Miracle-dz/UniFAR-FTUs huggingface dataset:
Supplementary Controller for Seamless Transitions Between Microgrids Operation Modes

This article proposes a supplementary controller for inverter based distributed generations (DGs) to damp out the power and frequency oscillations that may occur following the change in the operation mode of Microgrids (MG). The proposed supplementary controller is implemented in synchronous reference frame (SRF) using the port-controlled Hamiltonian modeling strategy. The proposed supplementary controller can be readily integrated into the existing controllers that are commonly used as the main controllers in inverter-based Distributed Generators (DGs). The proposed supplementary controller is designed in such a way that improves the response of DGs during the system oscillations without affecting the steady state reference tracking performance of the DGs. The proposed supplementary controller is able to inject damping to both relative-degree-one (RD1) and higher-relative-degree (HRD) states of the inverters. The effectiveness of the proposed supplementary control for enabling seamless transitions between operation modes of MGs is demonstrated using a set of time domain simulations in a multi-source MG.
Observer-Based Resilient Integrated Distributed Control Against Cyberattacks on Sensors and Actuators in Islanded AC Microgrids

Compared with centralized control, distributed control for microgrids offers higher reliability and scalability. However, distributed control faces severe problems for maintaining the microgrid cybersecurity, which is due to the absence of central controllers for monitoring participating generation unit activities. This article proposes an observer-based resilient distributed control for AC microgrids that estimates and compensates false data injection (FDI) attacks on sensors and actuators. The proposed resilient control relies on an integrated distributed control structure, which restores the rated frequency/voltage and offers the proportional active/reactive power sharing with reduced exchanges of control signals. The proposed control has no limitation on the number of disrupted DGs and does not need access to the attack information. The <inline-formula> <tex-math notation="LaTeX">${H} _{ {\mathrm {\infty }}}$ </tex-math></inline-formula> output feedback control is applied to guarantee the <inline-formula> <tex-math notation="LaTeX">${L} _{2}$ </tex-math></inline-formula>-gain boundedness of the control system. Several case studies are presented to verify the effectiveness of the proposed resilient distributed control in the PSCAD/EMTDC platform.
A Fastener Inspection Method Based on Defective Sample Generation and Deep Convolutional Neural Network

For the safety of railways, well-trained workers are required to check the fastener constantly, which shows the disadvantage of large time cost, huge labor cost and might being dangerous to workers. To address this and achieve automatic detection, an inspection model based on deep convolutional neural network (DCNN) is adopted in this paper. However, the inspection model suffering from the unbalanced training samples of defective vs normal due to defective fasteners are far less than normal fasteners in real railways. To tackle this problem, a novel sample generation method is proposed to generate defective fastener samples using the normal fasteners to realize sample augmentation. The comprehensive experiments are conducted on the collected real fastener samples and generated samples. The experimental results show that our method has good performance for fastener inspection on unbalanced samples and outperforms other state-of-the-art methods.
Identifying Hand Use and Hand Roles After Stroke Using Egocentric Video

Objective: Upper limb (UL) impairment impacts quality of life, but is common after stroke. UL function evaluated in the clinic may not reflect use in activities of daily living (ADLs) after stroke, and current approaches for assessment at home rely on self-report and lack details about hand function. Wrist-worn accelerometers have been applied to capture UL use, but also fail to reveal details of hand function. In response, a wearable system is proposed consisting of egocentric cameras combined with computer vision approaches, in order to identify hand use (hand-object interactions) and the role of the more-affected hand (as stabilizer or manipulator) in unconstrained environments. Methods: Nine stroke survivors recorded their performance of ADLs in a home simulation laboratory using an egocentric camera. Motion, hand shape, colour, and hand size change features were generated and fed into random forest classifiers to detect hand use and classify hand roles. Leave-one-subject-out cross-validation (LOSOCV) and leave-one-task-out cross-validation (LOTOCV) were used to evaluate the robustness of the algorithms. Results: LOSOCV and LOTOCV F1-scores for more-affected hand use were 0.64 ± 0.24 and 0.76 ± 0.23, respectively. For less-affected hands, LOSOCV and LOTOCV F1-scores were 0.72 ± 0.20 and 0.82 ± 0.22. F1-scores for hand role classification were 0.70 ± 0.19 and 0.68 ± 0.23 in the more-affected hand for LOSOCV and LOTOCV, respectively, and 0.59 ± 0.23 and 0.65 ± 0.28 in the less-affected hand. Conclusion: The results demonstrate the feasibility of predicting hand use and the hand roles of stroke survivors from egocentric videos.
Study of perovskite-based self-driving photodetectors with Schottky junction configuration

