Miracle-dz/UniFAR-FTUs huggingface dataset:
Coherent Clustering Method Based on Weighted Clustering of Multi-Indicator Panel Data

The identification of coherent clusters plays an important role in dynamic equivalence and active split control of power systems. The existing coherent clustering methods often adopt a single indicator, e.g. only based on the power angle curve to identify coherent clusters. In addition, in the coherency identification process, the feature extraction is not sufficient, which may cause the problem of inaccurate grouping. In this paper, a coherent clustering method based on weighted clustering of multi-indicator panel data (WCMPD) is proposed. First, the measurements including power angle increment, terminal voltage, and rotor kinetic energy increment from phasor measurement units (PMU) are selected from panel data to reflect the coherence of the generators. Second, the indicator weights and time weights are calculated based on the cross-sectional and time dimension of the panel data. In order to suppress the shortcomings of the coherent clustering method based on Euclidean distance, three distance functions (“horizontal absolute value,” “rate of change at adjacent time points,” and “fluctuation variation degree”) are defined, and then aggregated. At last, the distance matrices among generators are calculated and the coherent generators can be obtained based on the system cluster method. The simulation results on the EPRI-36 bus system and the North China power grid demonstrate that the proposed method has better clustering results than traditional methods.
Structural System Selection Using the Integration of Multi-Attribute-Decision-Making (MADM) Methods

A structural system carries all loads acting on the building and transfers them effectively to the soil through the foundation. Since it is the essential component of a building, selecting the most appropriate structural system is one of the critical decisions in the structural design. The design team, which consists of engineers and architects, is responsible for determining the structural system that will satisfy the owner's and end user's needs as well as the legal requirements. Due to the fact that a number of compromising and conflicting criteria may affect the structural system selection process, it is a difficult task and it should be considered as a multi-attribute-decision-making (MADM) problem. The main objective of this study is to provide the design teams with a MADM approach that will assist them in selecting the most appropriate structural system in a more objective and systematic manner. In the proposed approach, analytic hierarchy process (AHP) is used to compute the weights of the criteria and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is employed to rank the structural system alternatives. In order to demonstrate how the proposed can be applied in a real life problem, the structural system of a housing project in Istanbul, Turkey is selected via this approach. The findings of the model were discussed with the decision making team in the studied project and they stated that the proposed approach could be easily employed as a guideline in selecting the most appropriate structural system from the managerial viewpoint. This paper is the revised version of the paper that has been published in the proceedings of the Creative Construction Conference 2018 (Polat et al., 2018).
Application of Octree Map in Robotic Environment Reconstruction

For the autonomous navigation of robots in unknown environment, aiming at resolving the shortcomings of the traditional 3D point cloud map such as unclear navigational route planning, poor local scenes processing and large storage space, an octree-based 3D reconstruction method is presented, the octree map is used in RGB-D SLAM to realize the localization and mapping of the robot in this paper. The performance of the proposed approach is evaluated with both simulated and real data. The experimental results show that it can clearly plan the navigation path for the robot, effectively improve the ghosting phenomenon of point cloud maps. As well as, it storage space is less than point cloud maps under the same image resolution, and the advantage of octree maps storage space is more obvious when the image resolution is higher. Therefore, the binarized data form of the octree map, which can effectively optimize the reconstruction of the unknown environment mapping for a mobile robot.
Inhibition of indoleamine 2,3‐dioxygenase attenuates endotoxin‐mediated tolerance in granulosa cells through kynurenine pathway

