Miracle-dz/UniFAR-FTUs huggingface dataset:
When does (T) equal sat(T)?

Given a regular chain T, we aim at finding an efficient way for computing a system of generators of Sat(T), the saturated ideal of T. A natural idea is to test whether the equality {T}=Sat(T) holds, that is, whether T generates its saturated ideal. By generalizing the notion of primitivity from univariate polynomials to regular chains, we establish a necessary and sufficient condition, together with a Grobner basis free algorithm, for testing this equality. Our experimental results illustrate the efficiency of this approach in practice.
The Raukumara paleomagnetic domain: Constraints on the tectonic rotation of the East Coast, North Island, New Zealand, from paleomagnetic data

Abstract New paleomagnetic data from Miocene (Altonian-Otaian) sediments from the northeastern part of the Raukumara Peninsula gave declinations close to those expected for the Australian plate (c. 20° for 20 Ma rocks), and imply that no net tectonic rotation has affected this region since that time, in contrast to the large declinations and large clockwise tectonic rotations previously recorded for the Gisborne-Wairoa region. The boundary between these two regions is constrained to lie within a broad 50 km zone between Tokomaru Bay and Gisborne.
Time to reach near‐steady state in large aquifers

A new analytical solution of the flow equation has been developed to estimate the time to reach a near‐equilibrium state in mixed aquifers, i.e., having unconfined and confined portions, following a large hydraulic perturbation. Near‐equilibrium is defined as the time for an initial aquifer perturbation to dissipate by an average 95% across the aquifer. The new solution has been obtained by solving the flow system of a simplified conceptual model of a mixed aquifer using Laplace transforms. The conceptual model is based on two assumptions: (1) the groundwater flow can be reduced to a horizontal 1‐D problem and (2) the transmissivity, a function of the saturated thickness, is assumed constant on the unconfined portion. This new solution depends on the storativity of the unconfined portion, the lengths of the unconfined and confined portions and the transmissivity, assumed to be constant and equal in both portions of the mixed aquifer. This solution was then tested and validated against a numerical flow model, where the variations of the saturated thickness and therefore variations of the transmissivity were either ignored, or properly modeled. The agreement between the results from the new solution and those from the numerical model is good, validating the use of this new solution to estimate the time to reach near‐equilibrium in mixed aquifers. This solution for mixed aquifers, as well as the solutions for a fully confined or fully unconfined aquifer, has been used to estimate the time to reach near‐equilibrium in 13 large aquifers in the world. For those different aquifers, the time to reach near‐equilibrium ranges between 0.7 kyr to 2.4 × 107 kyr. These results suggest that the present hydraulic heads in these aquifers are typically a mixture of responses induced from current and past hydrologic conditions and thus climate conditions. For some aquifers, the modern hydraulic heads may in fact depend upon hydrologic conditions resulting from several past climate cycles.
LOT: Logic Optimization with Testability. New transformations for logic synthesis

A new approach to optimize multilevel logic circuits is introduced. Given a multilevel circuit, the synthesis method optimizes its area while simultaneously enhancing its random pattern testability. The method is based on structural transformations at the gate level. New transformations involving EX-OR gates as well as Reed-Muller expansions have been introduced in the synthesis of multilevel circuits. This method is augmented with transformations that specifically enhance random-pattern testability while reducing the area. Testability enhancement is an integral part of our synthesis methodology. Experimental results show that the proposed methodology not only can achieve lower area than other similar tools, but that it achieves better testability compared to available testability enhancement tools such as tstfx. Specifically for ISCAS-85 benchmark circuits, it was observed that EX-OR gate-based transformations successfully contributed toward generating smaller circuits compared to other state-of-the-art logic optimization tools.
Quantifying path exploration in the internet

A number of previous measurement studies [10, 12, 17] have shown the existence of path exploration and slow convergence in the global Internet routing system, and a number of protocol enhancements have been proposed to remedy the problem [21, 15, 4, 20, 5]. However all the previous measurements were conducted over a small number of testing prefixes. There has been no systematic study to quantify the pervasiveness of BGP slow convergence in the operational Internet, nor there is any known effort to deploy any of the proposed solutions.In this paper we present our measurement results from identifying BGP slow convergence events across the entire global routing table. Our data shows that the severity of path exploration and slow convergence varies depending on where prefixes are originated and where the observations are made in the Internet routing hierarchy. In general, routers in tier-1 ISPs observe less path exploration, hence shorter convergence delays than routers in edge ASes, and prefixes originated from tier-1 ISPs also experience less path exploration than those originated from edge ASes. Our data also shows that the convergence time of route fail-over events is similar to that of new route announcements, and significantly shorter than that of route failures, which confirms our earlier analytical results [19]. In addition, we also developed a usage-time based path preference inference method which can be used by future studies of BGP dynamics.
Well-posedness and Mittag-Leffler Euler integrator for space-time fractional SPDEs with fractionally integrated additive noise

