Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on fire risk assessment of subway operation based on fuzzy analytic hierarchy process

Fire is one of the most common accidents during subway operation. Once the fire risk is not reasonably controlled, it is very easy to cause serious casualties and property losses. In order to scientifically evaluate the fire risk level of subway operations and provide effective fire safety management measures for operating companies, this article systematically builds a four-tier system from the perspective of human factors, management factors, environmental factors, and equipment factors involved in subway operations. The subway operation fire risk evaluation index system is composed of three first-level indexes and 32 second-level indexes, and the weight of each index is calculated based on the analytic hierarchy process. Secondly, the fuzzy comprehensive evaluation method is used to give the calculation steps of the fire risk of subway operation. Finally, the model is used to conduct an empirical analysis of Metro Line 2 in a provincial capital city in Southwest China. It is concluded that the overall risk level of the subway line is level II, indicating that the fire risk of its operation is relatively small. The evaluation result is consistent with the actual operation of the subway line, indicating that the evaluation method has a certain applicability and effectiveness.
BBB: Simplifying Persistent Programming using Battery-Backed Buffers

Non-volatile memory (NVM) is poised to augment or replace DRAM as main memory. With the right abstraction and support, non-volatile main memory (NVMM) can provide an alternative to the storage system to host long-lasting persistent data. However, keeping persistent data in memory requires programs to be written such that data is crash consistent (i.e. it can be recovered after failure). Critical to supporting crash recovery is the guarantee of ordering of when stores become durable with respect to program order. Strict persistency, which requires persist order to coincide with program order of stores, is simple and intuitive but generally thought to be too slow. More relaxed persistency models are available but demand higher programming complexity, e.g. they require the programmer to insert persist barriers correctly in their program.We identify the source of strict persistency inefficiency as the gap between the point of visibility (PoV) which is the cache, and the point of persistency (PoP) which is the memory. In this paper, we propose a new approach to close the PoV/PoP gap which we refer to as Battery-Backed Buffer (BBB). The key idea of BBB is to provide a battery-backed persist buffer (bbPB) in each core next to the L1 data cache (L1D). A store value is allocated in the bbPB as it is written to cache, becoming part of the persistence domain. If a crash occurs, battery ensures bbPB can be fully drained to NVMM. BBB simplifies persistent programming as the programmer does not need to insert persist barriers or flushes. Furthermore, our BBB design achieves nearly identical results to eADR in terms of performance and number of NVMM writes, while requiring two orders of magnitude smaller energy and time to drain.
A Passive-Mixer-First Acoustic-Filtering Superheterodyne RF Front-End

This article presents an agile passive-mixer-first superheterodyne RF front-end that utilizes a gigahertz acoustic filter as its intermediate-frequency (IF) load—essentially a mixer-first acoustic-filtering RF front-end. The passive mixer frequency-translates a sharp but fixed-frequency acoustic-filtering response to a much higher and mixer-clock-defined tunable frequency while preserves input matching, high linearity, and introduces minimal loss. In contrast to low- or zero-IF passive-mixer-first receivers which often use active filters at baseband, using an acoustic filter as the IF load is fraught with fundamental challenges. We introduce ON-chip LC tanks, as an impedance shaper, to suppress the acoustic filter impedance components at harmonic frequencies and an all-passive recombination network at IF to share one acoustic filter among multiple paths. Also, we extend the existing analysis of mixer-first front-ends from assuming a load impedance with a low-pass frequency response to having a generic load impedance. Our analysis unveils impedance aliasing in a generic mixer-first front-end, motivating the need for an ON-chip impedance shaper. A front-end prototype using a 65-nm CMOS switched- LC passive mixer followed by an off-the-shelf 1.6-GHz surface-acoustic-wave (SAW) filter is designed. In measurement, the RF front-end operates across 2.5-to-4.5 GHz achieving 5.5-dB noise figure and +29.4-dBm IIP3 at 1 $\times $ bandwidth offset.
A Joint Detection-Classification Model for Weakly Supervised Sound Event Detection Using Multi-Scale Attention Method

Attention mechanism has been applied to the weakly supervised sound event detection (SED) and has achieved state-of-the-art performance, but most methods only concentrate along the time axis. In this paper, we propose the multi-scale time-frequency attention (MTFA) method to capture the intrinsic features at different scales both in time and frequency domain for audio tagging (AT) and SED. Our model is a unified network which can perform AT and SED simultaneously, it produces multi-scale attention-aware representations for SED with MTFA module, and a global pooling module maps the representations to presence probability of corresponding audio event for AT. To evaluate the proposed method, we conduct experiments on Task4 of Detection and Classification of Acoustic Scenes and Events (DCASE) challenge, and it achieves 57.9% (F1-score) in AT task and 0.71 (error rate) in SED task on evaluation set, which is comparable to the state-of-the-art results in the challenge.
Optimization of Economic Efficiency in Distribution Grids Using Distribution Locational Marginal Pricing

