Miracle-dz/UniFAR-FTUs huggingface dataset:
Memory, attention and prediction: a deep learning architecture for car-following

Car-following (CF) models are an appealing research area because they fundamentally describe the longitudinal interactions of vehicles and contribute substantially to an understanding of traffic flow. In this study, by combining numerous deep neural network structures to mimic the memory, attention and prediction (MAP) mechanisms of real drivers, a deep learning-based car following model named MAP is built. The proposed MAP learned CF behaviour from real-world datasets. Experiments on predicting future driving behaviour show that the MAP model with memory, attention and prediction mechanisms outperforms models without those mechanisms. Several analysis are conducted to understand the MAP model, and quantitatively provides some explanations of how MAP achieves the CF behaviour. A simulation is also presented and explicitly analysed. The results show that the proposed approach can produce space-time diagrams similar to real traffic. The analysis also shows that the supervised learning models generate the most likely, rather than the best, CF behaviour.
Collector System Topology for Large-Scale Offshore Wind Farms Considering Cross-Substation Incorporation

Double-sided ring topology has been widely applied in collector system planning for large-scale offshore wind farms (OWF), owing to its high reliability against cable faults. For collector systems with multiple substations, the conventional topology designs isolate the operation of substations, which requires high transformer capacity within each substation to satisfy the redundancy need. This paper first investigates the economic and reliability benefits of multi-substation incorporation (CSI), and then proposes a new double-sided ring topology with CSI for large-scale OWF collector systems. It encourages the transformer capacity sharing among multiple substations to improve the economic efficiency of collector system and in the meantime preserve the reliability advantage of ring topology. To achieve the optimal topology design, Fuzzy C-means (FCM) clustering method is adopted to locate substations and allocate turbines, and the Two-Phase Clark and Wright's saving algorithm is modified and applied to optimize the cable connection for the proposed topology so as to minimize the overall collector system cost. The proposed topology is tested and compared with traditional isolated topologies on two benchmark collector systems. The test results verify that the proposed the highest economic efficiency while maintaining the collector system reliability.
Bird's-eye View Image Generation with Camera Malfunction in Irradiation Environment

The Fukushima Daiichi nuclear accident occurred in 2011. Since then, many people have been committed to realizing the plant’s decommissioning. The investigation of the plant is necessary in the process of the decommissioning, however, there are a large amount of radioactive places that are dangerous for human. In a situation as described above, investigation by teleoperated robots are highly demanded [1, 2]. Nagatani et al. conducted gamma irradiation tests for the electric components of their robot and described that the components have enough radiation tolerance to be used for more than 100 h at a 10% safety margin in the assumed environment (100 mGy/h) [2]. In the future process of the decommissioning, there is a possibility of investigating in a tremendous high dose radiation environment where electric devices could malfunction within hours. Therefore the systems used there need to be fault tolerant, working properly even when some of its components have failed. When operators teleoperate robots at remote places, it is difficult to do their work with efficiency and accuracy. One of the techniques to solve this issue is the use of a bird’s-eye view system. It is a system generating the virtual third person view image which shows the robot and the surroundings from the top (Fig. 1). It helps operators understand relations between the robots and their surroundings and teleoperate them accurately [3]. A fault tolerant bird’s-eye view system has been proposed by our group [4]. The proposed system is based on the hypothesis that cameras attached to the system have malfunction one by one, and it can display bird’s-eye view images even though only one camera works well. In this study, a gamma irradiation experiment for our proposed system was conducted. Experimental results show that cameras attached to the system malfunctioned one by one, and that is effective for the teleoperation in the irradiation environment.
Application of the Digital Image Correlation Method to the Identification of Landslides

History shows that most earthquakes, which cause serious disaster, are induced by recent movement of faults. For example, the Chichi earthquake, happened on September 21 1999, has a magnitude of 7.3 and leaded to a great loss of lives and properties. The cause of this earthquake is the movement of the Chelungpu fault. The massive earthquake not only destroys the houses and roads, but also induces the landslides. Not only the earthquake but also the typhoon or heavy rainfall can induce the landslides. Because the destruction occurred mostly in remote areas, coupled with the traffic system disruption, the investigation and relief are very difficult. Digital image correlation (DIC) technique is a non-contact-type optical measurement technique. The progress of digital camera and the fast development of the computer calculation capability cause the digital image correlation technique widely applied to different research fields [1-6]. The landslides will change the appearance of the ground surface and the satellite image is already widely used in the remote sensing technology, therefore we can use the DIC method and the satellite image to monitor the occurrence of landslide. To determine the occurrence of landslides by comparing satellite images is mainly to find out the position, where correlation between two images is low. Although the algorithm of digital images correlation is to find out the highest correlation, it can be slightly modified to agree with our purpose. In this study, digital image correlation and satellite images are used to identify the occurrence of landslides. A preliminary results of automatic landslides identification are achieved by using DIC. NDVI (Normalized Difference Vegetation Index) and DEM (Digital Elevation Model) are also applied to reduce the misidentification rate.
Multi-Fidelity Physics-Constrained Neural Network and Its Application in Materials Modeling

