Miracle-dz/UniFAR-FTUs huggingface dataset:
A Clustering-based Approach for Topic Modeling via Word Network Analysis

This paper presents a clustering-based approach to topic modeling via analyzing word networks based on the adaptation of a community detection algorithm. Word networks are constructed with different word representations, and two types of topic assignments are introduced. Topic coherence score and the document clustering results are reported for topic model evaluation. Experimental results showed that it achieved comparable results with the current best. It also showed that the proposed approach produced a higher performance as the number of most relevant words gets larger in $C_{cv}$ coherence score.
Real-Time OF-based Trajectory Control of a UAS Rotorcraft Based on Integral Extended-State LQG

The actual paper proposes a robust optimal control strategy via an Extended-State Integral Linear Quadratic Gaussian (ES-iLQG) controller meant to drive the quadrotor motion to track a time-parametrized trajectory in presence of exogenous and endogenous disturbances. The herein enhanced LQG controller, includes an Extended-State Linear Kalman Filter (ES-LKF) utilised as a disturbance estimator, and an integral Linear Quadratic Regulator (iLQR). Results from a simulation stage exhibit the effectiveness of the proposed control scheme for trajectory tracking purposes. In this regard, promising experimental results were obtained from two scenarios: Trajectory tracking of an elliptical helix-shaped and an 8-shaped trajectories. It is noteworthy that the control law is computed onboard and relies on optical flow for translational motion control.
Analysis of Distributed Energy Storage as a Core Grid Infrastructure via Production Cost Modeling

Energy storage plays a pivotal role in enabling power system operation with more flexibility and resilience. Unlike current practice that considers energy storages as attached ancillary devices, this paper focuses on storages as a core infrastructure by looking at their spatial distribution in the system. A sensitivity analysis based on production cost modeling is conducted to demonstrate the benefits of distributed energy storages. First, the modeling of energy storages in production cost modeling is presented. Second, potential optimal locations of distributed energy storages in a power system are discussed. Finally, multiple scenarios with various numbers and locations of additional distributed energy storages in the WECC 2030 model are created. The production cost modeling results of these scenarios show that distributed energy storages have higher utilization compared to the centralized ES units and therefore provide significantly more benefits in terms of reduction in generation cost, emission cost, and volatility of location marginal prices. A saturation effect is observed suggesting the selection of optimal locations will further improve the benefits.
Exposure modelling to child's and adult's chest to EMF inside shielded areas

The effects of electromagnetic (EM) fields on a model of a child's and adult's chest in the shielded areas of a cellar and the compartment of a railway wagon are discussed in this work. Electromagnetic modeling based on the Finite Integration approach was used in this study. The simulations were run for a specific scenario in which the individual models were positioned in various shaded areas as close to the EM radiation source as possible. A PIF A antenna operating at 900 and 1800 MHz provided the radio frequency source for the EM field. The results were examined in terms of SAR values by measuring the absorption of EM radiation inside the chests of a toddler and an adult. The SAR values for the child chest model were higher than for the adult chest model, according to the results.
Sur les A [infini]-catégories

Nous etudions les A-infini-algebres Z-graduees (non necessairement connexes) et leurs A-infini-modules. En utilisant les constructions bar et cobar ainsi que les outils de l'algebre homotopique de Quillen, nous decrivons la localisation de la categorie des A-infini-algebres par rapport aux A-infini-quasi-isomorphismes. Nous adaptons ensuite ces methodes pour decrire la categorie derivee DA d'une A-infini-algebre augmentee A. Le cas ou A n'est pas muni d'une augmentation est traite differemment. Neanmoins, lorsque A est strictement unitaire, sa categorie derivee peut etre decrite de la meme maniere que dans le cas augmente. Nous etudions ensuite deux variantes de la notion d'unitarite pour les A-infini-algebres : l'unitarite stricte et l'unitarite homologique. Nous montrons que d'un point de vue homotopique, il n'y a pas de difference entre ces deux notions. Nous donnons ensuite un formalisme qui permet de definir les A-infini-categories comme des A-infini-algebres dans certaines categories monoidales. Nous generalisons a ce cadre les constructions fondamentales de la theorie des categories : le foncteur de Yoneda, les categories de foncteurs, les equivalences de categories. Nous montrons que toute categorie triangulee algebrique engendree par un ensemble d'objets est A-infini-pretriangulee, c'est-a-dire qu'elle est equivalente a H^0 Tw A, ou Tw A est l'A-infini-categorie des objets tordus d'une certaine A-infini-categorie A. Nous demontrons ainsi une partie des enonces d'algebre homologique presentes par M. Kontsevich pendant son cours ``Categories triangulees et geometrie'' a l'ENS en 1998.
On-orbit Calibration of ACS CTE Corrections for Photometry