Ovarian granulosa cells (GCs) have been shown to have innate immune capabilities, which modulate their native endocrine functions through toll‐like receptors (TLRs). We have recently shown that GCs exposed to lipopolysaccharide (LPS; 1.0 µg/mL) transiently regulate proinflammatory cytokine expression (interleukin 1β [IL‐1β], IL‐6, and tumor necrosis factor α) through chromatin remodeling. In the present study, we have demonstrated that GCs become tolerant to LPS on repeated exposure of LPS. To understand the mechanism of this endotoxin tolerance (ET) phenomenon in buffalo GCs, we have further studied the genome‐wide transcriptomic analyses in buffalo GCs (unpublished data) and identified indoleamine 2,3‐dioxygenase 1 (IDO1) gene, known to be involved in tryptophan catabolism, was found to be highly upregulated in endotoxin‐tolerant GCs. Real‐time gene expression analyses also showed similar results. Further analyses of tryptophan and tryptophan metabolite, kynurenine, showed that tryptophan was found to be depleted with the accumulation of kynurenine in the endotoxin‐tolerant GCs. The effect of IDO1 induced ET was reversed when cells were pretreated with IDO1 inhibitor (1‐methyl tryptophan, 1 mM). To the best of our knowledge, this is the first report describing the role of IDO1 gene in ET in GCs mimicked by repeated endotoxin exposure in vitro. In summary, the present study convincingly demonstrated that the tryptophan catabolism, through the kynurenine pathway, plays a crucial role as an immunomodulatory mechanism of ET in GCs. The finding could be exploited in developing potential therapeutics to treat impaired GCs function due to the ET underlying prolonged uterine or systemic infection leads to accumulation of endotoxin in follicular fluid.
Foreground Extraction via the Tensor-Based RPCA with Non-Convex Fused Sparsity

Foreground extraction has been a fundamental research topic in video analysis. Recently the non-convex penalty has been shown remarkable advantages in signal processing, and the fused sparsity is widely employed in image processing because it is able to preserve sharp edges that are usually the most important for clear object extraction. By decomposing video frames into low-rank background and sparse foreground in the tensor framework, a novel robust principal component analysis (RPCA) technique for foreground extraction is proposed in this paper. First, the tensor nuclear norm is employed to develop the spatio-temporal redundancy of background based on the circulant algebra. Secondly, the non-convex fused sparsity is utilized to describe foreground, which is able to enhance the smoothness of boundary. An efficient algorithm via using the alternating direction method of multipliers (ADMM) is proposed with convergence analysis. Extensive experiments on synthetic and real-world data sets show that our proposed technique outperforms the existing state-of-the-art techniques. In fact, to the best of our knowledge, this is the first time to integrate the nonconvex penalty and the fused sparsity into a tensor framework, which has demonstrated the superiority of performance.
High‐power broadband graphene non‐Foster circuit enabled class‐J GaN HEMT power amplifier

This paper presents high‐power broadband graphene non‐Foster circuit (NFC) enabled Class‐J GaN HEMT power amplifier (PA). A graphene resonant‐tunneling diode (RTD) NFC is proposed to provide negative differential resistance characteristics and to create an effective negative capacitance. The NFC is integrated in the input matching network of the Class‐J GaN HEMT PA to cancel out the transistor input parasitic capacitance so as to enhance PA bandwidth, efficiency, output power, and gain. The PA design is based on Cree's packaged GaN HEMT CGHV40030F biased with drain supply voltage of 50 V at quiescent drain‐to‐source current of 44 mA. The PA operates from 3.4 to 4.0 GHz with center frequency of 3.7 GHz. The effective negative capacitance of the NFC from 3.4 to 4.0 GHz stands at −3.3 to −6.0 pF. An effective capacitance of −3.7 pF has been obtained at 3.7 GHz. The PA has small signal gain of 16.1 dB at 3.7 GHz. Large signal simulation input power sweep from 1 to 33 dBm at 3.7 GHz, indicates that the PA has 57.8% drain efficiency, 54.7% power added efficiency (PAE), 44.6 dBm (28.8 W) output power and 11.6 dB transducer power gain at input power of 33 dBm.
On the Error Rate Analysis of Coded OFDM Over Multipath Fading Channels