Self-driving photodetectors have attracted much attention due to the advantages of the small size, low power consumption, maintenance-free. Although there are many researches on asymmetric self-driving photodetectors, most of them focus on the experimental control of materials and geometry, and lack of systematic theoretical research on the modulation mechanism of the device performance. Here, by coupling the electromagnetic response and the dynamics of semiconductor carriers via finite element method, we take perovskite as an example to systematically and detailedly explore the effects of the asymmetric Schottky barrier and doping concentration of the semiconductor on the response performance of the device from internal perspectives such as the distribution of the internal potential. It is found that a high doping concentration leads to the low short-circuit current and open-circuit voltage of the self-driving photodetector. Through the optoelectronic simulation and optimization, the MAPbI3-based self-driving photodetector with Au/Ag Schottky-junction shows excellent photoelectric performance at a wide spectral range (300 – 800 nm). It shows a high responsivity of 0.35 A/W and a specific detectivity of (5$\times$10)10 Jones under the 700 nm-wavelength illumination.
Hardware Architecture for Supersingular Isogeny Diffie-Hellman and Key Encapsulation Using a Fast Montgomery Multiplier

Public key cryptography lies among the most important bases of security protocols. The classic instances of these cryptosystems are no longer secure when a large-scale quantum computer emerges. These cryptosystems must be replaced by post-quantum ones, such as isogeny-based cryptographic schemes. Supersingular isogeny Diffie-Hellman (SIDH) and key encapsulation (SIKE) are two of the most important such schemes. To improve the performance of these protocols, we have designed several modular multipliers. These multipliers have been implemented for all the prime fields used in SIKE round 3, on a Virtex-7 FPGA, showing a time and area-time product improvement of up to 60.1% and 64.5%, respectively. These multipliers are also suitable for applications such as RSA, as shown by implementations for 512-bit, 1024-bit, and 2048-bit generic moduli on a Virtex-7 FPGA. Our fastest multiplier has been used in the implementation of SIDH and SIKE round 3. Employing six instances of this multiplier, SIDH completes after 7.33, 8.93, 13.39, and 18.67 milliseconds and the encapsulation and the decapsulation of SIKE is performed in 7.13, 8.68, 13.08, and 18.16 milliseconds over <inline-formula> <tex-math notation="LaTeX">$p_{434}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$p_{503}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$p_{610}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$p_{751}$ </tex-math></inline-formula>, respectively, which yields a least improvement factor of 1.23.
High Q factor Electrically Injected Green Micro Cavity

Green micro-cavity (MC) with a quality factor (Q) exceeding 6000 was demonstrated under current injection. The MC consists of two dielectric distributed Bragg reflectors (DBRs) and InGaN/GaN quantum wells (QWs) in between. To form a lateral optical confinement (LOC) structure, a low-index thin AlN layer was used to replace part of the p-GaN. The device showed multi-longitudinal mode emission, from 460 to 540 nm, and higher-order lateral confined modes were clearly observed. By optimizing the cavity fabrication processes and lateral optical confinement, the linewidth of resonant mode is as narrow as 0.082 nm, indicating a high Q value of 6039 in green spectral region. This is the highest value in electrically injected GaN-based MC to the best of our knowledge. In addition, three-dimensional (3D) confined optical states were observed and studied via angle resolved measurement for the first time in an electrically injected GaN-based MC. The emission characteristics of devices as a function of cavity length, as well as the loss mechanism inside the cavity were also systematically analyzed.
Turn-to-Turn Contact Resistance Measurement of No-Insulation REBCO Pancake Coil: External Field Dependence

The characteristics of no-insulation high-temperature superconducting (HTS) manet is dominated by the magnitude of the turn-to-turn contact resistance. A few techniques have been proposed to increase the turn-to-turn contact resistance. The relation between the turn-to-turn contact resistance and the magnet stability has also been investigated in simulations. Although the turn-to-turn contact resistance measurement was only the sudden-discharging method before, we proposed a low-frequency-AC current (LFAC) method. Using our proposed method, it is possible to measure the turn-to-turn contact resistance under various conditions. In a previous paper, we measured it when charging DC current to a single pancake coil. In this paper, the turn-to-turn contact resistance was measured by the LFAC method when an external field of 1–3 T was applied to a single pancake coil. The coil strain was also measured, and the relation of the turn-to-turn contact resistance and the coil strain was also discussed.
Optimization Method of Dynamic Beam Position for LEO Beam-Hopping Satellite Communication Systems

The beam-hopping (BH) technology applied to low earth orbit (LEO) satellite communication networks is a superior choice, but the long transmission delay partly caused by data packets waiting in the queue of satellite transponders will seriously affect the user experience. To shorten the packet queueing delay, in this paper, we propose an optimization method of dynamic beam position division for LEO BH satellite communication systems. Firstly, we analyze the packet queueing delay problem in BH satellites to find out the factors related to the queueing delay, and we find that the number of beam positions is negatively correlated with the queueing delay. Then, we turn the beam position division problem into a $p$ -center problem to try to cover all users with the least number of beam positions. The beam positions among the footprint of LEO satellites are determined dynamically by the user distribution and the traffic distribution. Finally, the performance evaluation of the proposed optimization method is carried out in real-time and the simulation shows that the beam position division optimized system we proposed can shorten the queueing delay up to 40% compare to the benchmark system without sacrificing throughput.
Access the diagnostic reliability and imaging evaluation of adnexal masses diagnosis ultrasonography, magnetic resonance imaging and computed tomography