ABSTRACT We present the first on-orbit calibration of the photometric losses due to imperfect CTE on ACS HRC and WFC. We utilized images of 47 Tuc from a CTE calibration program (GO 9648; PI Riess) to measure the dependence of stellar photometry on the number of parallel and serial transfers. For WFC, photometric losses are apparent for stars undergoing numerous parallel transfers (y-direction) and are ~1-2% for typical observing parameters rising to ~10% in worst cases (faint stars, low background). The size of the photometric loss appears to have a strong power-law dependence on the stellar flux, as seen for other CCD’s flown on HST. However, the dependence on background is surprisingly weak implying that post-flashing may have little advantage to mitigate CTE. No losses are apparent for WFC due to serial transfer (x-direction). Also for HRC, photometric losses arise from parallel transfer (~1% for typical observations, ~5% for worst case) but are not seen for serial transfer. Correction formulae are presented to correct photometric losses as a function of a source’s position, flux, background, time, and aperture size. The time dependence term will be better constrained from future data but is currently found to be approximately linear from measurements of charge deferred tails in dark frames.
Probability Correlation Learning for Anomaly Detection based on Distribution-Constrained Autoencoder

Network anomaly detection provides a reliable and stable service to detect faults and prevent security attacks effectively. However, existing detection methods still encounter many challenges. The supervised learning method is unsuitable because the anomaly samples are seriously sparse and hard to label. Unsupervised learning, as a promising method, is widely used while the discriminative features are ignored when reconstructing from the normal feature space. This paper proposes a novel probability correlation learning based on autoencoder called PCDetect, a semi-supervised learning method. Since we assumed the anomaly samples deviate from the distribution of normal samples, approximating the distribution of original data is proposed as an efficient preprocessing methodology to capture the discriminative features. Moreover, an encoder-decoder neural network associated with the proposed loss function is designed to learn the low-dimensional feature representation from raw data and constrain the latent representation to follow different referenced distributions based on a few anomaly labels. In this way, The correlation of the referenced distribution and the reconstruction of latent representation will be used to quantify the probability of anomaly. Extensive experiments are conducted on two public real-world datasets, NSL-KDD and UNSW-NB15. Results show the proposed PCDetect can efficiently cope with the imbalance and high-dimensional issues compared with several popular supervised learning methods, significantly improve the accuracy, and reduce the false rate as a whole compared with unsupervised learning.
Leader-Follower Based Two-AGV Cooperative Transportation System in 5G Environment

Cooperative transportation of large objects with a multi-AGV system is of great economic and practical significance. How to ensure the synchronized motion of the multiple AGVs, which are connected to each other by carriers, is the most critical and also the most difficult problem. In this paper, we propose a motion planning and control method for a cooperative transportation system, which consists of a carrier and two AGVs communicating with each other in 5G environment. In order to maintain a required constant distance between two AGVs during the movement, a leader-follower formation strategy based approach with the follower tracking the leader in real time is used. Specifically, the reference trajectory of the follower is calculated by the real-time trajectory of the leader. Then a tracking controller is designed for the follower so that it can follow the target trajectory. Experiments in 5G environment with actual industrial AGVs show that the proposed approach can ensure a smooth transportation motion and the maximum error of distance controlling of the two AGVs is within ±3cm.
Separating Simultaneous Seismic Sources using Robust Inversion of Radon and Migration Operators

