Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliability Evaluation Considering a Combined Framework Of Energy Storage and OHL Time Varying Thermal Rating

Operational flexibility of power system at critical conditions becomes a worthy goal to all network operators (NOs). Such goal is challenging because of the high penetration of Renewable energy resources (RES) as well as the rapid demand growth that add more stresses to the network lines reducing the network reliability levels. To that extent, this paper proposes a reliability evaluation framework incorporating energy storage systems (ESS). The method shows the effectiveness of utilizing the available energy storage (ESS) in the network during contingencies as a secondary application for the ESS beside its main application at normal conditions. In addition, the benefits from considering time varying thermal ratings (TVTR) with the ESS is investigated showing the impact of TVTR on both ESS sizing and ESS effectiveness at contingencies as well as the network reliability. The impact of the proposed model is evaluated through metrics based on nodal reliability indices and the Sequential Monte Carlo simulation (SMC) approach on the 24-Bus IEEE Reliability Test System. The results from the proposed method significantly reduced the expected interruption costs (EIC) by 32%.
Fast Weak-Bus and Bifurcation Point Determination using Holomorphic Embedding Method

A new method of solving the power-flow problem, the holomorphically embedded load-flow method (HELM) is theoretically guaranteed to find the high-voltage solution, if one exists, up to the saddle-node bifurcation point (SNBP), provided sufficient precision is used and the conditions of Stahl’s theorem are satisfied. Sigma (σ) indices, have been proposed as estimators of the distance from the present operating point to the SNBP, and indicators of the weak buses in a system. This paper investigates the theoretical foundation of the σ method and shows that the σ condition proposed in [10] will not produce reliable results and that a modified requirement can be used to produce a tight upper bound on the SNBP. A new HEM-based method is then proposed that can be used to estimate the weak buses in a system (from a steady-state voltage stability perspective) at all operating points through to the SNBP, using a single power-flow solution. Numerical results for the proposed approach are compared to traditional modal analysis for the IEEE 14-bus and 118-bus systems.
An Investigation on Inter-degeneration Effect in Body Channel Based Multi-node Wireless Power Transfer

Wireless body area network is encountering the problem of insufficient power supply. Wireless power transfer is one of the solutions to solve this problem. Utilizing human body with low transmission loss as a medium and no need for large antennas, body channel based wireless power transfer is expected to realize efficient multi-node energy transmission. However, charging multiple nodes simultaneously based on the above method is still lack in research. To exploit this issue, in this paper, Computer Simulation Technology (CST) and Cadence co-simulation platform is used to analyze the inter-degeneration effect between multiple nodes in the case of single-source double-harvester. Practical experiments are carried out to discuss the inter-degeneration effect between multi-node received power and different distances and angles. Based on the experimental results, an empirical model is established, which can provide guidance for further researches on body channel based multi-node wireless power transfer.
Simple Design Procedure of a Broadband Circularly Polarized Slot Monopole Antenna Assisted by Characteristic Mode Analysis

In this paper, a systematic design procedure of a compact and broadband circularly polarized (CP) antenna is proposed. The antenna is first designed with a C-shaped monopole, and then a C-shaped slotted patch is utilized to produce CP radiation in the lower frequency band. Thus, the antenna’s overall CP bandwidth (BW) is significantly increased. In addition, unlike the conventional method in which the operation is verified by the simulated surface current distribution, characteristic mode analysis (CMA) is carried out to give more insight into different modes on the antenna and generation of circular polarization. The CMA also helps to realize a structural optimization and identify an efficient feed location. The optimized antenna prototype with a compact size of $0.29\lambda _{o} \times 0.29\lambda _{o} \times 0.01\lambda _{o} \,\,(\lambda _{o}$ is the minimum wavelength at the minimum operation frequency) achieves a usable 10-dB reflection coefficient and 3-dB axial ratio fractional BW of 91% (2.1–5.6 GHz). The antenna realized broadside gain varies from 1.5 to 3.2 dBic within this measured overlapped BW.
Low Rank Matrix Completion for Recovering Missing Load Data in Power System

The missing of measurement is a phenomenon often happens in power system. In this paper, a method based on low rank matrix completion theory is proposed to recover the missing load data. The low rank matrix is constructed based on the linear approximation principle. Then the low rank matrix completion algorithm is derived based on the linearized Bregman method. Based on the real data of power grid, the method is tested and the error is calculated. The comparison of the error of recovered load data is made between low rank matrix completion algorithm and spline interpolation and extrapolation. The result shows that the algorithm based on low rank matrix completion is more effective and has stronger adaptability.
Analysis of Gait Stability Criterion Based on Cognition of Human Walking Balance Mechanism*