Training machine learning tools such as neural networks require the availability of sizable data, which can be difficult for engineering and scientific applications where experiments or simulations are expensive. In this work, a novel multi-fidelity physics-constrained neural network is proposed to reduce the required amount of training data, where physical knowledge is applied to constrain neural networks, and multi-fidelity networks are constructed to improve training efficiency. A low-cost low-fidelity physics-constrained neural network is used as the baseline model, whereas a limited amount of data from a high-fidelity physics-constrained neural network is used to train a second neural network to predict the difference between the two models. The proposed framework is demonstrated with two-dimensional heat transfer, phase transition, and dendritic growth problems, which are fundamental in materials modeling. Physics is described by partial differential equations. With the same set of training data, the prediction error of physics-constrained neural network can be one order of magnitude lower than that of the classical artificial neural network without physical constraints. The accuracy of the prediction is comparable to those from direct numerical solutions of equations.
A bistable piezoelectric harvester for wideband mechanical frequency excitation.

The developments of autonomous systems as for the self health monitoring, embedded systems are increasingly used in industrial applications. The energy supply is a key point for the development of such systems. Solutions based on battery are life time limited and the power supply trough wires aren't always appropriate and easy to install. The researches on power supply through harvesting systems are increasing in the same way as the autonomous systems. The researches on this fields progress in two ways: the mechanical structure and the electrical circuit. The paper focuses on the mechanical structure of the harvesting systems. A structure based on bistable configuration is presented. Usually, bistable systems are based on magnetic interaction or buckled beams. The proposed solution is abuckled spring-mass (BSM) harvesting solution using amplified piezoelectric actuators (APA®). The description of the architecture and the concept are presented in the first part of this document. In the second part, the presentation of the BSM first prototype based on standard product (APA120S®) is given and described. The second prototype based on APA50μXS® has been designed and modelled. The chirp and band-imited noise excitations are used to evaluate the proposed harvester's performances.
AND/OR trees for the learning of functional logic programs