In this letter, an (approximate) closed-form expression for the probability of codeword error is derived in coded orthogonal frequency division multiplexing over multipath fading channels. The derived error probability depends on the channel realization and can be used to decide the values of key parameters of finite-length codes and the signal-to-noise ratio so that a high reliability can be guaranteed in terms of the error probability for a given multipath fading channel.
Real-Time Trajectory Planning for Autonomous Parafoil in Obstacle-Rich Environment

Parafoil system is suitable for large-area and longtime surveillance and airdrop missions and has the advantages of simple structure, low cost and high load capacity. The system is utilized for delivery mission in open area, where there is no obstacles or few obstacles. After released from the airplane, the system performs a classical three-phases landing strategy consisting of homing, energy management and terminal landing. This paper utilizes the classical guidance framework and presents a revised method of terminal landing using Bezier curves to solve obstacles avoidance problems in obstacle rich environment for parafoil system. With the definition of Bezier curve and cost function, the terminal landing path generation problem is converted to an optimization problem and is solved using nonlinear optimizer. To deal with different environments, a terminal landing strategy is developed. The simulation results show its effectiveness on parafoil system terminal path planning.
Flexible-Rate SIC-Free NOMA for Downlink VLC Based on Constellation Partitioning Coding

Visible light communication (VLC) systems utilizing conventional superposition coding/successive interference cancellation (SPC/SIC)-based non-orthogonal multiple access (NOMA) suffer from the error propagation effect due to imperfect SIC. In this letter, we propose a flexible-rate SIC-free NOMA technique for downlink VLC systems, based on constellation partitioning coding (CPC) and uneven constellation demapping (UCD). By using CPC/UCD, SIC is not required and hence error propagation can be eliminated in NOMA-based VLC systems. Moreover, by selecting a proper bit allocation scheme, flexible-rate multiple access can be supported in the VLC system applying CPC/UCD-based NOMA. Proof-of-concept two-user VLC experiments verify that, compared with conventional SPC/SIC-based NOMA, the bit error rate performance of the near user can be greatly improved by using CPC/UCD-based NOMA, and hence the effective power allocation ratio range can be substantially extended.
Channel Estimation Method for Subarray Based Hybrid Beamforming Systems Employing Sparse Arrays

Hybrid beamforming systems are a cost and energy efficient architectural approach for large-scale antenna arrays operating at millimetre-wave frequencies. The separation of the beamforming process into an analogue beamforming network and a digital precoding part enables the reduction of digital channels while preserving a precise beam steering capability. Especially subarray-based hybrid beamforming systems distinguish them due to a low complex analogue beamforming network. However, to determine the ideal analogue and digital precoding matrices the channel state information has to be estimated. This estimation process is hampered by the electrical interconnection of different antenna elements within the analogue beamforming network. Hence, a separation of the antenna elements of the subarrays in the digital domain is not possible. Furthermore, actual channel estimation methods for hybrid beamforming systems are based on beam training techniques, which suffer from long estimation times. To overcome these problems we developed a two-stage channel estimation method for subarraybased hybrid beamforming systems using sparse array estimations. In the first stage, only one antenna element of each subarray at the transmitter is active during the channel estimation, resulting in a sparse array estimation. To distinguish the transmitters at the receiver side the transmitters are separated in the frequency domain using different orthogonal frequency division multiplexing subcarriers. For recovering the full-dimensional channel matrix we present two algorithms. The first algorithm is based on a two-dimensional interpolation of the channel matrix, while the second algorithm uses multiple subsequent channel measurements. The presented estimation method enables thereby a direct determination of the channel matrix with only one or a few measurements.
Magnetic Core-Shell Nanoparticle Enhanced SPR Biosensor for Immunoassay

A magnetic-nanoparticle(Fe3O4@Au) enhanced SPR biosensor is presented. A large sensor response was measured in an immunoassay experiment detecting Interleukin 17A, which is 18 times higher than that for direct format and 3.5 fold higher than for traditional sandwich format.
Research on Anti-Jamming Technology of Chaotic Composite Short Range Detection System Based on Underdetermined Signal Separation and Spectral Analysis