Background: Objective of the study was to evaluate role of diagnostic reliability of morphological characteristic of ovarian and adnexal masses to compare and correlated in sensitivity of ultrasonography, computed tomography, magnetic resonance imaging (USG with CT and MRI). Methods: This study was conducted in department of radiodiagnosis, Sri Aurobindo medical college and PG institute, Indore from August 2019 to September 2020. A total of 100 OPD patients of adnexal masses including both premenopausal and postmenopausal women. All 100 patients had undergone sonographic assessment and CA-125 levels were assessed; where 70 patients were correlated with CT and 30 patients were correlated with MRI with a standardized research protocol Results: A total of 100 patients included in the study. The mean age was 42.05±2.3. 68 (68%) patients were Premenopausal and 32 (32%) patients post-menopausal. 19 (19%) of patients had family history of ovarian carcinoma, whereas 81 (81%) of patients had negative family history of ovarian carcinoma. 32 (47%) patients in premenopausal group had increased Ca-125 levels, whereas 18 (56.2%) patients in postmenopausal had increased Ca125 levels. Conclusions: MRI proved to be highly sensitive and accurate in differentiating benign and malignant lesions of adnexal masses which were indeterminate on ultrasonography examination. Thus, MRI can be considered as second most confirmatory tool followed by tissue diagnosis in women with indeterminate masses.
Study of Oil/Pressboard Creeping Discharges under Divergent AC Voltage—Part 1: Fundamental Phenomena and Influencing Factors

This paper presents an experimental study of the fundamental phenomena of progressive creeping discharge as well as the influences of pressboard ageing and voltage amplitude under divergent AC voltages. A ramp-stress test is used to determine the partial discharge inception voltage (PDIV) and the flashover voltage of oil/pressboard interface versus pressboard ageing. Constant-stress tests are carried out to investigate the partial discharge (PD) behaviors, the pressboard surface temperature, and the oil-dissolved gases of progressive creeping discharges. It is found that the pressboard ageing affects only the interface PDIV. The progressive creeping discharges concentrate at the triple-junction and comprises probably oil corona discharges and surface discharges in pressboard dimples. If no pressboard damage is present, the progressive discharges exhibit in general a constant PD pattern but a diminishing intensity, and nevertheless can be sustained for the severely-aged pressboards under strong voltages. The underlying causes are correlated with the competing effects of pressboard ageing on interface moisture and the triple-junction field intensification. Gas analyses indicate the hydrogen is the principal faulty gas and the Duval's Triangle diagnoses the progressive creeping discharges as either low-energy or high-energy discharge fault. No pressboard overheating is observed during the discharges.
Energy-Efficient Task Offloading in Massive MIMO-Aided Multi-Pair Fog-Computing Networks

The energy-efficient task offloading problem of a massive multiple-input multiple-output (MIMO)-aided fog computing system is solved, where multiple task nodes offload their computational tasks to be solved via a massive MIMO-aided fog access node to multiple processing nodes in the fog for execution. By considering realistic imperfect channel state information (CSI), we formulate a joint task offloading and power allocation problem for minimizing the total energy consumption, including both computation and communication power consumptions. We solve the resultant non-convex optimization problem in two steps. First, we solve the computational task allocation and computational resource allocation for a given power allocation. Then, we conceive a sequential optimization framework for determining the specific power allocation decision that minimizes the total energy consumption of the fog access node. Given the computational tasks, the computational resources, and the power allocation, we propose an iterative algorithm for the system optimization. The simulation results show that the proposed scheme significantly reduces the total energy consumption compared to the benchmark schemes.
Hybrid Monocular SLAM Using Double Window Optimization

This letter presents a hybrid framework, both in front-end and back-end, for monocular simultaneous localization and mapping (SLAM), capable of utilizing the robustness of feature matching and the accuracy of direct alignment. In the front-end, the feature-based method is first used for coarse pose estimation that is subsequently taken by the direct alignment module as initialization for further refinement. In the back-end, a double window structure is constructed based on the maintained semi-dense map and the sparse feature map, of which the states are optimized via a multi-layer optimization scheme based on the reprojection constraints and the relative pose constraints. Our evaluation on several public datasets demonstrates that this hybrid design retains the superior resilience to scene variations of salient features, and achieves better tracking accuracy due to the integration of the direct modules, leading to a comparable performance with the state-of-the-arts.
All-Optical Hybrid VO$_{2}$/Si Waveguide Absorption Switch at Telecommunication Wavelengths

