified. To cope with the challenges that arise due to the increasing flood of devices/users and a diverse range of application requirements, new technologies and concepts must be integrated to enable their benefits. Service providers and business companies are looking for new areas of research to enhance overall system performance. This article gives a detailed survey about the recent 5G technologies, the solutions they provide, and the effect caused by their addition to current cellular networks. It is based on the three most important 5G concepts: Device to Device (D2D), Network Slicing (NS), and Mobile Edge Computing (MEC). This study proposes to design the future 5G networks by the integration of all three technologies. It is believed that spectrum efficiency, energy efficiency, and overall throughput will be greatly improved by using D2D. The system delay and computational load will be reduced as tasks will be handled by edge routers located at the base stations. Thus offloading the core network and the system capital expenses and operational expenses will be reduced significantly by slicing the network.
Antenna Switch Embedded in Transmission Line Transformers of Differential PA and LNA

An antenna switch embedded in the matching transmission line transformers (TLTs) of a differential power amplifier (PA) and LNA is presented, which selects the transmitter and receiver (Tx and Rx) in 5G communication systems. Because the switching function is implemented in the matching networks of a PA output and an LNA input, the chip size and insertion loss are reduced. A balun, an antenna switch, and matching networks of the PA and LNA are implemented simultaneously by carefully designing a three-port series-combining TLT with Tx and Rx switches. The measured insertion losses of Tx and Rx are 0.42 and 1.01 dB, respectively, at 28 GHz, and the isolation values of the Tx and Rx paths are 24.1 and 31.7 dB, respectively.
Architectures Synthesizing Method for Medium-Voltage Photovoltaic Power Electronic Systems

Numerous architectures for medium-voltage power electronic systems are investigated. To find out the architectures suitable for the medium-voltage photovoltaic power electronic systems, this paper gives a systematic study on medium-voltage power electronic systems (MVPESs) architectures for large-scale PV plants. A synthesis method of MVPESs is firstly introduced. It is composed of two steps. First, the power conversion chains are synthesized by traversing all possible designs of the multi-stage converters. Based on the power conversion chains, topologies are obtained by cascade connection or parallel connection. A data structure representing the MVPESs is also introduced that can help to synthesize the MVPESs using computer. The advantages and disadvantages of these MVPESs are also discussed. Two typical MVPES architectures are compared with efficiency and cost.
Improved Model Predictive Control Based on ADALINE algorithm

This paper proposes an improved adaptive model predictive control (MPC) based on ADALINE algorithm, which adopts well-designed convergence domain to minimize estimation error. The Finite Control Set Model Predictive Control (FCSMPC) is used in a three-phase three-level voltage source inverter (3L-VSI). The ADALINE is used to online update the inductance and resistance parameters of the predictive model. If the convergence domain is small, the traditional ADALINE -MPC will run incorrectly because the algorithm does not converge; if the convergence domain is large, it will cause large errors in the parameters estimated by the ADALINE. This paper aims to overcome this problem so that the ADALINE can choose a suitable convergence region, which provides better robustness and control accuracy for predictive control. Experiments have been applied to the grid-connected 3L-VSI and demonstrate the effectiveness of the proposed method.
Impacts of Coupling Effects on Stability Analysis of PMSG-based Wind Farm Integration through MMC-HVDC

Asymmetric control and dynamic characteristic of DC bus will cause frequency coupling effects which turn converter into a single input double output (SIDO) system. The interaction between two SIDO system is more complicated than the interaction between converter and passive grid impedance. This work focus on impacts of coupling effects on the wind farm integration through MMC-HVDC system. The paper firstly presents impedance modeling wind farm and MMC-HVDC considering the coupling effects separately, which are used to explain the coupling effects on the frequency characteristics and system stability analysis results. Then the developed model is used to illustrate the effect of the bandwidth of PMSG PLL controller, MMC-HVDC voltage controller and the degree of unbalance on impedance characteristic and system stability. The system stability analysis results are validated by numerical simulation of a PMSG-based wind farm integration through MMC-HVDC to prove the correctness of the theoretical analysis.
Partial Tiering: A Hybrid Merge Policy for Log Structured Key-Value Stores