This paper considers the space-time fractional stochastic partial differential equation (SPDE, for short) with fractionally integrated additive noise, which is general and includes many (fractional) SPDEs with additive noise. Firstly, the existence, uniqueness and temporal regularity of the mild solution are presented. Then the Mittag–Leffler Euler integrator is proposed as a time-stepping method to numerically solve the underlying model. Two key ingredients are developed to overcome the difficulty caused by the interaction between the time-fractional derivative and the fractionally integrated noise. One is a novel decomposition way for the drift part of the mild solution, named here the integral decomposition technique, and the other is to derive some fine estimates associated with the solution operator by making use of the properties of the Mittag–Leffler function. Consequently, the proposed Mittag–Leffler Euler integrator is proved to be convergent with order min{ 1 2 + α 2β (r + λ − κ), 1} if α + γ = 1, otherwise order min{ α 2β min{κ, r+λ}+(γ− 1 2 ), 1− ε} in the sense of L(Ω,H)-norm for the nonlinear case. In particular, the corresponding convergence order can attain min{α+ αr 2β +(γ− 1 2 ) − ε, α+ γ− ε, 1} for the linear case.
Hand gesture recognition using color and depth images enhanced with hand angular pose data

In this paper we propose a hand gesture recognition system that relies on color and depth images, and on a small pose sensor on the human palm. Monocular and stereo vision systems have been used for human pose and gesture recognition, but with limited scope due to limitations on texture, illumination, etc. New RGB-Depth sensors, that reply on projected light such as the Microsoft Kinect, have overcome many of those limitations. However, the point clouds for hand gestures are still in many cases noisy and partially occluded, and hand gesture recognition is not trivial. Hand gesture recognition is much more complex than full body motion, since we can have the hands in any orientation and can not assume a standing body on a ground plane. In this work we propose to add a tiny pose sensor to the human palm, with a minute accelerometer and magnetometer that combined provide 3D angular pose, to reduce the search space and have a robust and computationally light recognition method. Starting with the full depth image point cloud, segmentation can be performed by taking into account the relative depth and hand orientation, as well as skin color. Identification is then performed by matching 3D voxel occupancy against a gesture template database. Preliminary results are presented for the recognition of Portuguese Sign Language alphabet, showing the validity of the approach.
A dynamic data driven application system for wildfire spread simulation

Wildfire spread simulation plays important roles in wildfire management. Existing wildfire simulations are largely decoupled from real wildfires by making little usage of real time data. In this paper, a dynamic data driven application system is presented to incorporate the real time data into the simulation model, thus to improve the simulation results. The developed dynamic data driven application system is based on the DEVS-FIRE model and employs the particle filtering algorithm to estimate the state of fire spread. We describe the overall structure of the dynamic data driven application system for wildfire spread simulation. The major issues and computation models of this work are presented and experiment results are provided.
Automated Customization of On-Device Inference for Quality-of-Experience Enhancement

The rapid uptake of intelligent applications is pushing deep learning (DL) capabilities to mobile devices. However, the heterogeneities in device capacity, DNN performances, and user preferences make it challenging to provide satisfactory Quality of Experience (QoE) to mobile users. This paper studies automated customization for DL inference on mobile devices (termed as on-device inference), and our goal is to enhance user QoE by configuring the on-device inference with an appropriate DNN for users under different usage scenarios. The core of our method is a DNN selection module that learns user QoE patterns on-the-fly and identifies the best-fit DNN for on-device inference with the learned knowledge. It leverages an online learning algorithm, NeuralUCB, that has excellent generalization ability for handling various user QoE patterns. We also embed the knowledge transfer technique in NeuralUCB to expedite the learning process. However, NeuralUCB frequently solicits QoE ratings from users, which incurs non-negligible inconvenience. To address this problem, we design feedback solicitation schemes to reduce the number of QoE solicitations while maintaining the learning efficiency of NeuralUCB. A pragmatic problem, aggregated QoE, is further investigated to improve the practicality of our framework. We conduct experiments on both synthetic and real-world data. The results indicate that our method efficiently learns the user QoE pattern with few solicitations and provides drastic QoE enhancement for mobile devices.
Application of Neural Network and Global Optimization in History Matching

This article presents the application of global optimizers combined with Artificial Neural Networks (ANN) to the history matching problem. An evolutionary algorithm is executed on the proxy generated through the ANN technique. The results obtained from evolutionary algorithms are fine-tuned by using a local optimizer based on the Hooke and Jeeves optimization method. The methodology is applied in two reservoir models and promising results were obtained.
Ultrawideband propagation channels and their impact on system design