¥ ¦H§. ̈%©a« ̈ ¬y­ ̄®±°2 ́3OμR¶Uμ ̧·. 1oo1⁄4»1⁄2· μ1x·o3}·o­A®{®±°S·3⁄42À¿ÁμRÂÀ·o¿Á·o­A®±¶U®±2ÀÃ? ­ ̄ÃÄ6¶ ¿Á·. ®±°SÃaÅ1ÄÃ1 Æ·o­S·. 1x¶U®±2 ́­SÆ Ç ·. 1±ÈÉ·~Ê μ1x·o3±3±2 Ç ·ËÅS·oÌ. 2 ́3±2ÍÃ? ­É®}1±·. ·o3ÎÃ Ç ·. 1 ¶ÏÄ¢Ð­Ì~®±2ÀÃ? ­¶Â ÂÍÃÆ? 2ÀÌÁÂÀ¶­SÆ? ÐR¶UÆ·Ñ3⁄4ÒO°S·Ë¿Á·. ®±°SÃaÅ 2À3 ÓR¶3}·oÅÔÃ? ­ 3}· Ç ·. 1¶Â μR¶U1±®±2Í®±2ÀÃ? ­35»-°2ÀÌx°Ô¶ÂÀÂÀÃ%»ÕÐ3 ®±°S· 2À­RÅÐÌ~®±2ÍÃ? ­ÖÃÄ×­S·o3±®}·oÅ ¶­Å 1±·oÌ. ÐS1x3x2 Ç ·ÓR¶Ì±Ø Æ1±Ã? Ð­ÅËØ ­SÃE»OÂÍ·oÅSÆ·Ñ Ò °S·MÌ~Ã? ­3±®}1xÐÌ~®±2ÍÃ? ­3⁄4ÃÄ ®±°S·-Å·oÌ. 2À3±2ÍÃ? ­5®}1±·. ·{2 ́3"Æ? Ð2ÀÅ·oÅ5¶Ì. Ì~Ã1xÅ2 ́­SÆÙ®}Ã×®±°S·{Ú1Û ÜÝμ1x2À­RÌ. 2ÍμRÂÍ·ÑßÞ-·o­Ì~·oa®±°S· 3}·o¶U1xÌ° 3}μR¶Ì~· 2À31⁄2Ì~Ã Ç ·. 1±·oÅÏ2À­ ¶×3±°SÃ1±®yàC®}ÃUàáÂÍÃ? ­Æ×Ä¢¶3±°2ÀÃ? ­vÑ Ú ̄Ã1±·. Ã Ç ·. 1ooR¶×¿ ÐÂÀ®±2ÍμRÂÍ· ÅS·oÌ. 2 ́3±2ÍÃ? ­(®}1±·. · 2À3"ÃÓR®±¶2À­S·oÅË1¶U®±°S·. 1h®±°R¶­5¶×3±2À­SÆ? ÂÍ·M®}1x·. ·Ñ"â'·{3x°SÃ%»ã®±°¶U®h®±°·-¿Á·. ®±°SÃaÅ52 ́363±Ð2À®±¶UÓRÂÍ· Ä]Ã1 Ì. ÂÀ¶3±3±2ÀäRÌ. ¶U®±2ÍÃ? ­ μ1±ÃÓ>ÂÍ·o¿Ë3. Ñ å ̄æçvè3⁄4é ©êX§ë Û-·oÌ. 2 ́3±2ÍÃ? ­ìÒß1x·. ·o3.o ¬y­ÅÐRÌ~®±2 Ç ·$íRÐ­Ì~®±2ÍÃ? ­¶Â3⁄4ÜßÃÆ? 2ÀÌVî61±ÃÆ1x¶¿Ë¿52À­SÆ ï ¬Yí ÜXî1⁄2ðoß¬y­ÅÐRÌ~®±2 Ç ·5ÜlÃÆ? 2 ́Ì(î61±ÃÆ1x¶¿Ë¿Ë2 ́­SÆ ï ¬yÜßî1⁄2ðo Ú ̄2 ́­2À¿×Ð¿ÕÛ{·o3±Ì~1x2ÍμR®±2ÍÃ? ­ Ül·o­Æ®±° ï Ú ̄Û Ü ðÑ
Systematic Integration of Energy-Optimal Buildings With District Networks

The residential sector accounts for a large share of worldwide energy consumption, yet is difficult to characterise, since consumption profiles depend on several factors from geographical location to individual building occupant behaviour. Given this difficulty, the fact that energy used in this sector is primarily derived from fossil fuels and the latest energy policies around the world (e.g., Europe 20-20-20), a method able to systematically integrate multi-energy networks and low carbon resources in urban systems is clearly required. This work proposes such a method, which uses process integration techniques and mixed integer linear programming to optimise energy systems at both the individual building and district levels. Parametric optimisation is applied as a systematic way to generate interesting solutions for all budgets (i.e., investment cost limits) and two approaches to temporal data treatment are evaluated: monthly average and hourly typical day resolution. The city center of Geneva is used as a first case study to compare the time resolutions and results highlight that implicit peak shaving occurs when data are reduced to monthly averages. Consequently, solutions reveal lower operating costs and higher self-sufficiency scenarios compared to using a finer resolution but with similar relative cost contributions. Therefore, monthly resolution is used for the second case study, the whole canton of Geneva, in the interest of reducing the data processing and computation time as a primary objective of the study is to discover the main cost contributors. The canton is used as a case study to analyse the penetration of low temperature, CO2-based, advanced fourth generation district energy networks with population density. The results reveal that only areas with a piping cost lower than 21.5 k/100 m2ERA connect to the low-temperature network in the intermediate scenarios, while all areas must connect to achieve the minimum operating cost result. Parallel coordinates are employed to better visualise the key performance indicators at canton and commune level together with the breakdown of energy (electricity and natural gas) imports/exports and investment cost to highlight the main contributors.
Revealing evolved massive stars with Spitzer, WISE and SALT