The advent of high density 3D wide azimuth survey configurations has greatly increased the cost of seismic acquisition. Simultaneous source acquisition presents an opportunity to decrease costs by reducing the survey time. Source time delays are typically long enough for seismic reflection energy to decay to negligible levels before firing another source. Simultaneous source acquisition abandons this minimum time restriction and allows interference between seismic sources to compress the survey time. Seismic data processing methods must address the interference introduced by simultaneous overlapping sources. Simultaneous source data are characterized by high amplitude interference artefacts that may be stronger than the primary signal. These large amplitudes are due to the time delay between sources and the rapid decay of seismic energy with arrival time. Therefore, source interference will appear as outliers in denoising algorithms that make use of a Radon transform. This will reduce the accuracy of Radon transform de-noising especially for weak signals. Formulating the Radon transform as an inverse problem with an L1 misfit makes it robust to outliers caused by source interference. This provides the ability to attenuate strong source interference while preserving weak underlying signal. In order to improve coherent signal focusing, an apex shifted hyperbolic Radon transform (ASHRT) is used to remove source interferences. ASHRT transform basis functions are tailored to match the travel time hyperbolas of reflections in common receiver gathers. However, the ASHRT transform has a high computational cost due to the extension of the model dimensions by scanning for apex locations. By reformulating the ASHRT operator using a Stolt migration/demigration kernel that exploits the Fast Fourier Transform (FFT), the computational efficiency of the operator is drastically improved.
Bridging Scenarios in Reinforcement Learning with Continuously Generated Relaying Predictive Models

Transfer learning is an effective way to reduce expensive interactions with the physical environment in reinforcement learning (RL). Based on the correlation between scenarios, both the prior policy and historical experiences collected in the source domain may help to accelerate policy optimization in the target domain. However, without setting proper relaying scenarios, the discrepancy between domains may lead to sub-optimal policies or even negative transfer. In this paper, we firstly propose a continuously generated relaying predictive model (CRPM), which autonomously bridges the source domain and target domain with a series of gradually modi ed relaying scenarios. Then, we experimentally show that CRPM effectively reduces interactions required for policy optimization in the target domain. Besides, we combine CRPM with model-based RL, which further improves the performance. The CRPM also helps to improve the classical model-free algorithm by considering it as a particular case of transfer learning in the same domain. Experimental results show that CRPM helps to avoid sub-optimal policies and outperforms other algorithms in both the source and target scenarios.
Game-Theoretic Sectoral Demand Response Procurement in Multi-Energy Microgrid Planning

Multi-energy community microgrids (MGs) have been recognized as key enablers for harnessing distributed demand-side flexibility resources, especially when integrating storage. However, the literature on demand response-integrated community energy system design and dispatch optimization has, thus far, failed to concurrently maximize the flexibility potential in several energy carriers, thereby neglecting the potentially significant improvement opportunities of the associated business cases. In response, this paper introduces a novel Nash bargaining-based cooperative game approach for the optimal aggregator-mediated demand response scheduling of multi-energy community MGs serving electricity and thermal loads, as well as hydrogen as a transportation fuel. More specifically, the proposed approach systematically and effectively characterizes how the players share the resulting surplus from demand-side management in an equitable manner under the assumption that the interests of the players - the MG operator, sectoral demand response aggregators, and small-scale end-users - are neither completely opposed nor completely coincident. The proposed approach is then integrated into a meta-heuristic-based long-term MG planning method. A case study for a community-based residential users' aggregation scheme in Aotearoa-New Zealand demonstrates the effectiveness of the method in reducing the total discounted system cost of a multi-energy MG by ~14% (equating to US$1.9m) and ~31% (US$5.4m) respectively compared to the cases where: (i) the actors' behaviors are characterized using non-cooperative game theory under self-interestedness assumptions; and (ii) no demand response programs are implemented.
Multiwavelength Study of the Nebula Associated with the Galactic LBV Candidate HD 168625