The chaotic phase-modulated linear frequency modulation short-range detection system (CPLF-SrDS) is a new type of composite detection system. Compared with traditional methods, it benefits from the short-term randomness and long-term certainty of chaos and is more powerful in determining the distance. To design such a system, the key problem lies in robustly recovering the echo signal against externally suppressed interferences. Combining 4th-order cumulant and joint diagonalization, this paper first develops a new signal separation approach to realize an underdetermined separation of the echo signal and an interference signal from their mixture. Then, both bispectrum analysis and singular spectrum analysis are adapted to analyze the separated signals and extract their characteristic parameters. Furthermore, the GA-BP network is utilized to classify the echo and interference signals. Finally, the anti-interference analysis of this CPLF-SrDS is realized. The experimental results show the effectiveness of the proposed method in the presence of externally suppressed amplitude modulation (AM) interference and frequency modulation (FM) interference.
CPW-Fed Slot Antenna for Medical Wearable Applications

In this paper, a flexible antenna with a simple structure, small size (<inline-formula> <tex-math notation="LaTeX">$15mm\times 17mm\times 1mm$ </tex-math></inline-formula>), and light weight for medical wearable applications is proposed. The antenna consists of slot radiation elements fed by a coplanar waveguide structure and a floating ground. Flexible conductive cloth MKKTN260 is used to fabricate the antenna, while felt with good insulation is used as the substrate. The measured impedance matching bandwidth (<inline-formula> <tex-math notation="LaTeX">$\left |{ {S_{11} } }\right |$ </tex-math></inline-formula>less than −10dB) of the antenna is from 5.578 to 5.898GHz, which can cover the whole ISM 5.8GHz band (5.725–5.825GHz) and perform good wearable radiation characteristics. The floating ground structure and the interaction between slots make the antenna radiated efficiently (the measured peak realized gain is 4.85dBi at 5.8GHz) to the +Z direction, which is away from the human body. Meanwhile, without any specially designed reflecting structures, the specific absorption rate value is below the criterion set by the FCC and ICNIPR. The bending configurations are also studied for this antenna.
Carbon Orientation in the Diatom Phaeodactylum tricornutum: The Effects of Carbon Limitation and Photon Flux Density

Diatoms adapt to changing environmental conditions in very efficient ways. Among the mechanisms that can be activated, the reorientation of carbon metabolism is crucial because it allows the storage of energy into energy-dense molecules, typically lipids. Beside their roles in physiology, lipids are commercially interesting compounds. Therefore studies dealing with this topic are relevant for both basic and applied science. Although the molecular mechanisms involved in the reorientation of carbon metabolism as a response to a deficiency in nutrients such as nitrogen or phosphorus has been partially elucidated, the impacts of carbon availability on the implementation of the reorientation mechanisms remain unclear. Indeed, it has not been determined if the same types of mechanisms are activated under carbon and other nutrient deficiencies or limitations. The first aim of this work was to get insights into the physiological, biological and molecular processes triggered by progressive carbon starvation in the model diatom Phaeodactylum tricornutum. The second aim was to investigate the effects of the growth light intensity on these processes. For such a purpose three different photon flux densities 30, 300, and 1000 μmol photons m-2 s-1 were used. The results presented here demonstrate that under carbon limitation, diatom cells still reorient carbon metabolism toward either phosphoenolpyruvate or pyruvate, which serves as a hub for the production of more complex molecules. The distribution of carbon atoms between the different pathways was partially affected by the growth photon flux density because low light (LL) provides conditions for the accumulation of chrysolaminarin, while medium light mostly stimulated lipid synthesis. A significant increase in the amount of proteins was observed under high light (HL).
Substrate Integrated Waveguide based dual‐band bandpass filter using split ring resonator and defected ground structure for SFCW Radar applications