We present the results of optical spectroscopic observations of 54 candidate evolved massive stars revealed through the detection of mid-infrared nebulae of various shapes surrounding them with the {\it Spitzer Space Telescope} and {\it Wide-field Infrared Survey Explorer}. These observations, carried out with the Southern African Large Telescope (SALT) in 2010-2015, led to the discovery of about two dozens emission-line stars, of which 15 stars we classify as candidate luminous blue variables (cLBVs). Spectroscopic and photometric monitoring revealed significant changes in the spectra and brightness of four newly identified cLBVs, meaning that they are new members of the class of bona fide LBVs. We present an updated list of the Galactic bona fide LBVs. Currently, this list contains eighteen stars, of which more than 70 per cent are associated with circumstellar nebulae. We also discovered a very rare [WN] star - the central star of the planetary nebula Abell 48, and a WN3 star in a close, eccentric binary system with an O6V star in the Large Magellanic Cloud - the first-ever extragalactic massive star identified via detection of a circular shell around it. Most of the remaining targets are tentatively classified as OB, A and M stars.
Influence of Slow-Paced Breathing on Inhibition After Physical Exertion

This research aims to investigate whether slow-paced breathing (SPB) improves adaptation to psychological stress, and specifically inhibition, when it is performed before or after physical exertion (PE). According to the resonance model, SPB is expected to increase cardiac vagal activity (CVA). Further, according to the neurovisceral integration model, CVA is positively linked to executive cognitive performance, and would thus play a role in the adaptation to psychological stress. We hypothesized that SPB, in comparison to a control condition, will induce a better adaptation to psychological stress, measured via better inhibitory performance. Two within-subject experiments were conducted with athletes: in the first experiment (N = 60) SPB (or control – neutral TV documentary) was realized before PE (“relax before PE”), and in the second experiment (N = 60) SPB (or the watching TV control) was realized after PE (“relax after PE”). PE consisted of 5 min Burpees, a physical exercise involving the whole body. In both experiments the adaptation to psychological stress was investigated with a Stroop task, a measure of inhibition, which followed PE. Perceived stress increased during PE (partial η2 = 0.63) and during the Stroop task (partial η2 = 0.08), and decreased during relaxation (partial η2 = 0.15), however, no effect of condition was found. At the physiological level PE significantly increased HR, RF, and decreased CVA [operationalized in this research via the root mean square of successive differences (RMSSD)] in both experiments. Further, the number of errors in the incongruent category (Stroop interference accuracy) was found to be lower in the SPB condition in comparison to the control condition, however, these results were not mediated by RMSSD. Additionally, the Stroop interference [reaction times (RTs)] was found to be lower overall in “relax before PE,” however, no effect was found regarding SPB and Stroop interference (RTs). Overall, our results suggest that SPB realized before or after PE has a positive effect regarding adaptation to psychological stress and specifically inhibition, however, the underlying mechanisms require further investigation.
Hand-Eye Calibration: 4-D Procrustes Analysis Approach

We give a universal analytical solution to the hand-eye calibration problem <inline-formula> <tex-math notation="LaTeX">${AX} = {XB}$ </tex-math></inline-formula> with known matrices <inline-formula> <tex-math notation="LaTeX">${A}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${B}$ </tex-math></inline-formula> and unknown variable <inline-formula> <tex-math notation="LaTeX">${X}$ </tex-math></inline-formula>, all in the set of special Euclidean group SE(3). The developed method relies on the 4-D Procrustes analysis. A unit-octonion representation is proposed for the first time to solve such a Procrustes problem through which an optimal closed-form eigendecomposition solution is derived. By virtue of such a solution, the uncertainty description of <inline-formula> <tex-math notation="LaTeX">${X}$ </tex-math></inline-formula>, being a sophisticated problem previously, can be solved in a simpler manner. The proposed approach is then verified using simulations and real-world experimentations on an industrial robotic arm. The results indicate that it owns better accuracy and better description of uncertainty and consumes much less computation time.
Robust Distributed Stabilization of Heterogeneous Agents Over Cooperation–Competition Networks

Distributed stabilization problem is investigated in this brief for a class of heterogeneous multi-agent systems (MASs) in the presence of exogenous disturbances and cooperation-competition interactions. Specifically, the dynamics of the heterogeneous agents are governed by the second-order systems with the nonlinear intrinsic dynamics where the heterogeneity of agents is mainly reflected in the following three aspects: the intrinsic dynamics of agents, the heterogeneous velocity damping terms, and the exogenous disturbances. With the assumption that the exogenous disturbances are bounded, a discontinuous distributed protocol associated with a time-varying estimator of the agent are designed. Then, with the help of the LaSalle-Yoshizawa theorem for nonsmooth system and the Barbalat’s lemma, it is proved that no matter whether the network topology is structurally balanced or not, the heterogeneous MASs can achieve robust distributed stabilization asymptotically as long as the control parameters of the distributed protocol are chosen appropriately. Finally, the derived analytical results are demonstrated by performing a numerical example.
Dual-band slot microstrip patch antennas with dual-radiation modes for wireless communication

