nils-herrmann/clean_scirepeval huggingface dataset:
Clump splitting via bottleneck detection

Under-segmentation of an image with multiple objects is a common problem in image segmentation algorithms. This paper presents a novel approach for the splitting of clumps formed by multiple objects due to under-segmentation. The algorithm includes two steps: finding a pair of points for clump splitting, and joining the pair of selected points. In the first step, a pair of points for splitting is detected using a bottleneck rule, under the assumption that the desired objects have roughly convex shape. In the second step, the selected pair of splitting points is joined by finding the optimal splitting line between them, based on minimizing an image energy. The performance of this method is evaluated using images from various applications. Experimental results show that the proposed approach has several advantages over existing splitting methods in identifying points for splitting as well as finding an accurate split line.
Adaptive Droop Control for Effective Power Sharing in Multi-Terminal DC (MTDC) Grids

Following a converter outage in a Multi-Terminal DC (MTDC) grid, it is critical that the healthy converter stations share the power mismatch/burden in a desirable way. A fixed value of power-voltage droop in the DC link voltage control loops can ensure proper distribution according to the converter ratings. Here a scheme for adapting the droop coefficients to share the burden according to the available headroom of each converter station is proposed. Advantage of this adaptive (variable) droop scheme for autonomous power sharing is established through transient simulations on an MTDC grid with four bipolar converters and DC cable network with metallic return. Results for both rectifier and inverter outages under two different scenarios are presented. Post-contingency steady-state operating points obtained from transient simulation are shown to be consistent with those derived analytically. Impact of varying droop coefficients on the stability of the MTDC grid is established. An averaged model in Matlab/SIMULINK which has been validated against detailed switched model in EMTDC/PSCAD is used for the stability and modal analysis.
Anovel framework for automatic passenger counting

Wepropose anovel framework for counting passengers in a railway station. The framework has three components: people detection, trackingand validation. We detect every person using Hough circle when he or she enters the field of view. The person is then tracked using optical flow until (s)he leaves the field of view. Finally, the tracker generated trajectory is validated through aspatio-temporal background subtraction technique. The number of valid trajectories provides passenger count. Each of the three components of the proposed framework has been compared with competitive methods on three datasets of varying crowd densities. Extensive experiments have been conducted on the datasets having top views of the passengers. Experimental results demonstrate that the proposed algorithmic framework performs well both on dense and sparse crowds and it can successfully detect and track persons with different hair colors, hoodies, caps, long winter jackets, bags and so on. The proposed algorithm shows promising results also for people moving in different directions. The proposed framework can detect up to 30% more accurately and 20% more precisely than other competitive methods.
Modeling and stability analysis of MTDC grids for offshore wind farms: A case study on the North Sea benchmark system

Modeling of VSC-based multi-terminal DC (MTDC) grids for modal analysis and stability studies is reported considering bipolar converters and DC cable network with metallic return path. The proposed model is flexible enough to accommodate different converter grounding options and unbalance on the DC side due to cable and/or converter outage. A simplified version of the benchmark test system for the envisioned offshore MTDC grid in the North Sea is studied. Modal participation factor analysis under nominal and converter outage conditions is used to ascertain the nature and root cause of the dynamic responses. Comparison of the time-domain simulation results using the proposed averaged model in Matlab/SIMULINK against a detailed switched model in EMTDC/PSCAD confirm the accuracy of the modeling approach.
Computation of Fluid and Particle Motion From a Time-Sequenced Image Pair: A Global Outlier Identification Approach

Fluid motion estimation from time-sequenced images is a significant image analysis task. Its application is widespread in experimental fluidics research and many related areas like biomedical engineering and atmospheric sciences. In this paper, we present a novel flow computation framework to estimate the flow velocity vectors from two consecutive image frames. In an energy minimization-based flow computation, we propose a novel data fidelity term, which: 1) can accommodate various measures, such as cross-correlation or sum of absolute or squared differences of pixel intensities between image patches; 2) has a global mechanism to control the adverse effect of outliers arising out of motion discontinuities, proximity of image borders; and 3) can go hand-in-hand with various spatial smoothness terms. Further, the proposed data term and related regularization schemes are both applicable to dense and sparse flow vector estimations. We validate these claims by numerical experiments on benchmark flow data sets.
Droop Control of Distributed Electric Springs for Stabilizing Future Power Grid