We present high-resolution HST imaging of the nebula associated with the Galactic luminous blue variable candidate HD 168625, together with ISO imaging and Anglo-Australian Telescope echelle spectroscopy. The overall nebular morphology is elliptical, with the major axis at P.A. ≃ 120°. The dimensions of the nebula are 12″ × 16. ″7 at Hα and 15. ″5 × 23. ″5 at 4 μm. In the HST Hα image the nebula is resolved into a complex structure of filaments and arcs of different brightness. The asymmetry is lost in the HST continuum image, where the nebula appears more diffuse and richer in filaments and clumps with the shape of cometary tails. At 11.3 μm the nebular emission peaks in two diametrically opposite lobes located on the nebula boundaries and along its major axis. A very faint loop is also visible at optical wavelengths north and south of the shell. We suggest that the nebula is an ellipsoid with projected sizes of 14″ and 9″ (0.19 pc × 0.12 pc) along the right ascension and declination directions, respectively. This ellipsoid is expanding at 19 km s-1 and is dynamically as old as ≃4800 yr; it probably interacts with the stellar wind and the loop so that polycyclic aromatic hydrocarbon emission is detected from its caps, i.e., the lobes seen in the ISO images. The chemistry of the loop suggests that it is composed of unprocessed material, probably from the local interstellar medium swept by the stellar wind.
Droop-Free Distributed Frequency Control of Hybrid PV-BES Microgrid with SOC Balancing and Active Power Sharing

In this paper, we propose a droop-free distributed frequency control for the hybrid photovoltaic and battery energy storage (PV-BES) based microgrid. A distributed state of charge (SOC) balancing regulator achieves balanced SOC among the distributed generators (DGs) with BES utilizing a distributed average SOC estimator and the power sharing regulator ensures proportional power sharing among the PV-BES based DGs. These regulators generate two frequency correction terms which are then added to the microgrid rated frequency to generate references for the lower level controllers. The performance of the proposed distributed control is validated through real-time simulations in OPAL-RT, which demonstrates the effectiveness of the proposed control in achieving frequency regulation, SOC balancing, and active power sharing in the hybrid PV-BES units under both islanded and grid-connected operation modes.
Experimental detection of active defects in few layers MoS2 through random telegraphic signals analysis observed in its FET characteristics

Transition-metal dichalcogenides (TMDs), such as molybdenum disulfide (MoS2), are expected to be promising for next generation device applications. The existence of sulfur vacancies formed in MoS2, however, will potentially make devices unstable and problematic. Random telegraphic signals (RTSs) have often been studied in small area Si metal-oxide-semiconductor field-effect transistors (MOSFETs) to identify the carrier capture and emission processes at defects. In this paper, we have systemically analyzed RTSs observed in atomically thin layer MoS2 FETs. Several types of RTSs have been analyzed. One is the simple on/off type of telegraphic signals, the second is multilevel telegraphic signals with a superposition of the simple signals, and the third is multilevel telegraphic signals that are correlated with each other. The last one is discussed from the viewpoint of the defect–defect interaction in MoS2 FETs with a weak screening in atomically confined two-dimensional electron-gas systems. Furthermore, the position of defects causing RTSs has also been investigated by preparing MoS2 FETs with multi-probes. The electron beam was locally irradiated to intentionally generate defects in the MoS2 channel. It is clearly demonstrated that the MoS2 channel is one of the RTS origins. RTS analysis enables us to analyze the defect dynamics of TMD devices.
An optimized semi-empirical physical approach for satellite-based PM2.5 retrieval: embedding machine learning to simulate complex physical parameters