Vanadium dioxide (VO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula>) is one of the most promising materials for developing hybrid photonic integrated circuits (PICs). At telecommunication wavelengths, VO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula> exhibits a large change on the refractive index (<inline-formula><tex-math notation="LaTeX">$\Delta n \sim 1$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\Delta \kappa \sim 2.5$</tex-math></inline-formula>) between its insulating and metallic state. Such insulating-to-metal transition (IMT) can be triggered by light, which could enable all-optical hybrid VO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula>-waveguide devices. Here, we experimentally demonstrate an all-optical absorption switch using a hybrid VO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula>/Si waveguide fully compatible with the silicon photonics platform. All-optical characterization was carried out for TE polarization and at telecommunication wavelengths using an in-plane approach. The temporal dynamics were retrieved by means of pump-probe measurements. Our results show an extinction ratio of 0.7 dB/<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>m with a maximum switchable length of 15 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>m, a switching speed as low as 318 ns, and an energy per switch of 15.8 nJ. The inherit large optical bandwith of a non-resonant waveguide poses this device as a promising candidate for developing all-optical and broadband silicon PICs.
Techniques of Sarcasm Detection: A Review

The Sentiment Analysis can be considered as the data mining target of sentiment classification of the customer’s reviews available in text form. Sarcasm is a kind of statement that expresses a person’s downside feelings by using positive terms. Labelling sarcasm in typescript is a vital task for Natural Language processing to elude the delusion of the sarcastic statements as a verbatim statement. The finding of these types of sarcastic statements is tough for humans as well as for a machine. Sarcasm has a greater impact on efficiency of Sentiment Analysis models that are influenced by mendacious sentiments that often belong to sarcastic class. In this paper we will discuss the recent research works done in the field of sarcasm recognition, different techniques and challenges in sarcasm detection. Finest plan of action for extraction of sarcasm is Hybrid methodology of Deep learning. This study aids in acquiring the knowledge of phases of the model of sarcasm extraction.
On the Global Stabilization of a Class of Nonlinear Singularly Perturbed Systems Using Nonlinear H-infinity Control Approach

In this paper, a stabilizing controller for a class of nonlinear singularly perturbed systems is designed by using nonlinear H-infinity control approach. Since the stability and ${\mathcal{L}_2}$-gain of the uncertainty block does not depend on the perturbation parameter, it can be referred as a robust controller. Also, through two theorems, the local and global stabilization of the controlled system are proven. Design procedure is discussed. The proposed approach is used to design a stabilizing controller for the Lorenz system with some specific parameters. The controller can globally stabilize the Lorenz system, while the pervious methods presented for the nonlinear singularly perturbed systems can only stabilize it locally, or even are unable to stabilize it.
On the Sum Capacity of Dual-Class Parallel Packet-Erasure Broadcast Channels

We investigate a <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-user parallel packet-erasure broadcast channel. There is an ongoing effort to harness millimeter-wave bands, which are known to be unstable having high outage probabilities, by combining them with stable legacy bands. Motivated by this effort, we consider a <italic>heterogeneous</italic> scenario in which the parallel subchannels are categorized into two classes having different outage probabilities. For the two-user case, we characterize the sum capacity by developing an explicit achievable scheme and deriving a matching upper bound. In contrast to suboptimal schemes that apply coding on a per-subchannel basis only, our scheme applies coding <italic>across</italic> subchannels to exploit coding opportunities that arise from asymmetric outage probabilities more efficiently, thereby achieving optimality. By extending our scheme systematically to be applicable for the <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-user case, we show that it can provide significant gains over existing schemes. Compared to the <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-user scheme currently employed in practice, which allocates chunks of subchannels to users exclusively, we demonstrate the performance improvement attainable by our scheme to be substantial, as the multiplicative gain scales with <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>. Moreover, we find that our scheme outperforms a per-subchannel extension of state-of-the-art <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-user schemes by large margins, further reducing the optimality gap. Our results suggest a potential coding scheme that can be employed in future wireless systems to meet ever-growing mobile data demands.
The FPGA Hardware Implementation of the Gated Recurrent Unit Architecture

The long short-term memory (LSTM) is the most widely used recurrent neural network representation for modeling sequential data. However, it is assumed an expensive modeling architecture as it requires many hardware components to be implemented, which is inefficient in solving problems based on small datasets. Therefore, in this paper, we propose a novel hardware implementation of the Gated Recurrent Unit (GRU) as a smaller alternative recurrent structure of the LSTM. The GRU has a smaller structure than the LSTM, which simplifies hardware components’ implementation and reduces overall power consumption. The proposed GRU hardware implementation can be perfectly fit problems that depend on small datasets.