Distribution locational marginal pricing (DLMP) is an increasingly popular pricing signal that can be used to incentivize grid-friendly behavior of distributed energy resources (DER) to optimize economic efficiency in distribution grids. In this paper, a lossy direct-current optimal power flow (DCOPF) is utilized to obtain the iterative calculation framework for DLMPs. The two-stage algorithm iterates between the transmission system optimal power flow (OPF) and the distribution system OPF until no significant changes in DLMPs are observed. Real power losses are estimated using a static piecewise linear approximation technique. A sampling algorithm is proposed to minimize the possible convergence issues associated with the proposed mathematical model. DLMPs are calculated for the i) contemporary, ii) enhanced, and iii) meshed distribution grids using an IEEE 34-bus test feeder. The test transmission system is modeled using an IEEE 30-bus system. Finally, the calculated DLMPs in the enhanced grid are compared against three existing pricing mechanisms via three case studies to prove its validity and superiority, especially in congested systems with high penetration of price-responsive loads (PRLs).
Crossover Structure Separation With Application to Neuron Tracing in Volumetric Images

Morphology reconstruction of neurons from 3-D microscopic images is essential to neuroscience research. However, many reconstructions may contain errors and ambiguities because of the crossover neuronal fibers. In this article, an automatic algorithm is proposed for the detection and separation of crossover structures and is applied to neuron tracing for improving the neuron reconstruction results. First, a spherical-patches extraction (SPE)-Net is employed to detect the 3-D neuron crossover points and locate the crossover structures in neuron volumetric images. Second, a multiscale upgraded ray-shooting model (MSURS) is proposed to obtain robust results at different scales with high confidence and is employed to extract the crossover neuronal structure features. Then, a crossover structure separation (CSS) method is developed to eliminate the false connections of crossover structures and generate deformed separated neuronal fibers based on the extracted features to replace the original neurites signals. Experiments demonstrate that the SPE-Net for crossover point detection achieves average precision and recall rates of 73.89% and 79.66%, respectively, and demonstrate the proposed CSS method can improve 20.46% the performance of the reconstructions on average. The results confirm that the proposed method can effectively improve the neuron tracing results in volumetric images.
Object-Removal Forgery Detection Through Reflectance Analysis

While creating digital image forgeries, it is often necessary to hide an object from the image. For instance, to replace a person on a picture one would first remove the person on the image before inserting the new one. This process of suppression can be performed in many ways but almost always involve recreating some background textures. While recreating it, artists sometimes use common tools and apply smooth transitions to seamlessly blend the result. This operation can decrease the created texture sharpness. In this paper, we explore the possibility to reveal this effect to expose possible forgeries.
Autonomous Vehicles Scenario Testing Framework and Model of Computation: On Generation and Coverage

Autonomous vehicle (AV) technology started to shift the perception of the transportation systems. However, for AVs to operate at their optimum capabilities, they need to go through a comprehensive testing and verification process. While a large amount of research and funding has been provided for solving this problem, there is still a lack of a systematic method to develop standardized tests that can be used to judge if the decision-making capability functions are within acceptable parameters. To that end, the tests need to cover all possible situations that an AV may run into. This paper focuses on defining the notion of coverage mathematically when using pseudo-randomly generated simulations for testing. The approach defines new equivalence relations between scenes, which are the systems’ various states, to achieve this goal. Considering the substantial need for computation, even with the obtained coverage, we also introduce the mathematical definition of a sub-scene and additional strategies, such as expanding the equivalence classes of scenes and combining actors in scenes, to reduce the amount of testing required to certify AVs.
The diversity of the woody tree flora of Mont Sangbé National Park (west of the Ivory Coast)

The present study concerns the diversity of the woody tree flora of Mont Sangbe National Park (West of Cote d'Ivoire). The main objective was to analyze the diversity of the woody tree flora of this park impacted by human activities. Specifically, it involved (1) identifying the anthropogenic factors of the PNMS, sources of impact (2) assessing the impact of these activities on the diversity of the woody tree flora of the PNMS and (3) propose measures to mitigate biodiversity losses. To carry out the study, a device of 14 square blocks of 1 ha each was used on the impacted sites and the control sites in the different biotopes of the park. Each block was subdivided into 100 square plots of 100m² each. The results show that anthropogenic activities have reduced the flora richness of the park, modified its floristic composition and caused the disappearance of some status species. It was proposed as a measure to step up surveillance of the park.
The Application of SSANOVA Modeling in the Analysis of Formant Dynamics of Glide-vowel Sequences in Southern Fujian Hakka