The performance of ultrawideband (UWB) communications systems is determined by the propagation channels they operate in. This paper gives an overview of UWB channels and their impact on system design. The emphasis lies on (i) multiple-antenna systems and (ii) body-area networks. We discuss the frequency dependence of angular power spectra and show that spatial multiplexing can be used for achieving very high data rates in MIMO-UWB systems. For body-area networks, we And small delay spreads, so that high-rate communications can be supported with relatively simple receiver structures. Finally, we argue that the clustering structure and "soft onset" property of UWB power delay profiles strongly influence the design of ranging systems.
Estimation of Ridge Using Nonlinear Transformation on Density Function

Ridges play a vital role in accurately approximating the underlying structure of manifolds. In this paper, we explore the ridge’s variation by applying a concave nonlinear transformation to the density function. Through the derivation of the Hessian matrix, we observe that nonlinear transformations yield a rank-one modiﬁcation of the Hessian matrix. Leveraging the variational properties of eigenvalue problems, we establish a partial order inclusion relationship among the corresponding ridges. We intuitively discover that the transformation can lead to improved estimation of the tangent space via rank-one modiﬁcation of the Hessian matrix. To validate our theories, we conduct extensive numerical experiments on synthetic and real-world datasets that demonstrate the superiority of the ridges obtained from our transformed approach in approximating the underlying truth manifold compared to other manifold ﬁtting algorithms.
Oligocene clay mineralogy of the linxia basin: evidence of paleoclimatic evolution subsequent to the initial-stage uplift of the Tibetan Plateau

The clay mineral content of the Oligocene sediments in the Linxia Basin has been investigated using X-ray diffraction, scanning electron microscopy, and high-resolution transmission electron microscopy. The clay mineral assemblages are mainly mixed-layer illite-smectite (I-S), illite, kaolinite and minor palygorskite in the early-Middle Oligocene deposits, mixed-layer I-S, illite and kaolinite in the Middle Oligocene deposits, mainly illite and chlorite (usually >50–70 vol.%), mixed-layer I-S, and trace to minor palygorskite in the late Oligocene sediments, respectively. The mineral assemblage indicates a warm and seasonally humid climate in the Middle Oligocene, with an episode of warm and dry conditions in the early stage of the Middle Oligocene, and a trend of temperature decrease and more arid conditions in the late Oligocene. Climate evolution in the Oligocene corresponds with the significant elevation change in central Tibet since late Oligocene, and therefore, suggests that tectonic-forced cooling of climate took place in Linxia in the northeast margin of the Tibetan Plateau. The ubiquitous mixed-layer I-S and carbonates throughout the Oligocene sediments reflect relatively small fluctuations in climate conditions during the epoch. The changes in clay mineral components and feldspars in the late Oligocene suggest a variation in the source of clastic materials, which probably reflects an increase in erosion of soils and poorly weathered parent rock in more elevated or high-relief source areas during this period of tectonic uplift.
Effect of initial soil moisture conditions on runoff transport of manure-borne pathogens through vegetated filter strips

Title of Thesis: EFFECT OF INITIAL SOIL MOISTURE CONDITIONS ON RUNOFF TRANSPORT OF MANURE-BORNE PATHOGENS THROUGH VEGETATED FILTER STRIPS Fatima Araujo Cardoso-Gendreau, Master of Science, 2006 Directed By: Professor Adel Shirmohammadi, Department of Biological Resources Engineering Pollution of drinking and recreational water supplies with manure-borne pathogenic bacteria through surface runoff from agricultural lands is a public health threat wherever landscapes are exposed to animal manure, but, particularly, where there is concentrated animal production (e.g., Iowa). This study was conducted to investigate the effect of initial soil moisture conditions on the effectiveness of vegetated filters strips (VFS) to mitigate surface runoff transport of two surrogate pathogenic bacteria, Escherichia coli and Salmonella enterica enterica Typhimurium, from land-applied swine slurry. A 5% slope lysimeter containing clay loam soil was constructed, partitioned into vegetated and bare plots, and the plots instrumented to collect, measure, and sample runoff at different time intervals and at two distances from the slurry application area during rainfall simulations. Results indicated that the potential of VFS to attenuate runoff transport of pathogens was reduced under increased initial soil moisture conditions, indicating that infiltration is an important factor in the mitigation process. EFFECT OF INITIAL SOIL MOISTURE CONDITIONS ON RUNOFF TRANSPORT OF MANURE-BORNE PATHOGENS THROUGH VEGETATED FILTER STRIPS
DUFormer: A Novel Architecture for Power Line Segmentation of Aerial Images