How to evaluate the walking stability of robots and develop stable and effective walking control algorithms is a key research hotspot in the development of humanoid biped robots. At present, the main stability evaluation basis is zero moment point stability criterion. However, this method is poor in stability, flexibility and efficiency, which severely limits the walking ability of humanoid biped robot. This article is based on the human walking motion capture data, combining with the anatomical model, the kinematics forward solution algorithm which is used to calculate the trajectory of the human joint establish the kinematics model of the human walking process. This model analyzes the angular momentum balance and moment balance by introducing ground reference points and combining Euler's second theorem. Then on the base of these, we selected the forward distance between zero moment point and central moment axis, the vector plane centroid angular momentum and the acceleration of the center of mass in the forward direction as parameters to establish the human gait stability evaluation rules . Finally, The simulation results show that this stability criterion achieves an accurate discrimination of the walking gait stability of the human body and has high accuracy in determining the gait stability.
A 60-GHz CMOS Down-Conversion Mixer with High Conversion Gain and Low Noise Figure

In this paper, we present a 60-GHz single-balanced CMOS down-conversion mixer. The proposed mixer uses an on-chip active balun to furnish a differential output from an injected single-ended local oscillator (LO) signal. The millimeter-wave (mm-wave) active balun incorporates a cascode cross-coupled structure to generate the differential LO with a high voltage gain and minimum amplitude and phase mismatch. The overall mixer achieves a high conversion gain (CG) with a linearity and noise-figure performance that compare favorably with those of state-of-the-art designs. As a proof-of-concept, a 60-GHz mixer with a center intermediate-frequency (IF) of 20 GHz and output bandwidth of 3.2 GHz is designed and implemented in a 65-nm CMOS process. Measurement results show that the mixer achieves a peak conversion gain of $12.1~dB$ and 1-dB compression point of $-5dBm$. Furthermore, the fabricated mixer achieves a minimum double-sideband (DSB) noise figure of $6.5~dB$ over the bandwidth of interest. The chip consumes $11.5~mW$ from a 1-V supply and excluding the pads occupies $0.27~mm^{2}$ of silicon area.
A Neuromorphic Computing System for Bitwise Neural Networks Based on ReRAM Synaptic Array

Recent advances in neuromorphic computing system have shown resistive random-access memory (ReRAM) can be used to efficiently implement compact parallel computing arrays, which are inherently suitable for neural networks that require large amounts of matrix-vector multiplications (MVMs). In this work, we proposed a neuromorphic computing system based on ReRAM synaptic array to implement bitwise neural networks. The system contains a ReRAM synaptic array for parallel computation of bitwise MVMs, and a field-programmable gate array for data buffering and processing. To deploy the network on the system, a customized training scheme was required to adapt the trained network to the characteristic of ReRAM synaptic array with bitwise weights and inputs. We also managed the resolution of partial sum to reduce the bit width requirement of sense amplifier, thereby reducing power consumption. The measurement results show that the ReRAM synaptic array consumed only 0.27mW at 1V supply by using 1-bit sense amplifier while the system still maintained 97.52% accuracy on MNIST dataset.
Distributed Robust Reserve Scheduling in Congested Distribution Systems

Flexible electric load control is an important tool for the future power system in the face of recent challenges to the electric grid. This paper presents a control framework for combining optimal load scheduling for flexible loads, a dualised worst-case formulation of the uncertain disturbance prediction errors and reserve scheduling via a dualised worst-case formulation with a distributed method for congestion management in the distribution system via a subgradient algorithm. The suitability of the developed framework is demonstrated on a benchmark distribution system.
Fastened Unit Commitment with Loss Linearization for Distributed Generation Planning Studies

This paper presents an energy management strategy whose objective is the reduction of CO2 emissions of the power system on Jurong Island in Singapore. Distributed Generation (DG), with solar generation, energy storage, small gas turbine as well as controllable loads, is investigated. Such a procedure aims at being integrated in an optimal planning problem to find the best DG configuration and should then correspond to reasonable computational time. Thus a Mixed integer linear programming (MILP) technique is considered for the system simulated over a representative day. A specific attention is attached to the branch losses estimation with a modified DC power flow (DCPF). At first the method is tested for the base case scenario before investigating different configurations for the DG assets. Results are analyzed in terms of carbon emissions and grid losses.
Physisorption of Oxygen in SnO2 Nanoparticles for Perovskite Solar Cells