The present study adopts SSANOVA modeling to examine the age and regional differences in formant dynamics of two glide-vowel sequences (/wi/ and /wa/) in Meilin and Guanbei Hakka. The basic parameters of the statistical analysis like mean values, standard deviation, standard error, Euclidean distance were used. The Praat, a software program in speech analysis, was used for data labeling and tracking. The R, a software program in statistical computing and graphics, was used for drawing formant trajectories and bar plots. Based on SSANOVA plot of formant trajectories, formant trajectory length, and spectral rate of change, results reveal significant age differences in formants of the two glide-vowel sequences in Meilin Hakka, however, no significant age differences in formants have been found in Guanbei Hakka. This study provides the evidence that the glide of /wi/ and /wa/ of old speakers in Meilin Hakka is actually a labio-dental approximant, which has a feature of secondary articulation of the initial, whereas the glide of young speakers is a rounded element belonging to the final. Our results suggest that the delabialization of /w/ to /u/ in Meilin Hakka is a sound change in progress.
VIA: A Smart Scratchpad for Vector Units with Application to Sparse Matrix Computations

Sparse matrix operations are critical kernels in multiple application domains such as High Performance Computing, artificial intelligence and big data. Vector processing is widely used to improve performance on mathematical kernels with dense matrices. Unfortunately, existing vector architectures do not cope well with sparse matrix computations, achieving much lower performance in comparison with their dense counterparts.To overcome this limitation, we present the Vector Indexed Architecture (VIA), a novel hardware vector architecture that accelerates applications with irregular memory access patterns such as sparse matrix computations. There are two main bottlenecks when computing with sparse matrices: irregular memory accesses and index matching. VIA addresses these two bottlenecks with a smart scratchpad that is tightly coupled to the Vector Functional Units within the core.Thanks to this structure, VIA improves locality for sparse-dense computations and improves the index matching search process for sparse computations. As a result, VIA achieves significant performance speedup over highly optimized state-of-the-art C++ algebra libraries. On average, VIA outperforms sparse matrix vector multiplication, sparse matrix addition and sparse matrix matrix multiplication kernels by 4.22 ×, 6.14 × and 6.00 ×, respectively, when evaluated over a thousand sparse matrices that arise in real applications. In addition, we prove the generality of VIA by showing that it can accelerate histogram and stencil applications by 4.5 × and 3.5 ×, respectively.
Joint Route Planning and Traffic Signal Timing for Connected Vehicles: An Edge Cloud Enabled Multi-Agent Game Method

Rising traffic congestion has become a major challenge to urban areas. Route planning and traffic signal timing are widely used methods to improve traffic efficiency. Although these two optimization problems are tightly coupled with each other, they have traditionally been studied separately in existing works. In this paper, we propose a decentralized framework that enables dynamic orchestration of route planning and traffic signal timing to improve traffic efficiency. In this framework, vehicles and traffic lights coordinate to offload traffic optimization tasks to their respective virtual agents on the edge cloud. Furthermore, considering the group rationality of agents, we formulate the joint optimization problem as an evolutionary game. With effective interactions, the agents leverage replicator dynamics to find the Nash equilibria for the evolutionary game, which can coordinate the integrated behavior of multiple vehicles and traffic lights. The simulation results show that the proposed method outperforms the baseline solutions, which optimizes the route planning and signal timing separately.
Framework for Analyzing and Visualizing Topics and Sentiments on Social Media: the Case of MH 17 Tweets

This paper develops a framework for sentiment analysis and clustering of Russian and Finnish-language Twitter posts (tweets) that enables the comparison of different language speakers' reactions to the same brand, product, or event. The framework can be further developed to analyze tweets in more than two languages or from more than two regions. Namely, we develop a tweet stream clustering algorithm, which calculates sentiment, keywords, topic tags and growth rate of the harvested tweets. The system utilizes a translation matrix for document vectors in Finnish and Russian to enable comparison of Russian and Finnish-language tweet clusters in a cluster visualization view (sentiment, topics, keywords, growth rate of clusters). A map view also allows following the density of Twitter activity in a given geographical location. To illustrate the framework, we examine the Russian and Finnish language tweets about the Malaysia Airlines Flight 17 (MH17) crash on July 17, 2014.
Novel Snapback-Free SOI LIGBT With Shorted Anode and Trench Barriers