Power lines pose a signiﬁcant safety threat to unmanned aerial vehicles (UAVs) operating at low altitudes. However, detecting power lines in aerial images is challenging due to the small size of the foreground data (i.e., power lines) and the abundance of background information. To address this challenge, we propose DUFormer, a semantic segmentation algorithm designed speciﬁcally for power line detection in aerial images. We assume that performing sufﬁcient feature extraction with a convolutional neural network (CNN) that has a strong inductive bias is beneﬁcial for training an efﬁcient Transformer model. To this end, we propose a heavy token encoder responsible for overlapping feature re-mining and tokenization. The encoder comprises a pyramid CNN feature extraction module and a power line feature enhancement module. Following sufﬁcient feature extraction for power lines, the feature fusion is carried out, and then the Transformer block is used for global modeling. The ﬁnal segmentation result is obtained by fusing local and global features in the decode head. Additionally, we demonstrate the signiﬁcance of the joint multi-weight loss function in power line segmentation. The experimental results demonstrate that our proposed method achieves the state-of-the-art performance in power line segmentation on the publicly available TTPLA dataset.
Deep Learning-Based Vehicle Behavior Prediction for Autonomous Driving Applications: A Review

Behaviour prediction function of an autonomous vehicle predicts the future states of the nearby vehicles based on the current and past observations of the surrounding environment. This helps enhance their awareness of the imminent hazards. However, conventional behavior prediction solutions are applicable in simple driving scenarios that require short prediction horizons. Most recently, deep learning-based approaches have become popular due to their promising performance in more complex environments compared to the conventional approaches. Motivated by this increased popularity, we provide a comprehensive review of the state-of-the-art of deep learning-based approaches for vehicle behavior prediction in this article. We firstly give an overview of the generic problem of vehicle behavior prediction and discuss its challenges, followed by classification and review of the most recent deep learning-based solutions based on three criteria: input representation, output type, and prediction method. The article also discusses the performance of several well-known solutions, identifies the research gaps in the literature and outlines potential new research directions.
Post-processing of Scanned 3D Surface Data

3D shape acquisition has become a major tool for creating digital 3D surface data in a variety of application elds. Despite the steady increase in accuracy, most available scanning techniques cause severe scanning artifacts such as noise, outliers, holes, or ghost geometry. To apply sophisticated modeling operations on these data sets, substantial post-processing is usually required. In this paper, we address a variety of scanning artifacts that are created by common optical scanners and provide a comprehensive set of user-guided tools to process corrupted data sets. These include an eraser tool, low-pass lter s for noise removal, a set of outlier detection methods, and various up-sampling and hole- lling tools. These techniques can be applied early in the content creation pipeline. Therefore, all our tools are implemented to operate directly on the acquired point cloud. We also emphasize the need for extensive user control and an ef cient visual feedback loop. The effectiveness of our scan cleaning tools is demonstrated on various models acquired with commercial laser-range scanners and low-cost structured light scanners.
Evaluation of three 32-bit CMOS adders in DCVS logic for self-timed circuits

The efficient implementation of adders in differential logic can be carried out using a new generate signal (N) presented in this paper. This signal enables iterative shared transistor structures to be built with a better speed/area performance than a conventional implementation. It also allows adders developed in domino logic to be easily adapted to differential logic. Based on this signal, three 32-b adders in differential cascode switch voltage (DCVS) logic with completion circuit for applications in self-timed circuits have been fabricated in a standard 1.0-/spl mu/m two-level metal CMOS technology. The adders are: a ripple-carry (RC) adder, a carry look-ahead (CLA) adder, and a binary carry look-ahead (BCL) adder. The RC adder has the best levels of performance for random input data, but its delay is significantly influenced by the length of the carry propagation path, and thus is not recommended in circuits with nonrandom input operands. The BCL adder is the fastest but has a high cost in chip area. The CLA adder provides an intermediate option, with an area which is 20% greater than that of the RC adder. Its average delay is slightly greater than that of the other two adders, with an addition time which increases slowly with the carry propagate length even for adders with a high number of bits.
Efficient Point-Based Rendering Using Image Reconstruction

Image-space reconstruction of continuous surfaces from scattered one-pixel projections of points is known to potentially offer an advantageous time complexity compared to surface splatting techniques. We propose a new algorithm for hardware-accelerated image-space reconstruction using pull-push interpolation and present an efficient GPU implementation. Compared to published image-space reconstruction approaches employing the pull-push interpolation, our method offers a significantly improved image quality because of the integration of elliptic boxfilters and support for deferred Phong shading. For large point-based models, our GPU implementation is capable of rendering more than 50M points per second—including image-space reconstruction and deferred shading.