Persistent key-value stores have been widely adopted as a storage engine for modern IT infrastructures because they provide high performance with simple design principles. Moreover, many key-value stores commonly employ LSM-tree as their index structure due to its attractive features such as high write throughput and storage space efficiency. Unfortunately, LSM-tree has critical drawbacks in that it leads to write/read amplification problem. One of the prevalent solutions for remedying the write amplification problem is the tiering merge policy that reduces the number of rewrites by delaying merge operations. However, in spite of this advantage, the tiering merge policy may lead to a side-effect that induces the read amplification that increases search/scan cost for upcoming read operations. In this paper, we concentrate on mitigating the high read amplification problem of the tiering merge policy, while maintaining its low write amplification. To achieve this, we propose Partial Tiering, a novel merge policy which delays merge operations only for the non-read-intensive key-spaces. We have implemented a prototype based on PebblesDB and evaluated the performance benefits of our policy. Experimental results clearly show that our policy improves throughput by up to 1. 50x compared with the conventional policy while maintaining low write amplification.
Investigation of Channel Formation Due to Random Packing in a Burning Waste Bed

Obtaining energy from sustainable sources such as waste and biomass has required a significant extension of combustion technology. Many of the advanced technologies are based on thermal treatment in gas-solid packed-bed systems such as gasifiers, incinerators and biomass furnaces. In this paper channel formation in a packed bed of fuel solids as a result of the random packing process has been investigated. Channelling causes a severely uneven distribution of the primary airflow through a packed fuel bed and results in poor combustion performance of the furnace. By assuming Furnas packing, a general relationship is derived between the bed porosity and the particle size distribution and the proposed methodology is tested against limited experimental data. A probability density function (PDF) of truncated Gaussian type is assumed for the random size distribution at local areas within the bed and the local bed porosity is calculated accordingly. Then by solving the fluid flow equations through the porous bed, flow rate profiles are obtained at the top surface of the bed. Two particulate systems were investigated as a function of change in bed height and pressure drop through the grate. Depending on bed height and pressure drop through the grate, maximum local flow rate at the top surface of the bed can be 1.5 ∼ 2 times higher than the minimum flow rate for the particulate system with a narrower size range (2.5 mm–18 mm) while the ratio of the maximum to minimum flow rate can reach as high as 8 ∼ 32 for the particulate system with a wider size range (0.677 mm–20 mm). Visualization of the velocity profile inside the bed reveals that flow passages are slightly curved in some areas but straight in others. The largest channel observed presents a ‘perfect’ straight passage of airflow running from the very bottom of the bed to the very top of the bed. Channelling inside a burning bed of solid waste in a large-scale travelling grate incinerator plant was also investigated using a unique in-house prototype instrument. The result shows that the combustion processes within the bed were dominated largely by the circles of formation and subsequent collapse of channels.
Improved Power Quality Transformerless Single-Stage Bridgeless Converter Based Charger for Light Electric Vehicles

In this article, a bridgeless switched inductor Cuk (BSIC) converter based charger is presented to provide the low-cost and reduced-size charging solution for the light electric vehicles, i.e., LEVs, with enhanced performances at the supply side. Generally, the chargers of LEVs such as E-Rickshaws, E-Bike, and E-Cycle, are equipped with an additional converter to charge the batteries at low voltages (24–72 V). The switched inductor configuration improves the step-down dc voltage gain of the charger with only one stage and also improves the reliability at such low voltages. It is noteworthy that the cost associated with the sensors along with the size of the magnetic components is considerably reduced by operating the charger in discontinuous current mode condition. Moreover, the high-gain transformerless configuration further improves the cost, size, and efficiency of the charger. The effectiveness of the charger is tested on a laboratory prototype, for an 850 W rating with 220 V, 50 Hz nominal supply voltage conditions. The steady state and dynamic behaviors of the charger are analyzed under different operating conditions. Moreover, the behaviors of the charger during the initialization of charging process are analyzed for ensuring the soft starting of the charger. A basic comparison of the presented charger configuration with existing LEVs chargers is presented to highlight its advantages over the existing one.
An Adaptive Asynchronous Wake-Up Scheme for Underwater Acoustic Sensor Networks Using Deep Reinforcement Learning