This paper describes the droop control method for parallel operation of distributed electric springs for stabilizing ac power grid. It provides a methodology that has the potential of allowing reactive power controllers to work in different locations of the distribution lines of an ac power supply and for these reactive power controllers to support and stabilize the ac mains voltage levels at their respective locations on the distribution lines. The control scheme allows these reactive power controllers to have automatically adjustable voltage references according to the mains voltage levels at the locations of the distribution network. The control method can be applied to reactive power controllers embedded in smart electric loads distributed across the power grid for stabilizing and supporting the ac power supply along the distribution network. The proposed distributed deployment of electric springs is envisaged to become an emerging technology potentially useful for stabilizing power grids with substantial penetration of distributed and intermittent renewable power sources or weakly regulated ac power grid.
Locating Brain Tumors from MR Imagery Using Symmetry

Tumor/abnormality segmentation from magnetic resonance imagery (MRI) can play a significant role in cancer research and clinical practice. Although accurate tumor segmentation by radiologists is ideal, it is extremely tedious. Experience shows that for MRI database indexing purposes approximate segmentations can be adequate. In this paper, we propose a straightforward, real-time technique to find a bounding box around the brain abnormality in an MR image. Our algorithm exploits left-to-right symmetry of the brain structure. The proposed detection algorithm can play a useful role in indexing and storage of bulk MRI data, as well as provide an initial step or seed to assist algorithms designed to find accurate tumor boundaries.
Wavelet subband-based steam detection by multiple kernel learning

Wavelet transform coefficients have been shown as significant features for detecting steam and smoke. Wavelet transform is multi-resolution in nature; moreover, at each resolution, wavelet transform coefficients form a high dimensional feature set. In this paper we handle both these issues in a multiple kernel learning (MKL) framework. First, high dimensionality is handled by using a kernel function that measures similarity between two sets of wavelet coefficients at the same resolution. Next, we consider a convex combination of these kernel functions that correspond to all the available resolutions of the wavelet transform. The proposed MKL uses an L1 norm linear support vector machine (SVM) for sparse learning of the convex combination. Then, this mixture kernel function is used in an L2 norm nonlinear SVM for binary classification- image with steam or without steam. Our method yields encouraging results and outperforms other competing methods.
Considerations Toward Coordinated Control of DFIG-Based Wind Farms

This paper highlights the important considerations toward coordinated control of doubly fed induction generator (DFIG)-based wind farms for power oscillation damping. The effect of replacing one existing synchronous generator with a power system stabilizer (PSS) by a DFIG on the local mode and the mode shapes of the critical interarea modes are analyzed. With almost zero participation from the DFIG mechanical side and very little observability of low-frequency oscillatory modes in signals locally available at the wind farms, the choice of appropriate remote feedback signals is discussed. Relative controllabilities of the DFIG rotor current components are compared to determine the most effective control structure. A coordinated control design approach aimed at damping multiple oscillatory modes through more than one DFIG-based wind farm is demonstrated. Heuristic optimization is used for the design problem which is otherwise difficult to solve using an analytical approach. Modal analysis and nonlinear simulation results are presented to substantiate the findings.
Adaptive droop control for effective power sharing in multi-terminal DC (MTDC) grids

Following a converter outage in a Multi-Terminal DC (MTDC) grid, it is critical that the healthy converter stations share the power mismatch/burden in a desirable way. A fixed value of power-voltage droop in the DC link voltage control loops can ensure proper distribution according to the converter ratings. Here a scheme for adapting the droop coefficients to share the burden according to the available headroom of each converter station is proposed. Advantage of this adaptive (variable) droop scheme for autonomous power sharing is established through transient simulations on an MTDC grid with four bipolar converters and DC cable network with metallic return. Results for both rectifier and inverter outages under two different scenarios are presented. Post-contingency steady-state operating points obtained from transient simulation are shown to be consistent with those derived analytically. Impact of varying droop coefficients on the stability of the MTDC grid is established. An averaged model in Matlab/SIMULINK which has been validated against detailed switched model in EMTDC/PSCAD is used for the stability and modal analysis.
Frequency control for weak AC grid connected to wind farm and LCC-HVDC system: Modeling and stability analysis

Interconnection of DFIG-based wind farms with LCC-HVDC is challenging for very weak AC systems. This work focuses on establishing a modeling and control design framework to analyze frequency dynamics in such systems. To that end, an averaged model of the DFIG-based wind farm connected to LCC-HVDC system has been developed where grid frequency control is used to regulate the HVDC rectifier firing angle. This paper analyzes the effect of low Effective Short Circuit Ratio (ESCR) and the Effective DC Inertia Constant Hdc on the stability of the system. A systematic design process of the frequency controller parameters reveals a negative interaction between the generator speed-HVDC PLL-frequency controller mode and the DFIG-GSC controller mode.
Considerations toward coordinated control of DFIG-based wind farms