Abstract. Satellite remote sensing of PM2.5 (fine particulate matter) mass concentration has become one of the most popular atmospheric research aspects, resulting in the development of different models. Among them, the semi-empirical physical approach constructs the transformation relationship between the aerosol optical depth (AOD) and PM2.5 based on the optical properties of particles, which has strong physical significance. Also, it performs the PM2.5 retrieval independently of the ground stations. However, due to the complex physical relationship, the physical parameters in the semi-empirical approach are difficult to calculate accurately, resulting in relatively limited accuracy. To achieve the optimization effect, this study proposes a method of embedding machine learning into a semi-physical empirical model (RF-PMRS). Specifically, based on the theory of the physical PM2.5 remote sensing (PMRS) approach, the complex parameter (VEf, a columnar volume-to-extinction ratio of fine particles) is simulated by the random forest (RF) model. Also, a fine-mode fraction product with higher quality is applied to make up for the insufficient coverage of satellite products. Experiments in North China (35∘–45∘N, 110∘–120∘E) show that the surface PM2.5 concentration derived by RF-PMRS has an average annual value of 57.92 µg m−3 vs. the ground value of 60.23 µg m−3. Compared with the original method, RMSE decreases by 39.95 µg m−3, and the relative deviation is reduced by 44.87 %. Moreover, validation at two Aerosol Robotic Network (AERONET) sites presents a time series change closer to the true values, with an R of about 0.80. This study is also a preliminary attempt to combine model-driven and data-driven models, laying the foundation for further atmospheric research on optimization methods.
A Dynamic Association Strategy for Controller Load Balancing in Software-Defined Networks

Software-defined networks have been widely used in information infrastructure deployment due to the programmability adapting to the flexible changing of network requirements. Distributed multi-controller architecture enhances the scalability and reliability of SDN. Static association between controllers and switches cannot adapt to the change of loads on controllers. In this paper, a dynamic association strategy is proposed, which takes controller load balancing and the request overhead of switch as the optimizing goals. An improved Hungarian algorithm is utilized to adjust the association. Then Nash equilibrium is used in further optimization. This strategy can keep a small volume of controllers and switches involved in adjustment, saving network link and time costs, while reaching the load re-balance of controllers. Experiments show that it achieves satisfactory load balancing between controllers in various topologies, and has good scalability and performance in large-scale networks.
The Casimir effect

The purpose of these lecture notes is twofold. First we aim at introducing the reader to the basic concepts pertaining to Casimir forces, starting from the seminal work of Casimir. In a broader sense, we also review some aspects of dispersion forces, in particular the status of van der Waals forces in vacuum as well as in a finite density and non zero temperature medium. The Lifshitz theory of forces between dielectric bodies is briefly described. In the second place, the course deals with a more recent analysis of the Casimir force for metals based on an exact microscopic statistical mechanical treatment of matter and field fluctuations. It reveals that charges fluctuations inside the conductors cannot be ignored (as is done in the conventional Casimir calculation). It also helps clarifying present day controversies about the contribution of thermal fluctuations to the force and the proper way to recover the metallic case in the framework of the Lifshitz theory. Finally the occurrence of Casimir forces in critical phenomena is illustrated in the case of the Bose–Einstein condensation in a free Bose gas. The Casimir effect in other contexts (general quantum field theory, particle physics, cosmology, …) is not considered here.
A Reconfigurable Metal Rim Antenna With Smallest Clearance for Smartphone Applications

In this paper, a reconfigurable metal rim antenna with a small clearance and compact structure for 4G/5G smartphones is proposed. It consists of the system ground plane and a metal rim with two slits, in which a U-shaped slot of 1 mm (the smallest) clearance is realized between the system ground and metal rim. The theory of characteristic modes is applied to analyze the eigenmodes of the antenna so as to aid the optimum design. The characteristic modes (CMs) in the band of interest are studied, and an inductive coupling exciter is identified as the best since three CMs can therefore be generated in the lower frequency band (0.69-0.96 GHz), and an SP4T switch can be utilized to increase the bandwidth of the whole lower band. A prototype antenna of the optimized design was fabricated. A good agreement was obtained between the measured and simulated results. The 6-dB frequency bands are the lower band (0.69-0.96 GHz), the middle band (1.7- 2.7 GHz), and the higher 5G band (3.4- 3.6 GHz), respectively, and the total efficiencies are over 50% in all these frequency bands. They indicate that the antenna is a very good candidate for smartphone applications.