Underwater acoustic sensor networks (UWSNs), acting as a reliable and efficient infrastructure of the Internet of underwater things (IoUT), have attracted much research interest in recent years due to the wide range of their potential marine applications. The limited energy supply of underwater sensor nodes is a significant challenge that can be mitigated by the cyclic difference set (CDS)-based coordination asynchronous wake-up scheme. However, the CDS-based asynchronous wake-up scheme also introduces long delays in the neighbor discovery that deteriorates packet delay as well as the network lifetime. In this paper, we formulate the problem of policy selection for idle listening as a Markov decision process and exploit the framework of deep reinforcement learning to obtain the optimal policies of underwater sensor nodes. Furthermore, the long short-term memory (LSTM) networks are utilized to estimate the network traffic feature, which can improve the performance of the proposed adaptive asynchronous wake-up scheme. To verify the performance of the proposed scheme, simulations in different network scenarios are conducted with the comparison of random, fixed metric policies, and original CDS-based asynchronous wake-up schemes.
Analyzing Engineers Writing for Non-engineers

Engineers spend a considerable amount of time in communicating with technical and non-technical audiences when on work. Due to the high demands of good technical writing skills, most engineering faculties and educationists take special initiatives for fostering such attributes but writing skills for non-technical people is often overlooked. A large number of students stumble into writing with an inadequate sense of the significance of their audience — a problem that needs attention. This introductory study analyzes the engineering students’ writing when addressing non-technical people. We conducted short writing exercises in a third-year engineering course aiming at pitching an idea to non-technical audiences with a view to assessing their ability to adapt their writing according to the audiences. These writings are analyzed using the freely available text analyzing tools. The analysis revealed that students’ writings are complex and tend to address the more qualified people than general audiences. Furthermore, their writings are usually dominated by an analytical tone. The preliminary findings provide ample encouragement to further explore this topic and provide a basis for related practitioners to address this issue and develop strategies to overcome this issue.
Airport Taxiway Conflict Detection Method Based on Network Topology

Because of the movements of aircraft on the ground were difficult to predict, conflicts on the taxiway could not be detected by the methods of conflict detection in the air. According to the characteristics that aircraft on the ground are limited in their movements by the taxiway structure, an airport taxiway conflict detection method based on network topology was proposed. First, we built the network model based on airport taxiway structure, then we used map matching algorithm to locate the target in the network, at last the taxiway conflict could be detected by the topological relations of the targets. Results show that the method is provided with high performance and efficiency to detect the typical taxiway conflicts, and can be easily used in practical system.
Biometric Recognition of Infants using Fingerprint, Iris, and Ear Biometrics

Biometric recognition is often used for adults for a variety of purposes where an individual’s identity must be ascertained. However, the biometric recognition of children is an unsolved challenge. Solving this challenge could protect children from identity theft and identity fraud, help in reuniting lost children with their parents, improve border control systems in combatting child trafficking, and assist in electronic record-keeping systems. In order to begin the development of biometric recognition systems for children, researchers collected fingerprint, iris, and outer ear shape biometric information from infants. Each modality provides different challenges. Where possible, the performance of existing hardware and software that was developed for adults was assessed with infants. Where necessary, novel hardware or software was developed. For the ear modality, existing hardware and software which have previously been applied to adults were applied to children. For the iris modality, existing hardware was used to acquire the images, while adjustments to the existing preprocessing algorithms were applied to cater for the localisation and segmentation of infant irises. For the fingerprint modality, novel hardware and image processing software were developed to acquire fingerprints from infants, and convert the images into a format which is backward compatible with existing international standards for minutiae extraction and comparison. The advantages and disadvantages of using each of these modalities during the first year of life were compared, based on both qualitative assessments of usage, and quantitative assessments of performance. While there is no conclusively best modality, recommendations of usage for each modality were provided.
Monopole Operation of On-Load Faulty Valves Replacement of Modular Multilevel Converters (MMCs) in Bipolar MVDC Grids

This paper demonstrates monopole operation capability of MMCs used in bipolar MVDC grids, which can enable on-load faulty valves isolation and replacement. With the dedicated control scheme and the operation procedure, the mode transitions between bipolar operation mode, monopole operation mode and hot-swap of faulty valves can be implemented in a seamless manner without shutting down the MMC. Consequently, the MMC can virtually operate without interruption and deliver at least 50% of the rated power capacity even during the maintenance phase. Hence, the availability of the connected MVDC grids can be significantly enhanced. Validity of the proposed work has been verified by time-domain simulations.