This paper highlights the important considerations toward coordinated control of doubly fed induction generator (DFIG)-based wind farms for power oscillation damping. The effect of replacing one existing synchronous generator with a power system stabilizer (PSS) by a DFIG on the local mode and the mode shapes of the critical interarea modes are analyzed. With almost zero participation from the DFIG mechanical side and very little observability of low-frequency oscillatory modes in signals locally available at the wind farms, the choice of appropriate remote feedback signals is discussed. Relative controllabilities of the DFIG rotor current components are compared to determine the most effective control structure. A coordinated control design approach aimed at damping multiple oscillatory modes through more than one DFIG-based wind farm is demonstrated. Heuristic optimization is used for the design problem which is otherwise difficult to solve using an analytical approach. Modal analysis and nonlinear simulation results are presented to substantiate the findings.
A Novel Explicit Disturbance Model-Based Robust Damping of Interarea Oscillations Through MTDC Grids Embedded in AC Systems

This paper presents a novel approach to damp interarea oscillations by designing a robust multi-input multioutput supplementary controller for multiterminal dc (MTDC) systems embedded in ac grids. The key idea to achieve robustness lies in explicitly modeling the MTDC current injection as disturbances using an <inline-formula> <tex-math notation="LaTeX">${\mathcal H}_{\infty }$</tex-math></inline-formula> mixed-sensitivity formulation in the linear matrix inequality framework. Control directions are established by selecting wide-area feedback signals and the relative gain array computation. Robustness is assessed through dynamic simulations for scenarios including: first, disturbances on the ac side, second, disturbances on the dc-side such as loss of a converter pole including actuator, third, partial loss of feedback signal, and fourth, communication latencies. The performance of the proposed controller is compared against the conventional <inline-formula><tex-math notation="LaTeX">${\mathcal H}_{\infty }$ </tex-math></inline-formula> based design, using a four-terminal dc grid embedded within the New England–New York test system. The results suggest that the proposed approach demonstrates superior performance following dc-side disturbances, actuator outages, and latency.
Modeling adequacy for studying power oscillation damping in grids with wind farms and networked control systems (NCS)

Network delays and data-dropouts could have a significant impact on Cyber-Physical System (CPS). In this paper power grid with large-scale deployment of distributed and networked Phasor Measurement Units (PMUs) and wind energy resources is considered as an example of CPS. Modeling and simulation studies are done in a power system with 151 dynamic states for stabilizing electromechanical oscillations using remote PMU signals under different rates of data dropout, fault locations, and different degrees of nonlinearity. To that end a centralized state-feedback controller is designed to modulate the current references of Doubly Fed Induction Generator (DFIG)-based wind farm (WF). Modeling adequacy studies of a representative subtransient model of the grid and the averaged model of DFIG-based WF along with the representation of packet drop in the communication network by a Gilbert-Elliot model and Bernoulli model is performed.
An Architecture for FACTS Controllers to Deal With Bandwidth-Constrained Communication

Bandwidth constraints could have an adverse impact on the flexible AC transmission system (FACTS) controllers relying on signals communicated from distant locations. An observer-driven system copy (OSC) architecture is adopted here to deal with low data rates caused by the limited bandwidth availability. The basic idea is to use the knowledge of the nominal system to approximate its actual behavior during the intervals when data from the remote phasor measurement units (PMUs) are not available. This is corrected whenever the most recent states are obtained from the reduced-order observer at the PMU location. The closed-loop behavior deteriorates as the operating condition drifts away from the nominal. Nonetheless, significantly better response is achieved under limited bandwidth availability compared to the conventional approach of communicating the measured outputs. The deterioration is quantified in terms of the difference between the nominal and the offnominal condition.
Coordinated Control of Offshore Wind Farm and Onshore HVDC Converter for Effective Power Oscillation Damping

Damping contribution from wind farms (WFs) is likely to become a mandatory requirement as a part of the grid codes. For remote offshore WFs, connected through a voltage source converter (VSC)-based direct current link, the most convenient option for the onshore transmission system operator (TSO) is to modulate the reactive power at the onshore VSC within their own jurisdiction. In this paper, we show that supplementary control through the onshore VSC alone, although attractive for TSOs, could result in undesirable voltage variations in the onshore grid. On the other hand, modulation of active power output of the wind turbine generators (WTG) alone turns out to be inadequate due to the limited overload capability of the WTGs. Coordinated control over both onshore VSC and aggregated WF output overcomes the above limitations and is shown to be effective for power oscillation damping. A homotopy approach is used to design the coordinated controller, which can be implemented locally (at offshore WF and onshore converter site) using a decentralized architecture. This is a bilinear matrix inequality problem, which is solved by transforming these constraints into linear matrix inequality constraints. Case studies on two test systems show that the proposed controller yields similar system dynamic response as supplementary control through the WF alone.
New Insights Into Coupled Frequency Dynamics of AC Grids in Rectifier and Inverter Sides of LCC-HVDC Interfacing DFIG-Based Wind Farms