Abstract In this paper, a novel compact dual-band microstrip patch antenna with dual-radiation modes is investigated. The proposed antenna consists of a rectangular ground plane, a U-shaped feed probe, and an H-shaped slot radiating patch. By adjusting the size of these structures, a dual-band antenna can be obtained. In the low-frequency band, the antenna can radiate one radiation beam with high gain. In the high-frequency band, the antenna can achieve monopole-like radiation pattern. Therefore, an antenna prototype is fabricated and measured for validation. Good agreement between the simulated and measured results is observed in this paper. The antenna's operating frequency ranges are 3.6–3.85 GHz in the low-frequency band and 5.1–6.1 GHz in the high-frequency band with the reflection coefficient less than −10 dB. At 3.7 GHz, the antenna radiate one beam with 8.8 dBi realized gain. At 5.5 GHz, it exhibits dual-radiation beams directed to −48 and 48° with 5.6 and 5.5 dBi realized gain in the xoz-plane and −48 and 48° with 2.9 and 3.0 dBi realized gain in the yoz-plane. Therefore, the proposed antenna is a good candidate for wireless communication systems.
The use of subsurface for thermal energy transport in district networks

This study introduces a new concept of ATES system, which is called ATEST system, to fulfill the transport function while crossing the barriers in water transmission and pipe replacements. Firstly, analytical models were used to help understand the physical process and range the working conditions of the ATEST system. Then numerical models were used to prove the feasibility and the value of this new conceptual system. Acceptable system performance that can meet the heat demand was iterated in case simulation; and the economical advantages were identified by comparing it with traditional ATES systems. The ATEST system showed a greater practical value than the ATES system in: 1) solving the discrepancy between heat service and heat demand in space, and 2) crossing barriers where pipes cannot be buried. However, the system should be further modified in operation to acquire better performance and avoid practical problems.
A Translation Evaluation Function based on Neural Network

In this paper, we study the feasibility of using a neural network to learn a fitness function for a machine translation system based on a genetic algorithm termed GAMaT. The neural network is learned on features extracted from pairs of source sentences and their translations. The fitness function is trained in order to estimate the BLEU of a translation as precisely as possible. The estimator has been trained on a corpus of more than 1.3 million data. The performance is very promising: the difference between the real BLEU and the one given by the estimator is equal to 0.12 in terms of Mean Absolute Error.
Active and reactive power control of hybrid offshore AC and DC grids

The future ‘SuperGrid’ may requires the benefit of both offshore AC network and multi-terminal DC grid. AC cable limits the power transfer capability from the larger offshore wind farm, however, HVDC transmission system is economical viable for large power wind farm integration with the grid. Another approach to develop the offshore network infrastructure is by forming an offshore AC grid connecting several offshore wind farms. Then, this offshore AC network is connected with different onshore grid using HVDC system. This enhances the trade among the countries as well as provide an economical solution for wind energy integration. In this article, operational and control concept of voltage source converter is presented to integrate an offshore AC grid with an offshore DC grid. The article presents the control principle of offshore AC network frequency and voltage with respect to active and reactive power distribution in the AC network. Later, the principle of multi-terminal HVDC system is discussed with respect to power distribution using DC voltage droop control. Power distribution criteria are defined with respect to operator power-sharing requirement and network stability. In the end, a hybrid AC/DC offshore grid is modelled and simulated in MATLAB/SIMULINK to validate the distribution criteria.
Three-Dimensional Topological States of Phonons with Tunable Pseudospin Physics

Efficient control of phonons is crucial to energy-information technology, but limited by the lacking of tunable degrees of freedom like charge or spin. Here we suggest to utilize crystalline symmetry-protected pseudospins as new quantum degrees of freedom to manipulate phonons. Remarkably, we reveal a duality between phonon pseudospins and electron spins by presenting Kramers-like degeneracy and pseudospin counterparts of spin-orbit coupling, which lays the foundation for “pseudospin phononics”. Furthermore, we report two types of three-dimensional phononic topological insulators, which give topologically protected, gapless surface states with linear and quadratic band degeneracies, respectively. These topological surface states display unconventional phonon transport behaviors attributed to the unique pseudospin-momentum locking, which are useful for phononic circuits, transistors, antennas, etc. The emerging pseudospin physics offers new opportunities to develop future phononics.