Although SnO2 is widely used in perovskite solar cells (PSCs) as the electron transport layer, there is still a need for a detailed investigation regarding the impact of physisorption on the performance of PSCs. Here, we report the role of physisorption of oxygen species from the ambient atmosphere in the oxidation states and defective oxides at the surface of SnO2 nanoparticles for the performance of PSCs. The SnO2 nanoparticle's thin film shows a higher oxidation state (Sn–O) and lower charge trap sites at an annealing temperature of 100 °C, and the SnO2 film based PSCs yield an efficiency of 18.04%. The annealing process results in the gradual desorption of physically adsorbed oxygen species. Therefore, the annealing process of SnO2 nanoparticle thin films in atmosphere is the key factor to control the oxidation states and defective oxides at the surface of SnO2 nanoparticle thin films.
Efficient Computation of Multidimensional Lambertian Optical Absorption

Approximate analytic expressions are given for the absorption of light emanating from a nonuniformly illuminated Lambertian surface into an absorptive layer having a spatially uniform coefficient of absorption, α. This situation is particularly relevant for silicon solar cells, which have deliberately textured surfaces and grid fingers that create nonuniform illumination. The approach uses Fourier superposition to represent spatial variation in the plane of the surface, represented by a series of wavenumbers in each axis. It is observed that the absorption rate and flux density at any given distance, z, into the layer is given by an effective wavenumber, keff, that is the root-sum-square of the wavenumbers in the two axes. This allows for simple analytic expressions that, for each Fourier component, depend only on the dimensionless terms keffz and αz. This Fourier-superposition approach is computationally efficient compared with ray tracing, and is particularly effective when the nonuniform illumination is periodic and symmetric in each axis, in which case the Fourier superposition becomes a cosine series of spatial harmonics. An example illustrates the good fidelity that can be obtained using as few as ten harmonics in each axis.
Future Hour Study Using State Estimator Cases for Real-Time Operations

This paper identifies the approach and advantages of for using the node/breaker model for future hour studies for real-time operations. The necessary steps to create future hour base cases from a real-time State Estimator (SE) case are presented. Advantages of using SE cases for creating near term future hour cases for operation studies are discussed. How different applications such as Contingency Analysis, Path Operating Limit and Cascade Analysis operate is also discussed.Issues and gaps are presented when creating and analyzing operations studies for current hour, next hour and future hours. Idaho Power’s experience of automating the future hour study is presented. The approach implemented produced fast, reliable and accurate models for future hour studies. The automation features and suggested improvements have been implemented, tested and in production since the new NERC TOP-002-4 Std. , became enforceable in April 2017. This process has been implemented using a 10,000 bus, 100,000 node WECC system commonly referred to as the West Wide System Model.
Enabling Communication for Locked-in Syndrome Patients using Deep Learning and an Emoji-based Brain Computer Interface

Locked-in syndrome describes a condition in which patients are incapable of speaking or moving, although they do retain their cognitive capabilities. In this paper, we propose a novel Brain Computer Interface design using a versatile emoji-based symbol display and a deep learning solution to enable these patients to communicate using recordings obtained through electroencephalography (EEG). EEG signals are converted into images representing their spatiotemporal characteristics. Images are then classified using a deep convolutional neural network (CNN) to recognize the intended emoji symbol. A prototype of the proposed system was tested on five healthy volunteers, showing significant improvement in the recognition rate when compared to the classic LDA classifier.
Semi-parametric Decentralised Adaptive Control of Discrete-time Nonlinear Multi-agent Systems*

This paper investigates the challenging and significant problem of semi-parametric decentralised adaptive control in discrete-time nonlinear multi-agent systems, where parametric uncertainties and non-parametric uncertainties coexist. To deal with these two kinds of uncertainties, we introduce an auxiliary state to compensate non-parametric uncertainties. Then, we utilize a novel deadzone with threshold converging to zero to guarantee the boundedness of the estimated values of unknown parameters. Based on the certainty equivalence principle, semi-parametric decentralised adaptive controllers are designed to make sure that all agents track the reference state, and the closed-loop system achieves consensus tracking under the condition of strong couplings. Finally, the effectiveness of designed controllers is revealed through numerical simulation.
Practical Solution for the Low Inertia Problem in High Renewable Penetration Isolated Power Systems

Following time-constraining obligations under 2015 Paris Agreement, nations are racing to integrate more renewable energy generation into their power systems than ever before. While solutions for mitigation of renewable energy negative effects to power system stability exist, they are still complex and expensive. One of the most promising technologies, battery energy systems is widely advocated, but is still unable to solve basic challenge of renewable energy integration – low inertia. This paper presents a practical enabling technology in a form of synergy between a battery energy system and a synchronous machine, which is capable of supporting fully renewable power system while providing nominal power system inertia. For simplicity, the case for this technology is presented on an example of an Isolated Power System with very high renewable energy contribution.
Thermally Controlled Lab-on-PCB for Biomedical Applications