Coupling between frequency dynamics of the ac systems on both inverter and rectifier sides of the line-commutated converter HVDC with the rectifier station operating in frequency control is studied, along with the presence of large DFIG-based wind farms on the weak rectifier-side grid. An averaged model with 79 states, which includes dynamic models of grids on the rectifier and inverter sides, phase-locked loop, and the wind farm is derived. To develop a deeper understanding of the frequency dynamics, a simplified four-state nonlinear model is proposed, which, in turn, reveals strong coupling between frequency and ac voltage at the HVDC rectifier terminal. A firing angle correction strategy is proposed to decouple frequency–voltage interactions, thereby improving the frequency dynamics on the rectifier side. The four-state model is linearized to ascertain the interaction between rectifier- and inverter-side frequencies, and an analytical expression for the frequency dynamics in terms of gains of the frequency controller at the rectifier station is derived. Moreover, the proposed reduced-order model shows the implications of frequency droop control of the wind farms in improving frequency dynamics on both rectifier and inverter sides. Expressions for “synchronizing” and “damping torque” contribution from HVDC and wind farm are also established. The analytical expressions and the effectiveness of the proposed strategies are validated through nonlinear time-domain simulations.
Wide-Area Damping Control using Reduced Copy under Intermittent Observation: A Novel Performance Measure

Insight into the application of observer-driven reduced copy (ORC) to deal with data packet dropout during wide-area oscillation damping control through wind farms (WFs) is developed. The ORC technique tries to emulate the behavior of the power system by using the information of the nominal dynamics under intermittent observation. This brief presents a direct performance measure for ORC. To that end, a standard lemma relating the bound on the norm of the integral over the product of two functions is presented, which is proven using Hölder’s inequality. Based on the lemma, an expression is derived for the bound on the norm within an inter-sample interval for difference between the power system states in presence of data dropout and that under ideal communication. Such a bound, when evaluated in a relative sense, would be useful for system operators to perform online contingency screening and ranking from damping performance standpoint without running prohibitively expensive time-domain simulations. In addition, such a bound is also derived for the conventional feedback control (CFC). The data dropout is modeled using the Gilbert-Elliott model. The analytical results are validated using time-domain simulation of a 16-machine, 5-area New England-New York system with two doubly fed induction generator-based WFs.
A Structured Deep-Learning Based Approach for the Automated Segmentation of Human Leg Muscle from 3D MRI

In this paper, we present an automated algorithm for segmenting human leg muscles from 3D MRI data using deep convolutional neural network (CNN). Using a generalized cylinder model the human leg muscle can be represented by two smooth 2D parametric images representing the contour of the muscle in the MRI image. The proposed CNN algorithm can predict these two parametrized images from raw 3D voxels. We use a pre-trained AlexNet as our baseline and further fine-tune the network that is suitable for this problem. In this scheme, AlexNet predicts a compressed vector obtained by applying principal component analysis, which is then back-projected into two parametric 2D images representing the leg muscle contours. We show that the proposed CNN with a structured regression model can out-perform conventional model-based segmentation approach such as the Active Appearance Model (AAM). The average Dice score between the ground truth segmentation and the obtained segmentation image is 0.87 using the proposed CNN model, whereas for AAM score is 0.68. One of the greatest advantages of our proposed method is that no initialization is needed to predict the segmentation contour, unlike AAM.
An approach for wide-area damping control using multiple DFIG-based wind farm to deal with communication dropouts

In this paper, a systematic approach is proposed for wide-area oscillation damping control, which can handle data-packet dropout in the communication channels of a smart power grid with large-scale deployment of distributed and networked Phasor Measurement Units (PMUs) and wind energy resources. To that end, a reduced order dynamic equivalent model of the New England-New York power system with replacement of two existing synchronous generators (SGs) by two doubly-fed induction generator (DFIG)-based wind farms (WFs) is considered. One of these SGs was equipped with a power system stabilizer (PSS). The issues with electromechanical oscillation damping control through WFs using locally available signals is identified and a methodical way for appropriate selection of control input and remote feedback signals through modal analysis is presented. The remote feedback signals transmitted through communication channels encounter data dropout which is characterized by the Gilbert-Elliott model. Deterioration in the performance of the oscillation damping control is demonstrated when data-packet dropout takes place in the remote feedback signals from PMUs. An Observer-driven Reduced Copy (ORC) approach is proposed to improve the damping performance under data-packet drop scenarios where conventional feedback would suffer. Nonlinear time-domain simulations following large large disturbances (e.g., faults, line outages, etc.) demonstrate that the ORC gives significantly better performance compared to conventional feedback under higher data drop situations.