A novel fast-switching silicon-on-insulator lateral insulated gate bipolar transistor (SOI LIGBT) is proposed and investigated in this article. The proposed device introduces trench barriers (TBs) at the collector end based on shorted anode (SA) structure to eliminate the snapback effect. The introduced TB structure can make the flow path of electron current be compressed and extended when the SA LIGBT is turned on so that the opening of collector p+/n-junction is prior to that of collector n+/n-junction. At the same time, it retains the ability to extract unbalanced electrons when the SA LIGBT is turned off. Through the TCAD simulation, the obtained results show that snapback-free can be realized by changing trench depth and pitch between TB structures. Compared with the separated SA (SSA) LIGBT, the forward voltage drop of the proposed LIGBT is reduced by 13.9% with snapback-free and much shorter collector region, which also retains the ability to extract unbalanced electrons. Thus, under the same forward voltage drop of 1.49 V, the turn-off time, and loss of the proposed LIGBT is 20.3% and 21.1% lower than those of the conventional (Conv.) LIGBT, respectively. In general, the tradeoff between turn-off time and forward voltage drop of the proposed LIGBT has much better performance.
Power Enhancement in W-Band Pulsed Folded Waveguide TWT

To obtain higher power in <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-band traveling-wave tubes (TWTs), a modified folded waveguide (FWG) with non-concentric bends is introduced and demonstrated, which has higher coupling impedance compared with the normal FWG structure and is utilized to eliminate the band-edge instability of TWT. Phase velocity tapering (PVT) is also used to improve the interaction efficiency between the beam and the circuit. Furthermore, a higher beam current is used and the corresponding magnetic focusing system is designed to confine the beam. A prototype tube was then fabricated and tested at a beam current of 220 mA and beam voltage of 21.9 kV. The testing data show that this <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-band TWT is capable of delivering an output power of over 450 W with a 4.5-GHz bandwidth at a duty cycle of 10%, with a maximum power of 647 W and electronic efficiency of 13.4%. That is the highest output power and electronic efficiency test results of <inline-formula> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula>-band TWTs reported so far.
Trajectory Similarity Measure Design for Ship Trajectory Clustering

Trajectory similarity measure is an important factor in Ship trajectory clustering, its design influences the number and shape of the cluster. In order to design a trajectory similarity measure appropriate for ship trajectory clustering. The author of this paper proposed an improved trajectory similarity measure based on symmetrized segment-path short (SSPD), it calculates the distance in time series and enhance the weight of endpoints, solves the problem of SSPD cannot identify trajectory direction and endpoints inconsistent. To prove that the improved trajectory similarity measure performs better than other similarity measures, the author designed two experiments. In the first experiment, two similar ship trajectories were selected, then change their sampling rate, point position, trajectory length and trajectory direction, compared with other trajectory similarity measures, observe the distance change. In the second experiment, based on real Automatic Identification System data, the improved SSPD is compared with Dynamic Time Warping on ship trajectory clustering. Experiment shows the improved SSPD can get a better clustering result.
Research on Optimal Rolling Scheduling with over/under-Estimated Cost of Reserve Based on Chance Constrained Programming

In order to reduce the impact of wind power output prediction error on system operation, the forecast error as a random variable is organically linked to the reserve capacity regulation based on the combination of risk theory and reliability. Firstly, a day-ahead dispatching schedule is proposed. Then the joint probability of wind power prediction error due to leading time for forecast is analyzed. The mathematical analysis method is used to derive the overestimation and underestimation costs of the up- and down-spinning reserve, which are the items in the objective function of dispatch model. According to the rolling update of renewable energy output forecasting information, an intra-day rolling optimization method with power flow constraints satisfaction is proposed. A PSO algorithm with the strategy of nonlinear decreasing inertia weight is adopted for a better convergence of the intra-day model. Finally, an improved IEEE-RTS 24-node distribution network system is used as an example for simulation analysis. The simulation results show that the proposed method can effectively control the risk of prediction error by quantifying the reserve regulation.
Adaptive Approximation by General Haar's Spaces

Embedded spaces of Haar type on arbitrary irregular grids are discussed. The mentioned spaces are selected adaptively depending on the initial numerical flow. To expand the criteria for adaptability, two types of pseudo-measure are introduced. One type of pseudo-measure is defined on the segments of the real axis, and the other type is set on the subsets of the initial grid. Introduced concepts are used to construct embedded the Haar spaces with adaptivity properties in the norms of the spaces $C$. The approximate properties are determined by constructed spaces. The computational complexity of the obtained algorithm is investigated. The complexity is directly proportional to the length of the initial number flow.