In this paper, we present a novel dual‐band highly selective bandpass filter using Substrate Integrated Waveguide (SIW) technology. Designed bandpass filter is a combination of SIW structure with high‐pass characteristic, single rectangular split ring resonators (SRRs) as parallel LC resonator & dumbbell‐ shaped defected ground structure (DGS) with band rejection characteristic. Here, designed filter has pass band with high rejection values of −15.24 dB and − 18.43 dB and the insertion loss of 0.250 dB and 0.361 dB at 6 GHz and 8.55 GHz respectively. Designed SIW based dual‐band bandpass filter has 3‐dB fractional bandwidth (FBW) of 2.85% and 2.22% at 6GHz and 8.55 GHz respectively. The physical dimension of proposed structure is of 42 mm x 21 mm (1.77 λg x 0.88 λg). All the simulations and optimizations of the proposed structure are carried out in the Ansoft HFSS (high frequency structure simulator) software based on the finite element method. In order to verify the functionality of the proposed filter, structure is fabricated and tested.
Optimal scheduling of smart reconfigurable neighbour micro‐grids

Future smart distribution networks will include micro-grids (MGs) that are working in the neighbourhood. Owing to the penetration of renewable energy sources with probabilistic nature as well as deviation of load, MG may be faced with an overload or surplus power. The solution of this problem is to create and control a link between neighbour MGs for power exchange management. This study proposed a new framework for the optimal scheduling of smart reconfigurable neighbouring micro-grids (NMGs). Reconfiguration by managing the connection between MGs, through the opening and closing switches, finds the optimal structure of NMGs. Connectivity between NMGs is intended in two levels. In the first level, each MG can connect to adjacent MGs and exchange power, separately and without common area connection. In the second level, NMGs through a common area and opening or closing switches that couple them to the substrate can exchange power together. The objective of the study is to minimise load shedding of NMGs that are facing with power deficiency. The final structure selection is based on two different criteria (power loss in interconnection switches and reliability) point of view. The proposed method implemented on five NMGs system and numerical results show the effectiveness of the proposed NMGs optimal scheduling.
Network Traffic Threat Feature Recognition Based on a Convolutional Neural Network

This paper presents a novel algorithm for recognizing threats from communication network traffic features based on a Convolution Neural Network (CNN). The CNN extracts higher-dimensional network features from the network traffic dataset by deepening the number of its convolution layers. The transfer learning method with Principal Component Analysis (PCA) is applied for the CNN training. The transfer learning method trains the CNN initially with a small amount of dataset, and then it trains the network with the complete dataset. The PCA is a technique for analyzing, and simplifying dataset, and it often used to reduce the dimensionality of the dataset. The experimental results showed that the presented system could be an effective way for recognizing threats from a communication network.
Adaptive Fault-Tolerant Control for a Flexible Manipulator of Output-Constrained

Adaptive fault-tolerant control of actuator partial failure for a flexible manipulator with bounded disturbance and output constraints is proposed in this paper. The control laws are designed by the backstepping technique. , and the bounded disturbance is compensated via introducing a robust item. The Barrier Lyapunov Function is presented to prevent the output constraint violation. The stability of the closed-loop system is guaranteed via the Lyapunov method. Finally. , the effectiveness and rationality of the control scheme is finally verified by the simulation results.
On the Effectiveness of Standard Centrality Metrics for Interdependent Networks

This paper investigates the effectiveness of standard centrality metrics for interdependent networks (IDN) in identifying important nodes in preventing catastrophic failure propagation. To show the need for designing specialized centrality metrics for IDNs, we compare the performance of these metrics in an IDN under two different scenarios: i) the nodes with highest centrality of networks composing an IDN are selected separately and ii) the nodes with highest centrality of the entire IDN represented as one single network are calculated. To investigate the resiliency of an IDN, a threshold-based failure propagation model is used to simulate the evolution of failure propagation over time. The nodes with highest centrality are chosen and are assumed to be resistant w.r. t failure. Extensive simulation is conducted to compare the usefulness of standard metrics to stop or slow down the failure propagation in an IDN. Finally a new metric of centrality tailored for interdependent networks is proposed and evaluated. Also, useful guidelines on designing new metrics are presented.