This paper reports on the implementation and characterisation of a thermally controlled device for in vitro biomedical applications, based on standard Printed Circuit Board (PCB) technology. This is proposed as a low cost alternative to state-of-the-art microfluidic devices and Lab-on-Chip (LoC) platforms, which we refer to as the thermal Lab-on-PCB concept. In total, six different prototype boards have been manufactured to implement test mini-hotplate arrays. 3D mol-tiphysics software simulations show the thermal response of the modelled mini-hotplate boards to a current-controlled stimulus, highlighting their versatile heating capability. Comparing this with experimental results of the fabricated PCBs demonstrates the combined temperature sensing/heating feature of the mini-hotplate. This can provide a wider temperature range compared to that achieved in typical LoC devices. The thermal system is controllable by means of external off-the-shelf circuitry designed and implemented on a single-channel control board prototype.
Microscopic Simulation and Characteristics Analysis of Point Discharge Based on PIC-MCC Method

Point discharge is a typical kind of Partial Discharge (PD) behavior. The microscopic process of particle movement is simulated in this paper by combing particle in cell (PIC) method with Monte Carlo collision (MCC) method, which possesses great significance for researching partial discharge. Simulation results show detailed motion process and the Townsend discharge phenomenon. As a result of simulation process, macro characteristics such as PD currents are analyzed to study discharge property. PD current pulse waveform possesses the trend of steep rising edge follows Gaussian distribution while gentle falling edge obeys Power function. The effect of voltage difference, air-gap size and polarity on PD characteristics are discussed in this paper.
The Skyline Image Segmentation using Color and Detail Clustering

There are a lot of different segmentation methods used to locate objects or particular scene parts. One of the most interesting scene parts can be horizon or skyline. The proper skyline image segmentation includes proper division into three clusters: sky, skyline region and the rest of the image. This paper analyzes the influence of color for the skyline-based segmentation.
All Eyes on You: Distributed Multi-Dimensional IoT Microservice Anomaly Detection

The Internet of Things (IoT) is a Distributed System of cooperating Microservices $(\mu$ Ss). IoT services manage devices that monitor and control their environments. The interaction of the IoT with the physical environment creates strong security, privacy, and safety implications. It makes providing adequate security for IoT $\mu$ Ss essential. However, the complexity of IoT services makes detecting anomalous behavior difficult.We present a machine-learning based approach for modeling IoT service behavior by only observing inter-service communication. Our algorithm continuously learns $\mu$S models on distributed IoT nodes within an IoT site. Combining the learned models within and in-between IoT sites converges our $\mu$S models within short time. Sharing the resulting stable models among compute nodes enables good anomaly detection.As one application, firewalling IoT $\mu$ Ss becomes possible. Combining our autonomous $\mu$S modeling with firewalling enables retrofitting security to existing IoT installations. We enable retrofitting access control to existing non-secure IoT installations.Our proposed approach is resource efficient, matching the requirements of the IoT. To evaluate the quality of our proposed algorithm, we show its behavior for a set of common IoT attacks. We evaluate how domain knowledge enables us to decorrelate events on a node, and how adding context features improves the detection rate.
A Four-Port Ultra-Compact Terahertz Splitting Filter Based on Graphene Nanoribbon

A four-port ultra-compact plasmonic splitting filter based on graphene diamond ring resonator is proposed and investigated by using the finite-difference time-domain method. Numerical simulation results show that the transmission spectra can be affected by the structural parameters and the chemical potential of graphene. Especially, the resonant frequencies can be easily manipulated by changing bias voltage without changing the dimension parameters of the filter. The simple structure that consists of graphene nanoribbon waveguides and a graphene resonator shows both splitting and filtering capability. This compact intersection structure has potential applications in highly integrated optical circuits for terahertz frequency.
Evaluation of a Wearable and Wireless Human-Computer Interface Combining Head Motion and sEMG for People with Upper-Body Disabilities

In this paper, a wearable, wireless and multimodal 2-dimensional computer mouse control system is introduced for people with upper-body disabilities. The proposed human-computer interface system combines body-motion, measured using inertial measurement unit (IMU), to provide a cursor velocity and displacement control, and surface electromyography (sEMG) for target selection (left-click), using custom sensors made of electronic components of the shelf. Its functionality is demonstrated by using head motion and muscular activity detection from trapeze muscles to evaluate usability by people living with severe disabilities, congenital absence or amputation of upper-members, temporary limb traumatism, etc., preventing their utilization of tools such as mouse or keyboard. Performance using different control topologies, following the ISO/TS 9241-411:2012 standard encompassing the evaluation of physical pointing tasks, and compared to a computer mouse. On average, over the 3 participants, results show that the proposed interface can provide an index of performance of 0.18 bits/s versus 2.2 bits/s with a mouse pointer. Head motion combined with sEMG showed a 4% accuracy drop computer to the mouse while being more suitable for the severely disabled.